DIFFERENTIAL
INTERHEMISPHERIC
TRANSFER
FOR
ABSTRACT AND
SPECIFIC
VISUAL-FORM
INFORMATION
Christopher D. Nicholas & Chad J. Marsolek
University of Arizona
(Presented at the 3rd Annual Meeting of the Cognitive Neuroscience Society, San Fransisco, CA, April 1996)
Introduction
Evidence from long-term memory experiments suggests that relatively independent visual-form subsystems operate in the brain:
(Marsolek, 1995; Marsolek, Kosslyn, & Squire, 1992; Marsolek, Schacter, & Nicholas, in press)
In this experiment, we test whether similar results will be obtained in short-term memory comparison tasks. More important, we examine whether computational properties of these subsystems determine interhemispheric communication of visual information.
Example Displays
Method
Each trial consisted of a stimulus array with 4 characters (see above):
The stimulus displays were of two types:
Predictions
If SVF and AVF subsystems underlie comparisons in the SI and AC tasks, respectively, then:
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When the cerebral hemispheres must communicate with each other, performance involves a trade-off between distribution and degradation (Banich & Nicholas, in press)
AH trials:
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Hemispheric distribution of information: Reduced processing load per hemisphere (Dimond & Beumont, 1971) |
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Callosal degradation of information: Information must be transferred (Dimond, Gibson, & Gazzaniga, 1972) |
WH trials:
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No callosal degradation of information: Information does not need to be transferred |
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No hemispheric distribution of information: increased processing load per hemisphere |
The AC task requires perceptual and phonological or name processing:
Thus, an AH advantage is found for the AC task because it requires two stages of processing, whereas a WH advantage is found for the SI task because it requires only one stage of processing (Banich & Belger, 1990).
Subsystems Interpretation
An AVF subsystem is needed in the AC task. This subsystem should process relatively invariant features effectively, treating minor visual differences as noise that should be ignored:
Thus, an AH advantage is found for the AC task because the costs of degradation do not outweigh the benefits of distribution, whereas a WH advantage is found for the SI task because the costs of degradation do outweigh the benefits of distribution.
If the complexity of the comparison tasks (number of
processing stages required) determines the efficacy of interhemispheric
communication:
If the computational properties of the processing subsystems needed to perform the comparisons tasks determines the efficacy of interhemispheric communication:
For similar-case letters (e.g., S/s):
If an SVF subsystem is required for the SI task, and noisy versions of S and s cannot be distinguished effectively by this subsystem because these specific instances have very fine-grained distinctive information that may be affected greatly by collosal degradation, then:
For Dissimilar-case letters (e.g., A/a):
If an SVF subsystem is required for the SI task, and noisy versions of A and a can be distinguished effectively by this subsystem because these specific instances have relatively coarse distinctive information that may not be affected greatly by collosal degradation, then:
In this experiment, we test whether case similarity is the crucial
difference between letter groups by using the dissimilar-case letters
used in Experiment 1 and presenting visually similar instances of the
same dissimilar-case letter (e.g.,
and
; making them like the similar-case
letters used in Experiment 1).
Method
Each trial consisted of a stimulus array with 4 characters (see above):
Only dissimilar-case letters were used, however different
instances in the same abstract categories were always different-font,
same-case items (e.g.,
and
), not different-case items (e.g.,
A and a) as in Experiment 1.
48 subjects performed 256 trials of each comparison task (see above) per
experiment:
If the different-font (but same-case) instances of dissimilar-case
letters (
/
) are processed like different-case
instances of similar-case letters (S/s):
Summary
Hemispheric asymmetries for Abstract and Specific Visual-Form Comparisons:
Conclusions
Implications
These findings suggest that in order to understand interhemispheric communication and interaction, a computational subsystems approach may be more fruitful than approaches that rely on general principles of communication.
References
Banich, M. T., & Belger, A. (1990). Interhemispheric interaction: How do the hemispheres divide and conquer a task? Cortex, 26, 77-94.\
Banich, M. T., & Nicholas, C. D. (in press). Integration of processing between the cerebral hemispheres in word recognition. In Getting it right: In The cognitive neuroscience of right hemisphere language comprehension. Beeman, M, & Chiarello, C. (Eds.) Hillsdale, N. J.: Lawrence Erlbaum Associates.
Dimond, S. J., & Beumont, G. (1971). Use of two cerebral hemispheres to increase brain capacity. Nature, 232, 270-271.
Dimond, S. J., Gibson, A. R., & Gazzaniga, M. S. (1972). Cross-field and within-field integration of visual information. Neuropsychologia, 10, 379-381.
Liederman, J. (1986). Interhemispheric interference during word naming. International Journal of Neuroscience, 30, 43-56.
Liederman, J., Merola, J., & Hoffman, C. (1986). Longitudinal data indicate that interhemispheric independence increases during early adolescence. Developmental Neuropsychology, 2, 183-201.
Marsolek, C. J. (1995). Abstract-visual-form representations in the left cerebral hemisphere. Journal of Experimental Psychology: Human Perception and Performance, 21, 375-386.
Marsolek, C. J., Kosslyn, S. M., & Squire L. R. (1992). Form-specific visual priming in the right cerebral hemisphere. Journal of Experimental Psychology: Learning, Memory, and Cognition, 18, 492-508.
Marsolek, C. J., Schacter, D. L., & Nicholas, C. D. (in press). Form-specific visual priming for new associations in the right cerebral hemisphere. Memory & Cognition.
This research was supported by the National Institute of Mental Health Grant MH53959-01. The research was also supported by the McDonnell-Pew Cognitive Neuroscience Center, the Program in Neuroscience at the University of Arizona, and the Arizona Cognitive Science Program.
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