Data & Code

We are committed to conducting and promoting Open Science. We are working toward openly sharing well-organized data in a standard format, as well as well-documented code in Python. Data sharing repositories supported by the NIH BRAIN Initiative include DANDI (NHP) and DABI (human). We also use DataDryad (human). Neurodata Without Borders (NWB) is a standard data format used. Code sharing repositories include GitHub and Zenodo.

In addition, data and code related to our line of research is also hosted on our alumni web sites, some of which was done in collaboration. These sites include, in addition to our own (see below), the following alumni group websites: Batista Lab, Chandrasekaran Lab, Chestek Lab, Churchland Lab, Cunningham Lab, Gilja Lab, Kao Lab, Kaufman Lab, O'Shea GitHub, Sussillo GitHub, Yu Lab

First Neuropixels recordings from humans

• Data on Dryad, Code on Github and Code on Zenodo associated with Paulk et al. (2022) Nature Neuroscience. pdf url doi

NHP instructed-delay curl-force field motor learning reaching task, using Utah and Neuropixels arrays

• Data on Nature's site, Code on GitHub for repertoire change analysis and Code for TDR uniform-shift analyses associated with Sun*, O'Shea*, et al. (2022) Nature.

NHP instructed-delay center-out and maze reaching task, using Utah and Neuropixels arrays

• Tools
  • Informal 24 minute video (and slides) of Catalyst Neuro handoff to NPSL of data, data format (NWB), data repository (DANDI) and code / jupyter notebooks (GitHub) conversion work done as part of a Simons Foundation effort
  • Tutorials and conversion code
  • NWB Conversion Tools
  • NWB Jupyter Widgets
• Reaching to linearly and concentrically arranged targets, with M1 and PMd Utah array recordings
  • Data associated with Even-Chen N*, Sheffer B*, et al. (2019) PLoS Comp Bio pdf, and some Data.zip from the time of publication
• Reaching to targets in our maze task, with M1 and PMd Utah array recordings 
  • Data associated with Churchland MM*, Cunningham**, Kaufman, et al. (2012) Nature, and also used in Pei F*, Ye J*, et al. (2021) NeurIPS, Neural Latents Benchmark 2021
• Reaching to concentrically arranged targets, with M1 and PMd (mouse version) Neuropixel recordings
  • Forthcoming

WaveMAP analysis of extracellular waveforms

• Data on Dryad associated with Lee et al. (2021) eLife.

2 photon GCaMP imaging in NHP motor cortex during reaching and BMI control

• Data on Dryad, Code on Zenodo and Code on GitHub associated with Trautmann EM*, O'Shea DJ*, Sun X*, et al. (2021) Nature Communications. Also Supp data 1 xlxs and Supp data 1 url

Attempted handwriting BCI task, using Utah electrode arrays 

• Data and Code associated with Willett et al. (2021) Nature. pdf

LFADS: Latent Factor Analysis via Dynamical Systems

• Data and code associated with Pandarinath et al. (2018) Nature Methods. pdf
  • LFADS Run Manager .zip code on GitHub
  • LFADS .zip code on GitHub
  • AutoLFADS Tutorial which runs on Google Cloud Platform, from Prof. Chethan Pandarinath's group at Emory and Georgia Tech
• Sussillo D (3/22/18) LFADS seminar talk, Simons Institute for the Theory of Computing meeting, UC Berkeley

ERAASR: Removing electrical stimulation artifacts

• ERAASR code, with limited data and tutorial, associated with O’Shea & Shenoy (2018) Journal of Neural Engineering​

jPCA: Quantifying rotatory components of neural population activity

• M1/PMd Utah array recordings
• jPCA code, with limited data and tutorial, associated with Churchland MM*, Cunningham JP*, Kaufman MT, et al. (2012) Nature

MKsort spike sorter

• Prof. Matt Kaufman's MATLAB spike sorter written during graduate years at Stanford
• Code also distributed by Ripple LLC as open source software

Neural Variance (NV) Toolbox

• Code associated with Churchland MM*, Yu BM*, et al. (2010) Nature Neuroscience

GPFA Toolbox for single-trial neural population trajectory estimation

• Code associated with Yu BM, et al. (2009) J Neurophysiol