Modulation of metastable ensemble dynamics explains optimal coding at moderate arousal in auditory cortex DOI Creative Commons
Lia Papadopoulos, Su‐Hyun Jo, Kevin Zumwalt

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: April 5, 2024

Performance during perceptual decision-making exhibits an inverted-U relationship with arousal, but the underlying network mechanisms remain unclear. Here, we recorded from auditory cortex (A1) of behaving mice passive tone presentation, while tracking arousal via pupillometry. We found that discriminability in A1 ensembles was optimal at intermediate revealing a population-level neural correlate relationship. explained this arousal-dependent coding using spiking model clustered architecture. Specifically, show stimulus is achieved near transition between multi-attractor phase metastable cluster dynamics (low arousal) and single-attractor (high arousal). Additional signatures include arousal-induced reductions overall variability extent stimulus-induced quenching, which observed empirical data. Our results elucidate computational principles interactions pupil-linked sensory processing, variability, suggest role for transitions explaining nonlinear modulations cortical computations.

Language: Английский

Modulation of metastable ensemble dynamics explains optimal coding at moderate arousal in auditory cortex DOI Creative Commons
Lia Papadopoulos, Su‐Hyun Jo, Kevin Zumwalt

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: April 5, 2024

Performance during perceptual decision-making exhibits an inverted-U relationship with arousal, but the underlying network mechanisms remain unclear. Here, we recorded from auditory cortex (A1) of behaving mice passive tone presentation, while tracking arousal via pupillometry. We found that discriminability in A1 ensembles was optimal at intermediate revealing a population-level neural correlate relationship. explained this arousal-dependent coding using spiking model clustered architecture. Specifically, show stimulus is achieved near transition between multi-attractor phase metastable cluster dynamics (low arousal) and single-attractor (high arousal). Additional signatures include arousal-induced reductions overall variability extent stimulus-induced quenching, which observed empirical data. Our results elucidate computational principles interactions pupil-linked sensory processing, variability, suggest role for transitions explaining nonlinear modulations cortical computations.

Language: Английский

Citations

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