Decoding visual category information from scalp EEG data with logistic regression and support vector machine classifiers
Abstract: The brain represents different categories of visual stimuli through distinct patterns of neural activity. Much of the evidence for this idea comes from functional magnetic resonance imaging (fMRI) in humans. However, fMRI is an indirect measure of neural activity that has low temporal resolution, limiting its ability to accurately capture the temporal dynamics of … Read more