Table 3 Overview of the analysis scenarios presented as use cases for NEAO.

From: Improving data sharing and knowledge transfer via the Neuroelectrophysiology Analysis Ontology (NEAO)

Analysis

Description

Output folder

File name

1.1

PSD computation using the Welch method in the Elephant toolbox

/ reach2grasp / psd_by_trial / [session]

[trial ID].png

1.2

PSD computation using the multitaper method in the Elephant toolbox

/ reach2grasp / psd_by_trial_2 / [session]

[trial ID].png

1.3

PSD computation using the Welch method in the SciPy toolbox

/ reach2grasp / psd_by_trial_3 / [session]

[trial ID].png

2.1

ISI histograms of spike train surrogates obtained from experimental data using the uniform spike dithering method

/ reach2grasp / surrogate_isih_1 / [session]

[unit ID].png

2.2

ISI histograms of spike train surrogates obtained from experimental data using the trial shifting method

/ reach2grasp / surrogate_isih_2 / [session]

[unit ID].png

3

ISI histograms of spike trains generated by stationary Poisson or gamma processes

/ isi_histograms

[spike train index].png

  1. Three main analyses were implemented: (1) computation of PSDs of LFPs, (2) ISI histograms (ISIHs) of surrogate spike trains obtained from the data available in one dataset of the Reach2Grasp experiment (i140703-001_no_raw.nix), and (3) computation of ISIHs of artificially generated spike trains. Outputs of Analyses 1 and 2 that used the Reach2Grasp experimental dataset were grouped inside the folder reach2grasp, while the outputs of Analysis 3 were stored in the separate folder isi_histograms. For Analyses 1 and 2, variants of the analysis were implemented (three for Analysis 1 and two for Analysis 2), and each variant stored the results in distinct subfolders (psd_by_trial* for Analysis 1 and surrogate_isih_* for Analysis 2). In the folder structure, [session] corresponds to the session identifier in the Reach2Grasp experiment (i140703-001; subject N, recordings from July 3rd, 2014, first recording session of the day). In the file names of outputs in scenarios 1 and 2, [trial ID] is the trial identification number (obtained from the annotations of the behavioral events stored in the data file), and [unit ID] is the identifier of a single putative neuron assigned to the data object containing the single-unit neuronal spiking activity after spike sorting. In the file names of outputs in scenario 3, [spike train index] is the index of the spike train in the list where they were stored after their generation in the script. All queries presented as use cases are based on the full set of results obtained from Analyses 1–3.