Detecting cognitive states from the analysis of structural and functional images of the brain: two applications of Multi-Voxel Pattern Analysis on MRI and fMRI data
In recent years, the efficacy and accuracy of multivariate analysis techniques on neuroimaging data has been tested on different topics. These methods have shown the ability to decode mental states from the analysis of brain scans, for this reason it has been called “brain reading”. The predictions can be applied to general mental states, referring to stable conditions not related to a contingent task (e.g., a neurological diagnosis), or specific mental states, referring to task-related cognitive processes (e.g., the perception of a category of stimuli). According to several neuroscientists, brain reading approach can potentially be useful for applications in both clinical and forensic neuroscience in the future.
In the present dissertation, two applications of the brain reading approach are presented on two relevant topics for clinical and forensic neuroscience that have not been extensively investigated with these methods. In Section A, this approach is tested on decoding different levels of Cognitive Reserve from the pattern of grey matter volume, in two MRI studies. In Section B two fMRI studies investigate the possibility of decoding real autobiographical memories from brain activity.
The aim of this thesis is to contribute to the amount of studies showing the usefulness of multivariate techniques in decoding “mental states” starting from the analysis of structural and functional brain imaging data, as well as the potential uses in clinical and forensic settings
