# Efficient Two-Photon Voltage Imaging of Neuronal Populations at Behavioral Timescales

> **NIH NIH U01** · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · 2022 · $1,336,736

## Abstract

PROJECT SUMMARY
Understanding how information is processed in the mammalian neocortex has been a longstanding
question in neuroscience. While the action potential is the fundamental bit of information, how these
spikes encode representations and drive behavior remains unclear. In order to adequately address this
problem, it has become apparent that experiments are needed in which activity from large numbers of
neurons can be measured in a detailed and comprehensive manner across multiple timescales. Direct
measurements of action potentials have primarily been achieved by electrophysiology. However, such
measurements cannot easily be combined with other methods to assess the connectivity and molecular
properties of neurons. Integrating functional, anatomical, and genetic information is critical for
understanding how neuronal circuits are organized and computed. There have been long-standing efforts
in developing optical methods for measuring neuronal activity due to its compatibility to simultaneously
measure connectivity and molecular identity using fluorescent labeling techniques. We have developed a
two-photon-excitable genetically-encoded voltage-sensitive indicator and ultra-fast two-photon microscope
that enables optical measurements of action potentials deep into the brain. However, imaging at high
signal-to-noise beyond several minutes remains challenging due to photo-bleaching and risks of photo-
damage. In order for these new technologies to become more robust for neuroscience applications, it is
necessary to improve upon the stability, reliability, and efficiency of two-photon voltage imaging. To
achieve this, it requires a concerted effort between optical engineers, protein engineers, and
computational scientists to optimize instrumentation, sensors, and image analysis for broad
dissemination. This multi-investigator effort proposes to advance two-photon voltage imaging to enable
sustained tracking of population activity at timescales of animal behavior and learning.

## Key facts

- **NIH application ID:** 10516906
- **Project number:** 1U01NS128665-01
- **Recipient organization:** BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
- **Principal Investigator:** Jerry L Chen
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $1,336,736
- **Award type:** 1
- **Project period:** 2022-08-15 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10516906

## Citation

> US National Institutes of Health, RePORTER application 10516906, Efficient Two-Photon Voltage Imaging of Neuronal Populations at Behavioral Timescales (1U01NS128665-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10516906. Licensed CC0.

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