bioRxivNeurosciencePreprint
NeuroGFX: a graphical functional explorer for fruit fly brain circuits
Chung-Heng YehiD, Yiyin ZhouiD, Nikul H. Ukani, Aurel A. LazariD
Abstract
Recently, multiple focused efforts have resulted in substantial increase in the availability of connectome data in the fruit fly brain. Elucidating neural circuit function from such structural data calls for a scalable computational modeling methodology. We propose such a methodology that includes i) a brain emulation engine, with an architecture that can tackle the complexity of whole brain modeling, ii) a database that supports tight integration of biological and modeling data along with support for domain specific queries and circuit transformations, and iii) a graphical interface that allows for total flexibility in configuring neural circuits and visualizing run-time results, both anchored on model abstractions closely reflecting biological structure. Towards the realization of such a methodology, we have developed NeuroGFX and integrated it into the architecture of the Fruit Fly Brain Observatory (http://fruitflybrain.org). The computational infrastructure in NeuroGFX is provided by Neurokernel, an open source platform for the emulation of the fruit fly brain, and NeuroArch, a database for querying and executing fruit fly brain circuits. The integration of the two enables the algorithmic construction/manipulation/revision of executable circuits on multiple levels of abstraction of the same model organism. The power of this computational infrastructure can be leveraged through an intuitive graphical interface that allows visualizing execution results in the context of biological structure. This provides an environment where computational researchers can present configurable, executable neural circuits, and experimental scientists can easily explore circuit structure and function ultimately leading to biological validation. With these capabilities, NeuroGFX enables the exploration of function from circuit structure at whole brain, neuropil, and local circuit level of abstraction. By allowing for independently developed models to be integrated at the architectural level, NeuroGFX provides an open plug and play, collaborative environment for whole brain computational modeling of the fruit fly.
- organism: Drosophila
- research focus: software / tool
- research focus: database / resource
- research focus: benchmarking
- approach: experimental assay
- Citations
- 1
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- The Fruit Fly Brain Observatory: from structure to function
Nikul H. Ukani, Chung-Heng Yeh, … Aurel A. Lazar·bioRxiv·Dec 14, 2016
- The Fruit Fly Brain Observatory: From Structure to Function
Nikul H. Ukani, Chung-Heng Yeh, … Aurel A. Lazar·bioRxiv·Mar 18, 2019
- FlyBrainLab: Accelerating the Discovery of the Functional Logic of the Fruit Fly Brain in the Connectomic/Synaptomic Era
Aurel A. Lazar, Tingkai Liu, … Yiyin Zhou·eLifePeer-reviewed·Feb 22, 2021
- NeuroNLP: a natural language portal for aggregated fruit fly brain data
Nikul H. Ukani, Adam Tomkins, … Aurel A. Lazar·bioRxiv·Dec 14, 2016
- The Connectome Interpreter Toolkit
Yijie Yin, Judith Hoeller, … Albert Cardona·bioRxiv·Sep 29, 2025
- Generating an Executable Model of the Drosophila Central Complex
Lev E. Givon, Aurel A. Lazar·bioRxiv·May 23, 2016