Spike-based coupling between single neurons and populations across rat sensory cortices, perirhinal cortex, and hippocampus

Author:

Dorman Reinder1,Bos Jeroen J12,Vinck Martin A13,Marchesi Pietro1,Fiorilli Julien1,Lorteije Jeanette A M1,Reiten Ingrid4,Bjaalie Jan G4,Okun Michael5,Pennartz Cyriel M A1

Affiliation:

1. Systems and Cognitive Neuroscience Group, SILS Center for Neuroscience, University of Amsterdam , 1098 XH Amsterdam , The Netherlands

2. Donders Institute for Brain, Cognition and Behavior, Radboud University , 6500 HC Nijmegen , The Netherlands

3. Ernst Strüngmann Institute for Neuroscience in Cooperation with Max Plank Society , 60528 Frankfurt , Germany

4. Institute of Basic Medical Sciences, University of Oslo , NO-0316 Oslo , Norway

5. Department of Psychology and Neuroscience Institute, University of Sheffield , Sheffield S10 2TN , UK

Abstract

Abstract Cortical computations require coordination of neuronal activity within and across multiple areas. We characterized spiking relationships within and between areas by quantifying coupling of single neurons to population firing patterns. Single-neuron population coupling (SNPC) was investigated using ensemble recordings from hippocampal CA1 region and somatosensory, visual, and perirhinal cortices. Within-area coupling was heterogeneous across structures, with area CA1 showing higher levels than neocortical regions. In contrast to known anatomical connectivity, between-area coupling showed strong firing coherence of sensory neocortices with CA1, but less with perirhinal cortex. Cells in sensory neocortices and CA1 showed positive correlations between within- and between-area coupling; these were weaker for perirhinal cortex. All four areas harbored broadcasting cells, connecting to multiple external areas, which was uncorrelated to within-area coupling strength. When examining correlations between SNPC and spatial coding, we found that, if such correlations were significant, they were negative. This result was consistent with an overall preservation of SNPC across different brain states, suggesting a strong dependence on intrinsic network connectivity. Overall, SNPC offers an important window on cell-to-population synchronization in multi-area networks. Instead of pointing to specific information-coding functions, our results indicate a primary function of SNPC in dynamically organizing communication in systems composed of multiple, interconnected areas.

Funder

Netherlands Organization for Scientific Research

ICT

the European Union’s Horizon 2020 Framework Programme for Research and Innovation

Publisher

Oxford University Press (OUP)

Subject

Cellular and Molecular Neuroscience,Cognitive Neuroscience

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