# The encoding of uncertainty in the Drosophila compass system

> **NIH NIH R34** · HARVARD MEDICAL SCHOOL · 2021 · $761,719

## Abstract

Summary
Strategic behaviors often take account of uncertainty. For example, if we are presented with two conflicting
pieces of information, we give less weight to the more uncertain source of information – i.e., the source of
information that leads to lower accuracy overall. Notably, even insects behave as if they make strategic use of
their own uncertainty. Importantly, the neural correlates of uncertainty are essentially unknown. In this
collaborative project, we will use modeling and neural imaging to identify the neural correlates of uncertainty. We
will focus on the “compass” in the Drosophila brain. The intrinsic neurons of the compass (EPG neurons) form a
topographic map of heading direction. At any given moment, there is a “bump” of neural activity in the EPG
population which rotates like a compass needle as the fly turns. The position of the bump is influenced by internal
self-motion cues, external visual cues, and external wind direction cues. In previous theoretical work, the EPG
ensemble has been modeled as a ring attractor network. In general, ring attractors do not represent uncertainty
in the variable they are encoding. Most experiments characterizing compass neuron activity have been
performed either under conditions of extreme certainty (e.g., a bright visual cue), or extreme uncertainty (e.g.,
complete darkness). Therefore, it remains unclear how the system behaves under moderate uncertainty, and if,
under such conditions, it can still be well-described by standard ring attractor networks. Ideally, the compass
network would represent not only the fly's estimated heading direction, but also the uncertainty associated with
that estimate, so that behavioral strategies could be adjusted accordingly. In this project, we will investigate (1)
how uncertainty is represented, and (2) how it affects spatial learning. We will use a combination of algorithmic
modeling, network modeling, and in vivo imaging experiments combined with virtual reality environments.

## Key facts

- **NIH application ID:** 10298651
- **Project number:** 1R34NS123819-01
- **Recipient organization:** HARVARD MEDICAL SCHOOL
- **Principal Investigator:** Jan Drugowitsch
- **Activity code:** R34 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $761,719
- **Award type:** 1
- **Project period:** 2021-08-15 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10298651

## Citation

> US National Institutes of Health, RePORTER application 10298651, The encoding of uncertainty in the Drosophila compass system (1R34NS123819-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10298651. Licensed CC0.

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