# Decoding Astrocyte Signaling in Neural Circuitry with Novel Computational Modeling and Analytical Tools

> **NIH NIH R01** · VIRGINIA POLYTECHNIC INST AND ST UNIV · 2021 · $488,894

## Abstract

Astrocyte is the most abundant glia cell and significantly outnumbers neuron in the human brain. Long thought
to be primarily passive cell, astrocyte has been increasingly recognized as essential player with active
regulatory role in neural circuitry and pathology. Since a single astrocyte interacts with thousands of synapses,
other glial cells and blood vessels, it is well positioned to link neuronal information in different spatial-temporal
dimensions to achieve higher level brain integration. Indeed, neuron-astrocyte communication at synapses
regulates breathing, memory formation, motor function, and sleep, and are implicated in many neuropsychiatric
disorders. All these results provide strong rationale for modeling and analyzing astrocyte function, which will
provide unprecedented insights to our understanding how astrocytes function to regulate and protect brain and
how these functions can be exploited for astrocyte-based therapeutic targets.
Recent advances in the modern microscopy and ultrasensitive genetic encoded calcium indicators (GECI)
have enabled optical recording of astrocytic calcium dynamics – the excitatory state and functional readout of
astrocytes – in vitro, ex vivo and in vivo. Compared to the great experimental capability of generating
tremendous volumes of astrocyte functional data, the development of computational tools to analyze and
interpret the complex and big data is lagged far behind, which has severely jeopardized a deeper
understanding of the functional roles of astrocytes. To address the pressing need, we thus propose to develop
sophisticated computational tools for interpreting the complex calcium dynamics data, through judicious
application of advanced machine learning and systems theories. We have the following three specific aim.
Aim1). Developing computational tools to analyze the cellular properties of calcium signaling in a single
astrocyte. Aim2). Developing computational tools to analyze the network properties of calcium signaling in a
population of astrocytes. Aim3). Validating experimentally the computational tools, developing optimal
experiment protocol and disseminating the software packages.
Our preliminary studies on both synthetic and real datasets demonstrate the feasibility of our plans and
highlight the potential of analyzing astrocyte functional activity to understand neuronal circuitry and pathology,
including for the first time the surprising discovery of hyper-activity in Down’s syndrome astrocytes compared
to the normal astrocytes. This proposal is built on pre-established collaboration between two groups with the
much needed complementary expertise for accomplishing this project, (1) computational scientists (Yu lab at
Virginia Tech) and (2) experimental neuroscientists (Tian lab at UC Davis). The pre-established working
relationships, developed channels of communication and mechanisms for resource sharing will help insure that
the work will proceed in an efficient and effective manner.

## Key facts

- **NIH application ID:** 10102648
- **Project number:** 5R01MH110504-05
- **Recipient organization:** VIRGINIA POLYTECHNIC INST AND ST UNIV
- **Principal Investigator:** Guoqiang Yu
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $488,894
- **Award type:** 5
- **Project period:** 2017-04-14 → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10102648

## Citation

> US National Institutes of Health, RePORTER application 10102648, Decoding Astrocyte Signaling in Neural Circuitry with Novel Computational Modeling and Analytical Tools (5R01MH110504-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10102648. Licensed CC0.

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