How does the brain compute? Understanding this process could lead to many advances in science and technology. The Boyden, Flavell, Barabasi, and Tegmark groups propose to examine how the cells within the brain of a simple animal work together to generate the computations that underlie behavior. The teams will study C. elegans, a small worm with just a few hundred neurons, yet capable of learning and adaptive behavior in complex real-world environments.  The teams will apply new technologies to measure and control the neural circuits of C. elegans, in order to investigate how they works. The project will also generate new mathematical tools to analyze the data that is collected - tools that could help analyze how the brain goes wrong in disorders such as Parkinson's or Alzheimer's. Using the data acquired, the project will reveal how brain circuits compute, which could inspire new algorithms for machine learning and computer information processing. These in turn could have broad impact on economic prosperity as well as in advancing human quality of life.

The Boyden, Flavell, Barabasi, and Tegmark groups will launch a novel integrative endeavor to reveal how entire nervous systems - from sensory input neurons, to motor output neurons, and including the networks that underlie learning, decision making, and other processes - work together as emergent wholes to generate the computations that underlie behavior. They will utilize C. elegans, with just 302 neurons, yet capable of learning and adaptive behavior in complex real-world environments.  They will optimize and deploy novel technologies, including a new fluorescent voltage indicator for C. elegans, and a method for 3-D visualization of entire nervous systems with molecular information via physical expansion by up to 10,000 fold in volume. They will record neural and behavioral dynamics, imaging the activity of neurons throughout entire brains and even entire nervous systems of freely moving as well as fictively behaving C. elegans engaged in complex decision-making tasks, or forming new memories. They will then use expansion microscopy to map the structure and molecular profiles of entire individual nervous systems. They will analyze the resultant network structures to determine how individual variation in these features connect to details of an individual's behavior, and make mathematical models of the relevant neural circuits capable of predicting how the nervous system would respond in complex contexts. The outcome of their work will yield radical new theories of how nervous systems operate, as well as a diversity of tools for the neuroscience and computational communities.

This project is funded by Integrative Strategies for Understanding Neural and Cognitive Systems (NSF-NCS), a multidisciplinary program jointly supported by the Directorates for Computer and Information Science and Engineering (CISE), Education and Human Resources (EHR), Engineering (ENG), and Social, Behavioral, and Economic Sciences (SBE).

Agency
National Science Foundation (NSF)
Institute
Division of Undergraduate Education (DUE)
Type
Standard Grant (Standard)
Application #
1734870
Program Officer
Ellen Carpenter
Project Start
Project End
Budget Start
2017-09-01
Budget End
2019-08-31
Support Year
Fiscal Year
2017
Total Cost
$707,296
Indirect Cost
Name
Massachusetts Institute of Technology
Department
Type
DUNS #
City
Cambridge
State
MA
Country
United States
Zip Code
02139