Improving our understanding of the functional circuitry of the brain has important and manifold implications for our understanding of mental health, as well as fields like consciousness and computing. In the last decade, optical techniques have arisen that allow both recording and control of targeted neurons for brain mapping, and many of the best of these techniques employ multiphoton microscopes with spatial light modulator (SLM) technology and complex algorithms to shape the light and analyze increasingly large neural microcircuits in three-dimensions (3D). SLMs can arbitrarily shape the wavefront of light to create multiple independently targeted beams in 3D to control groups of neurons, with the maximum number of studied neurons being limited primarily by the laser power on the SLM. Because the SLM can mimic nearly any optical element, these versatile tools also provide additional capabilities when incorporated into microscopes, such as adaptive aberration correction and remote focusing. Despite the potential for SLMs to revolutionize the microscopes used in neuroscience, their adoption remains limited by the difficulty in incorporating the SLM into the expensive multiphoton microscope platforms used by investigators and by the complexity of integrating SLM control into the microscopy software. In this Phase II effort, Boulder Nonlinear Systems (BNS) and Dr. Darcy Peterka and the Yuste laboratory at Columbia University will address this barrier by developing a user-friendly bolt-on SLM module for existing multiphoton microscopes along with full software integration of the SLM into both open-source and commercial microscopy software. This work will leverage knowledge gained during the Phase I development of the Pocketscope, a portable and low-cost SLM microscope for simple in vitro neuroscience studies, and integrate close feedback from a range of industry partners and leaders in neuroscience. As part of this work, BNS will also improve the speed, power handling, and reliability of the SLMs and utilize their strategic commercial partner, Meadowlark Optics, to bring down SLM cost and improve software integration. Successful completion of this project will result in the new SLM-based microscope module, platform- indpendent software integration, and improved SLM joining the Phase I Pocketscope to provide a suite of powerful tools, each with their own impact and commercial niche, capable of transforming the optical exploration of neural networks.

Public Health Relevance

Improving our understanding of the functional circuitry of the brain has important and manifold implications for our understanding of mental health, as well as fields like consciousness and computing. In the last decade, optical techniques have arisen that allow both recording and control of targeted neurons for brain mapping, and many of the best of these techniques employ multiphoton microscopes with spatial light modulator (SLM) technology and complex algorithms to shape the light and analyze increasingly large neural microcircuits in three-dimensions. This project seeks to improve the adoption and dissemination of this powerful technique through close collaborations with industry and the neuroscience community to develop a user-friendly add-on SLM module and software for existing multiphoton microscopes.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Small Business Innovation Research Grants (SBIR) - Phase II (R44)
Project #
5R44MH109187-04
Application #
9120942
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Grabb, Margaret C
Project Start
2012-09-21
Project End
2018-04-30
Budget Start
2016-05-01
Budget End
2017-04-30
Support Year
4
Fiscal Year
2016
Total Cost
Indirect Cost
Name
Boulder Nonlinear Systems, Inc.
Department
Type
DUNS #
602673188
City
Lafayette
State
CO
Country
United States
Zip Code
80026
Yang, Weijian; Carrillo-Reid, Luis; Bando, Yuki et al. (2018) Simultaneous two-photon imaging and two-photon optogenetics of cortical circuits in three dimensions. Elife 7:
Friedrich, Johannes; Yang, Weijian; Soudry, Daniel et al. (2017) Multi-scale approaches for high-speed imaging and analysis of large neural populations. PLoS Comput Biol 13:e1005685
Carrillo-Reid, Luis; Yang, Weijian; Bando, Yuki et al. (2016) Imprinting and recalling cortical ensembles. Science 353:691-4