Tools, algorithms, and frameworks for managing and analyzing neural data (derived from original notes from the 2018 BRAIN Initiative Investigators Meeting by Liam Paninski)
- https://github.com/flatironinstitute/CaImAn
- https://github.com/zhoupc/CNMF_E
- https://github.com/cortex-lab/Suite2P
- https://github.com/jewellsean/FastLZeroSpikeInference
- https://github.com/losonczylab/sima
- https://www.biorxiv.org/content/early/2018/05/30/334706 (compression + denoising)
- https://github.com/bahanonu/calciumImagingAnalysis - Biafra Ahanonu (MIT)
- https://github.com/cortex-lab/KiloSort
- https://github.com/mouseland/kilosort2
- http://www.jrclust.org/
- https://github.com/flatironinstitute/ironclust
- https://github.com/paninski-lab/yass
- https://github.com/flatironinstitute/mountainsort
- https://github.com/pillowlab/BinaryPursuitSpikeSorting
- https://spyking-circus.readthedocs.io/en/latest/
- http://homepages.inf.ed.ac.uk/mhennig/herdingspikes/
- https://github.com/tridesclous/tridesclous
- http://neuralensemble.org/neo/ - Intracellular recording
- https://github.com/wjyangGithub/Holographic-Photostimulation-System (matlab tools for SLM targeting and hologram generation)
- https://bonsai-rx.org/
- http://www.openmaze.org/
- https://pni.princeton.edu/pni-software-tools/virmen
- https://github.com/dendritic/signals
- https://github.com/neurodata/ndreg - current reference registration for cleared brain data
- http://stnava.github.io/ANTs/ - reference for much human MRI
- https://github.com/khaledkhairy/EM_aligner
- https://abria.github.io/TeraStitcher/ - current reference implementation for linear stitching
- https://github.com/SainsburyWellcomeCentre/amap-python - automated mouse whole-brain registration
- https://github.com/google/neuroglancer WebGL-based viewer for volumetric data
- https://github.com/seung-lab/cloud-volume (for working with "precomputed" format of Neuroglancer)
- https://github.com/seung-lab/Alembic (aligning images of serial sections)
- https://github.com/saalfeldlab/render - current reference implementation for dynamic rendering of aligned data
- https://github.com/AllenInstitute/allensdk.eye_tracking
- https://github.com/kristinbranson/APT
- https://github.com/mkrumin/EyeTracking
- https://github.com/carsen-stringer/FaceMap
- https://github.com/kristinbranson/APT
- http://ilastik.org/
- https://github.com/AlexEMG/DeepLabCut
- https://github.com/carsen-stringer/FaceMap
- https://www.biorxiv.org/content/early/2018/05/30/331181
Spike train data analysis methods - encoding models, decoders, dimensionality reduction, etc
- http://xarray.pydata.org/en/stable/
- RF estimation (ASD prior): https://github.com/pillowlab/fastASD
- GLM fitting for trial-based data: https://github.com/pillowlab/neuroGLM
- Entropy Estimation: https://github.com/pillowlab/CDMentropy/
- Hypothesis testing: https://github.com/neurodata/mgc
- Linear dimensionality reduction: https://github.com/neurodata/LOL
- Classification and regression: https://github.com/neurodata/R-RerF
- http://catmaid.readthedocs.io/en/stable/
- https://github.com/google/neuroglancer
- http://www.geppetto.org/
- https://imagej.net/BigDataViewer
- http://www.alleninstitute.org/what-we-do/brain-science/research/products-tools/vaa3d/
- https://github.com/BrancoLab/BrainRender - brainrender 3d neuroanatomical renderings in python
Tracking provenance of data / analysis outputs. Automatic repopulation of databases as analysis algorithms are updated. Store both data and model simulation output
- https://mybinder.org/
- http://gigantum.io/
- https://colab.research.google.com/notebooks/welcome.ipynb
- https://www.kaggle.com/kernels
- https://crcns.org/
- https://neurodata.io/
- https://www.nitrc.org/
- http://datalad.org/
- https://portal.brain-map.org/
- Neural data science: accelerating the experiment-analysis-theory cycle in large-scale neuroscience; Liam Paninski, John Cunningham https://www.biorxiv.org/content/early/2017/10/02/196949