Abstract While current efforts in the analysis of neural circuits focus on interneuronal connectivity mediated by chemical synapses, less is known about the contribution of electrical synapses. Electrical transmission is mediated by neuronal gap junctions, which are widely distributed throughout the vertebrate brain.
Project Summary New tools are urgently needed to selectively target constructs that monitor and manipulate the activity of individual cell types without having to rely on genetic manipulation.
PROJECT SUMMARY Overview: We will extend and develop implementations of foundational methods for analyzing populations of attributed connectomes. Our toolbox will enable brain scientists to (1) infer latent structure from individual connectomes, (2) identify meaningful clusters among populations of connectomes, and (3) detect relationships between connectomes and multivariate phenotypes. The methods we develop and extend will naturally overcome the challenges inherent in connectomics: high-dimensional non-Euclidean data with multi-level nonlinear interactions.
The goal of this research is to establish new robust methods for manipulation of specific circuits and genetically defined neuron types in brains of model organisms with small molecules. While several chemical-genetic techniques are already available, these techniques have drawbacks that limit their utility.
There is an increasing need for efficient and robust software to process, integrate, and offer insight across the diversity of population imaging efforts underway across the BRAIN Initiative and other projects.
Abstract: Many cell types together assemble the functional circuitry of the human brain. For over a century, neuroscientists have categorized brain cell types by their features, including shape, position, physiology, molecules, and function. Single cell transcriptomics studies are now defining molecular cell types at a resolution not previously possible, uncovering a taxonomy of hundreds to thousands of brain cell types.
Project Summary The function of the nervous system is dependent on complex interactions between networks of neurons composed of multiple neuron types. Understanding how these networks function both in health and disease is dependent on understanding the precise connectivity between specific neuron types and their functional interactions in the intact brain.
Project Summary: (30 lines of text max) We propose to create an open-source cloud-based software system for real-time fMRI neurofeedback experiments. Our goal is to make real-time fMRI neurofeedback broadly accessible for both the scientific and clinical communities, in order to accelerate both basic research and the development and deployment of clinical treatments. Real-time fMRI neurofeedback (RT-fMRI) is an increasingly important area of research.
Two major recent advances have raised the possibility of fundamental breakthroughs in both basic and clinical neuroscience: the development of new tools to probe the nervous system with single-cell resolution as well as brain-wide scope, and breakthroughs in machine learning methods for handling complex data. Yet there remain crucial barriers to progress: while data acquisition tools are now broadly within the grasp of neuroscience researchers, the same cannot be said about data analytical tools that can tackle the complexities of the new data sets being gathered.
