Project Summary The theory hub put forward in this proposal will work to translate successful and powerful approaches to describing emergent collective behavior in physical systems so they can be applied to the brain.
PROJECT SUMMARY Neuroscience is producing increasingly complex data sets, including measures and manipulations of sub- cellular, cellular, and multi-cellular mechanisms operating over multiple timescales and in the context of different behaviors and task conditions. These data sets pose several fundamental challenges. First, for a given data set, what are the relevant spatial, temporal, and computational scales in which the underlying information-processing dynamics are best understood?
Project Summary / Abstract High-throughput experimental neuroscience has made it possible to observe behavior of many animals, as well as a large groups of neurons simultaneously, providing an exciting opportunity for figuring out how the neural system performs computations that underlie perception, cognition, and behavior. However, there is a major bottleneck in the scientific cycle of data analysis and data collection due to the complexity and scale of noisy, high-dimensional data.
Project Summary/Abstract How neural activity is coordinated within local microcircuits and across brain regions to drive behavior is a central open question in neuroscience. Recent advances in massively-parallel neural recording tech- nologies are producing dynamic activity maps during complex behaviors, with single-neuron granularity and single-spike resolution. To reveal fundamental dynamic features in these large-scale datasets, new principled and scalable computational methods are urgently needed.
Project Summary: The cortex must both track and process dynamically changing environments as well as store and combine diverse inputs to generate complex behavior. Further, the neuronal circuits that accomplish this must be malleable to changing contexts, such as during attention related tasks. Charged with these tasks it is perhaps unsurprising that the response dynamics of populations of cortical neurons is then dauntingly complex. Currently, we lack a deep understanding of the circuit mechanics that underlie the rich dynamics exhibited in the nervous system.
Summary The BRAIN initiative is enabling ground-breaking techniques for brain recordings that will permit a unique view onto the dynamics of neural activity. However, inferring brain function from multi-channel physiological recordings is challenging.
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.
