A NWB-based Dataset and Processing Pipeline of Human Single-Neuron Activity During a Declarative Memory Task

Contributors:
  1. Dehua Liang
  2. Andrea G.P. Schjetnan
  3. April Carlson
  4. Mailys Faraut
  5. Jeffrey M. Chung
  6. Chrystal M. Reed
  7. Suneil Kalia
  8. Adam N. Mamelak

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Description: A challenge for data sharing in systems neuroscience is the multitude of different data formats used. Neurodata Without Borders: Neurophysiology 2.0 (NWB:N) has emerged as a standardized data format for the storage of cellular-level data together with meta-data, stimulus information, and behavior. A key next step to facilitate NWB:N adoption is to provide easy to use processing pipelines to import/export data from/to NWB:N. Here, we present a NWB-formatted dataset of 1863 single neurons recorded from the medial temporal lobes of 59 human subjects undergoing intracranial monitoring while they performed a recognition memory task. We provide code to analyze and export/import stimuli, behavior, and electrophysiological recordings to/from NWB in both MATLAB and Python. The data files are NWB:N compliant, which affords interoperability between programming languages and operating systems. This combined data and code release is a case study for how to utilize NWB:N for human single-neuron recordings and enables easy re-use of this hard-to-obtain data for both teaching and research on the mechanisms of human memory.

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Note: The code provided in this repository is a snapshot of the code release. The updated, and version controlled code will be found on GitHub. Please see the code and README on there for the most up-to-date code. A NWB-based Dataset and Processing Pipeline of Human Single-Neuron Activity During a Declarative Memory Task Introduction This repository contains tools/methods to export human single...

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