Deep-Learning-Based Multivariate Pattern Analysis (dMVPA): A Tutorial and a Toolbox.

ABSTRACT: In recent years, multivariate pattern analysis (MVPA) has been hugely beneficial for cognitive neuroscience by making new experiment designs possible and by increasing the inferential power of functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and other neuroimaging methodologies. In a similar time frame, "deep learning" (a term for the use of artificial neural networks with convolutional, recurrent, or similarly sophisticated architectures) has produced a parallel revolution in the field of machine learning and has been employed across a wide variety of applications. Traditional MVPA also uses a form of machine learning, but most commonly with much simpler techniques based on linear calculations; a number of studies have applied deep learning techniques to neuroim

SUBMITTER: Kuntzelman KM 

PROVIDER: S-EPMC7960649 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature