# Data Science Core

> **NIH NIH U19** · UNIVERSITY OF CHICAGO · 2022 · $391,336

## Abstract

Two-photon calcium imaging combined with holographic optogenetic excitation offers a powerful new way to
read and control neuronal codes, with the potential to directly link spatiotemporal activity at single-neuron
resolution to behavior. The volume of data produced in such experiments is very large, involving sensory
inputs, acquired images, and behavioral outputs. Another contributor to data complexity are the holographic
light patterns produced that allow for optogenetic control of neuronal groups. Neither data nor analysis
approaches are standardized for this technology yet. The Data Science Resource Core will be essential to
enable the experimental studies proposed in these research projects, which span multiple laboratories and
sensory modalities. The three key aims of the Data Science Core will be (1) to facilitate data aggregation, (2) to
develop quality control on data acquisition and analysis, and (3) to enable theory guided experimental design.
The first aim is to standardize aggregation of data. We will deploy a new prototype Brain Platform graphical
user interface using data formats from the emerging Neurodata Without Borders structure. The Core will work
with all team members to integrate existing code written in multiple languages into the Brain Platform, which
will thus serve as local hubs for data aggregation and sharing. Once implemented, training materials will be
developed for broad dissemination of the Brain Platform
The second aim is to ensure the quality of data and analysis. Analysis codes from all team groups that is made
available through the Brain Platform will be regularly validated against each other and against ground-truth
data obtained in the technology core and other baseline data. Additionally, statistical analysis approaches will
be developed and implemented to enable power calculations for model inference.
The third aim is to enable theory guided experiment design and validation. This aim also will support data
analysis based on high-dimensional inference, including Granger causality, network criticality and stability
analysis, and intersection information.
Together, the three aims of the Data Science Core — standardized data aggregation, quality-controlled
analysis, and theory guided experimental design — will support robust, reliable and reproducible acquisition
and analysis of neural and behavioral data from experiments that use two-photon calcium imaging combined
with holographic optogenetic stimulation.

## Key facts

- **NIH application ID:** 10456141
- **Project number:** 5U19NS107464-05
- **Recipient organization:** UNIVERSITY OF CHICAGO
- **Principal Investigator:** WOLFGANG LOSERT
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $391,336
- **Award type:** 5
- **Project period:** 2018-09-15 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10456141

## Citation

> US National Institutes of Health, RePORTER application 10456141, Data Science Core (5U19NS107464-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10456141. Licensed CC0.

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