Understanding Circuits

ABSTRACT Short-term working memory is critical for all cognition. It is important to fluid intelligence by definition and is disordered in many psychiatric conditions. It is also an ideal model system for studying the link between the dynamics and functions of neural circuits. Short-term storage requires dynamics that are flexible enough to allow continuous incorporation of new information, yet stable enough to retain information for tens of seconds. Much is known about the neuronal substrate of short-term memory.

Project Summary Throughout life, humans and other animals learn statistical regularities in the natural acoustic environment. They adapt their hearing to emphasize the features of sound that are important for making behavioral decisions. Normal-hearing humans are able to perceive important sounds in crowded noisy scenes and to understand the speech of individuals the first time they meet. However, patients with peripheral hearing loss or central processing disorders often have problems hearing in these challenging settings, even when sound is amplified above perceptual threshold.

Project Summary/Abstract: There is significant current interest in understanding how neurons relate to whole-brain networks and how these networks coordinate to give rise to behavior.

PROJECT SUMMARY Understanding how individual neurons contribute to network functions is fundamental to neuroscience. Recent years have seen exciting progresses in the reconstructions of single-neuron morphologies and wiring diagrams at the level of individual synapses. Although these progresses offer promises of understanding neuronal networks, such understandings would not be reached if we do not understand how the structural details of single neurons contribute to the network connectivity.

PROJECT SUMMARY / ABSTRACT This project focuses on developing new analysis tools to investigate the mechanisms of information routing in primate fronto-striatal circuits during goal-directed behavior. These tools are part of a seamless analysis pipeline that will enable neuroscience researchers to rigorously test hypotheses fast and with a minimum of translation between incompatible strategies and tools. The rationale for developing these tools is that evidence from recent studies suggests that information routing and changes in routing happen during transient bursts of activity.

The brain uses its own previous activity to adapt to an ever-changing environment. This history dependent adaptation takes place at all scales of organization of the nervous system. The objective of this project is to develop a common theoretical formalism to be applied to multiple history dependent phenomena, from the biochemical reactions that underlie synaptic plasticity, to the emergent patterns in complex neural networks. At the core of this formalism is the recognition that most models of neuronal activity are based on the classical reaction-diffusion equation.

Abstract: Causality is central to neuroscience. For example, we might ask about the causal effect of a neuron on another neuron, or its influence on perception, action, or cognition. Moreover, any medical approaches aim at producing a causal effect – effecting improvements for patients. Randomized controlled trials (RCTs) are the gold standard to establish causality, but they are not always practical. For example, while we can electrically or optogenetically activate entire areas, large-scale targeted stimulation of individual neurons is hard.

The massive neural activity data collected through transformative new technologies present an incredible opportunity in facilitating the mission of the BRAIN Initiative and the wider neuroscience community: to understand brain function.

Project Summary A central goal of systems neuroscience is to relate behavior to its underlying circuit dynamics. This task is complicated by the complex and circuitous paths along which information flows as it is encoded and processed in the many steps between sensory inputs and motor outputs. Currently, we understand little regarding the organization and dynamics of interactions between brain areas. For example, we do not know the degree to which specific brain areas have separate representations versus when information is encoded jointly across brain areas.

A theory of population coding in the cerebellum In order to move accurately, the brain relies on internal models that predict the sensory consequences of motor commands. Evidence for this idea comes from human behavioral experiments [1-7] and animal lesion studies [8- 11], suggesting that the critical structure for forming internal models is the cerebellum.