Neural Dynamics in Extrastriate Cortex Underlying False Alarms

Abstract

The unfolding of neural population activity can be described as a dynamical system. Stability in the latent dynamics that characterize neural population activity has been linked with consistency in animal behavior, such as motor control or value-based decision-making. However, whether such characteristics of neural dynamics can explain visual perceptual behavior is not well understood. To study this, we recorded V4 populations in two male monkeys engaged in a non-match-to-sample visual change-detection task that required sustained engagement. We measured how the stability in the latent dynamics in V4 might affect monkeys’ perceptual behavior. Specifically, we reasoned that unstable sensory neural activity around dynamic attractor boundaries may make animals susceptible to taking incorrect actions when withholding action would have been correct (“false alarms”). We made three key discoveries: (1) greater stability was associated with longer trial sequences; (2) false alarm rate decreased (and response times slowed) when neural dynamics were more stable; and (3) low stability predicted false alarms on a single-trial level, and this relationship depended on the position of the neural activity within the state space, consistent with the latent neural state approaching an attractor boundary. Our results suggest the same outward false alarm behavior can be attributed to two different potential strategies that can be disambiguated by examining neural stability: (1) premeditated false alarms that might lead to greater stability in population dynamics and faster response time and (2) false alarms due to unstable sensory activity consistent with misperception.