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JOBB FÉLTEKE DOMINANCIA A VIZUÁLIS STATISZTIKUS TANULÁS KEZDŐFÁZISÁBAN József Fiser, Matthew E. Roser *, Richard N. Aslin # & Michael S. Gazzaniga * Brandeis.

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Presentation on theme: "JOBB FÉLTEKE DOMINANCIA A VIZUÁLIS STATISZTIKUS TANULÁS KEZDŐFÁZISÁBAN József Fiser, Matthew E. Roser *, Richard N. Aslin # & Michael S. Gazzaniga * Brandeis."— Presentation transcript:

1 JOBB FÉLTEKE DOMINANCIA A VIZUÁLIS STATISZTIKUS TANULÁS KEZDŐFÁZISÁBAN József Fiser, Matthew E. Roser *, Richard N. Aslin # & Michael S. Gazzaniga * Brandeis University, University of Rochester # and Dartmouth College*

2 Great diversity of proposed hemispheric specializations

3 Hemispheric differences in object perception For highly familiar objects: RH  metric and positional information LH  abstract categorical information RH  visual form informationRH  visual form information LH  conceptual associations RH  early information (low SF)RH  early information (low SF) LH  late information (high SF)

4 Object perception requires visual feature learning First, visual scenes are interpreted via already learned object featuresFirst, visual scenes are interpreted via already learned object features Next, search for new specific spatial co-occurrences and new arrangements among elements (emergence of new feature combinations) occursNext, search for new specific spatial co-occurrences and new arrangements among elements (emergence of new feature combinations) occurs Finally, explicit access to a new feature by developing associations and categorical and semantic meaningFinally, explicit access to a new feature by developing associations and categorical and semantic meaning Right hemisphereLeft hemisphere

5 Question: Can the process of learning new visual features be linked to differential involvement of the two brain hemispheres?

6 Six base-pairs Fit three base-pairs into 3 X 3 grid The basic paradigm Visual feature = spatio-temporal conjunction of separate shapes

7 Testing phase 2AFC task Base-pair vs. Non-base pair A B E F IJ A B Base-pair Non-base pairs IF

8 Split the base-pairs Modifying the paradigm 2 deg

9 Modified test phase Ipsilateral: Practice: RHTest: RH Practice: LHTest: LH Contralateral: Practice: RHTest: LH Practice: LH Test: RH Four lateralized test types

10 Subjects Normal subjects: Sixteen college students Callosotomy patient: V. P. (Corballis et al. Neurology 2001) SpleniumRostrum

11 Experimental procedure for normal subjects Practice: 144 scenes alternating randomly between the right and left visual fields144 scenes alternating randomly between the right and left visual fields Eye-movements monitored by iView to verify fixation (and hemifield stimulation)Eye-movements monitored by iView to verify fixation (and hemifield stimulation) Test: Six test trials in each of the four test types (Ipsi, Contra) x (RH, LH)Six test trials in each of the four test types (Ipsi, Contra) x (RH, LH)

12 Results with normal subjects Equal learning in all conditions  interhemispheric transfer Chance

13 V.P.'s testing schedule 1st day: practice 2nd day: practice, ipsilateral tests, practice, ipsilateral tests 3rd day: practice, ipsilateral tests, practice, ipsilateral tests 4th day: practice, contralateral tests 5th day: practice, contralateral tests Data collection in five days

14 Contralateral: No interhemispheric information transfer Ipsilateral: Strong right hemisphere advantage * Chance Results with the split brain patient

15 Conclusions The initial phase of extracting spatial statistical regularities from the visual input is dominated by right hemisphere processes These results predict a shift of relative brain activity from the right to the left hemisphere as visual perception shifts from naïve observation to a knowledge-based interpretation of the scene Visual statistical learning does not transfer across split hemispheres even when some limited transfer of higher-level word-related information is possible


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