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Three distinct weakly coupled gamma oscillatory networks within cortical columns in macaque monkeys' area V1

Drebitz, E.; Rausch, L.-P.; Gil, E. D.; Kreiter, A. K.

2023-10-02 neuroscience
10.1101/2023.09.30.560308 bioRxiv
Show abstract

A fundamental property of the neocortex is its columnar organization in many species. Generally, neurons of the same column share stimulus preferences and have strong anatomical connections across layers. These features suggest that neurons within a column operate as one unified network. Other features, like the different patterns of input and output connections of neurons located in separate layers and systematic differences in feature tuning, hint at a more segregated and possibly flexible functional organization of neurons within a column. To distinguish between these views of columnar processing, we conducted laminar recordings in macaques area V1 while they performed a demanding attention task. We found three separate regions with strong gamma oscillatory current source density (CSD) signals, one each in the supragranular, granular, and infragranular laminar domains. Their characteristics differed significantly in terms of their dominant gamma frequency and attention-dependent modulation of their gramma power and gamma frequency. In line, spiking activity in the supragranular, infragranular, and upper part of the granular domain exhibited strong phase coherence with their domains CSD signals but showed much weaker coherence with the other domains CSD signals. These results indicate that columnar processing involves a certain degree of independence between neurons in the three laminar domains, consistent with the assumption of multiple, separate intracolumnar ensembles. Such a functional organization offers various possibilities for dynamic network configuration, indicating that neurons in a column are not restricted to operate as one unified network. Thus, the findings open interesting new possibilities for future concepts and investigations on flexible, dynamic cortical ensemble formation and selective information processing.

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