Dataset Information

Modeling the spatiotemporal cortical activity associated with the line-motion illusion in primary visual cortex.

ABSTRACT: Our large-scale computational model of the primary visual cortex that incorporates orientation-specific, long-range couplings with slow NMDA conductances operates in a fluctuating dynamic state of intermittent desuppression (IDS), which captures the behavior of coherent spontaneous cortical activity, as revealed by in vivo optical imaging based on voltage-sensitive dyes. Here, we address the functional significance of the IDS cortical operating points by investigating our model cortex response to the Hikosaka line-motion illusion (LMI) stimulus-a cue of a quickly flashed stationary square followed a few milliseconds later by a stationary bar. As revealed by voltage-sensitive dye imaging, there is an intriguing similarity between the cortical spatiotemporal activity in response to (i) the Hikosaka LMI stimulus and (ii) a small moving square. This similarity is believed to be associated with the preattentive illusory motion perception. Our numerical cortex produces similar spatiotemporal patterns in response to the two stimuli above, which are both in very good agreement with experimental results. The essential network mechanisms underpinning the LMI phenomenon in our model are (i) the spatiotemporal structure of the LMI input as sculpted by the lateral geniculate nucleus, (ii) a priming effect of the long-range NMDA-type cortical coupling, and (iii) the NMDA conductance-voltage correlation manifested in the IDS state. This mechanism in our model cortex, in turn, suggests a physiological underpinning for the LMI-associated patterns in the visual cortex of anaesthetized cat.

SUBMITTER: Rangan AV

PROVIDER: S-EPMC1323193 | biostudies-literature | 2005 Dec

REPOSITORIES: biostudies-literature

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Modeling the spatiotemporal cortical activity associated with the line-motion illusion in primary visual cortex.

Rangan Aaditya V AV Cai David D McLaughlin David W DW

Proceedings of the National Academy of Sciences of the United States of America 20051201 52

Our large-scale computational model of the primary visual cortex that incorporates orientation-specific, long-range couplings with slow NMDA conductances operates in a fluctuating dynamic state of intermittent desuppression (IDS), which captures the behavior of coherent spontaneous cortical activity, as revealed by in vivo optical imaging based on voltage-sensitive dyes. Here, we address the functional significance of the IDS cortical operating points by investigating our model cortex response t ...[more]

PMID: 16380423

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Project description:Neurons in sensory areas of neocortex exhibit responses tuned to specific features of the environment. In visual cortex, information about features such as edges or textures with particular orientations must be integrated to recognize a visual scene or object. Connectivity studies in rodent cortex have revealed that neurons make specific connections within sub-networks sharing common input tuning. In principle, this sub-network architecture enables local cortical circuits to integrate sensory information. However, whether feature integration indeed occurs locally in rodent primary sensory areas has not been examined directly. We studied local integration of sensory features in primary visual cortex (V1) of the mouse by presenting drifting grating and plaid stimuli, while recording the activity of neuronal populations with two-photon calcium imaging. Using a Bayesian model-based analysis framework, we classified single-cell responses as being selective for either individual grating components or for moving plaid patterns. Rather than relying on trial-averaged responses, our model-based framework takes into account single-trial responses and can easily be extended to consider any number of arbitrary predictive models. Our analysis method was able to successfully classify significantly more responses than traditional partial correlation (PC) analysis, and provides a rigorous statistical framework to rank any number of models and reject poorly performing models. We also found a large proportion of cells that respond strongly to only one stimulus class. In addition, a quarter of selectively responding neurons had more complex responses that could not be explained by any simple integration model. Our results show that a broad range of pattern integration processes already take place at the level of V1. This diversity of integration is consistent with processing of visual inputs by local sub-networks within V1 that are tuned to combinations of sensory features.

Dataset Information

Modeling the spatiotemporal cortical activity associated with the line-motion illusion in primary visual cortex.

Publications

Modeling the spatiotemporal cortical activity associated with the line-motion illusion in primary visual cortex.

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