Mala Murthy

This study investigates how Drosophila males decide to stay or switch behaviors in response to competing social and environmental cues using a closed-loop paradigm and neural imaging.

The paper automatically aligns Drosophila connectomes to classify neurons and identify sex-specific and sexually dimorphic cell types in the ventral nerve cord.

The paper presents the first densely reconstructed adult fruit fly connectome integrating the brain and ventral nerve cord, revealing distributed control circuits involving local and long-range neural connections.

This paper introduces light beads microscopy (LBM) to enable high-speed volumetric imaging of Drosophila brains, revealing fast neural responses to auditory stimuli.

The paper shows that male Drosophila adjust their innate courtship strategy based on altered social feedback using optogenetics.

The paper identifies a new courtship behavior in Drosophila called 'waggling' and shows it is part of a structured sequence driven by P1/pC1 neurons.

The paper improves synapse detection in Drosophila brain connectomes using new neural networks, achieving better performance in challenging regions and improved neuron clustering.

The paper identifies and analyzes sexually dimorphic neurons in the Drosophila brain using connectome data to understand their connectivity and functional roles in behavior.

BIFROST registers diverse Drosophila brain imaging datasets into a common anatomical space, enabling cross-experiment and cross-modality comparisons with sub-10 micron precision.

The paper presents the first neuronal wiring diagram of a whole adult Drosophila brain, revealing synaptic connections and circuit mechanisms underlying sensorimotor behaviors.

The paper creates a computational model of the Drosophila brain connectome to study sensorimotor processing and validates predictions through experiments.

The paper completes the list of cell types in the Drosophila optic lobe and identifies connectivity rules, revealing new families and clusters related to visual functions.

The paper analyzes the network properties of the Drosophila whole-brain connectome, identifying rich club organization and signal integration/broadcasting neurons.

The paper provides a connectomic description of ascending and descending neurons in the Drosophila nervous system, revealing sexual dimorphism and motor-related circuits.

The paper uses artificial neural networks to classify neurotransmitters from electron microscopy images of Drosophila melanogaster synapses, achieving high accuracy and revealing ultrastructural differences.

The paper develops a simulation-based model to infer neural dynamics of memory during fly courtship, finding that adaptive population mechanisms transform song history into a mnemonic format.

The paper introduces the VCL Benchmark, a dataset for evaluating sound source localization algorithms in rodents using real and simulated audio data.

The paper profiles the transcriptomes of Drosophila male-specific P1 neurons in socially paired versus solitary males, identifying gene expression changes linked to courtship behavior and immune system interactions.

The paper introduces a method to learn a causal model of the fly brain using a connectome and optogenetic perturbation data, revealing that global brain dynamics arise from small, localized circuits.

The paper investigates how a single neural pathway in Drosophila generates context-dependent song sequences by switching between two regimes based on sensory input.

This study shows that forcing FruM expression in D. virilis females leads to male-typical behaviors but preserves female song and egg-laying, unlike D. melanogaster.

Annotating the 127,978-neuron FlyWire fly connectome yields 4,552 cell types, 3,094 cross-validated against the hemibrain; cell-type edges above 10 synapses or 1.1% of input recur over 90% across hemispheres.

The paper introduces a method to map deep network units to real neurons and shows that visual projection neurons in Drosophila form a distributed population code for social behavior.

The paper maps the auditory pathway in Drosophila, identifies new cell types, and reveals a network of neurons with continuous song mode preferences and non-hierarchical connectivity.

FlyWire enables collaborative proofreading of whole-brain connectomes through an online platform, demonstrating its utility in reconstructing and analyzing mechanosensory neuron circuits.

The paper reconstructs 3D cell nuclei in a Drosophila brain, identifying over 133,000 nuclei, mostly neurons, and highlights differences in nuclear size and cell density across brain regions.

The paper shows that quadratic filtering and divisive normalization in Drosophila auditory neurons create a robust representation of courtship song by exploiting its natural statistics.

This study identifies pC1-Alpha neurons in Drosophila females that drive persistent behaviors through recurrent neural connectivity.

The paper uses volumetric neural imaging to study auditory activity across the entire central brain of Drosophila, finding widespread and modality-general responses tuned to courtship song.

The paper develops an unsupervised method to identify internal states from behavioral data and applies it to courtship behavior in Drosophila, revealing three latent states and their neural basis.