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Predictive feedback to V1 dynamically updates with sensory input.

ABSTRACT: Predictive coding theories propose that the brain creates internal models of the environment to predict upcoming sensory input. Hierarchical predictive coding models of vision postulate that higher visual areas generate predictions of sensory inputs and feed them back to early visual cortex. In V1, sensory inputs that do not match the predictions lead to amplified brain activation, but does this amplification process dynamically update to new retinotopic locations with eye-movements? We investigated the effect of eye-movements in predictive feedback using functional brain imaging and eye-tracking whilst presenting an apparent motion illusion. Apparent motion induces an internal model of motion, during which sensory predictions of the illusory motion feed back to V1. We observed attenuated BOLD responses to predicted stimuli at the new post-saccadic location in V1. Therefore, pre-saccadic predictions update their retinotopic location in time for post-saccadic input, validating dynamic predictive coding theories in V1.

SUBMITTER: Edwards G

PROVIDER: S-EPMC5705713 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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Predictive feedback to V1 dynamically updates with sensory input.

Edwards Grace G Vetter Petra P McGruer Fiona F Petro Lucy S LS Muckli Lars L

Scientific reports 20171128 1

Predictive coding theories propose that the brain creates internal models of the environment to predict upcoming sensory input. Hierarchical predictive coding models of vision postulate that higher visual areas generate predictions of sensory inputs and feed them back to early visual cortex. In V1, sensory inputs that do not match the predictions lead to amplified brain activation, but does this amplification process dynamically update to new retinotopic locations with eye-movements? We investig ...[more]

PMID: 29184060

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Project description:Most sensory information destined for the neocortex is relayed through the thalamus, where considerable transformation occurs1,2. One means of transformation involves interactions between excitatory thalamocortical neurons that carry data to the cortex and inhibitory neurons of the thalamic reticular nucleus (TRN) that regulate the flow of those data3-6. Although the importance of the TRN has long been recognised7-9, understanding of its cell types, their organization and their functional properties has lagged behind that of the thalamocortical systems they control. Here we address this by investigating the somatosensory and visual circuits of the TRN in mice. In the somatosensory TRN we observed two groups of genetically defined neurons that are topographically segregated and physiologically distinct, and that connect reciprocally with independent thalamocortical nuclei through dynamically divergent synapses. Calbindin-expressing cells-located in the central core-connect with the ventral posterior nucleus, the primary somatosensory thalamocortical relay. By contrast, somatostatin-expressing cells-which reside along the surrounding edges of the TRN-synapse with the posterior medial thalamic nucleus, a higher-order structure that carries both top-down and bottom-up information10-12. The two TRN cell groups process their inputs in pathway-specific ways. Synapses from the ventral posterior nucleus to central TRN cells transmit rapid excitatory currents that depress deeply during repetitive activity, driving phasic spike output. Synapses from the posterior medial thalamic nucleus to edge TRN cells evoke slower, less depressing excitatory currents that drive more persistent spiking. Differences in the intrinsic physiology of TRN cell types, including state-dependent bursting, contribute to these output dynamics. The processing specializations of these two somatosensory TRN subcircuits therefore appear to be tuned to the signals they carry-a primary central subcircuit tuned to discrete sensory events, and a higher-order edge subcircuit tuned to temporally distributed signals integrated from multiple sources. The structure and function of visual TRN subcircuits closely resemble those of the somatosensory TRN. These results provide insights into how subnetworks of TRN neurons may differentially process distinct classes of thalamic information.

Dataset Information

Predictive feedback to V1 dynamically updates with sensory input.

Publications

Predictive feedback to V1 dynamically updates with sensory input.

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