인지과학 협동과정 송이구 visual working memory as decision making: compensation for...

인 지 과 학 협 동 과 정 송 이 구

Visual Working Memory as deci-sion making: compensation for memory uncertainty in reach

planning

Visual Working Memory (VWM)

System that actively maintains visual information to serve the needs of ongo-ing tasks. (Luck & Vogel, 2013)

Visual Working Memory

Online movement controlIntegration of visual information across eye

movementsVisual searchGaze correction following saccadic error

Visual Working Memory Studies

Since Luck & Vogel’s study in 1997, there has been an numerous researches about VWM

“Change Blindness Test” was able to notice the limitations of VWM

Visual Working Memory Studies

“Change Detection Task” quantify the capac-ity of VWM

WM capacity is correlated with individual differences in broad cognitive functions

Visual Working Memory Capacity

Researches in Working Memory capacity fo-cused on How quickly the information is refreshed How quickly the information decays

In VWM capacity, focuses on How many items can be remembered Recently, focus on content of working memory repre-

sentation

Visual Working Memory Capacity

Luck& Vogel (1997) used change detection task to estimate the capacity of the visual working memory. As a result found that about 3 or 4 items –was able

to accurately detect changes.

But shows only little information on how much we know Need to increase the amount of information Measure fidelity

Models of Visual Working Memory Capacity

How is the memory stored then?

Discrete Slots (Item-limited) Idea that memory is encoded as Slots

If limit is N, no more representations can be encoded All or None

Continuous Resource (Information limited) No limit like slots, however, precision of memory is

decreased as set size increase

Discrete Slots

Item limited

Change Detection paradigm Accordingly subjects accurately detected

the changes when fewer 3-4 items were shown displayed

Zhang & Luck(2008) Used a Mathematical Model to differentiate

Noisy memory representation OR Random guesses More than 3 items, rate of random guessing

increased

Continuous Resources

Information limited

Alvarez & Cavanagh used the term “Trade-off” between the relation of number of items and its resolution

Poor Memory representation Not a completeabsence

Integrated vs Independent

Object-basedLuck & Vogel(1997) – The number of features

in an object did not matter during change de-tection task (either 1,2, or even 4 features) “objects” are the units of visual working memory

Feature-basedXu(2002), Bays, Wu, &Husain(2011) – Objects

are not always encoded entirely

Better to have 2 features in 1 object than 1 feature in 2 objects

Then…? Possibilities Hierarchical feature bundles

Higher level – Integrated object Lower level – Independent features

How does the Visual Working Memory capac-ity reaching its limit influence motor planning and execution? (Ecologically relevant tasks)

-External cost bias the contents of visual memory?-External cost influence how people act on the basis of

uncertain memory information

Decision Making (Wine-glass problem)

Wine-Glass Problem Better to underestimate than to overestimate !...

Hypothesis

1. As set sizes increase, memory precision is lower

2. Subjects will undershoot during the over-shoot-penalty session and overshoot during undershoot-penalty session

3. As memory uncertainty grows, subjects will aim further away from the penalty area.

4. Contents of memory is biased due to the monetary costs related with memory error

Experiment

Method

Participants – 12 individuals (8 female) Age (18 – 35) / Normal Vision(corrected-to-normal) Two experimental sessions (conducted on separate

days) Minimum $20 + additional monetary incentives

Stimuli

“Smart Table” Glass surface with projection film Digital projector shooting arrays on the table

Subjects were to use the Stylus to aim at the intended area

Two Sessions Undershoot-penalty Overshoot-penalty

Two types targets1. One colored targets 2. Three colored targets

Procedure

Every trial began by pressing the “Start-cross”

Display the target (either 1 or 3 object) for 1500 ms Retention interval was presented for 1000 ms Subjects then completed odd/even digit judgment

Recall trial or Discrimination trial

Procedure

Recall Trial Subjects were told to touch the area where the cue

was previously given Given feedback - Monetary payoff or penalty Hit = 10 ¢ Penalty area = 20 ¢ Neither

= 0 ¢ 100 trials per block – 400 trials in total

Procedure

Discrimination Trial Given cue, judge whether the cue is further or

closer than the previously given stimuli No feedback 50 trials per block – 200 trials in total Designed to observe if the memory was biased by

penalty condition

Results

2 x 2 Within subject ANOVA

Mean relative aim differed as penalty condition differs F(1,11) = 19.62 p=0.001 η^2=0.44

Set size influenced by penalty condition F(1,11) = 10.15 p=0.009 η^2 = 0.120 The bigger the set size, the further the mean aim

Results

Since, discrimination trials did not get any feed-back nor had anything to do with monetary incen-tives, participants had no reason to apply post-mnemonic decision strategy

No significant shift across penalty conditions F(1,11) = 1.38 p=0.27 η^2 = 0.02

Meaning during recall trials subjects applied Adap-tive decision strategy!

Post-experiment survey 9 out of 12 participants claimed to aim way from penalty

regions

Is the result a in motor planning? Fixed Heuristic (aim away from penalty area)

Or Consideration of costs derived from memory error and

memory uncertainty

Discussion

Any other factors that should be considered to bias the working memory? Or was the monetary cost in the experiment not an appropriate exam-ple for costs by memory error? -Since the monetary cost is actually not an “negative cost”

to the participants. (Just earning less instead of losing)

Would categorical perception bias the informa-tion encoding into the working memory?

What is more likely as VWM encoding process?

Thank You

끝 !!

Reference

• Brady, T., Konkle, T., & Alvarez, G. (2011). A review of visual mem-ory capacity: Beyond individual items and toward structured rep-resentations. Journal of Vision, 4-4.

• Hartshorne, J. (2008). Visual Working Memory Capacity and Proac-tive Interference. PLoS ONE.

• Hollingworth, A., Richard, A., & Luck, S. (2008). Understanding the function of Visual Short-Term Memory: Transsaccadic memory, object correspondence, and gaze correction. Journal of Experimen-tal Psychology: General, 137(1), 163-163.

• Kawasaki, M., & Yamaguchi, Y. (2014). Individual visual working memory capacities and related brain oscillatory activities are mod-ulated by color preferences. Frontiers in Human Neuroscience Front. Hum. Neurosci.

• Kording, K. (2007). Decision Theory: What "Should" the nervous system do? Science, 318(5850), 606-610.

• Lerch, R., & Sims, C. (2015). Visual Working Memory as Decision Mak-ing: Compensation for Memory Uncertainty in Reach Planning. Re-trieved October 14, 2015.

• Luck, S., & Vogel, E. (1997). The capacity of visual working memory for features and conjunctions. Nature, 390, 279-281.

• Luck, S., & Vogel, E. (2013). Visual Working Memory Capacity: From Psychophysics and Neurobiology to Individual Differences. Trends in Cognitive Sciences, 17(8), 391-400.

• Ma, W., Husain, M., & Bays, P. (2014). Changing concepts of working memory. Nature Neuroscience, 17(3), 347-356.

• Makovski, T., & Jiang, Y. (2009). The role of visual working memory in attentive tracking of unique objects. Journal of Experimental Psychol-ogy: Human Perception and Performance, 1687-1697.

• Oh, S., & Kim, M. (2004). The role of spatial working memory in visual search efficiency. Psychonomic Bulletin & Review, 275-281.

• Sims, C., Jacobs, R., & Knill, D. (2012). An ideal observer analysis of visual working memory. Psychological Review, 807-830.