Systems Neuroscience

 DESCRIPTION (provided by applicant): Neuronal circuits in the brainstem control life-sustaining functions, in addition to driving and gating active sensation through taste, smell, and touch. We propose to exploit the advent of molecular and genetic tools to undertake cell lineage marking, cell phenotyping, molecular connectomics, and methods from machine learning and image processing to construct an integrated anatomical and functional atlas of the brainstem. This will enable us to generate anatomical wiring diagrams for the brainstem circuits that control or facial actions.

 DESCRIPTION (provided by applicant): Behaviors are sequences of actions that are executed in the proper order and correct setting to achieve a goal. Action sequences and their association with the specific environmental contexts in which they are beneficial can be hardwired, as in the case of innate behaviors, or learned and flexible, as in the case of adaptive responses to changing surroundings.

 DESCRIPTION (provided by applicant): The brain evolved complex recurrent networks to enable flexible behavior in a dynamic and uncertain world, but its computational strategies and underlying mechanisms remain poorly understood. We propose to uncover the network basis of neural computations in foraging, an ethologically relevant behavioral task that involves sensory integration, spatial navigation, memory, and complex decision-making.

 DESCRIPTION (provided by applicant): The brain is a massively interconnected network of regions, each of which contains neural circuits that process information related to combinations of sensory, motor and internal variables. Adaptive behavior requires that these regions communicate: sensory and internal information must be evaluated and used to make a decision, which must then be transformed into a motor output.

 DESCRIPTION (provided by applicant): The purpose of this RFA is to promote the integration of experimental, analytic and theoretical capabilities for the examination of neural circuits and systems. This proposal is highly responsive to the RFA in that it links several different neuroscience labs to develop new technologies that provide for simultaneous multistate imaging and applies these technologies to the examination of how neuronal dynamics in mammalian cortex varies as a function of brain state and development.

 DESCRIPTION (provided by applicant): The system that controls smooth pursuit eye movements is one of the most accessible, promising systems for understanding how neural circuits transform sensory inputs into actions. Pursuit is a natural, ecologically- relevant behavir that allows primates to track moving objects of interest in the visual world.

 DESCRIPTION (provided by applicant): To address the core question underlying the Obama Brain Initiative to better understand the function of complex brain circuits, we propose a multi-scale recording and data analysis project to study the dynamical interactions between sensory cortex, motor cortex, and the basal ganglia in the process of motor planning and execution. The multi-scale approach will involve simultaneous recordings at the cellular, network, and systems level in head-fixed behaving mice trained to perform a rewarded locomotor task.

 DESCRIPTION (provided by applicant): The anatomical substrates and cellular mechanisms underlying reward-dependent learning have been studied for decades, but the specific circuit and network interactions between the cortex, striatum, and midbrain that mediate action selection have not been systematically investigated. Here, we bring together three different investigators with specialized expertise in each of these three brain regions.

Project Summary/Abstract A central problem in neuroscience is to understand how activity arises from neural circuits to drive animal behaviors. Solving this problem requires integrating information from multiple experimental modalities and organization levels of the nervous system. While modern neurotechnologies are generating high-resolution maps of the brain-wide neural activity and anatomical connectivity, novel theoretical frameworks are urgently needed to realize the full potential of these datasets.

Over the past several decades, the ability to record from large populations of neurons (e.g., multi-electrode arrays, neuropixels, calcium imaging) has increased exponentially, promising new avenues for understanding the brain. These data have the promise to provide a qualitatively different view of activity within and across brain areas than was previously possible, but the effort will require the development of advanced analytical tools.