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Dynamical modeling of multi-scale variability in neuronal competition

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Variability is observed at multiple-scales in the brain and ubiquitous in perception. However, the nature of perceptual variability is an open question. We focus on variability during perceptual rivalry, a… Click to show full abstract

Variability is observed at multiple-scales in the brain and ubiquitous in perception. However, the nature of perceptual variability is an open question. We focus on variability during perceptual rivalry, a form of neuronal competition. Rivalry provides a window into neural processing since activity in many brain areas is correlated to the alternating perception rather than a constant ambiguous stimulus. It exhibits robust properties at multiple scales including conscious awareness and neuron dynamics. The prevalent theory for spiking variability is called the balanced state; whereas, the source of perceptual variability is unknown. Here we show that a single biophysical circuit model, satisfying certain mutual inhibition architectures, can explain spiking and perceptual variability during rivalry. These models adhere to a broad set of strict experimental constraints at multiple scales. As we show, the models predict how spiking and perceptual variability changes with stimulus conditions.Benjamin P Cohen, Carson C Chow, and Shashaank Vattikuti show that dynamical mutual inhibition models can explain variability during neuronal competition at two scales: neuronal spiking activity and perceptual rivalry variability. These models make predictions for how spiking and perceptual variability will change with stimulus conditions.

Keywords: perceptual variability; variability; neuronal competition; variability neuronal; rivalry

Journal Title: Communications Biology
Year Published: 2019

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