Causal brainwide interactions underlying internal states and decisions

Summary/Abstract, Project 2 Even in the same environment, an animal may make different decisions on different occasions, because its internal state, such as engagement in a task, interacts powerfully with external inputs to determine behavior. This proposal’s overarching goal is to understand how internal states influence decisions and to identify the underlying neural mechanisms. The team is part of the International Brain Laboratory (IBL), an established consortium that has developed a standardized mouse decision-making task and standardized methods for training, neural measurement, and data analysis, along with a working, scalable infrastructure for sharing data. The goal of Project 2 is to establish the causal influence of brain regions and cell types on inter-regional communication and state-dependent decision-making by integrating optogenetic perturbations at specific times during the task with simultaneous recordings of neural populations and functional ultrasound. We will consider two types of internal states: engaged/disengaged task performance and left/right biases due to the statistical structure of the environment, which varies across blocks of trials. In Aim 1, we will examine the role of subcortical structures in state-dependent decision-making with systematic optogenetic manipulations while well-trained mice perform the IBL decision task. In Aim 2, we will examine the causal effects of inhibiting target regions and/or cell types of interest on communication between other regions, using Neuropixels probes and functional ultrasound. In Aim 3, to integrate our results, we will develop dynamical computational models of multi-region population activity during our causal manipulations. These models will account for the effects of manipulation in one brain region on behavior and activity in other regions, and their dependence on internal states. The results will help interpret our experiments and refine them by suggesting other combinations of regions to record and manipulate. Together, these experiments will integrate cutting-edge experimental and computational methods to characterize the causal interactions of brainwide regions and their dependence on internal state.