What Do Dynamic Receptive Field Properties Reveal About Computation in Recurrent Thalamocortical Circuits?
Recurrently connected artificial neural networks can classify input patterns through iterative feedback reverberations. We have utilized simultaneous multi-single unit recordings to investigate sensory processing in the rat somatosensory thalamocortical system, which is recurrently interconnected. Punctate stimulation of facial whiskers produced a complex, spatiotemporally distributed series of response peaks across neuronal ensembles in both the ventroposterior thalamus (VPM) and somatosensory (SI) cortex. Correlation matrices relating the timing of these peaks in all histograms constructed using VPM vs. SI neurons revealed an orderly series of post-stimulus correlation “peaks and valleys”, indicating that the dynamic properties of receptive fields in both VPM and SI are caused by reverberatory interactions between them. Canonical correlation analyses suggest that these interactions may reflect computational recognition of patterns of stimulus movement across the whiskers.
KeywordsReceptive Field Neuronal Ensemble Longe Latency Response Whisker Stimulation Medium Latency Response
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