Imaging Neural Networks with Time-Resolved Fluorescence Microscopy

Abstract

We propose to build a scanning confocal microscope (tr-SCM) for time-resolved fluorescence imaging of neuronal action potentials. Picosecond-resolution time-correlated singlephoton counting (TCSPC) electronics will be used to image fluorescence lifetime (FLIM) and Fšrster resonant energy transfer dynamics (FLIM-FRET), as well as to track single fluorophores using antibunching measurements and correlation spectroscopy (FCS). With these capabilities, voltage sensitive quantum dots (QDs) will be optimized for high temporal and spatial resolution imaging of action potentials in vitro. Direct imaging of the neuronal membrane potential with sub-threshold sensitivity is not currently possibly with any optical technique, and would dramatically advance the study of synaptic inputs/outputs, and neural plasticity. Thus, voltage sensitive quantum dots and the proposed tr-SCM directly impacts many efforts within Columbia UniversityÕs DoD funded MURI that will greatly advance our goals of imaging structural and functional connectivity in neural networks. At the same time, this tool will impact technologies aimed at increasing the energy efficiency of lighting, displays, and detectors that can increase the autonomy of soldiers in the field.

Document Details

Document Type
DoD Grant Award
Publication Date
Sep 11, 2018
Source ID
W911NF1610211

Entities

People

  • Jonathan Owen

Organizations

  • Army Contracting Command
  • Columbia University
  • United States Army

Tags

Fields of Study

  • Physics

Readers

  • Nanoscale Plasmonic Nanotechnology
  • Neuroscience
  • Quantum Dot Semiconductor Device Photonics and Graphene Optoelectronic Materials and THz Physics.

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • AI & ML - Neural Networks
  • Microelectronics
  • Quantum Computing