Choice-dependent delta-band neural trajectory during semantic category decision making in the human brain
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The dataset and code provided correspond to Manuscript Number: ISCIENCE-D-23-09408R1, titled "Choice-dependent delta-band neural trajectory during semantic category decision making in the human brain."This dataset comprises delta and alpha filtered data from a total of 19 participants. Each .mat file contains 800 cells, representing the number of trials. Each cell contains a matrix of size 128 x 1750. Here, 128 denotes the number of EEG channels, and 1750 represents the number of time points. Time points are sampled from -1 s to 2.5 s relative to the onset of the first stimulus, with a 2ms interval.The participants' behavioral data are stored in separate .mat files for each run (or block). Upon loading these files, a struct named "data" is loaded, containing six variables, each representing a 1 x 200 vector:Cat1: Represents the category of the first stimulus. It takes a value of 1 for animate words and 2 for inanimate words.Cat2: Denotes the category of the second stimulus. It is assigned 1 for animate words and 2 for inanimate words.Same: Indicates the correct response for each trial. A value of 1 signifies a match between the categories of Stimulus 1 and Stimulus 2, while 2 indicates a non-match.Resp: Records the participant's decision for each trial. A value of 1 denotes a match between the categories of Stimulus 1 and Stimulus 2, whereas 2 represents a non-match.RT: Represents the participant's response time in seconds for each trial.Corr: Indicates the correctness of the participant's response. A value of 1 signifies a correct response, while 0 indicates an incorrect response.
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Cited on 01 July 2024
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Publication Details
Subfield
Artificial Intelligence
Field
Computer Science
Domain
Physical Sciences
Confidence Score
40%
Source
Scholar Data Model