MULTISCALE CONTROL AND ANALYSIS OF IN-VITRO BRAIN CELL NETWORKS
Abstract
The dynamics of the brain have inspired a wide range of the promising models for learning and Artificial Intelligence. Successful machine learning architectures, such as deep neural networks and reservoir computers share some similarities in structure and dynamics to the networks of brain cells. Yet the network of brain cells in human brains far outperforms artificial intelligence. The goal of the project is to take the first steps to develop multiscale control and analysis tools that will allow for the creation of a novel in-vitro addressable brain cell networks. Rather than simply observing activity in brain cell networks, our goal is to design a network that is addressable. By addressable we mean that we will provide input to the network that changes network activity, and read out the resulting changes in the dynamics of the network. Specifically, our first goal is to build a brain cell network with cell lines that can be optogenetically activated. Our second goal is to develop characterizations of the dynamics of the system, specifically the response of spatio-temporal calcium waves and voltage dynamics to optogenetic activation. The development of multiscale measurement techniques for a broad range of brain cell network dynamics will yield a tool useful for analysis of complex network properties, particularly learning and ultimately cognition.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 12, 2021
- Source ID
- FA95502010368
Entities
People
- Wolfgang Losert
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of Maryland