connectome

A curated list of fruit fly connectome projects: MaleCNS, FlyWire, brain simulations, embodied models, games, and research tools.

Simulate the C. Elegans worm brain in your browser and interact with the worm as it moves around

A fruit fly connectome as a drone pilot. Camera -> fly eyes -> spiking brain -> descending neurons -> drone. Live 3D demo in your browser.

Experimental Drosophila-inspired camera-to-robot bridge. Working mock neural backend, optical flow, IMU feedback and UDP motor control. MaleCNS integration planned.

A 302 neuron network on the real C. elegans wiring diagram, with a steering layer for local language models.

Graph theory analysis of brain MRI data

Python library for analysis of neuroanatomical data.

micapipe from the Multimodal imaging and connectome analysis lab (http://mica-mni.github.io) at the Montreal Neurological Institute. Read The Docs documentation below

STAGIN: Spatio-Temporal Attention Graph Isomorphism Network

A dynamic connectome mapping module in python.

A performant, powerful query framework to search for network motifs

Real fly anatomy and model-output starter. Custom license requires web UI and repository attribution.

Connectome Mapper 3 is a BIDS App that implements full anatomical, diffusion, resting/state functional MRI, and recently EEG processing pipelines, from raw T1 / DWI / BOLD , and preprocessed EEG data to multi-resolution brain parcellation with corresponding connection matrices.

Embodied Drosophila: 138,639-neuron whole-brain connectome simulation (FlyWire v783) in a biomechanical body (NeuroMechFly v2 / MuJoCo). Vision, olfaction, gustation, flight, and emergent behaviors — all from the real connectome.

Compose chunk operators to create a pipeline for local or distributed petabyte-scale computation

A unified framework for skeletonization, morphological analysis, and connectivity analysis.

Emergent behaviour and neural dynamics in artificial agents tracking odour plumes

A prediction-based extension of network-based statistics.

Please use the new version of LiFE: www.github.com/brain-life/encode

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