Systems Neuroscience

Data-driven analysis for neuronal dynamic modeling

Project Summary / Abstract Our main goal is to unravel communication dynamics in the brain, as they relate to various sensory-motor actions and to the learning process. The sensory-motor system operates through the concerted interaction of multiple closed-loops feedback systems. While some broad level knowledge is available about single neuron properties and general high-level operations, we lack understanding of functional aspects of neural dynamics, of inter-neuronal interactions and of the modular interaction and integration of brain regions contributing to motor activity.

Measuring, Modeling, and Modulating Cross-Frequency Coupling

PROJECT SUMMARY Although rhythms are a prominent feature of brain activity, the role of rhythms in brain function (and dysfunction) remains elusive. Rhythms have been proposed to organize information transfer within and between brain regions by modulating neural excitability at different time scales. Rhythms have also been proposed to interact across these different time scales, a phenomenon labeled cross-frequency coupling or CFC.

Mental, measurement, and model complexity in neuroscience

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?

Real-time statistical algorithms for controlling neural dynamics and behavior

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.

Discovering dynamic computations from large-scale neural activity recordings

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.

Neuronal population dynamics within and across cortical areas

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.

Building analysis tools and a theory framework for inferring principles of neural computation from multi-scale organization in brain recordings

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.

Efficient resource allocation and information retention in working memory 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.

Tools for modeling state-dependent sensory encoding by neural populations across spatial and temporal scales

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.

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