Published on Fri Jul 30 2021

Coherent mapping of position and head direction across auditory and visual cortex

Mertens, P. E. C., Marchesi, P., Oude Lohuis, M. N., Krijger, Q., Pennartz, C. M. A., Lansink, C. S.

Neurons in primary visual cortex (V1) may not only signal current visual input but also relevant contextual information such as reward expectancy and the subject's spatial position. Such location-specific representations need not be restricted to V1 but could participate in a coherent mapping throughout sensory cortices.

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Abstract

Neurons in primary visual cortex (V1) may not only signal current visual input but also relevant contextual information such as reward expectancy and the subject's spatial position. Such location-specific representations need not be restricted to V1 but could participate in a coherent mapping throughout sensory cortices. Here we show that spiking activity in primary auditory cortex (A1) and lateral, secondary visual cortex (V2L) of freely moving rats coherently represents a location-specific mapping in a sensory detection task performed on a figure-8 maze. Single-unit activity of both areas showed extensive similarities in terms of spatial distribution, reliability and position coding. Importantly, reconstructions of subject position on the basis of spiking activity displayed decoding errors that were correlated between areas in magnitude and direction. In addition to position, we found that head direction, but not locomotor speed or head angular velocity, was an important determinant of activity in A1 and V2L. Finally, pairs of units within and across areas showed significant correlations in instantaneous variability of firing rates (noise correlations). These were dependent on the spatial tuning of cells as well as the spatial position of the animal. We conclude that sensory cortices participate in coherent, multimodal representations of the subject's sensory-specific location. These may provide a common reference frame for distributed cortical sensory and motor processes and may support crossmodal predictive processing.