(MURI17) Multiscale analysis of bioinspired low energy information processing: from organelles to organisms

Abstract

This proposal seeks to address a fundamental question – What is the memorycapacity of a brain and how does the brain process information with high energy efficiency?The storage capacity in a computer memory is measured in bits, each of which can have a valueof 0 or 1. In the brain, information is stored in the form of synaptic strength, a measure of howstrongly activity in one neuron influences another neuron to which it is connected. When twoneurons on either side of a synapse are active simultaneously, that synapse becomes stronger, aform of memory.Approach to solve the problem We propose here a multidisciplinary, multiscale approach thatwill establish the relationships between energy homeostasis and memory storage from the organellelevel to the organisms. We will conduct experiments in cell cultures of increasing complexity andin the fruit fly Drosophila melanogaster and develop the theoretical and computational frameworkto identify the mechanisms underlying energy and information in these systems. Insights gainedfrom the proposed work will have an impact on our understanding of how biological systemscouple energy homeostasis and information processing.Impact of results on the field The results from this work will have impact on our understandingof (a) the molecular biology of energy homeostasis in neurons, (b) sources and sinks of energyconsumption in neurons, and (c) how memory storage is affected by energy availability in singledendritic spines and neural circuits.

Document Details

Document Type
DoD Grant Award
Publication Date
Apr 09, 2018
Source ID
FA95501810051

Entities

People

  • Padmini Rangamani

Organizations

  • Air Force Office of Scientific Research
  • United States Air Force
  • University of California, San Diego

Tags

Readers

  • Data Mining and Knowledge Discovery.
  • Distributed Systems and Data Platform Development
  • Nanocomposite Materials Science

Technology Areas

  • Biotechnology