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The role of cortical feedback in the generation of the temporal receptive field responses of lateral geniculate nucleus neurons: a computational modelling study

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Abstract

The influence of cortical feedback on thalamic visual responses has been a source of much discussion in recent years. In this study we examine the possible role of cortical feedback in shaping the spatiotemporal receptive field (STRF) responses of thalamocortical (TC) cells in the lateral geniculate nucleus (LGN) of the thalamus. A population-based computational model of the thalamocortical network is used to generate a representation of the STRF response of LGN TC cells within the corticothalamic feedback circuit. The cortical feedback is shown to have little influence on the spatial response properties of the STRF organization. However, the model suggests that cortical feedback may play a key role in modifying the experimentally observed biphasic temporal response property of the STRF, that is, the reversal over time of the polarity of ON and OFF responses of the centre and surround of the receptive field, in particular accounting for the experimentally observed mismatch between retinal cells and TC cells in respect of the magnitude of the second (rebound) phase of the temporal response. The model results also show that this mismatch may result from an anti-phase corticothalamic feedback mechanism.

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Abbreviations

LGN:

Lateral geniculate nucleus

PY:

Cortical pyramidal cell

RE:

Reticular cell

RE nucleus:

Thalamic reticular nucleus

RF:

Receptive field

RGC:

Retinal ganglion cell

STRF:

Spatiotemporal receptive field

TC:

Thalamocortical cell

V1:

Primary visual cortex

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Authors and Affiliations

  1. Centre for Computational and Theoretical Neuroscience, University of Plymouth, Drake Circus, Plymouth, PL4 8AA, UK

    Nada Yousif & Mike Denham

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  1. Nada Yousif
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  2. Mike Denham
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Correspondence to Nada Yousif.

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Yousif, N., Denham, M. The role of cortical feedback in the generation of the temporal receptive field responses of lateral geniculate nucleus neurons: a computational modelling study. Biol Cybern 97, 269–277 (2007). https://doi.org/10.1007/s00422-007-0171-3

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  • DOI: https://doi.org/10.1007/s00422-007-0171-3

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