Biology subjects

Hattori, D.

Publications and source records attributed to Hattori, D..

4 recordsLinked to original sources

bioRxiv2026

Path knockout: an analysis tool for connectome-driven circuit discovery

Neural circuits in the brain transform sensory information into perceptual, emotional and motor output. The connectome -- a synaptic-resolution wiring diagram of all neurons in a nervous system -- provides a neuroanatomical blueprint for identifying different circuits that mediate specific computations. However, its sheer scale and complexity pose a significant challenge in extracting functionally relevant multi-synaptic pathways. Here we established path knockout, a connectome analysis method that identifies dominant multi-synaptic pathways. Path knockout uses the input fraction of each synaptic connection as a surrogate for the probability that information transfer succeeds across that synapse and calculates approximate probability, or connection strength, that at least one path succeeds among all multi-synaptic paths between defined source and sink neuron populations. It then quantifies the importance of each interneuron by assessing the impact of its removal on the connection strength. We demonstrate that path knockout outperforms other methods for pathway analysis and identifies known and novel interneurons in the Drosophila circuits. Using path knockout, we identified a convergent circuit motif linking sexually dimorphic aggression command neurons to a shared isomorphic visual pursuit pathway. Path knockout is implemented such that it runs in minutes on a standard computer. Thus, path knockout provides a scalable and generalizable framework for connectome-driven circuit discovery.

neuroscience↗

bioRxiv2025

A dopamine circuit regulates locomotor initiation and persistence in Drosophila

Decisions to initiate or terminate locomotion reflect the commitment of an animal to expend energy and thus must be appropriately regulated. Dopaminergic system has been implicated in locomotor regulation but how it controls these decisions remains unclear. Here we show that a dopamine circuit in Drosophila mushroom body regulates cue-induced locomotor initiation and termination by integrating locomotor history and current motivation. This circuit consists of the locomotor-initiator mushroom body output neurons, MBON09, and the locomotor-terminator MBON21. Previous locomotor initiation by default suppresses the propensity of future initiation through depression of MBON09 activity by locomotion-sensitive dopamine afferents, preventing redundant action. Locomotor persistence is promoted through combined inhibition of MBON21 by MBON09 and by distinct dopamine afferents that receive fluctuating motivational signals. Persistent locomotion under high motivational state, in turn, causes dopamine-dependent MBON09 facilitation, reinvigorating locomotor initiation program. Our results revealed a dopaminergic mechanism to transform recent behavior and current motivation into a moment-by-moment internal state that in turn regulates locomotor decisions.

neuroscience↗

bioRxiv2023

A rapid and bidirectional reporter of neural activity reveals neural correlates of social behaviors in Drosophila

Neural activity is modulated over different timescales encompassing sub-seconds to days reflecting changes in external environment, internal state, and behavior. Using Drosophila as a model, we have developed a rapid and bidirectional reporter that provides a robust cellular readout of recent neural activity. This reporter utilizes nuclear vs cytoplasmic distribution of CREB-regulated transcriptional coactivator, CRTC. Subcellular distribution of GFP-tagged CRTC (CRTC::GFP) bidirectionally changes on the order of minutes and reflects both increases and decreases in neural activity. We establish an automated machine-learning-based routine for efficient quantification of reporter signal. Using this reporter, we demonstrate acute mating- evoked activation of peptidergic neurons. We further investigate the functional role of the master courtship regulator gene, fruitless, and show that fruitless is necessary to ensure activation of male arousal neurons by female cues. Together, our results establish CRTC::GFP as a bidirectional reporter of recent neural activity suitable for examining neural correlates in behavioral contexts.

neuroscience↗

bioRxiv2022

A neural theory for counting memories

"Ive never smelled anything like this." "Ive seen you once before." "Ive heard this song many times." Keeping track of the number of times different stimuli have been experienced is a critical computation for behavior. This computation occurs ubiquitously across sensory modalities, and naturally without reward or punishment. However, the neural circuitry that mediates this computation remains unknown. Here, we propose a theoretical two-layer neural circuit that can store counts of stimulus occurrence frequencies. This circuit implements a data structure, called a count sketch, that is commonly used in computer science to maintain item frequencies in streaming data. Our first model implements the count sketch data structure using Hebbian synapses and outputs stimulus-specific frequencies. Our second model uses anti-Hebbian plasticity and only tracks frequencies within four count categories ("1-2-3-many"), which we suggest makes a better trade-off between the number of categories that need to be distinguished and the potential ethological value of those categories. Using real-world datasets, we show how both models can closely track the frequencies of different stimuli experienced, while being robust to noise, thus expanding the traditional novelty-familiarity memory axis from binary to continuous. Finally, we show that an implementation of the "1-2-3-many" count sketch -- including network architecture, synaptic plasticity rule, and output neuron that encodes count categories -- exists in a novelty detection circuit in the insect mushroom body, and we argue that similar circuit motifs also appear in mammals, suggesting that basic memory counting machinery may be broadly conserved.

neuroscience↗