Biology subjects

Turner-Evans, D. B.

Publications and source records attributed to Turner-Evans, D. B..

6 recordsLinked to original sources

bioRxiv2026

Divergent excitatory and inhibitory signaling in a head direction circuit

Neural cell types are often clustered into inhibitory, excitatory, or neuromodulatory populations. However, the signaling mechanism between two neurons ultimately depends on their neurotransmitter-receptor pairings. Here, we demonstrate an example of a glutamatergic population of neurons that appears to either excite or inhibit their downstream partners depending on the type of glutamate receptor expressed in the downstream cell type. The upstream population encodes a sinusoidal head direction signal. The downstream partners that are excited by glutamate encode the same signal while the downstream partners that are inhibited by glutamate encode a 180{degrees} phase-shifted copy. The upstream population therefore appears to pass on two different phases of the same signal by making either excitatory or inhibitory connections to different downstream partners.

neuroscience↗

bioRxiv2025

Octopamine instructs head direction plasticity

Many plasticity rules rely on adjusting the strength of synapses between pairs of cells based on their coincident activity. We uncovered a new mechanism for coincidence detection in the Drosophila head direction network. To maintain an accurate sense of direction, head direction neurons that signal orientation during navigation must learn to anchor to relevant external sensory cues in novel environments. Yet the synaptic mechanism for this form of unsupervised learning is unknown in any organism. In Drosophila, GABAergic visual inputs converge onto head direction neurons, and these inhibitory synapses change strength with experience to learn the relationship between visual landmarks and head direction. However, how coincident pre- and postsynaptic activity is detected across this inhibitory synapse is not understood. We discovered that neurons which release the monoamine octopamine close a feedback loop that conveys postsynaptic head direction activity onto presynaptic terminals of visual inputs. This octopamine pathway is required for anchoring the head direction network to visual cues. Furthermore, pairing structured activation of octopamine neurons with a visual cue is sufficient to drive rapid plasticity, even without postsynaptic head direction cell activity. Previous work has extensively characterized coincidence detection mechanisms at excitatory synapses; our work defines a novel mechanism for coincidence detection at an inhibitory synapse, in which postsynaptic activity is relayed via a neuromodulatory neuron onto presynaptic terminals.

neuroscience↗

bioRxiv2024

Predicting neuronal firing from calcium imaging using a control theoretic approach

Two-photon calcium imaging has become a powerful tool to explore the functions of neurons and the connectivity of their circuitry. Frequently, fluorescent calcium indicators are taken as a direct measure of neuronal activity. These indicators, however, are slow relative to behavior, obscuring functional relationships between an animals movements and the true neuronal activity. As a consequence, the firing rate of a neuron is a more meaningful metric. Converting calcium imaging data to the firing of a neuron is nontrivial. State of the art methods depend largely on neural networks or non-mechanistic processes, which may yield acceptable correlations between calcium dynamics and the frequency at which a neuron fires, but do not illuminate the underlying chemical exchanges within the neuron or require significant data to be trained on. Leveraging modeling frameworks from chemical reaction networks (CRN) coupled with modern control architectures, a new algorithm is presented based off of fully deterministic ordinary differential equations (ODEs). This framework utilizes model predictive control to challenge state of the art correlation scores while retaining the interpretability that comes inherent with a model. Moreover, these computations can be done in real time, thus enabling online experimentation informed by neuronal firing rates. To demonstrate the use cases of this architecture, it is tested on a ground truth dataset courtesy of the spikefinder challenge. Finally, the predictive power of the methodology put forward here is underscored by demonstrating its ability to aid in the creation of novel indicators utilized in two-photon imaging. Author summaryWe put forward a novel approach to infer when neurons fire as a function of calcium concentration. These calcium recordings are useful for imaging whole populations of neurons, such as those found in the brain, but act only as a proxy for the true underlying spiking occurrences. Moreover, these calcium traces are unfortunately noisy. To uncover the actual firing times we apply modern control architectures to a framework built from chemical reaction equations. The result is accurate, fast enough to provide information in real time, and highly interpretable. More broadly this analysis process aids understanding in contexts where methods of measurement obfuscate the desired ground truth information. Not just capable of inference, prediction is possible thanks to the fully mechanistic formulation provided here. Specifically, we may quantify how indicators, which allow the tracking of calcium, behave in the presence of differing conditions. In more general terms, this framework also enables understanding of the tools used to measure the desired underlying signals.

neuroscience↗

bioRxiv2023

A rotational velocity estimate constructed through visuomotor competition updates the fly's neural compass

Navigating animals continuously integrate velocity signals to update internal representations of their directional heading and spatial location in the environment. How neural circuits combine sensory and motor information to construct these velocity estimates and how these self-motion signals, in turn, update internal representations that support navigational computations are not well understood. Recent work in Drosophila has identified a neural circuit that performs angular path integration to compute the flys head direction, but the nature of the velocity signal is unknown. Here we identify a pair of neurons necessary for angular path integration that encode the flys rotational velocity with high accuracy using both visual optic flow and motor information. This estimate of rotational velocity does not rely on a moment-to-moment integration of sensory and motor information. Rather, when visual and motor signals are congruent, these neurons prioritize motor information over visual information, and when the two signals are in conflict, reciprocal inhibition selects either the motor or visual signal. Together, our results suggest that flies update their head direction representation by constructing an estimate of rotational velocity that relies primarily on motor information and only incorporates optic flow signals in specific sensorimotor contexts, such as when the motor signal is absent.

neuroscience↗

bioRxiv2020

A connectome of the Drosophila central complex reveals network motifs suitable for flexible navigation and context-dependent action selection

Flexible behaviors over long timescales are thought to engage recurrent neural networks in deep brain regions, which are experimentally challenging to study. In insects, recurrent circuit dynamics in a brain region called the central complex (CX) enable directed locomotion, sleep, and context- and experience-dependent spatial navigation. We describe the first complete electron-microscopy-based connectome of the Drosophila CX, including all its neurons and circuits at synaptic resolution. We identified new CX neuron types, novel sensory and motor pathways, and network motifs that likely enable the CX to extract the flys head-direction, maintain it with attractor dynamics, and combine it with other sensorimotor information to perform vector-based navigational computations. We also identified numerous pathways that may facilitate the selection of CX-driven behavioral patterns by context and internal state. The CX connectome provides a comprehensive blueprint necessary for a detailed understanding of network dynamics underlying sleep, flexible navigation, and state-dependent action selection.

neuroscience↗

bioRxiv2019

The neuroanatomical ultrastructure and function of a biological ring attractor

Neural representations of head direction have been discovered in many species. A large body of theoretical work has proposed that the dynamics associated with these representations is generated, maintained, and updated by recurrent network structures called ring attractors. We performed electron microscopy-based circuit reconstruction and RNA profiling of identified cell types in the heading direction system of Drosophila melanogaster to directly determine the underlying neural network. We identified network motifs that have been hypothesized to maintain the heading representation in darkness, update it when the animal turns, and tether it to visual cues. Functional studies provided additional support for the proposed roles of individual circuit elements. We also discovered recurrent connections between neuronal arbors with mixed pre- and post-synaptic specializations. Overall, our results confirm that the Drosophila heading direction network contains the core components of a ring attractor while also revealing unpredicted structural features that might enhance the networks computational power.

neuroscience↗