A NWB-based dataset and processing pipeline of human single-neuron activity during a declarative memory task.

Area of Science:

• Systems Neuroscience
• Neurophysiology
• Cognitive Neuroscience

Background:

• Data sharing in systems neuroscience is hindered by diverse data formats.
• Neurodata Without Borders: Neurophysiology 2.0 (NWB:N) offers a standardized solution for cellular data, metadata, and behavioral information.
• Standardized formats are crucial for data interoperability and reuse.

Purpose of the Study:

• To present an NWB:N-formatted dataset of human single-neuron recordings.
• To provide analysis code for importing/exporting data to/from NWB:N.
• To facilitate the adoption of NWB:N for human neurophysiology research.

Main Methods:

• Recorded single neurons from the medial temporal lobes of 59 human subjects during a recognition memory task.
• Formatted electrophysiological recordings, stimulus information, and behavioral data into the NWB:N standard.
• Developed analysis pipelines for data import/export in MATLAB and Python.

Main Results:

• A dataset of 1863 single neurons from human subjects is now available in NWB:N format.
• Code for analyzing and interoperating NWB:N data (stimuli, behavior, electrophysiology) is provided for MATLAB and Python.
• The NWB:N compliant data ensures cross-platform and cross-language compatibility.

Conclusions:

• This release serves as a case study for utilizing NWB:N in human single-neuron recordings.
• The provided data and code promote re-use for both educational and research purposes.
• Facilitates research into the neural mechanisms of human memory through accessible, standardized data.