To move around in their surroundings in meaningful and goal-directed ways, a skill known as navigation, humans and animals rely on a series of complex cognitive (i.e., mental) processes. Navigation is also supported by the so-called head direction system, a neural network that keeps track of the direction in which an animal is facing, acting as an “internal compass.”

This system forms a so-called topographic map, organizing neurons in ways that correspond to specific head directions. While the contribution of the head direction system to navigation was explored in the past, its underpinning neural mechanisms have not yet been fully elucidated.

Researchers at Harvard Medical School carried out a new study investigating the processes through which the brains of Drosophila (fruit flies) represent head direction. Their findings, published in Nature Human Behavior, offer new insight into the processes through which the fruit fly brain creates representations of the environments they are moving in.

“Navigation requires us to take account of multiple spatial cues with varying levels of informativeness and learn their spatial relationships,” wrote Melanie A. Basnak, Anna Kutschireiter and their colleagues. “We investigate this process in the Drosophila head direction system, which functions as a ring attractor and a topographic map of head direction.”

To study the head direction system of fruit flies, Basnak, Kutschireiter and their colleagues used a combination of experimental techniques and technological tools. Firstly, they used a technique called population calcium imaging that can be used to track the activity of neurons.

Calcium imaging allows scientists to detect the influx of calcium ions that results from neurons firing electrical signals (i.e., action potentials).

In their experiment, the team simultaneously recorded the activity of entire neuron populations in the brains of fruit flies, as opposed to that of individual neurons. While they collected recordings using calcium imaging, the authors used a virtual reality set-up to control what the flies were seeing.

“Using population calcium imaging and multimodal virtual reality environments, we show that increasing cue informativeness improves encoding accuracy and produces a narrower and higher bump of activity,” wrote Basnak, Kutschireiter and their colleagues.

“When cues conflict, the more informative cue exerts more weight. A familiar cue is weighted more heavily and used to guide the remapping of a less familiar cue. When a cue is less informative, it is remapped more readily in response to cue conflict. All these results can be explained by an attractor model with plastic sensory synapses.”

The researchers found that when representing an environment, the brains of flies appear to give more “weight” to familiar cues and tend to adjust cues that are less familiar and thus deemed less “reliable.” Notably, they also observed individual differences in the navigation behavior of the flies they examined.

In their paper, the researchers introduce a model network that could explain their findings, which is rooted in a previously introduced model (i.e., the ring attractor model). In the future, their work could help to improve existing models of spatial navigation, while also potentially informing the development of bio-inspired robots and AI systems.

“Mechanistically, our results can be explained by a ring attractor model with a high rate of synaptic modification at sensory synapses onto HD cells,” they wrote.

“Conceptually, our findings show how continuous synaptic plasticity allows ongoing spatial learning and inference in a dynamic environment, albeit at the cost of reducing the stability of the system’s representational coordinate frame. Thus, our results highlight the fundamental tradeoff between stability and flexibility in the brain’s navigational centers.”

© 2025 Science X Network