One second of memory maintenance was evaluated to determine EEG metrics ability to track memory load and its variations connected with the lateral presentation of objects in the visual hemi-field. An initial approach focused on features gathered from the N2pc time series to detect the memory load using ensemble learners. Conversely, the secondary approach employed a regularised support vector classifier to predict the area of N2pc event-related components, identifying 6 levels of memory load and stimulus location.
EEG-Based Methods to Characterize Memorised Visual Space
Nascimben M.Primo
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2020-01-01
Abstract
One second of memory maintenance was evaluated to determine EEG metrics ability to track memory load and its variations connected with the lateral presentation of objects in the visual hemi-field. An initial approach focused on features gathered from the N2pc time series to detect the memory load using ensemble learners. Conversely, the secondary approach employed a regularised support vector classifier to predict the area of N2pc event-related components, identifying 6 levels of memory load and stimulus location.File in questo prodotto:
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