Sensory integration dynamics in a hierarchical network explains choice probabilities in cortical area MT

• DOI: 10.1038/ncomms7177
• Publication Date: 2015-02-04T12:17:57Z
• Authors: Klaus Wimmer; Albert Compte; Alex Roxin; Diogo Peixoto; Alfonso Renart; Jaime de la Rocha
• Keywords: Male; Neurons; 0301 basic medicine; Decision Making; Motion Perception; Models, Psychological; Choice Behavior; Macaca mulatta; Article; Temporal Lobe; 03 medical and health sciences; Parietal Lobe; Visual Perception; Animals; Nerve Net; Photic Stimulation; Probability; Visual Cortex

AbstractNeuronal variability in sensory cortex predicts perceptual decisions. This relationship, termed choice probability (CP), can arise from sensory variability biasing behaviour and from top-down signals reflecting behaviour. To investigate the interaction of these 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.