Leveraging multisensory decisions to understand brain wide decision circuits

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The goal!of the proposed research is to uncover the brain wide circuits and local computations that together allow animals to combine multiple, diverse sources of information to guide decision-making. Specifically, these experiments will investigate how mammals integrate sensory signals over time and across sensory modalities. The main hypothesis is that in addition to sense-specific circuits, auditory and visual decisions rely on common, core decision circuits for decision-related computations, such as evidence accumulation and action selection. Within these structures, targeted connectivity between excitatory and inhibitory neurons supports persistent activity and competition for action selection. The proposed method to test this hypothesis is to measure and manipulate neural activity in mice trained to make perceptual decisions about auditory and visual stimuli. Three approaches, taken together, form the core of the proposal to evaluate this hypothesis and provide a new view of decision-making circuits. First, the degree to which auditory and visual decisions activate overlapping or largely separate neural structures will be evaluated based on wide field imaging of cortex-wide activity during decision-making. Cortex-wide activity will be measured in transgenic mice that express calcium indicators in cortical excitatory neurons. Classifiers and decision-making models we will used to link activity in a given brain structure to decision-making computations. This approach will uncover candidate areas that are active during auditory, visual or multisensory decisions. Next, optogenetic suppression of these candidate areas will be used to evaluate their causal role in decision-making. A model-based comparison of behavior on suppression and control trials will evaluate the effects of disruption on decision-related computations such as event discrimination, evidence accumulation, and action planning. Finally, areas that are identified as causal for specific decision computations will be investigated more closely to understand how these computations are implemented by single neurons. 2- photon microscopy will be used to image populations of single neurons. The experimental subjects will be transgenic mice in which inhibitory neurons emit red fluorescent light that is independent of the green fluorescence that is used as an estimate of neural activity. These two separate signals make it possible to distinguish excitatory from inhibitory neurons and evaluate their respective roles in decision-making. Single-trial classifiers will be used to evaluate the ability of excitatory and inhibitory populations to predict the animal’s choice. The outcome of this experiment will be used to distinguish candidate models of decision-making.