# A Brain-Wide Neural Network for Glucosensory-Motor Integration During Hypoglycemia

> **NIH NIH R01** · UNIVERSITY OF SOUTHERN CALIFORNIA · 2020 · $393,384

## Abstract

Hypoglycemia-associated autonomic failure (HAAF) is a serious complication that develops as a consequence
of insulin therapy and recurrent hypoglycemia, primarily in people with type 1 diabetes, but increasingly in type
2. HAAF attenuates epinephrine and compromised glucagon counterregulatory responses (CRRs), and develop
'hypoglycemic unawareness'. It can be fatal. All the mechanisms currently proposed for HAAF involve the brain.
This means that understanding the organization of the brain network that controls glycemia is a fundamental
objective for understanding the causes of HAAF. However a major impediment is the far from complete picture
of all the components of this network together with its detailed connectome. The goal of this proposal is to
determine where information from diverse glucosensory sites distributes within the brain and where potential
integrative sites are located. It will use state-of-the-art neurotropic viral tracing techniques, functional Fos
mapping, and a novel neuroinfomatic tool (Axiome) developed at USC that is designed to extract network
interactions from complex neuroanatomical datasets. Three specific aims will explore structural and functional
interactions between the motor systems that drive endocrine CRRs from the adrenal medulla and pancreas, and
key glucosensing regions that are located inside and outside the blood brain barrier: the ventromedial
hypothalamus (VMH), the area postrema, and the wall of the hepatic portal vein. Of particular importance for
HAAF is that two of these regions are important because of their contributions to the endocrine CRRs that
develop from rapid- (VMH) and slow-onset (hepatic portal vein) hypoglycemia. Slow-onset hypoglycemia is
thought to be most prevalent in iatrogenic insulin-induced hypoglycemia in diabetes. These new findings will
combine these connectional and functional results in a totally novel way thereby identifying major network
components and significantly improving our understanding of how the brain controls glycemic counterregulation
and how this breaks down in HAAF.

## Key facts

- **NIH application ID:** 9980895
- **Project number:** 5R01DK121531-02
- **Recipient organization:** UNIVERSITY OF SOUTHERN CALIFORNIA
- **Principal Investigator:** Alan G Watts
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $393,384
- **Award type:** 5
- **Project period:** 2019-08-01 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9980895

## Citation

> US National Institutes of Health, RePORTER application 9980895, A Brain-Wide Neural Network for Glucosensory-Motor Integration During Hypoglycemia (5R01DK121531-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9980895. Licensed CC0.

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