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Page 1: ABCDEF FF CAFBFFCDEF FF ˇB˘ ˆ˙ ˝˛ ˚F˜ F ˘! #B$accs2014/proc.pdf · 2014-02-27 · Structural and Functional networks underlying auditory processing in children with autism

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Page 2: ABCDEF FF CAFBFFCDEF FF ˇB˘ ˆ˙ ˝˛ ˚F˜ F ˘! #B$accs2014/proc.pdf · 2014-02-27 · Structural and Functional networks underlying auditory processing in children with autism

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Page 3: ABCDEF FF CAFBFFCDEF FF ˇB˘ ˆ˙ ˝˛ ˚F˜ F ˘! #B$accs2014/proc.pdf · 2014-02-27 · Structural and Functional networks underlying auditory processing in children with autism

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Page 4: ABCDEF FF CAFBFFCDEF FF ˇB˘ ˆ˙ ˝˛ ˚F˜ F ˘! #B$accs2014/proc.pdf · 2014-02-27 · Structural and Functional networks underlying auditory processing in children with autism

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Structural and Functional networks underlying auditory processing in children with autism

INTRODUCTION: A wide range of enhancements and deficits in auditory function have been reported in individuals with Autism Spectrum Disorders (ASD). These include impaired perception of speech on one hand and enhanced responses to musical sounds on the other. It has also been suggested that music-based interventions engage a multimodal brain network and may hence be useful in entraining functions which are impaired in autism. The main objective of our study is to identify the structural and functional networks involved in processing spoken speech, sung speech and music in children with autism as compared to typically developing children with a view to designing interventions targeted at entraining these communication networks via early music-based training.

METHODS: We conducted a passive-listening task with three kinds of stimuli –spoken words, sung words and piano tones in a sparse-sampling, event-related fMRI paradigm. Words were bisyllabic nouns or verbs commonly used by children. The task was performed by 44 participants, 22 children with an ASD diagnosed using DSM IV, CARS2 and ADOS criteria in the age range 6-16 years and 22 typically developing (TYP) age and gender-matched controls 90 volumes in 3 runs were acquired with TR=10s in a 3T MRI scanner along with a high resolution T1 image and diffusion images. Data analysis was performed using SPM5 and FSL-FDT.

RESULTS: Our preliminary results showed that sung words engaged a robust bilateral temporal network with in both ASD and TYP. In contrast, the networks recruited for spoken word perception were more right-lateralized in ASD. The spoken networks for ASD also showed decreased inferior frontal activation which was related to the verbal ability in the ASD group. Furthermore, a diffusion tensor imaging analysis revealed that the inferior frontal activation was correlated with the decreased integrity of the white-matter tract connecting left temporal and frontal regions in ASD. A subsequent functional connectivity analysis using psychophysiological interactions further confirmed that fronto-temporal connectivity, which was disrupted during spoken word perception, was preserved during sung-word listening in children with ASD. CONCLUSION: Our results show that fronto-temporal functional connectivity is preserved during sung word perception across the autism spectrum and is independent of language ability and underlying white matter structure. In summary, our findings demonstrate the ability of song stimuli to overcome the structural deficit for speech perception across the autism spectrum and provide a mechanistic basis for the efficacy of song and music-based interventions in ASD. Future behavioural experiments will lend support for use of such song-based music interventions.

Authors: Megha Sharda and Nandini C. Singh

National Brain Research Centre

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Effect of COMT, 5-HT2A and 5-HTTLPR polymorphisms on brain morphometry in

schizophrenia and healthy subjects

Anupa A Vijayakumari, John P John, Harsha N Halahalli, Bhavani Shankara Bagepally, Pradip Paul,

Priyadarshini Thirunavukkarasu, Nagaraj S. Moily, Meera Purushottam, Sanjeev Jain

Abstract

With the advent of neuroimaging techniques like Computerized Tomography (CT), Magnetic

Resonance Imaging (MRI) and Diffusion Tensor Imaging (DTI), brain morphometric

abnormalities have been extensively reported in schizophrenia. However, apart from enlarged

ventricles and whole brain volume reductions, no other brain morphometric abnormality has

been consistently associated with the disorder. The main source for this variability could be the

genotypic heterogeneity of the study samples, given our understanding that schizophrenia is a

polygenic disorder. Moreover, epistatic interactions and epigenetic alterations play a pivotal

role in mediating regional brain volumetric changes. We attempted to examine the influence of

polymorphisms of three risk genes which mediate monoamine signalling in the brain, viz.,

catechol-o-methyl transferase (COMT), 5-hydroxytryptamine transporter (5-HTTLPR) and 5-

hydroxytryptamine 2A (5HT2A) on brain morphometry in patients with schizophrenia and

healthy subjects. The study was carried out at National Institute of Mental Health and

Neurosciences (NIMHANS), Bangalore, India. A total of 80 subjects (patients with

schizophrenia=41; healthy subjects=39) belonging to Dravidian ethnicity from South India were

recruited for this case control study. All the participants underwent magnetic resonance

imaging and were genotyped for COMT, 5HTTLPR and 5HT2A polymorphisms. We examined the

effect of COMT, 5HT2A and 5-HTTLPR polymorphisms individually as well as additively on

regional brain volumes using an imaging-genomics approach. A dominant model of COMT

Val158Met polymorphism (Met/Met vs. Val/Met + Val/Val or AA vs. GA+GG) was shown to be

associated with brain morphometric changes in healthy young adults (Honea et al., 2009,

Zinkstok et al., 2006). In subjects who were at high risk for psychosis, gene-dose effects of the

Val allele on reduction gray matter volume in anterior cingulate has been reported (McIntosh et

al., 2007). Therefore, we assumed a dominant model for the COMT Val158Met polymorphism

to examine the effect of the risk Val allele on brain volumes. Also for the 5HTTLPR

polymorphism, a dominant model (Long/Long vs. Long/Short+ Short/Short or LL vs. LS+SS) was

assumed, since the short allele was found to act in a dominant fashion (Hranilovic et al., 2004).

Voxel-based morphometric (VBM) approach was employed to carry out all the morphometric

comparisons using Analysis of Covariance model after adjusting for age, gender and total brain

volume. VBM analysis across phenotypes (schizophrenia vs. healthy subjects) showed

significant gray matter volume reductions in the left anterior culmen and posterior declive in

patients with schizophrenia when compared to healthy subjects at family wise error (FWE)

cluster defining threshold (FWEc; cluster defining threshold: Puncorrected< 0.001; k= 793 voxels).

Irrespective of phenotype, individuals with the risk allele T (n=14) of the His452Tyr (rs6314)

polymorphism of 5HT2A showed significantly greater regional brain volumes in the left inferior

temporal and inferior occipital gyri (FWEc; cluster defining threshold: Puncorrected< 0.001; k= 988

voxels) in comparison to those homozygous for the C allele (n=66). Genotype-wise comparisons

of gray matter volumes using the dominant model for COMT and 5-HTTLPR revealed group

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differences only at an uncorrected threshold (p<0.001, 20 voxel extent threshold). Subjects with

GG or AG genotype of rs4680 of COMT (n=61), irrespective of phenotype, showed decreased

gray matter volumes in right anterior cingulate, bilateral medial frontal gyrus, right declive,

right superior temporal gyrus, right fusiform gyrus, right uncus, right frontal sub-gyral region

and left lingual gyrus compared to those individuals with AA genotypes (n=63). In case of 5-

HTTLPR, the individuals carrying SS or LS genotypes (n=63) showed decreased gray matter

volumes in the right anterior culmen and middle frontal gyrus when compared to LL individuals

(n=17) (p<0.001, 20 voxel extent threshold). Exploration of the additive effects of risk genes on

brain volumes yielded differences between those subjects who had 2 or more risk genotypes

(n=53) of the above 3 risk genes vs. those who had 1 or less risk genotypes (n=27) at an

uncorrected threshold (p<0.001, 20 voxel extent threshold). Those with higher loading of risk

alleles had lower regional brain volumes in the right superior frontal and right medial frontal

gyri. In conclusion, the volumetric alterations observed in our study can be interpreted as an

independent function of the individual and additive effects of the multiple schizophrenia risk

genes on brain volume, rather than a function of the disorder per se.

References

HRANILOVIC, D., STEFULJ, J., SCHWAB, S., BORRMANN-HASSENBACH, M., ALBUS, M., JERNEJ, B. &

WILDENAUER, D. 2004. Serotonin transporter promoter and intron 2 polymorphisms:

relationship between allelic variants and gene expression. Biol Psychiatry, 55, 1090-4.

MCINTOSH, A. M., BAIG, B. J., HALL, J., JOB, D., WHALLEY, H. C., LYMER, G. K., MOORHEAD, T. W.,

OWENS, D. G., MILLER, P., PORTEOUS, D., LAWRIE, S. M. & JOHNSTONE, E. C. 2007.

Relationship of catechol-O-methyltransferase variants to brain structure and function in a

population at high risk of psychosis. Biol Psychiatry, 61, 1127-34.

ZINKSTOK, J., SCHMITZ, N., VAN AMELSVOORT, T., DE WIN, M., VAN DEN BRINK, W., BAAS, F. &

LINSZEN, D. 2006. The COMT val158met polymorphism and brain morphometry in healthy

young adults. Neurosci Lett, 405, 34-9.

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Similarities and Differences in Thai and Telugu Motion Event Descriptions

Jordan Zlatev, Y. Viswanatha Naidu and DuggiralaVasanta

Address all correspondence to: Jordan Zlatev <[email protected]>

The binary language typology proposed by Talmy (1991), and extended with an additional equipollent

type by Slobin (2004) has been the focus of numerous linguistic and psycholinguistic investigations of

motion events (e.g. Bohnemeyer et al. 2007; Filipovič 2007; Croft et al. 2010). Despite occasional

reservations, there seems to be a general consensus that e.g. Germanic and Slavonic languages are (1)

satellite-framed, i.e. tend to express the Path component of motion events in a satellite, and that e.g.

Romance and Semitic languages are (2) verb-framed, i.e. tend to express Path in the verb, while (3)

serial-verb languages like Thai (Zlatev &Yanklang 2004) and Ewe (Ameka & Essegbey 2006) differ

in providing convenient slots for the expressionof Path, Manner and Deixis.

However, any clear two-type or three-type division of languages on the basis of their expression of

motion situations (and extensionsto other semantic domains) is problematic. For other thing, there is

considerable intra-typological and even intra-linguistic variation (Croft et al. 2010). Another problem

is that the basic concepts of Path, Manner, “Satellite” and even Motion have been ill-defined,

motivating the need to re-work motion typology from the ground (Zlatev et al. 2010). As a

contribution to this effort, we compare two languages that differ genealogically and typologically to a

considerable extent: Telugu (cf. Viswantha Naidu & Vasanta 2011) which is highly inflective and

Thai, which is highly analytical. While Talmy (1991) claimed that Tamil (closely related to Telugu

typologically) should be seen as verb-framed, and Slobin (2004) offers Thai as a clear example of an

“equipollent” language, we first show that these two languages have a number of analogous resources

for the expression of motion and spatial semantics:

Thai uses, as mentioned, series of Manner (wing ‘run’), Path (khaw ‘enter’) and Deictic (ma

‘come’) verbs, while Telugu combines main verbs expressing Path/Direction or Deixis

(veLLADu ‘go’) with verbal participles of Manner (parigett-kunTu ‘run’), as well as

“explicator verbs” (cf. Abbi 2004).

Speakers of both languages express Manner, especially in colloquial circumstances, through

(reduplicative) expressives/ideophones, e.g. tàkiaak-tàkaaj ‘move frantically’ (Thai),

cakacakaa ‘fast paced walking’ (Telugu).

In addition to verbs Thai uses de-verbalized prepositions (e.g. càak ‘from’) and Telugu

locative case markers (e.g. -nuMDi ‘from’) to express Path.

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Both languages make systematic use of nominals expressing different values of the category

Region, as Thai naj/nOOk and Telugu lO/bayaTi (‘inside/outside’), which in Telugu can take

the case markers above, e.g. lO-nuMDi‘from-inside’.

To compare how these resources are used in actual language use, we performed a study in which 15

adult speakers of Telugu narrated the well-known “frog story” based on pictorial stimuli (cf.

Strömqvist & Verhoeven 2004), comparing these descriptions with those of 10 adult speakers of Thai,

collected previously (Zlatev & Yangklang 2004). Qualitative and quantitative comparisons showed

similar rates of expressing the category Path/Direction (through verbs and prepositions/cases markers)

and Region (though locative nouns), but higher rates of Manner and Deixis expression in Thai, while

Telugu speakers tended to mention Landmark/Ground elements more often. We present tentative

explanations of these differences, arguing for the need to take into consideration factors such as

“degree of grammaticalization” which have been mostly neglected in motion event typology.

References

Abbi, A. (2004). Typology of ‘manner’ in verb sequences in South Asian languages. Indian Linguistics 65: 1-29.

Ameka, F.&Essegbey, J. (2006).Elements of the grammar of space of Ewe.Grammars of space: Explorations in

Cognitive Diversity, ed. by Stephen C. Levinson and David P. Wilkins, 359-99. Cambridge: Cambridge

University Press

Bohnemeyer J., N.J. Enfield, J. Essegbey, I. Ibarretxe-Antuñano, S. Kita, F. Lüpke& F.K. Ameka.(2007).

Principles of event segmentation: the case of motion events. Language 83, 495-532.

Croft W., J. Barðdal, W.B. Hollmann, V. Sotirova& C. Taoka. 2010. Revising Talmy’s typological classification

of complex event constructions. In H.C. Boas (ed), Contrastive Studies in Construction Grammar.

Amsterdam: John Benjamins, 201-235.

Filipovič L. 2007. Talking about Motion:A Crosslinguistic Investigation of Lexicalization Patterns. Amsterdam /

Philadelphia: John Benjamins.

Slobin, D. (2004). The many ways to search for a frog: linguistic typology and the expression of motion events.

In Strömqvist and Verhoeven, 219-257.Mahawah, NJ: Lawrence Erlbaum.

Strömqvist, S. &Verhoeven, L. (2004).Relating events in narrative: Typological and contextual

perspectives.Mahawah, NJ: Lawrence Erlbaum.

Talmy, L. (1991). Path to realization: a typology of event conflation. Proceedings of the Berkeley Linguistics

Society 17.480-520.

Viswantha Naidu, Y., & Vasanta, D. (2011). On verbalizing motion in Telugu. Indian Linguistics 72, 182-194.

Zlatev, J.&Yangklang, P. (2004). A third way to travel: The place of Thai in Motion-Event typology. In

Strömqvist and Verhoeven, 159-190. Mahawah, NJ: Lawrence Erlbaum.

Zlatev, J, Blomberg, J., David, C. (2010). Translocation, language and the categorization of experience. In Space

in Language and Cognition: The State of the Art and New Directions, V. Evans and P. Chilton (eds.), 389-

418. London: Equinox.

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Group differences for Rotation Related Negativity (RRN) while Reading

Gunjan Khera1, and Thomas Lachmann2

1 Indian Institute of Technology Ropar, Department of Humanities and Social Sciences, Roopnagar, Punjab, India. 2 Technical University of Kaiserslautern, Department of Social Sciences, Cognitive and Developmental Psychology, Kaiserslautern, Germany. Mental-rotation is the well-known phenomenon that reaction time increases linearly with the angles of rotation. Dyslexics are not impaired responding on mental rotation task but they fail in suppression of symmetry in the representation of graphemes at decision stage. This deficit is termed as Functional Coordination deficit (Lachmann, 2002) between grapheme and phonological letter representations in dyslexics. The behavioral results so far indicated that group effect in mental rotation tasks occur late, in the decision stage of information processing (Heil, 2002). Neuronal mechanisms underlying mental rotation are still discussed. Therefore psycho physiological methods need to be applied to understand the neuronal group differences by using the paradigm of mental rotation. Letters G, F and R were used with no visual or phonological similarity and were presented in normal and mirrored rotations forming three different levels of angular disparity of rotation from upright position with a difference of 600 each. We expect Rotation Related Negativity (RRN) as a function of the complexity associated with angular disparity of rotation resulting to reduced late positive component. Where the perceptual encoding of mental rotation task for dyslexics and control children occur? Both the groups perform mental rotation at the same time? Or it’s an early or late processing for dyslexics in comparison to controls? The data was collected on German’s 12 dyslexic children, 19 control children. In general, reaction time increased with an angular disparity of rotation (Heil & Rolke, 2002). As predicted, identical effects of mental rotation occurred for both the groups (Rusiak, Lachmann, Jaskowski and van Leeuwen, 2007) and Dyslexics were slower in responding to the letters than control children because of the visual and phonological problems for encoding of letters at the decision stage (lachmann, 2002). According to the ERP's RRN was present for Parietal electrodes (P3, Pz and P4) and was absent for frontal (F3, Fz and F4) and central (C3, Cz and C4) electrodes. Bilateral effects of rotation for parietal electrodes (P3, Pz and P4) were found with no hemispheric advantages for both groups. RRN was present only for controls in the time window of 400-700ms. Dyslexics showed some late effects (800-1000ms) in perceptual encoding but the typical trend of RRN was absent. Possibly, they showed reduced RRN because they were engaged more in distinguishing between normal and mirrored rotations. Differences between the groups in the later time window (800-1000) could also be explained as confusion between normal and mirrored rotations. On the other hand the results also suggest that dyslexics were using a different strategy for performing mental rotation (Horst et al., 2012).

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Perceptual Span of Readers of Hindi in Devanagari

This study was conducted to determine the size of the perceptual span of readers of Hindi written

in Devanagari through eye-tracking experiments. The symmetric region of maximal visual acuity

surrounding a fixation, called the visual span, is very narrow, extending to about a degree on

either side of the fixation. The perceptual span, on the other hand, has been defined as “the size

of the effective visual field in reading” (Rayner 1998). It is the optimal number of characters that

can be seen by a reader, which, when decreased, affects reading but when increased does not

facilitate reading. The two have been found to be incongruent in studies on English (McConkie &

Rayner 1975), Chinese (Chen & Tang 1998), Japanese(Osaka 1992, 1987)and Hebrew (Pollatsek

et.al. 1981) showing thereby that perceptual span is not entirely determined by visual acuity.

Perceptual span is affected both in size and symmetry by the script and possibly by the language that is

being read. In English the perceptual span extends to about 14-15 characters to the right of the fixation

and 3-4 characters to the left (McConkie & Rayner 1975). The perceptual span in reading a typical

Japanese text consisting of a combination ofkana andkanji scripts extends to only 7 character spaces to

the right (Osaka 1987, 1992). Chinese has a perceptual span with 3-4 characters to the right of fixation

and information to the left of the fixation does not seem to have any significant effect on reading speed or

accuracy (Chen & Tang, 1998).

Although previous works have suggested a role of information density in modulating perceptual span

(Chen & Tang, 1998 ), the types of information that do so, need further study. Based on the findings of

studies conducted in different languages, we designed and ran a set of experiments to determine the size

of the perceptual span for readers of Hindi written in the Devanagari script. Our hypothesis is that the

perceptual span for readers of Hindi in Devanagari will fall between those for English and Chinese

because of the phonemic density of the script.

Experiments I & II

The two experiments involved eye-tracking, on an Eyelink 1000 (SR Research) eye-tracker. The

experiments were run on 20 subjects. There were 50 sentences, each with 5 conditions, which were

counterbalanced, displaying one condition of each sentence to each subject using Rayner’s gaze-

contingent moving window paradigm (Rayner 2001). Every participant therefore ran through 50 trials in

the experiment. The first two experiments were controlled for the number of aksharas or blank spaces

displayed to the left of the fixation, with no restriction on the number of aksharas or blank spaces

displayed to the right of the fixation. The control condition required sentences to be completely displayed

with no visual restrictions on either side. A multiple choice question followed each sentence to test

reading accuracy.

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Experiments III and IV

The second pair of experiments used the same set of stimuli and followed the same design as the first pair

of experiments. The number of characters to the right of the fixation were controlled using a gaze-

contingent moving window paradigm, with no restrictions on the number of aksharas or blank spaces

displayed to the left of the fixation.

Experiment V

This experiment had a similar set of stimuli, with an additional 90 sentences added to the set of stimuli in

the previous experiments. Each participant ran through 140 sentences.The design of the experiment was

the same as in the first two sets of experiments except that there were only two conditions: a control

condition in which the stimuli were displayed in their entirety without any masking on either side of the

fixation and a second condition using the gaze-contingent moving window paradigm displaying only the

aksara fixated upon along with three aksharas to the left of the fixation and seven aksharas to the right,

based upon the results obtained from the previous experiments.

Results

Experiment I, II, III and IV

The reading time for each stimulus was measured under the various conditions. The reading time for the

control condition, where the whole sentence was displayed with no restrictions on visibility was taken as

the base with which the reading times under all the other conditions were compared. A linear mixed

model was used and the log of RT (Reading Time) was taken as the dependent variable. The statistical

analysis in the first set of experiments showed that the condition with 3 characters visible on the left of

the fixation allowed significantly faster reading than all the other conditions except the control condition.

In the second set of experiments, the condition with 7 characters on the right of the fixation allowed

significantly faster processing compared to all the other conditions except the control condition (P<0.05

in both cases).

Experiment V

Experiment V confirmed the results from the previous experiments. There was no significant difference in

reading time under the two conditions.

Conclusion

The five experiments mentioned above led to the conclusion that the perceptual span of readers of Hindi

in Devanagari consists of 11 aksharas (including blank spaces): 3 to the left of the fixation, the akshara

under fixation and 7 aksharas to the right of the fixation.

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Conscious Recognition of Neuro-Feedback

Introduction: The aim of this paper is to assess Neuro-Feedback as a method for studying the

relationship between neural activity and subjective experience. We will operate within the specific

context of frontal lobe alpha-beta rhythms, and mental states like ‘relaxing’ and ‘concentrating’.

Traditional Neuroscience treats subjective experience as an epiphenomenon and therefore, doesn’t engage with it directly. As a reaction to this trend, the program of Neuro-Phenomenology was put

forth (Varela, 96). Here, both experience and neural activity are placed on equal footing. The aim is

to study the ways in which they mutually constrain each other rather than assuming one is causally

prior to the other. This alternate line of inquiry has much to contribute to mainstream Cognitive

Science, but it faces a number of hurdles. Notably, there’s the practical difficulty of collecting first

person and third person data along a common timeline, and then the theoretical problem of

establishing causality between data from two completely different epistemological domains. A recent

paper (Bagdasaryan, 2013) discusses these challenges at length and offers Neuro-Feedback as a

pragmatic solution.

Neuro-Feedback setups involve subjects learning to regulate their own neural activity. This is made

possible by transforming their neural activity into visual or auditory sensory stimuli. In this way, the

stimulus both affects, and is affected by, the subject’s brainwaves. This has a fairly long history of

being used for Psycho-Therapy, but the same can’t be said of its use as a research tool in the Cognitive Sciences. This is surprising, because as a paradigm it can offer a number of advantages.

This is because in Neuro-Feedback, subjective experience of perceiving and controlling a certain

neural activity becomes braided with objective measures of the same, in an iterative causal loop

(Bagdasaryan et al, 2013). This potentially allows us to overcome both the practical challenge of

placing data from first and third-person approaches along a common timeline, and the theoretical

challenge of establishing causality between the two.

Method: For us to realize this potential, however, we need to first establish that there is, in fact, a

subjective experience of perceiving and controlling neural activity that is accessible to our conscious

selves. For this, we offer a simple experiment, where subjects discriminated between auditory

feedback, and non-feedback situations. Here, subjects were made to put on an EEG cap developed

in our lab (built using only open-source resources), and also a pair of earphones (this was done after

obtaining informed consent according to appropriate ethical standards).

In the feedback cases, the tones coming out of the earphones depended on the subject’s neural

activity according to some rule (frontal lobe alpha/beta ratio mapped to pitch of MIDI piano tones),

while in the non-feedback cases, the tones did not depend on the subject’s neural activity at all, and

instead were coming from a pre-recorded file. The only way subjects could discriminate between the

two cases was to learn to consciously perceive how their mental states related to the tones in

feedback or to consciously control the tones by manipulating their own mental state. All other

possibilities, like subjects using muscular activity instead of mental activity, or recognizing some

artifact present in the recorded sound, were controlled for.

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Results: We found that subjects could discriminate between the two cases with a frequency higher

than chance. We also collected the cognitive strategies subjects used through an interactive interview

which involved the subject demonstrating, in real-time, his or her strategies to the interviewer. In

general, we found that subjects who adopted a control strategy over an estimation strategy did

better, which agrees with studies in the literature which claim that our perceptual abilities come after

our control abilities during the development of new sensorimotor skills (Kotchoubey, 2002).

Largely, subjects used what can be called a ‘relaxation’ strategy for driving the tones one way (higher pitch), and a ‘concentration’ strategy for driving the tones lower (in pitch). This agrees well with the

literature on alpha and beta rhythms, but more than that it also adds interesting nuances to what we

mean by the words ‘relaxation’ and ‘concentration’ if indeed those are the most apt terms to describe

the mental actions that best relate to the alpha -beta ratio.

Future Studies: In the future, we plan to see how users get better with more training, and how

these skills transfer to situations where there’s no help from any artificial device. We also want to explore other setups with the device involving more features of the brainwaves, and in turn ‘richer’ soundscapes. Within these setups it would very interesting to see what meaning the various qualities

of the tones will carry about mental states/actions; what will it mean for the tones to be ‘mellow’ or ‘steady’ or ‘stretched’ or ‘flat’, and how will the meaning vary among the different subjects.

Keywords: Neurofeedback, Alpha Rhythm, Brain Music, Neurophenomenology, Brain States,

Perception

Bibliography:

Bagdasaryan, Juliana, and Michel Le Van Quyen. "Experiencing your brain: neurofeedback as a new

bridge between neuroscience and phenomenology." Frontiers in human neuroscience 7 (2013).

Kotchoubey, Boris, et al. "Can humans perceive their brain states?." Consciousness and Cognition 11.1

(2002): 98-113.

Varela, Francisco J. "Neurophenomenology: A methodological remedy for the hard problem."

Journal of consciousness studies 3.4 (1996): 330-349.

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A computational model of dopamine-serotonin modulation in

Basal Ganglia: Towards understanding the cognitive deficits in

Parkinson's Disease patients.

B. Pragathi Priyadharsini

1, V. Srinivasa Chakravarthy

1, Balaraman Ravindran

2,

Ahmed Moustafa3

Department of Biotechnology1, Department of Computer Science and Engineering2,

Indian Institute of Technology, Madras, Chennai, 600036, India.

School of Social Sciences and Psychology3, University of Western Sydney.

[email protected]

Extended Abstract Summary:

Efficient decision making typically requires optimizing a dual objective:

maximize reward; while minimizing risk. In our risk-based decision making

framework, this dual objective is embodied in a Utility function (U) which is a linear

sum of expected reward or Value, V, and reward variance or Risk, h. Experimental

evidence suggests that the striatum serves as a substrate for value computation

(O'Doherty et al, 2006). In our recent modelling work, we proposed that the striatum

can compute risk also in addition to value, opening up the possibility that the Basal

Ganglia (BG) are capable of risk-based decision making. In that model it was

proposed that the serotonin (5HT) in the striatum can be interpreted as the weighting

factor that combines value and risk terms in the utility function (Priyadharsini et al.,

2012). This novel way of associating 5HT to risk based decision making successfully

reconciled the diverse functions of this neuromodulator in reward, punishment, and

risk learning, under a unified framework.

The model of Priyadharsini et al. (2012), which was a lumped model, is currently

expanded into a network model of BG. We show, from theoretical considerations, that

the activity of D1R expressing Medial Spiny Neurons (MSNs) in the striatum

represents value, while the activity of MSNs that co-express D1R and D2R can

represent risk. We propose that serotonergic projections to striatum modulate the

activity of D1-D2 co-expressing neurons, so as to alter risk-sensitivity. The proposed

network model of BG was applied to explain the results from the following cognitive

test beds: 1) a stochastic two armed bandit problem of bee foraging (Real et al, 1981),

and 2) a reward learning study on healthy controls and Parkinson's Disease (PD)

patients by Bodi et al. (2009) showing an increased reward sensitivity in the recently

medicated patients, whereas an increased punishment sensitivity in the never-

medicated PD patients.

Introduction:

Decision making in Reinforcement Learning (RL) involves maximization of

the rewards obtained. When these rewards are uncertain, the optimal policy should

seek to minimize the variances in the reward (also termed as risk), while maximizing

the mean of the rewards received on executing an action [1]. In risk-based decision

making, this composite aim is achieved by combining the mean reward (Value) and

reward variance (Risk) in a single function known as the Utility function [2]. A group

of nuclei in the midbrain called the Basal Ganglia (BG) are functionally capable of

performing this task of risk based decision making [3] through RL [4]. BG dynamics

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affect the action selection through direct pathway (DP) or indirect pathway (IP) [5] –

the terms DP and IP notify the method by which BG influences the cortical activity

that eventually controls action execution. The direct influence of the striatum (nucleus

that is the major input port of BG) on Globus Pallidus interna (GPi: nucleus that is the

output port of BG) is known as DP; whereas the indirect influence of the striatum

through Globus Pallidus externa - Subthalamic nucleus (GPe-STN) on GPi is known

as IP. Neuromodulators such as dopamine (DA) and serotonin play key roles in BG's

action selection dynamics.

Serotonin is known to influence risk based decision making – On reducing the level of

brain tryptophan (a serotonin precursor) risky choices are more preferred to safe

choices [6, 7]. In our earlier work [8], we have proposed that the role of serotonin in

BG can be interpreted as the weighting factor that combines value and risk in utility

function. The model of [8] was able to explain the some of the divergent roles of

serotonin in punishment sensitivity, time scale of reward prediction, and risk

sensitivity, and combine them in a single framework. In that model, dopamine (DA)

was interpreted as Temporal Difference error (h) consistent with its interpretation in

actor-critic models of BG [4]. The model of [8] was a lumped model that did not

concern with mapping the various components of the model to biological

counterparts. In this work we present a network model of BG, cast within an

expanded Reinforcement Learning (RL) framework. This network model of BG is

tested on various tasks, to prove its efficiency in modelling dopamine and serotonin

regulated risk based decision making.

Methods:

In the proposed model (schema in Fig. 1), the value (V) function (Eqn. 1a) is

related to the activity of the D1 receptor (R) expressing medium spiny neurons (MSN)

in the striatum; and the risk (h) function (Eqn. 1b) to the activity of the D1R and D2R

coexpressing (D1R-D2R) MSNs. The utility (U) function [8] is then built as a

combination of value and serotonin modulated risk function (Eqn. 1c) in which the

serotonin is represented by the parameter g. In the equations, x(st,at) denotes the

cortical input representing a selection function for state (represented by s) and action

(a) at time (t); and WD1/D2/D1D2 represents the synaptic weight associated with the

D1R, D2R and D1D2R expressing MSNs respectively. The response of each MSN

(D1/D2/D1D2)R is characterised by its gain function (そD1/D2/D1D2) (Fig. 2), which we

assume is modulated by striatal dopamine, hV (Eqn. 2). We represent the gain function

of D1R neurons as an increasing sigmoid of hV (Eqn. 3a), whereas for the D2R

neurons it is a decreasing sigmoid function of hV (Eqn. 3b). D1R-D2R co-expressing

neurons are proposed to have an even gain function (Fig. 2), which combines the gain

functions of D1R and D2R expressing neurons (Eqn. 3c).

The D1R MSNs in the model project via DP (whose activity is denoted by xDP – Eqn.

4), and the sum of D2R and the serotonin-modulated D1R-D2R MSNs activity project

(xIP – Eqn. 5) through IP. The GPe-STN dynamics for input xIP is provided by Eqn. 7.

The action selection happens in the GPi (Eqn. 8a) by following GEN (Go-Explore-

NoGo) policy that is dependent on the change in utility function (hU: Eqn. 6) as

opposed to our previous works of using hV [5, 9, 10]. Representing the final activity of

each pathway as a product of respective そD1/D2 (hU) and the weights of each pathway

(そD1*WD1*x(s,a) for DP, and そD2*VSTN for IP) at the GPi ensures that the higher value

of hU drives the hill-climbing on the utility function by choosing the same action

selected at the previous time-step of the input (x) presentation ('Go' dynamics). The

lesser value of hU does the opposite by withholding from choosing any actions

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('NoGo' dynamics). The intermediary values of hU result in exploration of action space

('Explore' dynamics). It is assumed that the connections between GPi (Eqn. 8a) and

thalamus (Eqn. 8b) are Inhibitory. The activity in thalamus is taken to be simply the

negative of that seen in GPi (Eqn. 8). The action possessing the maximum xThal is

taken to be selected (Eqn. 8b). Here wSTN-GPi denotes the weight of the synaptic

connection between STN and GPi, and k is a time constant.

1

1 2

t t D t t

t t D D t t

t t t t t t

V( s ,a ) W x( s ,a ) ( a )

h( s ,a ) W x( s ,a ) ( b )

U( s ,a ) V( s ,a ) h( s ,a ) ( c )

(1)

V t t(t) r V(s ,a )

(2)

1 1 1

2 2 2

1 2 1 2 1 2

D t t D D V t t

D t t D D V t t

D D t t D D D D V t t

W ( s ,a ) ( ( t ))x( s ,a ) ( a )

W ( s ,a ) ( ( t ))x( s ,a ) ( b )

W ( s ,a ) ( ( t ))x( s ,a ) ( c )

(3)

1 1DP D U D t tx ( (t ))W x(s ,a ) (4)

2 2

1 1 2 1 2

IP D U D t t

D t t D D U D D t t

x ( ( t ))W x( s ,a )

sign(W x( s ,a )) ( ( t )) W x( s ,a )

(5)

1 1U t t t t(t ) U(s ,a ) U(s ,a )

(6)

.

STNs STN STN STN GPE

STN STN STN

.

GPEg GPE GPE GPE STN IP

u u w V x

V tanh( u )

x x w x V x

(7)

Figure 1: Illustrating

the striatal D1R,

D2R, D1R-D2R

MSNs, Direct (DP),

Indirect (IP)

pathways of BG.

GPi i

.

gpi GP DP STN Gpi STN

.

ThalThal Thal DP STN Gpi STN

x x ( x w V ) (a)

x x ( x w V ) (b)

(8)

Results:

This approach has been able to successfully model key properties of risk based

decision making, in a stochastic two armed bandit framework. One such behavior that

is captured by our network model is the non-linearity in action selection seen in

humans – risk aversive in the case of rewarding outcomes and risk seeking in the case

of punitive outcomes [11] (Fig. 3). The network model also explains the risk sensitive

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nature of the bees in a foraging task [12] (Fig. 4). Further, we modelled a reward

learning study on healthy controls and PD patients by Bodi et al. (2009). In this

model, the never-medicated condition was implemented by limiting hV in Eqn. 2; and

the recently-medicated condition by a constant (>1) multiplicative factor to hV. The

model reproduces the main experimental results (Fig. 5) viz., increased reward

sensitivity in the recently medicated, while there is an increased punishment

sensitivity in the never medicated PD patients [13].

Finally, we propose that our network model can help us understand the effect of

dopamine and serotonin on the BG dynamics, in controls and PD condition, since it

takes into account the neurological correlates for the lumped model [8] through the

striatal (D1R, D2R, D1D2R MSN) cellular correlate properties present naturally. This

model could be applied to understand the BG-dopamine and serotonin related

cognitive and emotional disorders including impulsivity, anxiety, depression,

schizophrenia and bipolar disorder.

Keywords: Decision making, Reinforcement learning, Basal Ganglia, Striatum,

Dopamine, Serotonin, Value, Risk, reward, punishment.

References: 1. Sutton, R., Barto, A., Reinforcement Learning: An Introduction. Adaptive Computations and

Machine Learning1998: MIT Press/Bradford.

2. Bell, D.E., Risk,return and utility. Management Science, 1995. 41: p. 23-30.

3. d'Acremont, M., et al., Neural correlates of risk prediction error during reinforcement

learning in humans. Neuroimage, 2009. 47(4): p. 1929-39.

4. Joel, D., Y. Niv, and E. Ruppin, Actor-critic models of the basal ganglia: new anatomical and

computational perspectives. Neural Netw, 2002. 15(4-6): p. 535-47.

5. Chakravarthy, V.S., D. Joseph, and R.S. Bapi, What do the basal ganglia do? A modeling

perspective. Biol Cybern, 2010. 103(3): p. 237-53.

Figure 2: The characteristic gain

functions representing various DA

receptors containing MSNs. The unit h on the X-axis defines DA activity. In our

study, we assume it to be represented by

hV (Eqn. 2) or hU (Eqn. 6) appropriately.

Figure 3: The probability of choosing the

safe reward is plotted against g (representing serotonin) in rewarding and

punitive cases. In the rewarding case, safe

reward: [r = 1; p = 1], risky reward: [r = 2

with a p = 0.5, else r = 0]. Similarly in the

punitive case, safe reward: [r = -1; p = 1],

risky reward: [r = -2 with a p = 0.5, else r

= 0] (here 'r' denotes reward and 'p'

denotes probability).

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6. Long, A.B., C.M. Kuhn, and M.L. Platt, Serotonin shapes risky decision making in monkeys.

Soc Cogn Affect Neurosci, 2009. 4(4): p. 346-56.

7. Murphy, S.E., et al., The role of serotonin in nonnormative risky choice: the effects of

tryptophan supplements on the "reflection effect" in healthy adult volunteers. J Cogn

Neurosci, 2009. 21(9): p. 1709-19.

8. Priyadharsini, B.P., B. Ravindran, and V.S. Chakravarthy, Understanding the role of

serotonin in basal ganglia through a unified model, in Artificial Neural Networks and

Machine Learning–ICANN 20122012, Springer. p. 467-473.

9. Kalva, S.K., et al., On the neural substrates for exploratory dynamics in basal ganglia: A

model. Neural Netw, 2012. 32: p. 65-73.

10. Sridharan, D., P.S. Prashanth, and V.S. Chakravarthy, The role of the basal ganglia in

exploration in a neural model based on reinforcement learning. Int J Neural Syst, 2006.

16(2): p. 111-24.

11. Kahneman, D., Tversky, A.;, Prospect theory: an analysis of decision under risk.

Econometrica, 1979. 47: p. 263-292.

12. Real, L.A., 1981. Ecology 62: p. 20-26

13. Bodi, N., et al., Reward-learning and the novelty-seeking personality: a between- and within-

subjects study of the effects of dopamine agonists on young Parkinson's patients. Brain, 2009.

132(Pt 9): p. 2385-95.

Figure 4: Testing our model on the risk based

decision making framework: Implementing the

bee foraging task (Real. 1981). The bees were

let to forage with blue and yellow flowers

providing the same mean reward, but with

varying probability. The reward schedule is

blue: r = 1(1), yellow: r = 3(1/3) and 0(2/3).

The numbers in brackets denote the

probability. After a certain number of trials

(trial 15: Red line, II), the contingencies were

reversed for the blue and yellow flowers.

Graph III denotes the expt. result from [12],

and I denotes our model result.

Figure 5: Reward learning in

Controls and PD patients (Bodi et

al, 2009)

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1

Modeling Choices at the Individual Level in Decisions from Information

Search

Neha Sharma1*and Varun Dutt2

1 School of Computing & Electrical Engineering, Indian Institute of Technology, Mandi

2 School of Computing and Electrical Engineering, School of Humanities and Social Sciences, Indian Institute of Technology, Mandi

*Academic Block, Paddal Ground, Indian Institute of Technology, Mandi -175001, H.P, India [email protected]

ABSTRACT Information search before making a consequential choice is a practice we commonly follow in our daily life. For example, we try clothes before dressing for a party, and we taste different wines in a wine-tasting before deciding on what to buy. The act of searching for information before making a consequential choice has been studied in the laboratory using the sampling paradigm (Gonzalez & Dutt, 2011; Hertwig et al., 2004). In the sampling paradigm, respondents are presented with gambles with two options, risky and safe (represented by two blank buttons). The risky option has two outcomes, high and low, with a probability distribution that is unknown to the respondents. The safe option, in constrast, gives a constant outcome with a probability = 1.0 (the respondents do not know this probability). During information search, the respondents can sample both options by pressing on either of the two buttons as many times as they want to and in any order they desire. Each click of a button reveals an outcome that is generated using the underlying probability distribution. Once respondents are satisfied with their sampling, they are asked to make one final consequential choice. Popular models of human choice in the sampling paradigm have so far been used to predict the final choice aggregated across participants (Sharma & Dutt, in press). For example, according to Sharma and Dutt (in press), the Primed-Sampler (PS) model(Hertwig,2011), the Natural-Mean Heuristic (NMH) model(Hertwig & Plesac,2010), and the Instance-Based Learning (IBL) model(Gonzalez & Dutt,2011) are popular algorithms for explaining aggregate choices. However, this aggregation does not explain how individual participants search for information and consequently choose one of the options. Here, we test the ability of the three computational models of aggregate choice to explain individual choices after information search. The PS model depends upon the recency of sampled information, where the model looks back a few samples on each option before making a final choice. On the other hand, the NMH model is a generic case of the PS model. In this model, one calculates the natural mean of outcomes observed on each option during sampling, making a final choice for the option with a larger natural mean. Similarly, the IBL model consists of experiences (called instances) stored in memory. Each instance’s activation is a function of the frequency and recency of the corresponding outcomes observed during sampling in different options. These activations are used to calculate the blended values for each option, where the option with the highest blended value is the one chosen at final choice.

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2

In order to compare human and model choices at the individual level, we consider “observations” in the data. An observation is a participant playing a gamble in a dataset. We evaluate an “error ratio” (i.e., the ratio of incorrectly classified final choices between model and human observations divided by the total number of observations). Firstly, for each observation in human data, we determine the final choice (risky or safe). A similar final choice is then derived for a model observation by exposing the model to the way humans sampled information. This derived choice is then compared to the choice made by the corresponding human observation. The final choices from each of the three models is simulated for 2,370 observations and then compared to the same number of human observations in the largest publically available dataset in the sampling paradigm (the Technion Prediction Tournament dataset). For a model, the error-ratio is calculated as: Error Ratio = (RS+SR)/ (RS+SR+RR+SS) Where, RS was the number of observations where the model predicted a safe choice but the human made a risky choice. SR was the number of observations where the model predicted a risky choice but human made a safe choice. Similarly, the RR and SS were the number of observations, where a model predicted the same choice (risky or safe) as made by a human observation in human data. The smaller the value of the error ratio, the more accurate is a model in accounting for individual choices of human participants. For some observations, a model was equally likely to choose a safe or a risky choice. Such cases were discarded from the error ratio calculation and were termed as uncategorized (UN) cases. Thus, more are the number of uncategorized cases; the poorer is the corresponding model’s algorithm in accounting for the size of human data. Our results from model simulation show that the NMH model performs best at accounting for the individual choice and it is followed by the PS and IBL models (see error ratio in Table 1). However, both the PS and NMH models also have 26 and 33 UN cases compared to 0 such cases from the IBL model. These UN cases decrease the efficiency of the NMH and PS models. Table 1. Summary of results from the three DFE models. Model Parameters UN Observations Error ratio PS N = 17 26 0.173 NMH - 33 0.161 IBL d=9.42, j=0.32 00 0.255 Up to recently, literature in judgment and decision making had compared models by evaluating their performance at the aggregate level. In such comparisons, the average risk-taking from the model was compared to the average risk-taking from human data. However, we compared a model’s performance at the individual participant level. We find that that the top three models of aggregate choice are able to account for individual choices up to a certain extent (error ~ 15% to 25%). Our immediate future research in this area will be to investigate the reasons for the errors from models in more detail and to improve model algorithms to achive greater accuracy. Keywords: Instance-Based Learning, Natural-Mean Heuristic, sampling, choice, decision making, cognitive models. Acknowledgment: The authors are grateful to Dr. Ido Erev, Technion - Israel Institute of

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Technology, for providing the Technion Prediction Tournament dataset. Also, the authors would like to thank Indian Institute of Technology, Mandi for providing computational resources for this project. References: 1. Gonzalez, C., & Dutt, V. (2011). Instance-Based Learning: Integrating Sampling and Repeated Decisions From Experience.

Psychological Review. Advance online publication

2. Hertwig, R. (2011). The psychology and rationality of decisions from experience. Synthese.

3. Hertwig, R., & Pleskac, T. J. (2010). Decisions from experience: Why small samples? Cognition, 115, 225–237. 4. Decisions from Experience and the Effect of Rare Events in Risky ChoicePsychological Science August 2004 15: 534-539,

5. Sharma. N. & Dutt. V.(in press)” Decisions from Experience: How Models of Aggregate Choices Explain Individual Choices?”,In 4th IEEE International Advance Computing Confrence,Gurgaon,India,2014.

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Effect of Language Proficiency on the Processing Cost associated with

Language Switching

Mishra Khushboo Ashok Kumar*, H. S. Asthana**, I. L. Singh**

Department of Psychology,

B.H.U., Varanasi.

Keywords: Language Switching, Language Proficiency, Inhibitory control model, Processing cost

Language switching has become an inevitable ingredient of bilingual discourse. Recent experimental

studies have provided an insight into the co-activation and interaction of two languages among

bilinguals’. Inhibitory Control Model (Green, 1998), postulates that this co-activation results in a

competition across languages. Thus, in order to resolve this competition one of the two languages has

to be inhibited. The decision as which language will be inhibited lies on the will of the speaker or the

contextual cues. Switching from one language to other involves some amount of cognitive cost in

terms of increased reaction time and error rate in comparison to monolingual condition. In addition,

dominance in a particular language plays a crucial role in the profile of cognitive cost associated with

language switching. Studies have also found that when the native language dominant bilinguals

switch from native (dominant) language to a non-native (less dominant) language, they require less

time than switching from non-native language to their native language. Further, studies have also

addressed the problem of balanced bilingualism in this context. These studies report less

asymmetrical profile in the context of language switching amongst them. Previous studies assessed

language dominance in terms of self-rated proficiency in both of the languages. However, many other

latent factors may affect the proficiency in a particular language such as frequency of usage of a

language in day to day living and confidence in a particular language. The present study intends to

take into account not only the participants self-rating on the reading, writing, speaking, and

comprehension but also on the confidence in speaking and understanding and frequency of usage of a

particular language.

Hypotheses:

1. Hindi dominant bilinguals would require more cognitive cost in backward switching (English

to Hindi) in comparison to forward switching (Hindi to English).

2. Balanced bilinguals would not differ in terms of the cognitive cost in both forward and

backward switching.

*Research Scholar

**Professor

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Method:

Sixteen bilinguals with age range of 23 to 28 years participated in the study. The participants

were assessed on the Language Self-Evaluation Scale (LSES). This scale requires participants to

rate their proficiency not only on the various aspects of language (like reading, writing, verbal and

comprehension) in general, but also in varied day to day activities. LSES also provides subjective

rating on the frequency on language usage by the participants, in various contexts. Cued Picture-

naming task was used to examine the cognitive cost associated with language switching. The task

was developed using Superlab Software version 4. Cedrus voice key was used to record the voice

onset reaction time (VoRT) of the participants. The audio file of the responses were also maintained

using an external microphone in order to later check the accuracy of the response. The stimulus

involved ten line drawings which were to be named by the participants on the basis of the language

cues. In the task, a single trial constituted of a fixation cross, then the language cue, which could be

either へ へ or say was followed by the presentation of a line drawing. The participant was required to

name the picture as soon as it was flashed over the computer screen. When the word へ へ was flashed

the participant were required to name the line drawing in Hindi while when the word say was flashed

the participant were required to name the picture in English . The picture disappeared from the

computer screen as soon as the participant responded to it. After the participant responded to the

picture, a blank screen was flashed over the computer screen. The whole experiment involved 600

trials. The participants were provided short rest pause of five sec after every 20th trial and a long rest

pause of 30 sec after every 200th trial.

The Pictorial description of the task is depicted below:

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Design:

A 2 (Proficiency: Hindi dominant bilinguals and Balanced bilinguals) × 2 (Transition: Hindi

to English, English to Hindi) mixed factorial design with repeated measures on the last factor was

employed.

Results:

Table 1: Mean and SD of Hindi dominant and balanced bilinguals against transition

Proficiency

Transition

Forward Switching

Mean (SD)

Backward Switching

Mean (SD)

Hindi dominant bilinguals 854.32 (52.45) 931.30 (95.54)

Balanced bilinguals 1005.11 (101.16) 1098.14 (159.26)

Figure 1: Mean reaction time of Hindi dominant and balanced bilinguals against transition

The main effect of proficiency yielded an F ratio of F (1, 7) = 9.481, p = .018, indicating that

the mean change score was significantly greater for balanced bilingual group (M = 1051.63, SD =

113.43) than for Hindi dominant bilinguals (M = 892.81, SD = 73.12). The main effect of Transition

yielded an F ratio of F (1, 7) = 13.974, p = .007, indicating that the mean change score was

significantly higher in the backward switching (M = 1014.72, SD = 76.21) than in the forward

switching (M = 929.72, SD = 61.89). The interaction effect was non-significant, F (1, 7) = 0.075, p =

0.79. Further, t test revealed significant effect of transition for the Hindi proficient bilinguals (t =

4.468, df = 7, p = .003) but not for balanced bilinguals (t = 1.873, df = 7, p = .103).

0

200

400

600

800

1000

1200

Balanced Bilinguals Hindi Dominant

Bilinguals

Forward Switching

Backward Switching

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Discussion:

The present study examined the effect of language proficiency on the processing cost

associated with language switching. The results clearly indicate significant mean difference of

backward and forward switching among Hindi dominant participants. This finding supports the first

hypothesis which stated that Hindi dominant bilinguals will require more cognitive cost in backward

switching in comparison to forward switching.

Results further reveal that the mean difference was found non-significant in the case of

balanced bilinguals and support the second hypothesis that there will be no significant difference

amongst balanced bilinguals in the cognitive cost in forward and backward switching. However,

balanced bilinguals required more reaction time in backward switching (M =1098.14) as compared to

its counterpart forward switching (M = 1005.11). Thus further research is required in this context.

Overall, the findings of this study clearly indicate that language proficiency does play a

crucial role in the context of language switching. Also, higher proficiency in a particular language

results in asymmetry in the switching profile.

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Page 56: ABCDEF FF CAFBFFCDEF FF ˇB˘ ˆ˙ ˝˛ ˚F˜ F ˘! #B$accs2014/proc.pdf · 2014-02-27 · Structural and Functional networks underlying auditory processing in children with autism

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Page 57: ABCDEF FF CAFBFFCDEF FF ˇB˘ ˆ˙ ˝˛ ˚F˜ F ˘! #B$accs2014/proc.pdf · 2014-02-27 · Structural and Functional networks underlying auditory processing in children with autism

Title: Laterality in the Iowa Gambling Task: Does sensitivity to rewards-punishment alter regulatory control? Author: Dr. Varsha Singh, Assistant Professor, Humanities and Social Sciences, Indian Institute of Technology Delhi, New Delhi 110016, India. Introduction and research problem: The right hemispheric dominance observed in decision-making in the Iowa Gambling Task (IGT) is yet to be understood. The task involves rewards and punishments that are processed along the dual routes of intertemporal attributes, reflecting cognition-intensive processing, and frequency attributes, reflecting automatic processing. Drawing from dual process theories and lateralization related to reward-punishment, it was hypothesized that handedness as a measure of laterality would have an effect on regulatory control (defined as a failure of cognition-intensive systems to over-ride automatic processing systems), and that the effect would differ across reward and punishment variants of the task. Methods and design: The Edinburg Handedness Inventory was used to compare laterality quotients [left-handers (quotient ≤ 50), mixed-handedness (51–99), right-handedness (≥ 100)] and usage of dominant or non-dominant hand (left and right hand) to perform the IGT in two variants (reward and punishment) (N = 320, males = 160). Decision-making scores were entered into a 2 (attribute: intertemporal/frequency) × 2 (hand recruited: left/right) mixed-design ANOVA, analyzed for three groups (handedness: left/mixed/right); variants were analyzed separately. Results and discussion: In the reward variant, the effect of attribute was significant across all three conditions of handedness (p < .05 for left-handedness; p < .01 for mixed- and right-handedness), although the interaction effect of attribute and hand recruited was insignificant (p = .09 in mixed-handedness). In the punishment variant, the effect of attribute as well as the interaction effect of attribute and hand recruited were insignificant across the three groups. As expected, lateralization of regulatory control reflected in the effect of attribute type showed differential effects of hand recruitment in variant type across conditions of handedness.

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A pilot study evaluating efficacy of sung vs. spoken speech to facilitate social attention and communication in children with Autism Spectrum Conditions Arkoprovo Paul, Jeffrey Valla, Megha Sharda and Nandini C Singh National Brain Research Centre, Manesar, Gurgaon 122050, India.

Background: Children with Autism Spectrum Conditions (ASC) experience significant impairments in social and communication development which have been shown to improve with early intervention efforts. Although the research so far has primarily concentrated on deficits in the speech and social communication domain, recent behavioural studies have provided evidence for preserved or enhanced musical abilities in ASC (Heaton, 2012). At the same time, there has been an increasing interest in the use of music for rehabilitation in various neuro-cognitive disorders, with a special emphasis on improving socio-communicative responsiveness in children with ASC (Accordino et al, 2007, Wan et al, 2011). Recent neuroimaging studies on children with ASC have shown robust engagement of the auditory cortex to sung speech as compared to spoken speech stimuli [Lai et al, 2012; Sharda et al, 2013 (under review)]. This suggests that the use of sung speech may be beneficial for children with ASC not only as a tool for learning social engagement and emotional-cues, but also as a neural ‘back door’ for improving social attention and communication.

Objectives: The aim of the current study is to investigate the behavioural salience of sung speech as opposed to spoken speech on attention, engagement and responsiveness in existing treatment programmes for children with ASC. Methods: 14 children aged 3-5 years, diagnosed with or at risk of having Autism Spectrum Conditions, have so far participated in this ongoing study. The diagnosis of ASC has been made using DSM V and/or ICD-10 criteria. A detailed questionnaire was used to acquire background information regarding family and medical history and developmental milestones of each child. Participants undergo a thrice-a-week, 12 week long intervention programme (36 sessions) administered by a team of qualified therapists in a clinical setting. The programme includes two parts; Part I is integrated in group sessions and Part II is integrated in individual sessions. In Part I children are passively exposed to videos with sung or spoken narrative content Part II includes eliciting active responses to spoken and sung forms of distinct categories of verbal directives delivered by therapists.. These sessions are video-recorded for post-hoc observational coding of metrics like joint attention, eye gaze, orienting, repetitive behaviour etc. by blind raters. Results: Data collection is in progress. Preliminary data indicate increased engagement and responsiveness to sung stimuli in children with ASC based on assessment and analysis of observational videos. These preliminary findings are encouraging and suggest that music may be effective in improving attention and communicative function in ASC. Conclusion: The outcomes of the study will be instrumental in establishing the efficacy of using song and music-based approaches to improve social attention and communication in children with ASC and provide a framework for developing effective therapeutic interventions.

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Application of Eye Movement Saccades to Build a Brain Computer Interface

Mounika Mesa 1, Anuj Shukla 2 4, Bapi Raju Surampudi 2 3

1 Dept. Of Computer Science Engineering, Rajiv Gandhi University of Knowledge Technologies, Basar.

2 Centre for Neural and Cognitive Sciences, University of Hyderabad. 3 School of Computer & Information Sciences, University of Hyderabad. 4 Dept. of Neurology, Nizam’s Institute of Medical Sciences, Hyderabad.

Patients with disabilities such as locked-in, motor neuron diseases have a limitation to use common communication devices like keyboard, mouse, joy stick, mobile touch screen etc. Brain Computer Interface (BCI), an innovative frontier of science and technology is a direct communication system that responds to the thoughts of users suffering with such adverse ailments and gives feedback to the users by converting their 'command' into an input control for a device. Eye tracking provides a more convenient environment for studying selection or classification-based strategies for BCI development. There are several existing research investigations considering eye blinks as selection command or input modality in BCI. However, such systems usually seem to be less accurate and slow compared to other modalities. It is also tedious to account for involuntary eye blinks in eye tracking experiments. Hence, in this paper, we present a simple, effective tool based on the usage of eye movement saccades for typing keys on a virtual keyboard.

The assumptions made are: the response time required to select a key (keyboard/keypad) manually with fingers is higher compared to selecting it using eye movement saccades. The user’s intent to select a ey using motor activity depends on a priori visual information related to the position of target key in the setup.

The experimental setup for data acquisition using eye tracking is designed using SR Experiment Builder while the recording data is acquired using EyeLink-1000 and is further analysed using Data Viewer. On the other hand, the same experimental setup is designed using Psych Toolbox where the data is acquired without using eye tracker and is analysed using MATLAB. A total of 6 blocks, each containing 10 trials pertaining to key selection is used as the stimulus. We chose a virtual model of numerical keyboard of a standard keyboard excluding the key-5 whose position is used for the fixation cross in our setup. Three normal users participated in this experiment who gave a prior consent of participation. The trials are designed in such a way that the user is directed to the next trial only on fixating at the centre cue of the screen followed by the stimulus in which the focus of the user rests on the interest area pertaining to the highlighted key for at least 1500ms.

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Figure-1: Frame-wise representation of the trials in the experimental design

The validation of the eye trac r’s recording data is done using the user's eye movement video trial frames and the key response of the users for randomized and sequential trial blocks and the eye movements and key responses show consistent results. To account for our assumptions and differences in response times across trials of all the blocks and users, we averaged the amount of time spent on each key for all the respective trials. This gaze duration measure represents the proportion of time a user spends on a particular highlighted key relative to all the other keys within a trial.

Figure-1: Graph showing the averaged reaction time plots across users for all trials of each key

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The graph plotted for the averaged reaction time across trials of each key and users shows a significant variation under the assumed conditions,

Where, Response time represents the time required by a user to respond to the stimulus displayed. ET_sequence represents the data collected using eye tracker when the keys 0-9 were presented sequentially across each block, Whereas, Non_ET sequence represents the occurrence of highlighted keys from 0-9 in a sequential manner in visuo-motor domain.

Non_ET_random represents the occurrence of highlighted keys from 0-9 which are randomized across the trials.

The above results show that the users are faster in performing the virtual key press by their saccades as compared to the manual responses. This allows us to think that saccadic signals as a potential mode of input to register response for people with hand disabilities or hemiplegic patients where people of this category are unable to use their hand for the basic life function. Especially these days, cell smart phones, tablet and computers are a common mode of communication. The use of saccadic response to select keys for dialling a number or typing emails would enable us to use it as a new mode of input. With this revolutionary and essential change, we can include people suffering from specific disabilities to the main stream and provide them with equal opportunities to interact with their environment effectively.

This could further be extended and used to create a setup to visually access all the keys of a virtual keyboard and control an environment of augmented reality.

Finally, it is not about convenience but for severely disabled people, development of such an interface could be the most important breakthrough representing a revolutionary and a technological improvement in the quality of life.

References:

1. Lalor EC, Kelly SP, Finucane C, et al. Steady-State VEP-based brain-computer interface control in an immersive 3D gaming environment. EURASIP Journal on Applied Signal Processing. 2005; pg:3156–3164.

2. Tangsuksant et.al. Directional Eye Movement Detection System For Virtual Keyboard Controller. BMEiCON. 2012.

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ROLES OF EXPRESSIONS IN CONSTRUING MEANING AT THE LEVEL OF DISCOURSE:

A STUDY OF NOMINALS AND DEMONSTRATIVES IN BENGALI

Soumya Sankar Ghosh, PhD Scholar, Jadavpur University

[email protected] Abstract Constructing meaning at the level of discourse always involves incorporation of large amount of information. The present work will show (i) the role of linguistic expressions in controlling the inflow of information in discourse interpretation and will also explore (ii) the role of the linguistic expressions in licensing valid inferences while interpreting a discourse. In doing so, the paper will conceptualize a linguistic expression as a repository of default structural information. This default structural information in conjunction with the background knowledge of the interpreter is crucial in figuring the intended sense of a communiqué.

While exploring the issues of meaning construction at the level of discourse, this work will compare the meaning construing capacities of nominals and demonstratives in Bengali. What motivates me in comparing these two types of expressions’ meaning construing capacities is as follows: Unlike nominals, demonstratives possess no contents. As a consequence, the role of demonstratives in the construction of meaning remains purely context sensitive; whereas the meaning construing capacities of the nominals are a complex interplay of context and the content. It is being argued by Ghosh [1], discourse level processing should have some sort of model-theoretic explanation for how in a context a particular nominal is connected with its other senses, since the meaning construing potentiality is determined strictly by the context. Sometime these connections are explicitly stated (as is the case with demonstratives), and sometime connections are inferred if the expressions are contentive (as is the case with nominals). In my approach, I will try to augment a model of language processing at the level of discourse, proposed by Karmakar and Kasturirangan [2,3,4,5], to maximize the scope of the model.

The proposed model conceives a linguistic expression as a mental regulation consisting of intending function (= I f) and contending function (= Cf). I f is useful in activating default contextual information associated with a particular linguistic expression; whereas Cf is unique in coercing the default contextual information for establishing connections across the discourse. These two functions, I will show, play a crucial role not only in construing meaning at the level of discourse but also in determining coherence and logical stability of a linguistic discourse.

References 1. Ghosh, S.S. (forthcoming). “Roles of Nominals in Construing Meaning at the Level of Discourse: With a Special

Reference to the Language Data drawn from Bengali”. To be presented at SCONLI 8, University of Kashmere. 2. Karmakar, S. and R. Kasturirangan (2011). “Structural and Structuring: Issues in designing an expression.”

In Jadavpur Journal of Philosophy, Vol. 21, No. 1, pp. 87-102. Kolkata, India: Jadavpur University. 3. Karmakar, S. and R. Kasturirangan (2011): “Metaphors and Creativity: Constructing Meaning in Language.” In

Proceedings of the Fifth Indian International Conference on Artificial Intelligence, 1710-1717. IICAI. Tumkur, India: Siddaganga Institute of Technology (India), St. Mary's University (Canada), EKLaT Research (India), and Infobright .

4. Karmakar, S. and R. Kasturirangan (2010). “Perspectivizing Space in Bダ┕lダ Discourse.” In Proceedings of the 32nd Annual Conference of the Cognitive Science Society, pp. 826-830. CSS. Austin, TX: Cognitive Science Society.

5. Karmakar, S. and R. Kasturirangan (2010). “Cognitive processes underlying the meaning of complex predicates and serial verbs from the perspective of individuating and ordering situations in Bダ┕lダ.” In Proceedings of the First International Conference on Intelligent Interactive Technologies and Multimedia, pp. 81-87. ACM. Allahabad, India: ACM IIIT Allahabad Professional Chapter & North India ACM-SIGCHI.

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Are an ability to shift attention and creative cognition related?

Priyanka Srivastava*, Saskia Jaarsveld**, Thomas Lachmann**

Cognitive Science Lab* International Institute of Information Technology, Hyderabad, India

Center for Cognitive Science, Cognitive and Developmental Psychology**

University of Kaiserslautern, Germany

Abstract

Objective

The current study aims to investigate the relationship between an ability to shift attention from one target/ task to another and creative cognition. We assume that performance on both tasks, although evolving in different time scales, might be based on a general cognitive flexibility. Two experiments were conducted (N1=50, with SPM; N2=50, with APM) by employing attentional blink (AB),working memory operation span (WM OSPAN), Raven’s progressive matrices (RPM), creative reasoning task (CRT), and test for creative thinking and drawing production (TCT-DP).

Methodology

Participants:

Total hundred and five volunteered (63 male and 42 female, between 18-30 years) participated in both the study for pay. The participants were recruited from either by the advertised email send to Kaiserslautern University students’ email-id, by contacting them by phone call from the list of participants showed interest to participate in future experiments. All participants reported having correct to normal vision. Participants were not familiar with the purpose of the experiment.

Materials:

In attentional blink (AB) or rapid serial visual presentation (RSVP), an array of English letters along with two digits were presented at the centre of the screen. Digits were presented as targets, with varying temporal gap from lag 1 to lag 8. Participants’ task was to identify the targets and report at the end of a particular trial. Participants were seated at a viewing distance of about 50 cm from the fixation mark (+).

Standard Progressive Matrices, and Advance Progressive matrices (SPM/APM) consisted of sixty and thirty six incomplete matrices respectively. Each incomplete matrix is displayed together with eight alternative possible answers. Participants’ tas was to complete the matrix by selecting the correct answer from the multiple alternatives given below. Participants were instructed to give the corresponding responses on a separate sheet given along with APM booklet.

Creative reasoning tas (CRT) consisted of an empty 3x3 matrix. Participants’ tas was to create an APM-like puzzle. Participants were instructed to make a puzzle similar to the puzzles they have solved. The puzzle was expected to have an answer / missing piece as well. Participants were requested to make the puzzle as original and complex as possible.

In working memory operation span (OSPAN) task, participants were presented with mathematical operation – word pairs varying from two to six sets. Participants’ task was to read the

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operation out loud and press “yes” or “no” to indicate whether the given answer was correct or incorrect and then recall the words in the order of the presentation. Procedure:

The study consisted of two sessions, including AB, WM OSPAN, SPM/APM, TCT-DP, and CRT. Half the participants performed AB followed by WM or vice versa in first session and APM/SPM followed by CRT and then followed by TCT-DP or vice versa, in second session. In this case, SPM/APM was always followed by CRT, but TCT-DP temporal order was changed across participants. In addition, sessions were also counter balanced across participants. The overall experiment lasted for approximately two hours.

Results and Conclusion

Currently, analysis is in progress. Based on second experiment (consisted of AB, WM OSPAN, CRT, APM and TCT-DP), N=50, results showed no significant correlation (p>.05) between AB and creative reasoning, suggesting possibly distinct cognitive mechanisms underlying these two processes. More can be suggested based on further analysis, which is expected to be completed soon.

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Affect and time perception

Bhawna, Shalini Mittal, Mithilesh Tiwari, Yogesh Kumar Arya and Tushar SinghDepartment of Psychology, Banaras Hindu University, Varanasi

There is a large body of literature to show the role of emotions in cognitive activity. However,

there is a dearth of studies analyzing the relationship between emotional states and estimation of

time durations. Furthermore, studies that have been conducted to investigate the relationship

between emotions and time perception have typically yielded inconclusive results. One possible

reason for these inconsistent findings might be the uses of non standardized emotional

manipulations that restrict the quantification and the replication of the results rather problematic.

Also these studies have used different type of emotional stimulus where the comparability of

these stimuli is a question. Having these gaps in mind the present study was conducted to

examine the effect of perceiver’s affective state and affective valance of the stimulus on

perception of time under retrospective paradigm. A total of 55 participants watched a visual clip

depicting a crime scene affectivity of which was manipulated by providing additional details

about the scene. Participants’ task was to reproduce the time duration for the stimulus. The

findings of the initial statistical analyses suggest that the estimation of the time duration was

significantly influenced by the affective state of the perceiver and perceived affective valence of

the clip. The detailed results are discussed in light of the existing theories of time perception and

are expected to add interesting findings to the current literature.

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On the road to being a simultaneous biliterate: cortical circuits in children learning to

read two distinct writing systems

Authors: S. Cherodath1 and N. C. Singh1*

Affiliations: 1National Brain Research Centre, NH-8, Nainwal Mode, Manesar, India - 122051

Abstract: The emergence of bilingual societies has given rise to educational milieu wherein

children are required to be biliterate, namely acquire reading skills in distinct writing

systems. To investigate how biliteracy shapes developing cortical reading networks, we

performed functional imaging on 34 simultaneous Hindi-English biliterate children matched

on reading ability across languages, as they read word and nonword stimuli. Hindi, an

alphasyllabary and English - an alphabetic system, differ in consistency of sound-to-letter

mapping or orthographic depth. Consequently, the inconsistent orthography of English

necessitates discrete reading strategies – lexical retrieval and phonological assembly, unlike

Hindi which being transparent, relies only on assembled phonology. Simultaneous biliterate

children recruited a shared reading network comprising bilateral hippocampi, precentral and

postcentral gyri (BA 3/4), middle and inferior occipital gyri (BA 18/19) and cerebellum,

which we attribute to similarity in phonological units across both languages. Factorial

analysis showed that stimulus type (word/nonword) modulated activity in bilateral inferior

frontal opercula (BA 44/48), superior parietal (BA 7) and left inferior parietal lobules (BA

40), and angular gyrus (BA 39). Orthographic differences were revealed by subsequent

comparisons which showed differential activation patterns for words and nonwords in

English but not in Hindi. Our findings also revealed an important role for hippocampus for

non-native language reading in children. We provide novel evidence for the role of

orthographic depth in shaping cortical reading processes early in development. Our results

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demonstrate that developing biliterate reading networks not only exploit similarities in

phonological representation but are also sensitive to differences in orthographic depth.

Keywords: bilingualism; development; fMRI; language; reading acquisition.

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Abstract

Hand proximity attenuates attention capture by a feature singleton

Tony Thomas and Meera M. Sunny

Many recent studies have shown that objects nearer to ones limbs are processed differently relative to objects farther away. While some studies have shown preferential processing of targets, others have shown a performance cost in detecting targets presented nearer the hands as compared to without hands. That is, there seems to be two different effects that play out in hand proximity, one where there is a priority for objects near the hand, and others in which disengagement becomes slower for objects near the hand. However, there is no conclusive evidence for this hypothesis and it seems that there is a contradiction in the literature with both a benefit and a cost associated with objects in the peri-hand space. The first two experiments were conducted to check whether the hand-proximity effect is replicable and if so, to see whether it survives in the presence of a countering effect in terms of bottom-up salience. In Exp.1, participants performed a standard letter search task in two different display sizes (6 and 12). During the search, they either placed an index finger on each of the four corners of the monitor (‘with hand’) for a fixed number of trials or rested the hand on their lap (‘without hand’). In the ‘with hand’ condition, the target appeared either within 876 pixels from the index finger (near condition) or more than 876 pixels from the index finger (far condition). Relative to the without hand condition, a steeper RT slope was found in the ‘with hand’ condition indicating a relatively inefficient search. Prima facie, this conforms to the earlier findings of a cost associated with hand proximity and hence supports slower attentional disengagement near the hands. In addition, better performance in near than far condition also fits with findings suggesting an increased prioritization of targets falling in the area near the hand. The second study was done to see whether this prioritization would persist even when there is a task irrelevant singleton distractor present in the search display. In Exp.2, every trial had one of the letters presented in red colour, and could coincide with the target in 1/9th (1/6th and 1/12th for display size 6 and 12 respectively) of all the trials. In spite of the presence of the singleton, the results showed that targets presented nearer to the hand was responded to faster than to those targets presented farther away, suggesting that the hand-proximity effect over-rides bottom-up salience effects. Moreover, we found a stronger capture for the without hand condition as compared to the with hand conditions suggesting that the proximity of the hand to the target attenuates capture by a feature singleton. We also found that there is some capture in the far condition as compared to the near condition. Overall, the results provide further empirical support for the hand-proximity effect and also suggest that it interferes with a bottom-up or salience based allocation of attention.

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Is Implicit Sequence Learning impaired in Deaf Children with Cochlear Implants?

Authors: Srinivasa Rao Bheemani ,Centre for Neural and Cognitive Science.,

Bapi Raju Surampudi , School of Computer & Information Sciences., & Center for Neural and Cognitive Sciences, University of Hyderabad.

Introduction

Deafness, a lack of sense of hearing may exist from birth, unless identified in early

stages and intervened appropriately, a period of auditory deprivation can result in cortical

reorganization and subsequent deficiencies in sequencing abilities and language development

(Sharma & Dorman, 2006), specifically, because auditory stimulus by its very nature is a

sequential signal extended over time. Indeed, previous work suggests that the profoundly

deaf showed some disturbances in (non auditory) functions related to time, such as serial

order, and immediate serial recall (Horn, Davidson, Pisoni, & Miyamoto, 2005; Marschark,

2006). A cochlear implant (CI), is an electronic device that directly stimulates the auditory

nerve to create the percept of hearing. It provides the means to successfully develop spoken

language skills.

Visual implicit sequence learning experiments on deaf children (Cochlear implanted),

conducted by Conway et al (2010) using Artificial Grammar Learning (AGL) paradigm,

showed that normal-hearing children‟s sequence learning was significantly better than that of

deaf children, who on average showed no learning. Furthermore, deaf children were not

impaired on several other non- sequencing tasks; such as visual-spatial memory and tactile

perception.

Serial Reaction Time (SRT) paradigm developed by Nissen and Bullemer (1987), is

considered better than the AGL paradigm to measure implicit learning for several reasons

(Destrebecqz & Cleeremans, 2001). The probabilistic version of SRT task is particularly

appropriate and is more ecologically valid (Jiménez & Vázquez, 2005). In the SRT task,

subjects typically watch one of four dots light up in a predetermined order and respond by

pressing the corresponding button. Learning results in faster and more accurate performance

on these patterned blocks as compared with a block of random trails. Hence, it is felt that

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there is a need to know whether implicit learning is affected in deaf children with CI, when

measured using SRT task.

Method

Subjects

Three groups of children , each group consisting of 25 children aged 8-12 years with

deafness, were included in the study; those that are fitted with cochlear implants; those fitted

with hearing aids and children with normal hearing as a control group. These children have

normal vision with the following inclusion criteria.

• Hearing Impairment: Bilateral Severe to Profound congenital hearing loss (> 70dB)

• No known neurological and psychological problems, cognitive and motor problems

Equipment and Procedure

SRT task was designed using Matlab and Cogent software. 1/3 inch circle (black color) is

presented in a sequence of locations generated from a second – order markov process (ex. 1-

2-1-3-4-2-3-1-4-3-2-4) inside one of the four 1- inch square boxes, aligned horizontally, and

separated by 2cm gap (against white color back ground) on the screen using Dell laptop

computer. The children were instructed to press the corresponding key, as fast as possible,

when the circle is present in the box. Subjects had to respond with their left and right index

and middle fingers that were placed on the keys „Z‟, „X‟, „N‟, and „M‟. The reaction time

(RT) is recorded for each response. The next trial is presented after 250ms after the response.

11 blocks of 100 trials each were presented. In blocks 1-9 and 11 the stimuli followed a

repeated probabilistic sequence of 10 elements. In the10th block stimuli were presented in a

random sequence. Explicit knowledge about the sequence is tested using interview method,

by taking written responses.

Mean response times (RT) for each of the 11 blocks for all the 3 groups is calculated. The

difference in RT in the random block 10 and the preceding and the following structured

blocks 9 and 11 were taken as an index of sequence learning and also in blocks 1through 10.

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Results, Discussion & Conclusions:

Fig.1: Block wise mean reaction time for different populations

Blockwise reaction times from 1-11 clearly demonstrated a learning effect as

expected in a standard SRT paradigm, in all the three groups of children i.e. children with

normal hearing (Normal), children with deafness fitted with cochlear implants (CI) and

hearing aids (HI). The mean values of reaction times (RT) for blocks 9, 10, and 11 for the 3

groups are shown in table-1.

Table-1: SRT results of the three groups

Further to know the statistical significance of learning effect, repeated measures

ANOVA was performed with “group” as a between-subjects factor and “blocks” as a within-

subjects factor., ANOVA showed an insignificant effect for the group [F (2, 61) =2.245,

P>0.05] but showed a significant effect for the factor blocks on response time [F (10,52)

=11.825, P<0.05]. Lack of a significant Interaction between group and block [F (20, 106) =

0.914, P>0.05] suggests that improved RTs due to practice did not vary with the type of

rehabilitation device.

The result of this study demonstrate that visual sequencing skills are not impaired in

deaf children fitted with cochlear implants, which is in contrast with the finding of the study

Group Mean of Reaction Time in ms Block 1 Block 9 Block 10 Block 11

Children with Normal Hearing 906.06 674.83 895.45 648.43 Deaf Children with CI 1076.03 700.26 801.11 627.77 Deaf Children with Hearing Aid 1213.26 836.16 1000.97 777.18

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conducted by Conway et al (2010). The deviation may possibly be due to procedural

variations, as it was said that the SRT task is a better paradigm to measure the sequence

learning than AGL??, since it is more ecologically valid (Destrebecqz & Cleeremans, 2001).

Better reaction time performance in deaf children with cochlear implants compared to those

with hearing aids might be due to the restoration of hearing and auditory experience post

implantation. Further studies have to be carried out on a larger scale to explore disturbances

in sequence learning skills in deaf children fitted with various rehabilitation devices.

References:

Conway, C.M., Pisoni, D.B., Anaya, E.M., Karpicke, J., & Henning, S.C (2010). Implicit sequence learning in deaf children with cochlear implants. Developmental Science, pp 1-14.

Destrebecqz, A., & Cleeremans, A. (2001). Can sequence learning be implicit? New evidence with the process dissociation procedure. Psychonomic Bulletin & Review, 8, 343-350.

Horn, D.L., Davis, R.A.O., Pisoni, D.B., & Miyamoto, R.T. (2005). Development of visual attention skills in prelingually deaf children who use cochlear implants. Ear and Hearing, 26, 389-408.

Jimenez, L., & Vazquez, G. (2005). Sequence learning under dual-task conditions: Alternatives to a resource-based account. Psychological Research, 69, 352-368.

Marschark, M. (2006). Intellectual functioning of deaf adults and children: ansers and questions. European Journal of Cognitive psychology, 18, 70-89.

Nissen, M.J. and Bullemer, P. (1987) Attentional requirements of learning: evidence from performance measures Coognitive Psychology. 19, 1-32.

Sharma, A., & Dorman, M.F. (2006). Central auditory development in children with cochlear implants: Clinical implications. Advances in Oto-Rhino-Laryngology, 64, 66-88.

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Affective Influences on Prospective Memory

Sushma Kumari and Tushar Singh Department of Psychology, Banaras Hindu University, Varanasi, India

Prospective memory, referred as remembering to do something in the future, is a distinct form of

memory that encompasses the formation, retention, and future retrieval of intended actions that

are encoded for future purposes. It has been divided into two task categories namely habitual

tasks or routine tasks and episodic tasks or non-routine and less frequent tasks. Similar to other

forms of memory, prospective memory has also been shown to be affected by emotional state of

the person and/or of the task. Studies have found that the emotional valence of an intended action

seems to exhibit effects on the likelihood that the task is remembered and carried out. However,

for uncomfortable intentions there might be a relatively high probability of that they remain

unperformed. Studies have interpreted better performance of highly anxious participants as an

evidence that anxiety leads people to monitor the environment and the passage of time more

frequently, which results in better prospective memory performance. Studies also provide

evidences that negative emotional states might interfere with the accurate remembering to carry

out future intentions, but not with the accurate remembering of past information.

Forty-eight undergraduate students of both the genders falling in the age group of 18 years to 25

years were asked to give their daily agenda of work they had decided for the day, like things that

they need to buy from the shop or any mails that they need to receive. They were also

administered questions to assess their mood states like how they were feeling or whether they

had a good sleep last night. At the end of the day a follow up report was taken from all the

participants of the intended tasks remembered and accomplished. The results demonstrate that

prospective memory is enhanced when participants are in a positive emotional state and that this

effect is related to better performance of intended actions. The results also demonstrated that the

nature of the task also have significant effect on its prospective remembering. The detailed

results presented in full paper are expected to explain the existing theories and researches in this

area and proposes some to the unanswered research questions open for future investigations.

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A NOVEL “EMOTIONAL ODDBALL PARADIGM”: TO STUDY THE INFLUENCE OF EMOTIONS ON TIME PERCEPTION

Anvita Gopal1, Anuj Shukla12 & S. Bapi Raju1

1Centre for Neural & Cognitive Sciences, University of Hyderabad

2 Department of Neurology, Nizams Institute of Medical Sciences, Hyderabad

According to Einstein, “When a man sits with a pretty girl for an hour, it seems like a minute. But let him sit on a hot stove for a minute -- then it's longer than any hour. That's relativity”. This famous statement suggests that unpleasant events are perceived to be longer than pleasant events, even when both are exposed for the same time duration. Time, as a fundamental cognitive activity is sometimes influenced by our emotional state of mind. Several studies have shown that in an elated state time seems to move faster whereas in a sad or bored state time seems to move at a slower pace or it seems to stand still. It has also been seen that people experiencing a dangerous and/or a traumatizing situation, such as in case of robbery, report that the event seemed to be everlasting compared to those who were bystanders or eyewitnesses. This perceived expansion in time is referred to as Time Subjective Expansion (TSE).

Studies based on emotion and time perception have shown that perceived duration of emotional stimuli seemed to be longer than in the case of neutral stimuli. Arousal based models suggest that emotional stimuli elicit heightened responses than the neutral ones. On the other hand, attention based models suggest that this phenomenon occurs due to allocation of attention which causes violation of time judgement in different emotional states. According to Ohman et al. (2001), negative facial expressions detract attention away from temporal processing more than positive expressions, which in turn is likely to alter our perception of time. Droit-Volet et al. (2007) conducted a series of experiments to study how emotion influences our temporal judgement in which they found that both sad and happy faces with Duchenne smile produced an overestimation of time, while non-Duchenne smile did not.

So far, most studies have employed Temporal bisection task, Emotional regulation paradigm and Attentional-blink paradigm to study the impact of different emotions on perception of time (Droit-Volet et al., 2007; Mella et al., 2011; Anderson et al., 2001). In a Temporal bisection task, the subject needs to report the perceived duration of each stimulus as either long or short. In the Emotional regulation paradigm, the focus of the subject was to be modulated between one of the three, namely: time, emotion or both simultaneously, in accordance with the instructions given by the experimenter. The Attentional- blink paradigm has also been studied for emotional and neutral stimuli, where after the identification of a target stimulus (T1), there is transient impairment in the awareness of a subsequently presented target (T2) and this impairment shows an interaction between T1-T2 temporal lag (early versus late).

The Oddball paradigm is a well-established method to study time perception, which is used in a wide range of studies with various stimuli and shows the expansion and contraction effect, yet it has not been applied to study emotions. In an Oddball paradigm, the subject is expected to judge the time duration of an oddball stimulus within a train of standard durations.

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According to Tse et al. (2004) when an oddball occurs, more information about the stimulus is processed per unit of objective time, leading to TSE and therefore the oddball is perceived longer than the standard durations.

The aim of the present study is to introduce a novel “Emotional Oddball Paradigm” to study the influence of emotion on time subjective expansion (TSE).

Methodology: The stimuli utilized to conduct this experiment were photographs of human faces. Four observers (2 males and 2 females, mean age 23years) were presented an oddball (Happy/Sad face) in a train of standards (Neutral faces). They were asked to respond whether the duration of the oddball stimulus was longer or shorter with respect to the standard. The standard was presented for 1050ms throughout the experiment with a jittered inter stimulus interval (ISI). The 5 objective oddball durations varied from 450, 600, 750, 900 and 1200ms.The design of the oddball experiment follows that of Tse et al. (2004).

Results and Interpretation: The analysis was done in Matlab, where all data was gathered and analysed. The average results of the pilot data on 4 subjects are shown in Figure 1. The Point of Subjective Equality (PSE) is the point at which the observer responded “longer” on half the trials, which was obtained by fitting a Weibull curve at ~738ms. Thus, an oddball lasting ~738ms was judged longer in duration as a standard lasting 1050ms. The TSE was calculated by dividing the standard duration presentation time by the PSE value, which is equal to ~1423ms, showing that the oddball was thought to expand for 1423ms. The subjects identified the emotions with 98% accuracy.

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Based on the results we can conclude that an expansion is visible in the presented emotional stimuli and influences our time perception, which is consistent with literature that emotional stimuli (sad/happy faces) produce an overestimation of time. The results of the study also helped to establish a novel “emotional oddball paradigm” where one can have a quantitative measure of subjective time expansion which happens due to emotional stimuli. It helped us to calculate how long the perceived duration of the oddball seems to be and not just whether it was perceived as longer or shorter, but a value to objectify the measure.

The current results add to the growing evidence that perception of time may be fundamentally linked to our subjective experience, in this case, our emotions.

References:

1. Droit-Volet, S. & Meck, W. (2007). How emotions colour our perception of time. Trends in Cognitive Science.

2. Mella, N., Conty, L., Pouthas, V. (2011). The role of physiological arousal in time perception: Psychophysiological evidence from an emotion regulation paradigm. Brain and Cognition.

3. Tse, P.U., Intriligator, J., Rivest, J., Cavanagh, P. (2004). Attention and the subjective expansion of time. Perception & Psychophysics.

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1

Field dependence-independence, emotional arousal and eyewitnessmemory accuracy

Yogesh Kumar Arya, Tushar Singh, Mithilesh Tiwari & Shalini MittalBanaras Hindu University

Varanasi, India

Eyewitness account of a crime scene is highly dependent on human memory which is subject to

various kinds of errors resulting from number of different reasons. A large body of literature

suggests that the accuracy of eyewitness memory is challenged by a number of factors. These

factors have been examined carefully in different studies. However, the eyewitness memory

accuracy in relation to field dependent-independent (FDI) cognitive style remains less explored.

Field dependent individuals (FD) have been found to differ from field independent (FI)

individuals with respect to selection and organization of information available in the

environment. It has been found that FI individuals, as compared to FD, organize information in

more effective ways and perform better on learning and memory tasks. Such findings from

different studies suggest a possible link between (FDI) cognitive style and accuracy of

eyewitness memory. The present study examined and compared the accuracy of eyewitness

memory among high and low field independent individuals. A total of 77 participants (34 male

and 43 female) divided into FD and FI groups on the basis of Group Embedded Figures Test.

Participants were shown a movie clip depicting a crime scene and were tested for their memory

for central and peripheral details embedded in the video clip. Participants were also asked to rate

their emotional arousal on mood adjective check list immediately after showing the video clip.

Results of the study indicated that FI and FD individuals did not differ significantly in terms of

their emotional arousal. However, FI significantly recall both central and peripheral details more

accurately then their FD counterparts. The results are discussed in light of differentiation theory

and are expected to provide new insight into the existing literature.

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Is there Similar Decline in Visual and Spatial domains of Visuo-spatial

Working Memory with aging?

Abstract

Visuo-spatial working memory (WM) decline with advancing age is a well established fact. But,

there is no agreement on whether, a particular visual or spatial information declines as similarly

as the visuo-spatial information as a whole. The present study addressed this question in a

lifespan sample of 80 participants between 40-80 years old. Three specific tasks were designed

for visual, spatial and visuo-spatial working memory. Random recall of different symbols only;

and location only within 5 x 5 matrices of blank squares were used for visual and spatial

domains, respectively. However, for combined visuo-spatial WM, a participant was asked to

recall the specific symbol with respect to its location within 5 x 5 matrices of blank squares. The

task started from a set of two symbols and continued up to a set of seven symbols maximum. All

three domains were statistically analyzed using MANOVA. It was found that, a performance

across visual WM was better than the spatial WM in each of the age groups. Moreover,

significant differences were found between visual and spatial WM score [F (4, 75) = 32.65, p >

.05]; visual and visuo-spatial WM score [F (4, 75) = 34.43, p > .05]. However, no significant

difference was found between spatial and visuo-spatial WM score. In addition, the decline

pattern of spatial domain was similar to visuo-spatial domain as a whole. This result revealed

that the decline of visuo-spatial WM system with aging is primarily a decline of information

associated with the location of the objects appeared in the visual system. Hence, possible

interpretations of these findings are suggested and the theoretical and clinical implications

considered.

.

Key words: Visuo-spatial WM, aging.

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Page 111: ABCDEF FF CAFBFFCDEF FF ˇB˘ ˆ˙ ˝˛ ˚F˜ F ˘! #B$accs2014/proc.pdf · 2014-02-27 · Structural and Functional networks underlying auditory processing in children with autism

Neural mechanisms of verb processing: An ERP study with locative alternations.

Abhilasha & Narayanan Srinivasan

Centre of Behavioural and Cognitive Sciences, University of Allahabad, Allahabad, India

A verb is considered to be the binding agent in a sentence. It is only after the incorporation of a verb that a sentence assumes its complete meaning. Verbs with similar meaning can appear in different constructions, e.g. Content-locative and Container-locative constructions. The two constructions have different meaning frames where the focus is on the content in a sentence in content-locative construction whereas in the container-locative construction, it is the container that is being focused upon as the object of the sentence. Locative alternation rule suggests that if a verb can appear in a content-locative construction, then it can also appear in a container-locative construction, and vice versa. But this rule does not apply to all the verbs making the constructions anomalous and results in more errors. So far, very few studies have been conducted on the processing of verbs that are content-locative or container-locative. The purpose of the current study is to map the time course of sentential syntactic and semantic processing in the context of the use of these different types of verbs resulting in an anomalous or meaningful sentence construction. We investigate the way in which the content- and container-locative verbs influence the sentence processing in English using ERP as indices. We expected a N400 effect at the critical word (verb). The words from a sentence were presented in a sequence at the centre of the screen for 500 ms with an inter-stimulus interval of 700 ms. Sentences were either anomalous or not-anomalous (two way construction). The participants were required to make an acceptability judgment regarding the meaningfulness or appropriateness of the sentence by pressing a key. The data was analyzed and subjected to a 2x2 ANOVA. There was no significant difference in the judgment time of the two constructions. ERP results show a significant N400 effect in the form of a large negative waveform within the time frame of 360-670 ms after the critical word (verb) onset at the frontal electrode sites. We found a main effect for anomaly within this time window, F (1, 16) =4.720, p< .05, where the anomalous constructions elicited a larger N400 amplitude in comparison to the two way (non-anomalous) constructions. The interaction effects were not significant. The effect is found in the frontal electrodes predominantly towards the left side of the hemisphere. Sentence processing is incremental and by using locative alternations the study shows how different verb types are processed in a particular sentential context.

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1

The effect of task load and distraction on discrimination.

Leander Rodrigues, Hemalatha Ramachandran, Aninha Lobo

Sophia College for Women, Mumbai 400 026

Abstract:

Background

Potentially threatening negative stimuli are more rapidly processed and are generally

more difficult to ignore than neutral ones. The amygdala has been implicated in the

detection of these emotionally significant stimuli and the prefrontal cortex (PFC) and

anterior cingulate cortex (ACC) in attentional control over these stimuli. Empirical

support has been obtained for an inverse functional connectivity between the

amygdala and prefrontal cortex (PFC). The present study examines the effect of

task load on processing resources and the extent to which emotional stimuli:

negative, unpleasant pictures produce interference on a discrimination task that

demands attention. To what extent does task load have an effect on top-down

attentional control mechanisms and bottom up processing of distractors, particularly

emotional ones?

Method and Material:

Thirty four college students participated in this study, in which distractor presence,

distractor valence (negative arousing vs. neutral pictures), Gabor patch sinusoidal

grating orientation of the patches presented to the left and right of the centre of the

picture (match/same vs. nonmatch/different) and attentional load (angular difference

of the sinusoidal gratings on nonmatch trials: easy 90˚ vs. difficult 6˚) were

manipulated. Neutral pictures consisted of photographs of people, animals, human

body parts and the negative arousing pictures consisted of photographs of mutilated

bodies of humans and animals, attack and disgust scenes selected on the basis of a

prior study. Distractor presence was the between subjects variable.

Each picture was presented in the centre of the screen flanked by two Gabor

patches. Participants were instructed to look at the centre, ignore the task irrelevant

picture and respond as quickly and as accurately as possible, whether the sinusoidal

gratings with a 90˚ or a 6˚ difference in orientation (easy vs. difficult) were the same or different. The order of the unpleasant and the neutral pictures was randomized

within the block. The difficulty of the discrimination task within each block was fixed.

Each block had the same number of match and non-match trials and the same

number of unpleasant and neutral pictures. Feedback was given to the participant

during training. The order of the experimental blocks was randomized across

participants.

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2

Results:

No significant differences were observed on speed of response (RT) across the

conditions. However significant differences were obtained on level of accuracy.

Using signal detection theory analysis, it was observed that sensitivity (d’) was greater on the easy blocks and there was a shift in response criterion; from liberal on

difficult trials to conservative on easy trials. There was greater accuracy when there

was no distractor present and on the easy block (low load).

Accuracy was also higher when the Gabor patch orientations matched. There was a

block (load) x grating orientation (match non-match) interaction effect. Accuracy was

lower on difficult, high load, non-match trials (6˚ difference between left and right

Gabor patches), accuracy was highest on easy, low load, non-match trials (90˚ difference between left and right Gabor patches).

There was a significant interaction between distractor valence (negative/neutral) and

attentional load (easy/difficult block). The interaction between distractor valence,

attentional load and grating orientation match approached significance. Accuracy

was lower on difficult, high load, non-match trials whereas on the easy block, there

was no significant difference in accuracy as a function of grating orientation match or

distractor valence.

The high exogenous attention load of the main task, specifically in the presence of

distractors in the difficult non-match condition, may have drained processing

resources and capacity available for active control and led to a criterion shift in

response.

Conclusion:

Although the load of the main task affects distractor processing, further work is

necessary to understand how distractor relevance and participant motivation for

engaging in the main task, modulated by individual differences, influences

performance.

keywords: attentional load, emotional distraction, discrimination

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Effect of instructionally induced affective arousal on time

perception Tushar Singh and Yogesh Kumar Arya

Department of Psychology, Banaras Hindu University, Varanasi, U. P. India 221005

Though the progressing of objective time is linear and is in constant unites, there are plenty of

research findings to show that temporal judgment about passing of an event is based upon a

number of factors including characteristics of the perceiver (such as age, personality traits,

degree of stress and arousal), participants’ activity during a time span (cognitive load of task)

and characteristics of the events to be judged (such as presentation duration, sensory modality,

complexity etc.). Literature in this area also suggests that perception of time is also affected by

variations in external stimulation and by the cognitive and affective state of the individual.

However, efforts to explore time perception in relation to the subjective emotional state and

emotional nature of the event (external stimulus) have been very few. Further, such studies have

used stimulus with different affective valance where the comparability of the stimulus is a

serious question. Taking the aforesaid gaps into account the present study examined the effect of

emotional arousal, generated through differential instruction about a single ambiguous stimulus,

on perception of time duration using prospective and retrospective paradigms. Forty adults were

asked to listen to a 20 second audio clip, affective valence of which was altered by providing

different pre-information about the nature of the sound clip. For one group of participants it was

told to be intrusive and anxiety provoking while in for the others it was told to be neutral in

valence. After listening to the clip the participants were asked to reproduce the time duration of

the sound clip and to report their current arousal level and affective state. For half of the

participants the experiment was conducted under retrospective paradigm while for other half it

was conducted under prospective paradigm. Results revealed that differential pre-information

about the nature of the sound clip resulted in different arousal level and affective state among the

two groups and the estimated time duration of the audio clip was found to be significantly lower

among participants experiencing negative affective state and higher arousal level as compared to

their counterparts. Further, such differential effect of affective valence and arousal on time

perception was observed only in retrospective paradigm. These results have been discussed in

view of existing theories and are expected to contribute significantly to the existing literature.

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ACCS 2014 March 3rd to 5th New Delhi

ABSTRACT(Revised)

Koinophilia and its Exaptation: A Key Trigger to Cognitive Development ?

M K Unnikrishnan, Manipal University, Manipal

Since the overwhelming majority of unusual features (physical, behavioural, auditory and olfactory) are maladaptive, sexual creatures will almost certainly have evolved sensory systems, over a period of billions of years of sexual selection, for avoiding aberrant mates. This phenomenon, termed koinophilia, which has been, rather surprisingly, relegated to near obscurity, could have served as an early evolutionary trigger for the development of the sensory apparatus, chiefly olfactory, visual and auditory, which helped sexual creatures to discriminate against aberrant mates. “Features that cannot fail to be noticed by potential mates viz. social behaviour, body morphology, colouration, song and …. motor function are most likely to be constrained by koinophilia”, said Koeslag, the protagonist of koinophilia (Koeslag,1990) Koinophilic mate selection maintains phenotypic conservatism among sexual forms, leads to sexual isolation, canalise the species, prevent non-cryptic mutations from spreading, create aversion to phenotypic novelty and thereby stabilise social animals against mutants. (Koeslag,1990, Koeslag 1994, Koeslag 1995)

Thus, the koinophilia-driven mate-choice probably kick-started the early cognitive development by unifying cognitive and affective domains: first by integrating visual, auditory and olfactory stimuli into a wholesome experience for directing mate choice; and subsequently the affective domain, which developed by generating a strong affinity for modal features, together with aversion for deviations from the norm.

While natural selection can explain the development of all organisms, the cognitive sophistication in humans has been too quick to be attributed to evolutionary adaptation alone. Gould argued that a process of exaptation (coopting of previously evolved features for novel purposes) is critical to the unique human cognitive machinery, which stems from the reuse of neural circuitry for multiple cognitive functions (Skoyles, 1999). Thus koinophilia-driven abhorrence for phenotypic aberrations not only engendered an infatuation for modal features ( experienced as attractiveness and described as beauty by humans) but also facilitated detection of subtle variations from the norm, chiefly in outliers ; thereby enabling the identification of individuality, a major survival need in large social groups. Unsurprisingly,

the face fusiform area (FFA), believed to be dedicated to face recognition, has also been found to play a role in evaluating attractiveness. The affinity for modal mates, experienced by man as ‘attractiveness’ or ‘beauty’ cannot be sidelined because of the overwhelming emotional responses ‘beauty’ evokes in man. That emotional expressions could be predicted from the patterns of neural activity recorded in FFA seems to supports this argument(Harry et al 2013).

The extended role of the FFA towards non-innate cognitive skills such as expert pattern recognition (cars, birds, greebles etc.) understanding degraded speech and recognizing board patterns in chess games further support neural reuse. Cognitive impairment reduces functional connectivity with FFA (Bokde et al 2006). Recent reports suggest functional subdomains within FFA including one for functional communication verbs! Neural plasticity facilitates the exaptationary expansion of cognitive functions in the context of sensory sophistication spurred by koinophilic mate selection. Thus the neural circuits that evaluate mate fitness could have been expanded and redeployed towards a plethora of higher cognitive functions in humans, including the highly evolved aesthetic sensibility and the potential to acquire non-innate cognitive skills.

Koinophilia-driven cognitive development is fundamental to recognizing one’s own species, because understanding the external phenotype of one’s own species -- the prototypical category in the biosphere -- is the sine qua non for survival. The ability to distinguish one’s own species as a ‘category’ probably developed into a more general ability to categorize living and nonliving objects in the world. When such ‘categorization’ is coupled with the Exception Report mechanism (Unnikrishnan 2009, Unnikrishnan 2012) that helps within-category recognition of individuality, koiniphiliic mate-choice could have jumpstarted a basic feature of ‘category perception’ that predates humans.

A recent review of cluster analysis of brain activity suggests that the FFA contains cell populations that have the potential to represent multiple categories (Cuckur et al 2013, Ross et al, in press ) That the FFA is the common denominator, not only in a variety of experiences and mental representations, but also in the execution of several interrelated complex tasks, does not seem surprising, given the expansive evolutionary history of sexual selection in general and the rapid exaptation-triggered developments specific to humans.

Keywords: koinophilia, face fusiform area, exaptation, exception report of face recognition, evolution, category perception

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Visuo-spatial recall and reproduction of geometrical shapes and math equations as a function of presentation style – static, block and animation

Niyati Mishra, Vamshi Velagapuri, and Kavita Vemuri*

International Institute of Information Technology, Hyderabad

[email protected]

______________________________________________________________________________

Abstract

An effective mode of presentation of learning material is of interest to technologists and cognitive scientists. Topics requiring recall and reproduction of complex drawings like in engineering, sciences or geometrical shapes at the school level require thorough investigation so as to customize presentation of diagrams. Towards this, a study to compare visuo-spatial constrcution and reproduction ability of stimuli presented in static, block/sequential and animation mode was conducted. Seventy-one 4th and5th grade students of a government school were shown simple 2-D geometrical shapes (Figure 1) and mathematical equations (Figure 2) using a projector. The participants were divided into three nearly equal groups and the order of presentation of the modes was mixed to account for possible higher recall rate of the last rendered image. The participants were asked to draw (paper and pencil) from memory the geometrical shapes and select the correct mathematical equation from a multiple choice questionnaire. For the geometric shapes, scoring was on the number of lines, nodes, axial orientation and relative proportionality and identification of the exact spatial position of a digit or operation was the metric for the math equations. The animated mode of presentation of the geometrical shapes and math equations scored high (Figure 3) in conjunction with previous studies (Mayer et al.,2003, Moreno & Mayer, 2007, Hoffler & Leutner, 2007, Goldstein et al.1982,), as action, even that which is observed, emphasizes motor actions . Interesting comparison is between the other two modes, where we noticed that for the geometrical shape slightly complex and not very familiar (Figure 1c) , the static mode of presentation scored higher in recall than the same presented in block or sequential mode, whereas for a less complex figure 1b the average score higher for block than static and nearly equal to animation. A similar result also noticed for the asymmetrical math equation (Figure 2c). The lower scores for block mode for shapes with depth suggest that the process of ‘stitching’ two parts of a figure with non-connecting nodes or symmetry in edges increases the visual processing cognitive load compared to assimilation when the whole figure is presented as a static complete image. The ‘explosion’ or block type of presentation is unable to provide temporal information as is available for animation (Lowe ,1999) while the human cognition seems to be able break-up components and sub-components and form hierarchical mental representations ((Narayanan and Hegarty 2002) with a static whole image. The findings are particularly relevant when presenting complex

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diagrams like engine drawings, where ‘explosion’ style of presentation is commonly used as animation is data intensive. The findings from this study also raise interesting questions on perception of depth.

Figure 1: The geometrical shapes used as the stimulus.

Figure 2: The math equations considered for this study.

Figure 3: The average scores for each presentation mode for figure (b & c) & equation (b& c) and the average across all modes.

Discussion and conclusions

The comparison between the ‘block’ mode with that of animation and static presentation is interesting to understand mechanisms employed by the human brain to process, store and ‘stitch’ together visual information presented in discrete parts. From the preliminary study, it can be deduced that the steps involved in ‘stitching’ of shapes with depth is more involved than the ability to form a continuous linked mental representation and assimilation of the same. Further

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experiments with varied set of shapes are required to check the role of nodes and edges as anchoring points. An extension would be to look at complex visual images like faces.

Acknowledgement

We acknowledge the help of Suvarna Rekha for help in conducting the experiment in the school. Also acknowledge the government school, Madhapur, Hyderabad for allowing us to conduct the experiment.

References

Goldstein, A., Chance, J., Hoisington, M., and Buescher, K.,(1982) Recognition memory for pictures: dynamic vs. static stimuli. Bull. Psychonomic Soc. 20,37 -40

Hoffler, T., Leutner, D. (2007). Instructional animation versus static pictures: A metaanalysis Learning and Instruction, 17, 722-738. Lowe, R. K. (1999). Extracting information from an animation during complex visual learning. European Journal of Psychology of Education, 14, 225–244. Mayer, R. E., & Dow, G. T., Mayer, S. (2003). Multimedia learning in an interactive self explaining environment: What works in the design of agent-based microworlds? Journal of Educational Psychology, 95, 806-813 Mayer, R. E., Heiser, J., and Lonn, S. (2001). Cognitive constraints on multimedia learning: When presenting more material results in less understanding. J. Educ. Psychol. 93: 187–198.

Moreno, R., & Mayer, R., (2007). Interactive multimodal learning environments: Educational Psychology Review. Special Issue: Interactive Learning Environments: Contemporary Issues and Trends,19(3), 309–326.

Narayanan, N. H. & Hegarty, M. (2002). Multimedia design for communication of dynamic information. International Journal of Human-Computer Studies, 57, 279-315.

______________________________________________________________________________

.

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The Nature Of Word Generalization In Learning Novel Concepts

Sujith Thomas ([email protected])Department of Computer Science and Engineering

Indian Institute of Technology

Kanpur, India 208016

Harish Karnick ([email protected])Department of Computer Science and Engineering

Indian Institute of Technology

Kanpur, India 208016

Abstract

We conduct a word learning experiment using artificial wordcategories to study the human word generalization behaviour.We hypothesize that the word generalization behaviour will bebased on similarity even when the positive examples of a wordshare a defining feature. The results of the experiment supportour hypothesis.

Introduction

Fast-mapping is the ability—that humans have—to learn a

new word from just a few examples. Studies have shown

that this fast-mapping can be modelled using Bayesian

inferencing in a structured similarity based hypothesis

space (Tenenbaum & Xu, 2000; Xu & Tenenbaum, 2007; Ab-

bott, Austerweil, & Griffiths, 2012). The studies conclude

that human word generalization for natural category objects

is mostly similarity based. By similarity based generalization

we mean that a word is generalized to a new object based

on its similarity with the positive examples of the word. But

can we say the same thing for an artificially constructed word

category that clearly has a set of defining features?

A definition based model of word generalization would try

to check if the new object satisfies a set of conditions that is

satisfied by the positive examples of the word. We hypothe-

size that the word generalization for an artificial word cate-

gory—having a set of defining features— will still be based

on similarity and not on the set of defining features.

In our word learning experiment we use artificial objects

having boolean features. We use Formal Concepts (Ganter,

Wille, & Wille, 1999) for our definition based generalization.

For Similarity based generalization we use the similarity mea-

sure given by a Linear Regression Model.

Experiment

In this experiment 24 participants were shown six positive

and six negative examples of a word. The participants were

then asked whether the word applies to a new example. The

generalization behaviour was then compared with the Formal

Concept based generalization and Similarity based general-

ization.

Figure 1 shows a sample stimulus that was used in our ex-

periment. The top row lists the positive examples of a novel

word. The middle row lists the negative examples and the

last row lists the test examples. The test examples are shown

Figure 1: The figure shows a sample stimulus. The top row

lists the positive examples, middle row the negative examples,

and the bottom row the test examples, for a novel word. All

the positive examples have a five pointed blue star with a red

border. The participants are shown the test examples one by

one and asked if the word applies to the test example.

to a participant one at a time. The participant is then asked

whether the word—for which the positive and negative exam-

ples are shown—applies to the test example.

In Figure 1 all positive examples contain a five pointed star

with a blue background and a red border. This is the only

feature that is present in all the positive examples and not

present in any of the negative examples.

If the generalization behaviour is based on a set of neces-

sary and sufficient conditions then the experimental results

should show that more people generalize the word to test ex-

amples C and D compared to test examples A and B. This is

because among the test examples only C and D contain the

star with a blue background and a red border. On the other

hand, if the generalization behaviour is based on similarity

then the experimental results should show that more people

generalize the word to test examples A and D.

Figure 2 shows another sample stimuli. We used six stimuli

similar to those shown in Figures 1 and 2. Table 1 lists the

four types of test examples corresponding to each stimulus.

There were 24 (6×4) test questions in total.

Results

Table 2 shows how the participants generalized a word to a

test example belonging to each of the four types shown in

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Figure 2: The figure shows another sample stimulus. The

top row lists the positive examples of a novel word, middle

row the negative examples, and bottom row the test examples.

All positive examples have an eight pointed star with a white

background and orange border. The participants are shown

the test examples one by one and asked if the word applies to

the test example.

Table 1: The four types of test examples for each stimulus

Similar to +positive

examples?

Satisfies the Formal

Concept?

Type 1 Yes Yes

Type 2 Yes No

Type 3 No Yes

Type 4 No No

Table 2: Table shows the result for each type of test example.

There were 144 responses corresponding to each test exam-

ple type. Frequency column shows the fraction of the trials

for which a word was generalized to a test example type. Per-

centage column shows the percentage corresponding to the

frequency value.

Frequency Percentage

(out of 144)

Type 1 122 84.7%

Type 2 108 75%

Type 3 53 36.8%

Type 4 30 20.8%

Table 1. There were 144 responses corresponding to each

test example type. The difference between the Type 2 test

example frequency and Type 3 test example frequency was

found to be statistically significant using the Wilcoxon Signed

Ranks Test (W (21) = 24, p < .001). The results show that

a word is generalized more frequently to Type 1 and Type 2

test examples compared to Type 3 and Type 4 test examples.

Figure 3 shows the 24 test examples divided into two

groups —those that satisfy the Formal Concept and those that

do not. We find the average percentage of participants who

generalize a word to the test examples in each of these two

groups. If the generalization behaviour is based on Formal

Concept then we would expect the average percentage to be

Figure 3: The 24 test examples are divided into two groups

—those that satisfy the Formal Concept and those that do not.

The figure shows the average percentage of participants who

generalized the word to the test example in each group. The

figure also shows the average similarity between a test exam-

ple in a group and the positive examples of a word.

closer to 100% for one group and closer to zero for the other.

Figure 3 shows the average percentage of participants who

generalized a word to the test examples in each group. We

see that for both the groups the average percentage is closer

to 50%. Spearman Rank Correlation Coefficient between the

generalization made by the participants and the generaliza-

tion based on necessary and sufficient conditions was found

not to be statistically significant (r(574) = .15,ns).

Figure 4 shows the 24 Test examples divided into two

groups based on their similarity to the positive examples of a

word. If the participant generalization behaviour is based on

similarity then we would expect this percentage to be closer

to 100% for one group and closer to zero for the other. The

data in Figure 4 confirms this. Spearman Rank Correlation

Coefficient between the generalization made by the partici-

pants and the generalization based on similarity was found to

be statistically significant r(574) = .51, p < .001).

Figure 5 shows how the percentage of participants who

generalized a word to a test example varies with the average

similarity between the test example and the positive exam-

ples. In the figure we see that the percentage increases with

the average similarity. The Spearman Rank Correlation Coef-

ficient between the two variables was found to be significant

(r(22) = .87, p < .005).

Conclusion

The above results show that the generalization behaviour for

the word learning experiment is better modelled using the

similarity based generalization compared to a definition based

generalization.

References

Abbott, J., Austerweil, J., & Griffiths, T. (2012). Constructing

a hypothesis space from the web for large-scale bayesian

Page 130: ABCDEF FF CAFBFFCDEF FF ˇB˘ ˆ˙ ˝˛ ˚F˜ F ˘! #B$accs2014/proc.pdf · 2014-02-27 · Structural and Functional networks underlying auditory processing in children with autism

Figure 4: The 24 test examples are divided into two groups

based on their average similarity with the positive examples.

The figure shows the average percentage of participants who

generalized the word to the test example in each group. The

figure also shows the average similarity between a test exam-

ple in a group and the positive examples of a word.

Figure 5: Figure shows how the percentage of participants

that generalized a word to a test example varies with the aver-

age similarity of the test example with the positive examples.

Spearman Rank Correlation Coefficient is statistically signif-

icant (r(22) = .87, p < .005).

word learning. In Proceedings of the 33rd annual meeting

of the cognitive science society (pp. 54–59).

Ganter, B., Wille, R., & Wille, R. (1999). Formal concept

analysis. Springer Berlin.

Tenenbaum, J., & Xu, F. (2000). Word learning as bayesian

inference. In Proceedings of the 22nd annual conference of

the cognitive science society (pp. 517–522).

Xu, F., & Tenenbaum, J. (2007). Word learning as bayesian

inference. Psychological review, 114(2), 245–272.

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