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A neural network model of attention-modulated neurodynamics

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Abstract

Visual attention appears to modulate cortical neurodynamics and synchronization through various cholinergic mechanisms. In order to study these mechanisms, we have developed a neural network model of visual cortex area V4, based on psychophysical, anatomical and physiological data. With this model, we want to link selective visual information processing to neural circuits within V4, bottom-up sensory input pathways, top-down attention input pathways, and to cholinergic modulation from the prefrontal lobe. We investigate cellular and network mechanisms underlying some recent analytical results from visual attention experimental data. Our model can reproduce the experimental findings that attention to a stimulus causes increased gamma-frequency synchronization in the superficial layers. Computer simulations and STA power analysis also demonstrate different effects of the different cholinergic attention modulation action mechanisms.

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Authors and Affiliations

  1. Department of Biometry and Engineering, SLU, Uppsala, Sweden

    Yuqiao Gu & Hans Liljenström

  2. School of Automation and Energy Engineering, Tianjin University of Technology, Tianjin, P.R. China

    Yuqiao Gu

Authors
  1. Yuqiao Gu
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  2. Hans Liljenström
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Correspondence to Hans Liljenström.

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Gu, Y., Liljenström, H. A neural network model of attention-modulated neurodynamics. Cogn Neurodyn 1, 275–285 (2007). https://doi.org/10.1007/s11571-007-9028-7

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  • DOI: https://doi.org/10.1007/s11571-007-9028-7

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