OPTOPHYSIOLOGY: INTERFEROMETRIC IMAGING OF THE INTRINSIC NEURAL SIGNALING

Abstract

Research Title: Optophysiology: interferometric imaging of the intrinsic neural signaling Principle Program Officer: Dr. Patrick O. Bradshaw, Currently, studies of neurons and neural networks require very invasive methods, such as insertion of electrodes, as well as viral transfection and exogenous staining for fluorescence imaging of the voltage- and Ca indicators, which affect cellular metabolism and cannot be routinely applied to humans. Retina is the origin of visual perception and the most accessible “window” to the brain. Electrophysiological methods of retinal research, provide very coarse spatial and temporal resolution, and fluorescence imaging of the physiological activity cannot be used due to light sensitivity of the photoreceptors.We propose a revolutionary approach: non-invasive imaging of the intrinsic neural activity at cellular resolution, with diverse and far-reaching implications for developing the tools for studying neural networks in general and the retina, in particular. Changes in electric potential of a biological cell lead to nearly instantaneous sub-micrometer changes in its shape, which are measurable using interferometry. Unlike fluorescence imaging or electrophysiological techniques, interferometric imaging is non- invasive and can be done in the near-infrared range, without stimulating the photoreceptors. Using this approach in transmission (quantitative phase imaging) and in reflection (phase-resolved optical coherence tomography), we will examine the activity of many individual neurons in a massively parallel way while delivering visual stimuli at cellular resolution.

Document Details

Document Type
DoD Grant Award
Publication Date
Aug 12, 2021
Source ID
FA95502010186

Entities

People

  • Daniel Palanker

Organizations

  • Air Force Office of Scientific Research
  • Stanford University
  • United States Air Force

Tags

Fields of Study

  • Physics

Readers

  • Medical Imaging.
  • Neural Network Machine Learning.
  • Vision Science/Vision Psychology/Cognitive Neuroscience.

Technology Areas

  • AI & ML