All NWB conversions

Michale Fee

Massachusetts Institute of Technology

Project started May 2022

Developed NWB conversion tools for the Fee lab's neurophysiology datasets studying neural mechanisms of learning and behavior. The conversion pipeline supports complex data structures from electrophysiological recordings and behavioral measurements, with specialized interfaces for processing and analyzing neural activity patterns during behavioral tasks.

Data and methods
Zebra finchelectrophysiologybehavioral tracking
Conversion code
fee-lab-to-nwb
Published datasets
Funded under
SCGB NWB Adoption
Related work

James DiCarlo

Massachusetts Institute of Technology

Developed NWB conversion tools for the DiCarlo lab's neuroscience datasets. The conversion pipeline processes data from Macaca mulatta (rhesus macaques), including Utah array recordings acquired using the Intan data acquisition system, behavioral data encoded in the MWorks format, and visual stimuli presented as images or video. Additionally, the pipeline incorporates an optimized spike-threshold crossing algorithm and tools for calculating peristimulus time histograms (PSTH).

Mehrdad Jazayeri

Massachusetts Institute of Technology

Developed NWB conversion tools for the Jazayeri lab's primate neurophysiology datasets studying cognitive timing and mental navigation. The conversion pipeline handles complex neural recordings from multiple brain regions including dorsomedial frontal cortex and entorhinal cortex during sophisticated behavioral tasks.

Beth Buffalo

University of Washington

Developed NWB conversion tools for the Buffalo lab's multi-modal neurophysiology data, handling both raw and processed neural recordings from Neuralynx systems, sorted spikes, and behavioral measurements in non-human primates doing hippocampal tasks. The conversion pipeline includes a graphical interface for metadata editing and supports various data formats including NCS, MAT, and NEX files.

Bob Datta

Harvard University

Developed NWB conversion tools for the Datta lab's behavioral neuroscience datasets, featuring photometric recordings and optogenetic manipulations in mice. The conversion pipeline handles multi-modal data including fiber photometry signals, behavioral measurements, and closed-loop optogenetic stimulation data studying dopamine dynamics during spontaneous behavior.