Predicting Subject Traits From Brain Spectral Signatures: An Application to Brain Ageing.

ABSTRACT: The prediction of subject traits using brain data is an important goal in neuroscience, with relevant applications in clinical research, as well as in the study of differential psychology and cognition. While previous prediction work has predominantly been done on neuroimaging data, our focus is on electroencephalography (EEG), a relatively inexpensive, widely available and non-invasive data modality. However, EEG data is complex and needs some form of feature extraction for subsequent prediction. This process is sometimes done manually, risking biases and suboptimal decisions. Here we investigate the use of data-driven Kernel methods for prediction from single channels using the EEG spectrogram, which reflects macro-scale neural oscillations in the brain. Specifically, we introduce the id

SUBMITTER: Jarne C 

PROVIDER: S-EPMC11660765 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature