The trial-to-trial variability of cortical neurons correlates with variability
in behavioral reports. This relationship can arise from sensory variability
biasing behaviour, as the result of cortical population dynamics, and from top-
down signals reflecting behaviour [1,2]. Here, we study the impact of the
dynamics of sensory evidence integration in perceptual decision tasks on the
"choice probability" (CP) of sensory neurons. To examine the interaction of the
different mechanisms during the decision-making process, we use a hierarchical
network model composed of reciprocally connected sensory and integration
circuits. Consistent with monkey behaviour in a fixed-duration motion
discrimination task, the model integrates sensory evidence transiently, giving
rise to a decaying bottom-up CP component. However, the dynamics of the
hierarchical loop recruits a concurrently rising top-down component, resulting
in sustained CP. We compute the CP time-course of neurons in the medial temporal
area (MT) and find an early transient component and a separate late contribution
reflecting decision build-up. The stability of individual CPs and the dynamics
of noise correlations further support this decomposition. Our model provides a
unified understanding of the circuit dynamics linking neural and behavioural
variability.
[1] K. Wimmer, D.Q. Nykamp, C. Constantinidis, and A.Compte. Nat. Neurosci.
17(3):431-439 (2014).
[2] K. Wimmer, A. Compte, A. Roxin, D. Peixoto, A. Renart, and J. de la Rocha. Nat. Commun.
6:6177 (2015).