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<p>Our perception of the world depends on a complex interplay between external sensory inputs and our internal states. How and where in the brain these interactions are implemented remain poorly understood. To address these questions, we measured membrane potential (<i>V</i><sub>m</sub>) of single V1 neurons in macaque monkeys performing a reaction-time visual detection task. Here we show that most V1 neurons gradually depolarize in preparation for target onset, and that variations in this buildup are correlated with the monkey’s reaction times. Further, we show that fluctuations in <i>V</i><sub>m</sub> after target onset are correlated with choice, and that these covariations strongly depend on the location and contrast of the target. Finally, we show that a simple computational model with fluctuating multiplicative gain can account for our results. Thus, the surprising covariations between <i>V</i><sub>m</sub> of single V1 neurons and behavior are implemented by internal-state-related nonlinear modulations operating at, or before, V1.</p>

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Fluctuating internal states mediate neural–behavioral covariations in V1

  • 期刊论文

  • 发表日期：

    2026年5月13日

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  • Baowang Li,
  • Jason M. Samonds,
  • Yuzhi Chen,
  • Thibaud Taillefumier,
  • Nicholas J. Priebe,
  • Eyal Seidemann

摘要

Our perception of the world depends on a complex interplay between external sensory inputs and our internal states. How and where in the brain these interactions are implemented remain poorly understood. To address these questions, we measured membrane potential (Vm) of single V1 neurons in macaque monkeys performing a reaction-time visual detection task. Here we show that most V1 neurons gradually depolarize in preparation for target onset, and that variations in this buildup are correlated with the monkey’s reaction times. Further, we show that fluctuations in Vm after target onset are correlated with choice, and that these covariations strongly depend on the location and contrast of the target. Finally, we show that a simple computational model with fluctuating multiplicative gain can account for our results. Thus, the surprising covariations between Vm of single V1 neurons and behavior are implemented by internal-state-related nonlinear modulations operating at, or before, V1.