Informatics

Towards an integrated analytics solution to creating a spatially-resolved single-cell multi-omics brain atlas

PROJECT SUMMARY The maintenance and function of the nervous system depends on cell-cell interactions among neuronal and non-neuronal cell populations, which occur through physically binding cell membrane surface or secreted proteins, triggering signaling cascades that activate cell-type gene regulatory programs. The cell-cell interactome responds and regulates the microenvironment which is altered in physiological processes such as brain development and aging, or during the onset and progression of different neuropsychiatric disorders.

Unified, Scalable, and Reproducible Neurostatistical Software

Project Summary Many advances in modern neuroscience rely on electrophysiological recordings of large neural populations (e.g. many hundreds of cells) or high-resolution measurements of animal behavior (e.g. from video). These datasets have unlocked a wide range of genuinely transformational scientific opportunities, as they enable us to draw reliable statistical inferences about individual animal subjects at precisely encapsulated moments in time. However, these statistical models are complex and non-trivial to implement in computer software.

A scalable cloud-based framework for multi-modal mapping across single neuron omics, morphology and electrophysiology

Project Summary Categorizing individual neurons into different groups, or cell types, is a classical approach to studying the nervous system. With increasingly more tools being invented to observe the neurons, new criteria were created to characterize different aspects, or modalities, of the cells. While these modality-specific categorizations have enabled in-depth knowledge in neuroscience, the inconsistencies across different criteria leave data integration across modalities technically difficult.

DDALAB: Identifying Latent States from Neural Recordings with Nonlinear Causal Analysis

Summary The goal of this proposal is to develop DDALAB, a software platform that will make it possible for researchers to identify latent cortical states and analyze the flow of information in large populations of neurons using Delay Differential Analysis (DDA). Although DDA can be used to analyze any time series data, we will initially focus on EEG recordings from the scalp and iEEG data recordings directly from the brain.

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