December 2022
Volume 22, Issue 14
Open Access
Vision Sciences Society Annual Meeting Abstract  |   December 2022
Multichannel recordings in neuroscience: new computational methods for fluctuating neural dynamics and spatiotemporal patterns
Author Affiliations & Notes
  • Lyle Muller
    Department of Mathematics, Western University, London, ON, Canada
    Brain and Mind Institute, Western University, London, ON, Canada
  • Gabriel Benigno
    Department of Mathematics, Western University, London, ON, Canada
    Brain and Mind Institute, Western University, London, ON, Canada
  • Alexandra Busch
    Department of Mathematics, Western University, London, ON, Canada
    Brain and Mind Institute, Western University, London, ON, Canada
  • Zachary Davis
    The Salk Institute for Biological Studies, La Jolla, CA, USA
  • John Reynolds
    The Salk Institute for Biological Studies, La Jolla, CA, USA
  • Footnotes
    Acknowledgements  This work was supported by Gatsby Charitable Foundation, the Fiona and Sanjay Jha Chair in Neuroscience, CIHR and NSF (NeuroNex Grant No. 2015276), the Swartz Foundation, NIH Grants R01-EY028723, T32 EY020503-06, T32 MH020002-16A, P30 EY019005, Compute Canada, and BrainsCAN at Western University.
Journal of Vision December 2022, Vol.22, 4461. doi:https://doi.org/10.1167/jov.22.14.4461
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      Lyle Muller, Gabriel Benigno, Alexandra Busch, Zachary Davis, John Reynolds; Multichannel recordings in neuroscience: new computational methods for fluctuating neural dynamics and spatiotemporal patterns. Journal of Vision 2022;22(14):4461. https://doi.org/10.1167/jov.22.14.4461.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

With new multichannel recording technologies, neuroscientists can now record from neocortex of awake animals with both high spatial and temporal resolution. Early recordings during anesthesia revealed spontaneous and stimulus-evoked waves traveling across the cortex. While for some time these waves were thought to disappear in awake states, our recent work has revealed traveling waves in visual cortex of awake animals. To study neural recordings during irregular, fluctuating activity in the awake state, we have developed a computational technique that we termed generalized phase (GP). The GP approach allows us to analyze the dominant fluctuation in broadband neural data at each moment in time, thus permitting analysis of the constantly occurring irregular neural activity at the single-trial level. By quantifying GP at each electrode on a multielectrode array, we have studied spontaneous fluctuations in awake marmosets as they await a faint visual target during a detection task. We find that ongoing fluctuations propagate as intrinsic traveling waves (iTWs) across the multielectrode array, modulate background firing rates, and strongly influence visually evoked responses. To understand the underlying mechanism for these waves, we then studied a large-scale spiking network model with balanced excitatory and inhibitory interactions. By scaling this model to the size of marmoset area MT, we find that time delays from unmyelinated horizontal fibers can profoundly shape the weakly correlated activity known to model the awake state (the “asynchronous-irregular” [AI] regime) into iTWs. In this state, only a small fraction of the local neural population spikes as an iTW passes. We call this unique operating mode, where the benefits of the AI state in local networks can coexist with iTWs propagating across the cortex, the “sparse wave regime”. We discuss potential roles for these sparse waves in dynamically modulating neural sensitivity during active visual processing.

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