Sensorimotor behaviors require processing of behaviorally relevant sensory cues and the ability to select appropriate responses from a vast behavioral repertoire. Modulation by the prefrontal cortex (PFC) is thought to be key for both processes, but the precise role of specific circuits remains unclear. We examined the sensorimotor function of anatomically distinct outputs from a subdivision of the mouse PFC, the anterior cingulate cortex (ACC). Using a visually guided two-choice behavioral paradigm with multiple cue-response mappings, we dissociated the sensory and motor response components of sensorimotor control. Projection-specific two-photon calcium imaging and optogenetic manipulations show that ACC outputs to the superior colliculus, a key midbrain structure for response selection, principally coordinate specific motor responses. Importantly, ACC outputs exert control by reducing the innate response bias of the superior colliculus. In contrast, ACC outputs to the visual cortex facilitate sensory processing of visual cues. Our results ascribe motor and sensory roles to ACC projections to the superior colliculus and the visual cortex and demonstrate for the first time a circuit motif for PFC function wherein anatomically non-overlapping output pathways coordinate complementary but distinct aspects of visual sensorimotor behavior.

Abstract-We study a model for cascade effects over finite networks based on a deterministic binary linear threshold model. Our starting point is a networked coordination game where each agent's payoff is the sum of the payoffs coming from pairwise interaction with each of the neighbors. We first establish that the best response dynamics in this networked game is equivalent to the linear threshold dynamics with heterogeneous thresholds over the agents. While the previous literature has studied such linear threshold models under the assumption that each agent may change actions at most once, a study of best response dynamics in such networked games necessitates an analysis that allows for multiple switches in actions. In this paper, we develop such an analysis. We first establish that agent behavior cycles among different actions in the limit, we characterize the length of such limit cycles, and reveal bounds on the time steps required to reach them. We finally propose a measure of network resilience that captures the nature of the involved dynamics. We prove bounds and investigate the resilience of different network structures under this measure.

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Significance Deep brain stimulation (DBS) in the subthalamic nucleus (STN) is highly effective for treating the motor symptoms of Parkinson’s disease (PD). However, the neural mechanisms by which DBS acts are unknown. PD symptoms are tied to altered brain rhythms in basal ganglia (BG) and particularly the striatum. We develop a biophysical model of a BG neural pathway and show how beta oscillations can emerge throughout BG in PD. We then establish a mechanism by which DBS in STN can interrupt these abnormal rhythms and restore the brain’s capability to produce and regulate normal rhythms lost with dopamine depletion. Our research suggests mechanisms to leverage striatal gamma and theta oscillations to counter aberrant dynamics and enhance the therapeutic effects of DBS.