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Hemispheric asymmetry in perception: a differential encoding account.

Janet H Hsiao1, Ben Cipollini, Garrison W Cottrell

  • 1University of Hong Kong, Hong Kong. jhsiao@hku.hk

Journal of Cognitive Neuroscience
|March 2, 2013
PubMed
Summary
This summary is machine-generated.

Hemispheric asymmetry in processing local and global features may stem from differing brain connection structures, not just frequency filtering. This neurocomputational model suggests anatomical differences drive these cognitive variations.

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Computational Modeling

Background:

  • Hemispheric asymmetry in processing local and global features is well-documented.
  • Previous theories attributed this to differences in frequency filtering between hemispheres.
  • However, neurophysiological evidence supporting frequency filtering differences is limited.

Purpose of the Study:

  • To test the hypothesis that hemispheric asymmetry arises from differences in anatomical connections beyond the sensory encoding stage.
  • To model differential encoding in the left and right hemispheres using distinct connection structures.

Main Methods:

  • Developed two simple encoding networks with varied connection structures to model hemispheric differences.
  • Modeled connection structures based on generalized neuroanatomical evidence from auditory to visual modalities.
  • Hypothesized more distal connections in left hemisphere models (language areas) and more local connections in right hemisphere models (homotopic regions).

Main Results:

  • The neurocomputational model naturally produced processing differences between the two simulated hemispheres.
  • Differential frequency filtering effects also emerged within the model.
  • Results indicate that connection structure asymmetries can explain observed processing asymmetries.

Conclusions:

  • Hemispheric asymmetry in processing local and global features may be primarily driven by asymmetries in anatomical connection structures.
  • This challenges the prevailing view that frequency tuning differences are the main cause.
  • The findings highlight the role of network architecture in cognitive function.