Recurrent attractor networks have long been the leading theoretical explanation for working memory. In these circuits, neurons excite one another in loops, so that a pattern of activity, once ignited, sustains itself long after the triggering stimulus has vanished. Neurons in the prefrontal cortex of primates show exactly this kind of persistent firing during memory tasks, outlasting the intrinsic time constants of their membranes by orders of magnitude, which argues that the persistence comes from the network rather than from any single cell. But attractor networks carry an inherent trade-off. A circuit tuned to hold activity stably is notoriously hard to switch off, and models have typically solved this by adding abstract gates that control when the attractor is allowed to run. What those gates look like in real biology, synapse by synapse, has remained unclear.

The fan-shaped body of the fruit fly, part of a navigation centre called the central complex, offered the research team led by Aaron Lanz and Katherine Nagel at NYU School of Medicine an unusually tractable place to look. Connectomics has mapped this region with synaptic precision, and genetic tools allow researchers to record from identified cell types in walking flies. Within the fan-shaped body, two local neuron types, called hΔK and PFG, are reciprocally connected in a ring, forming the most numerous recurrent connections of any columnar pair in the central complex. PFG neurons also receive direct inputs from the fly’s internal compass in the ellipsoid body, while both populations get broad input from tangential neurons. The architecture is strikingly reminiscent of classic working memory models: local recurrent excitation, structured input, and global inhibition.

Using two-photon calcium imaging in flies walking on an air-supported ball, the researchers confirmed that both hΔK and PFG neurons show a localized bump of activity that switches on with odour and persists while the fly maintains its heading. When the bump turned off, the fly’s trajectory deviated from its goal, linking the neural persistence directly to navigational behaviour. Whole-cell patch clamp recordings then probed where this persistence comes from. Injecting current into hΔK neurons produced rapid responses with no lingering excitation, ruling out intrinsic membrane properties. Instead, when the team optogenetically activated upstream tangential neurons, hΔK cells responded with slow, persistent excitation that vanished when recurrent signalling from hΔK itself was blocked with tetanus toxin. Persistence, in other words, is a property of the loop, not the neuron.

The synaptic details proved to be the study’s most surprising twist. Excitation arriving at hΔK is slow, likely carried by neuropeptides and modulators, since PFG neurons express no classical fast transmitter at all, only tyramine, myoinhibitory peptide and diuretic hormone 31. Inhibition, by contrast, is fast: two tangential neuron types, FB5V and FB6M, deliver rapid GABAergic inhibition that depresses over time and can be converted to excitation by the blocker picrotoxin. When the researchers built a computational model of the circuit based on real connectome weights, with 30 hΔK neurons, 18 PFG neurons and a global inhibitory unit, this speed asymmetry turned out to be crucial. With fast recurrent excitation, only a narrow band of excitation and inhibition strengths produced stable persistence; small parameter changes flipped the network between transient and non-decaying regimes. With slow excitation, a broad regime of tuneable persistence emerged, allowing the duration of the memory to be graded smoothly by modest changes in synaptic strength, matching the variability seen in the flies.

But a stable memory still needs a switch. Close inspection of the imaging data revealed that hΔK and PFG, despite their tight anatomical coupling, behave alike only during straight goal-directed runs. During turns and rest, the two populations decouple: PFG neurons maintain a low-amplitude bump that slides across the fan-shaped body in register with the fly’s heading, exactly like the compass it receives, while hΔK activity largely disappears and reappears only when the fly settles on a new direction. When the experimenters rotated the wind by 90 degrees mid-trial, low-amplitude PFG bumps followed the heading change faithfully, whereas high-amplitude bumps stayed fixed in place. A single population could thus flip between tracking the compass and holding a goal, depending on its own activity level.

The mechanism the team proposed is disarmingly elegant: disinhibition. In the connectome, only PFG neurons receive direct compass input, and that feedforward input is several-fold weaker than the recurrent connections between hΔK and PFG. In the model, when hΔK is strongly inhibited, the recurrent loop is functionally broken and PFG simply follows its compass input. The moment inhibition is lifted, recurrence locks the current compass value into place, and both populations snap into a high-amplitude, positionally stable bump, like a latch in digital logic capturing whatever value was on the line. Simulations showed that disinhibition could write a heading into memory at any chosen moment, and that sequential disinhibition bouts could update the stored goal to new compass positions.

Imaging the two inhibitory tangential types in behaving flies supported the model’s predictions with remarkable fidelity. FB5V neurons, which inhibit only hΔK, are tonically active but strongly suppressed by odour, and the suppression continues through the goal-directed run after the odour ends. Moment to moment, FB5V activity is negatively correlated with upwind velocity and positively correlated with angular speed, and it surges during large turns and whenever the fly deviates from its goal. FB6M, which inhibits both populations, shows a related pattern, suppressing during wind and rising during turns, though the model suggests it permissively regulates both populations together rather than decoupling them. The dendrites of these neurons sit in brain regions encoding odour and pre-motor signals, providing a plausible route by which sensory events and the fly’s own behaviour gate the memory circuit.

The study’s broader significance lies in the design principle it exposes. Rather than building an attractor from a uniform pool of excitatory neurons, the fly splits the network in two: one half, PFG, carries the content of the memory by receiving the compass input, while the other half, hΔK, receives the inhibitory gate that controls the timing of memory formation. Separating content from timing allows a circuit that is anatomically fixed to change its function on the timescale of a behaviour, switching between following information and storing it. Slow excitation, whether from peptides, modulators or the NMDA receptors familiar from mammalian working memory models, stabilizes the attractor across a forgiving range of synaptic weights, while fast disinhibition provides the write command. The authors suggest this motif could be general, potentially allowing other attractor networks, including line attractors and sequential dynamics, to be flexibly engaged and disengaged by sensory input or internal state. For a brain the size of a poppy seed, it is a strikingly computer-like solution, and one that neuroscientists studying working memory in larger brains will now be eager to look for.

Subject of Research: Recurrent attractor circuit mechanisms for rapid gating of navigational working memory in the Drosophila central complex

Article Title: A split attractor design for rapidly writing a navigational goal

Article References: Lanz, A. J., Kathman, N. D., Hao, E., Ermentrout, B., & Nagel, K. I. (2026). A split attractor design for rapidly writing a navigational goal. Nature. https://doi.org/10.1038/s41586-026-11144-9

Image Credits: AI Generated

DOI: 10.1038/s41586-026-11144-9

Keywords: Drosophila, attractor networks, working memory, navigation, fan-shaped body, disinhibition, connectomics, calcium imaging, whole-cell recording, computational modelling, synaptic dynamics, central complex

The German Research Foundation, known as the DFG, is supporting the venture with approximately 1.8 million euros over six years. The Emmy Noether Program is one of the most prestigious funding instruments available to early-career researchers in Germany, designed to allow outstanding scientists to build their own independent research groups and qualify for a university teaching career. For Farnworth, the award provides not only financial security but also the freedom to assemble a dedicated team and pursue a long-term scientific vision without the constraints that often accompany more narrowly defined project grants.

Farnworth arrived in Mainz on August 1, 2026, and his group is based at the Institute of Developmental Biology and Neurobiology, where he works in close proximity to the Neural Circuits Lab. The group is additionally affiliated with the Focus Program Translational Neurosciences and the Institute of Pathophysiology, giving it access to a broad network of neuroscientific expertise. The team he is assembling will consist of one postdoctoral researcher, two doctoral researchers, and a part-time technical assistant, a configuration typical of an Emmy Noether group and large enough to combine genetic experimentation, single-cell molecular analysis, and advanced imaging within a single laboratory.

The central question driving the new group is deceptively simple: why are some neural circuits far more evolutionarily flexible than others? Within a single brain, neighboring structures can follow dramatically different evolutionary trajectories. One region may be extensively remodeled across lineages, with new cell types appearing, cell numbers expanding or contracting, and connectivity patterns shifting, while another region remains essentially unchanged over vast stretches of evolutionary time. Understanding what makes a neural circuit conservative or permissive to change would illuminate a fundamental principle of how brains evolve, with implications reaching far beyond insects.

To tackle this question, Farnworth focuses on two well-characterized regions of the insect brain. The first is the mushroom bodies, paired structures best known for their roles in learning and memory, particularly in the context of olfactory association. The second is the central complex, a midline-spanning network of neuropils that serves as the insect’s navigation and orientation hub, integrating sensory information to control walking, turning, and spatial orientation. Over the course of insect evolution, these two regions have diverged sharply in their histories. Mushroom bodies have been extensively remodeled in different groups of insects, reflecting adaptations to widely varying lifestyles, whereas the central complex has remained comparatively conserved, preserving a recognizable ground plan across lineages.

Farnworth’s hypothesis is that the answer to this contrast may lie in development. During the development of an insect, many thousands of nerve cells and millions of connections arise from a comparatively small number of neural stem cells. Specific developmental programs determine which cell types are formed, how many cells of each type are produced, and which connections they establish with one another. We want to understand how these programs change over the course of evolution and how these changes allow neural circuits to adapt to different lifestyles and environmental conditions, Farnworth explains. If the developmental programs governing the mushroom bodies are inherently more modular or more tolerant of variation than those governing the central complex, that could explain why one structure has been free to diversify while the other has been locked in place.

Testing this idea requires a comparative framework, and the group has selected four insect species that together span a wide swath of the insect evolutionary tree: the common fruit fly Drosophila melanogaster, the red flour beetle Tribolium castaneum, the clonal raider ant Ooceraea biroi, and the Indianmeal moth Plodia interpunctella. Each species represents a distinct lineage, and each brings a different lifestyle to the comparison. The fruit fly is the canonical genetic model with a compact brain; the beetle represents holometabolous insects with a different larval development; the clonal raider ant offers a social species in which brain regions involved in learning and communication have adapted to colony life; and the moth adds a lineage with sophisticated olfactory-driven behaviors. By comparing homologous brain structures across these species, the researchers can distinguish features that have been conserved from those that have changed.

Methodologically, the project combines single-cell analyses, genetic tools, and high-resolution imaging. Single-cell approaches allow the team to catalog which cell types are present in each brain region of each species, effectively producing molecular census lists that can be compared across lineages. Genetic methods make it possible to trace the lineages of neural stem cells and to manipulate developmental programs experimentally, revealing how changes in stem cell behavior translate into changes in adult circuitry. High-resolution imaging, meanwhile, documents the anatomy of the resulting circuits, from the positions of cell bodies to the fine structure of the connections they form. Together, these techniques allow the researchers to determine which components of neural circuits have been conserved over evolutionary time and where changes have occurred in cell types, cell numbers, or connectivity.

The work exemplifies an approach often described as neuro-evo-devo, the intersection of neuroscience, evolutionary biology, and developmental biology. Rather than studying a single model organism in isolation, this framework treats development as the mechanism through which evolutionary change is enacted. Mutations do not reshape adult brains directly; they alter developmental programs, and it is these altered programs that produce different cell types, different cell numbers, and different wiring patterns in the next generation. By reading the developmental programs of multiple species and comparing their outputs, researchers can reconstruct how evolutionary transformations in the brain actually happened, and potentially predict which kinds of changes are easy for evolution to make and which are difficult.

For Farnworth, the move to Mainz represents the culmination of a research trajectory that has taken him through several of Europe’s leading institutions. He has been studying the evolution and development of the insect brain since his doctoral research. At the University of Göttingen, he investigated the development of the central complex in fruit flies and red flour beetles, gaining firsthand experience with the comparative approach that now anchors his independent program. Most recently, at the University of Bristol, he studied the evolution of neural circuits in butterflies, extending his comparisons to a lineage in which visual and cognitive adaptations are especially pronounced. JGU provides an excellent research environment for my neuro-evo-devo approach, which seeks to understand brain evolution through its development, Farnworth says. This combination of strong developmental and evolutionary biology is rare. JGU also offers excellent core facilities, particularly in imaging. With the Emmy Noether funding now secured and the group taking shape in Mainz, the coming six years promise to shed new light on one of neuroscience’s deepest questions: how the tiny brains of insects are built, and why evolution has rewritten some parts of their blueprint while leaving others untouched for hundreds of millions of years.

Subject of Research: Evolution and development of neural circuits in the insect brain

Article Title: Evolutionary neurobiologist Max Farnworth joins JGU from Bristol with Emmy Noether Funding

Article References: Evolutionary neurobiologist Max Farnworth joins JGU from Bristol with Emmy Noether Funding. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: neuroscience, evolutionary biology, developmental biology, insect brain, Emmy Noether Program, DFG, mushroom bodies, central complex, neural circuits, Johannes Gutenberg University Mainz, single-cell analysis, neuro-evo-devo