Aurel A. Lazar

The paper introduces NeuroGraphBench, a tool for interactively exploring Drosophila connectomes to model neural circuit function.

This paper characterizes the functional logic of Drosophila's early olfactory system, identifying how it processes odorant information into a time and rank-based representation for classification.

The paper shows how houseflies maintain visual accuracy during fast motion by using synaptic high-frequency jumping, which enhances visual bandwidth and reduces delays.

The paper shows that steady-state and transient responses in the Drosophila Antennal Lobe are due to presynaptic and postsynaptic Local Neurons, modeled as differential Divisive Normalization Processors that extract semantic and syntactic odor information.

The paper investigates how the Drosophila early olfactory system separates odorant mixtures by analyzing spatio-temporal responses and formulating the problem as a blind source separation task.

The paper shows that the Divisive Normalization Processor (DNP) can faithfully represent input information through invertible operations in both auditory and visual stimuli processing.

The paper models the functional logic of the Drosophila Mushroom Body by analyzing connectivity and odorant representation in neural circuits.

The paper introduces a programmable model to analyze the functional logic of the Drosophila antennal lobe by characterizing its input-output behavior through glomeruli and feedback loops.

The paper analyzes synaptic connectivity in Drosophila lateral neuron clock cells to identify distinct connectomic types and their roles in circadian timekeeping.

The paper introduces a programmable ontology for modeling the functional logic of the Drosophila brain, integrating it with a computational platform and demonstrating its use in analyzing olfactory circuits.

FlyBrainLab integrates neuroanatomical, neurogenetic, and electrophysiological data to enable interactive exploration and modeling of Drosophila brain circuits.

The paper develops a molecular model of odorant transduction in Drosophila OSNs, quantifying combinatorial encoding complexity and highlighting gaps in current data.

The paper introduces the Fruit Fly Brain Observatory, an open-source platform for integrating and analyzing fruit fly brain data and models.

NeuroGFX provides a graphical interface for exploring fruit fly brain circuits by integrating computational modeling and biological data.

NeuroNLP provides a web-based portal for exploring fruit fly brain circuit data using natural language queries and 3D visualization.

The paper introduces the Fruit Fly Brain Observatory, an open platform for integrating and visualizing fruit fly brain data and models, with tools for querying and simulating neural circuits.