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MRI datasets Healthy and Alzheimer's disease: Yes [36] Open Connectome Project Database of different circuitry frameworks and neuroimaging datasets, including volumetric datasets, atlases, and connectomics research Human, mouse, bat, zebrafish, insect, other Multilevel: brain regions, connections, neurons, gene expression patterns Images and 3D ...
The Neurophysiological Biomarker Toolbox (NBT) is an open source MATLAB toolbox for the computation and integration of neurophysiological biomarkers (e.g., biomarkers based on EEG or MEG recordings). [1] The NBT toolbox has so far been used in seven peer-reviewed research articles, and has a broad user base of more than 1000 users. [2]
Brainstorm is a collaborative, open-source application dedicated to the analysis of brain recordings including MEG, EEG, fNIRS, ECoG, depth electrodes and animal invasive neurophysiology. [30] The objective of Brainstorm is to share a comprehensive set of user-friendly tools with the scientific community using MEG/EEG as an experimental technique.
The datasets from various governmental-bodies are presented in List of open government data sites. The datasets are ported on open data portals. They are made available for searching, depositing and accessing through interfaces like Open API. The datasets are made available as various sorted types and subtypes.
EEG electrode positions in the 10-10 system using modified combinatorial nomenclature, along with the fiducials and associated lobes of the brain. When recording a more detailed EEG with more electrodes, extra electrodes are added using the 10% division , which fills in intermediate sites halfway between those of the existing 10–20 system.
EEGLAB is a MATLAB toolbox distributed under the free BSD license for processing data from electroencephalography (EEG), magnetoencephalography (MEG), and other electrophysiological signals. [ 1 ] [ 2 ] Along with all the basic processing tools, EEGLAB implements independent component analysis (ICA), time/frequency analysis, artifact rejection ...
The original GDF specification was introduced in 2005 as a new data format to overcome some of the limitations of the European Data Format for Biosignals (EDF). GDF was also designed to unify a number of file formats which had been designed for very specific applications (for example, in ECG research and EEG analysis). [2]
The dataset has rigorously considered 4 environment factors under different scenes, including illumination, occlusion, object pixel size and clutter, and defines the difficulty levels of each factor explicitly. Classes labelled, training/validation/testing set splits created by benchmark scripts. 1,106,424 RBG-D images images (.png and .pkl)
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