Multi-voxel pattern analysis of fMRI data predicts clinical symptom severity
نویسندگان
چکیده
منابع مشابه
Multi-voxel pattern analysis of fMRI data predicts clinical symptom severity
Multi-voxel pattern analysis (MVPA) has been applied successfully to a variety of fMRI research questions in healthy participants. The full potential of applying MVPA to functional data from patient groups has yet to be fully explored. Our goal in this study was to investigate whether MVPA might yield a sensitive predictor of patient symptoms. We also sought to demonstrate that this benefit can...
متن کاملMulti-Voxel Pattern Analysis of fMRI Data
The central goal of cognitive neuroscience is to understand how information is processed in the brain. To accomplish this goal, researchers studying human cognition are increasingly relying on multi-voxel pattern analysis (MVPA); this method involves analyzing spatially distributed (multi-voxel) patterns of functional MRI activity, with the goal of decoding the information that is represented a...
متن کاملBeyond mind-reading: multi-voxel pattern analysis of fMRI data.
A key challenge for cognitive neuroscience is determining how mental representations map onto patterns of neural activity. Recently, researchers have started to address this question by applying sophisticated pattern-classification algorithms to distributed (multi-voxel) patterns of functional MRI data, with the goal of decoding the information that is represented in the subject's brain at a pa...
متن کاملVoxel Selection of fMRI Data using Multi- Voxel Pattern Analysis to Predict Neural Response
fMRI system shows that all the information of the brain that is represented in the subject of the brain at a particular point in time. The MVPA approach has lead to several impressive facts of brain reading. fMRI data uses Multivoxel pattern analysis (MVPA) approach to relate the neural activities to cognition. A challenging factor is to build a generalizable classification model because the nu...
متن کاملUsing multi-voxel pattern analysis of fMRI data to interpret overlapping functional activations.
Norman et al. [1] recently reviewed the use of multi-voxel pattern analysis (MVPA) of fMRI data. They provided examples that showed that patterns of activation across a set of voxels can contain far more information about mental states than the more typically used univariate approach. Patterns of fMRI activation can be used to discriminate cognitive states (sometimes called ‘mind reading’), to ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: NeuroImage
سال: 2011
ISSN: 1053-8119
DOI: 10.1016/j.neuroimage.2011.04.016