# A neurocomputational assay of gastrointestinal interoception in anorexia nervosa

> **NIH NIH R01** · LAUREATE INSTITUTE FOR BRAIN RESEARCH · 2021 · $724,878

## Abstract

PROJECT SUMMARY
Given that anorexia nervosa (AN) has the highest mortality rate of any psychiatric illness and current
treatments show limited efficacy, there is a crucial need to better understand the brain mechanisms driving the
pathophysiology of this disorder. This proposal combines an experimental medicine approach focused on
gastrointestinal (GI) interoception with computational modeling to probe neural circuits of interoception and
appetite-related gastric processing in AN. The goal is to identify perceptual and neural markers for AN at the
individual patient level and apply machine learning methods to test clinical outcomes prediction longitudinally.
Supported by our preliminary data, this proposal is based on the premise that the pathophysiology of AN
includes a computational dysfunction manifested by cognitive suppression of the expected precision of afferent
interoceptive signals associated with hunger, which reduces their motivational influence and facilitates
maladaptive and avoidant eating behaviors. We propose a case-control study with 65 AN and 65 healthy
comparisons who will undergo extensive baseline testing using a novel GI interoception probe during
measurement of symptoms, behavior, circuits, and physiology. Sensory stimulation will occur during the
premeal period, anchoring responses to an anticipatory context with high relevance to the disorder. These
individuals will be followed for 180 days to examine clinical outcomes. A computational approach will examine
the basic hypothesis that AN individuals have lower sensory precision for GI interoception and that the degree
of sensory imprecision is related to clinical characteristics. Moreover, we will examine the relationship of this
imprecision to circuit and physiological measures. We will then apply machine learning approaches to these
neurophysiological and perceptual measures to longitudinally test the prediction of clinical outcomes. Achieving
the aims of this project will provide unique insights into the pathophysiology of AN by arbitrating whether AN is
a consequence of “top-down” or “bottom-up” dysregulation in the nervous system, which could transform our
understanding of how intrinsic interoceptive disturbances lead to AN. Pragmatically, it will result in new
technologies for identifying interoceptive dysfunction at the individual level, allowing psychiatry to develop
diagnostic and predictive biomarkers of AN. Thus the neurocomputational assay of gastrointestinal
interoception in AN could be used to develop low-cost, scalable, and objective tools for identifying dysfunction
in individual patients, to facilitate neurobiologically-based definitions of recovery, and to predict the risk of
relapse following treatment. Finally, this proposal lays the groundwork for the future development of precision
psychiatric interventions such as perceptual retraining therapies to target (and recalibrate) abnormal brain-
body interactions.

## Key facts

- **NIH application ID:** 10278979
- **Project number:** 1R01MH127225-01
- **Recipient organization:** LAUREATE INSTITUTE FOR BRAIN RESEARCH
- **Principal Investigator:** SAHIB S. KHALSA
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $724,878
- **Award type:** 1
- **Project period:** 2021-09-01 → 2026-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10278979

## Citation

> US National Institutes of Health, RePORTER application 10278979, A neurocomputational assay of gastrointestinal interoception in anorexia nervosa (1R01MH127225-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10278979. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*