Sources and implications of whole-brain fMRI signals in humans

Classification of Whole Brain fMRI Activation

Functional magnetic resonance imaging (fMRI) is an imaging technology which is primarily used to perform brain activation studies by measuring neural activity in the brain. It is an interesting question whether patterns of activity in the brain as measured by fMRI can be used to predict the cognitive state of a subject. Researchers successfully employed a discriminative approach by training cla...

Classification of Whole Brain fMRI Activation Patterns

Functional magnetic resonance imaging (fMRI) is an imaging technology which is primarily used to perform brain activation studies by measuring neural activity in the brain. It is an interesting question whether patterns of activity in the brain as measured by fMRI can be used to predict the cognitive state of a subject. Researchers successfully employed a discriminative approach by training cla...

Sparse representation of whole-brain fMRI signals for identification of functional networks

There have been several recent studies that used sparse representation for fMRI signal analysis and activation detection based on the assumption that each voxel's fMRI signal is linearly composed of sparse components. Previous studies have employed sparse coding to model functional networks in various modalities and scales. These prior contributions inspired the exploration of whether/how spars...

Nonlinear Complexity Analysis of Brain fMRI Signals in Schizophrenia

We investigated the differences in brain fMRI signal complexity in patients with schizophrenia while performing the Cyberball social exclusion task, using measures of Sample entropy and Hurst exponent (H). 13 patients meeting diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM IV) criteria for schizophrenia and 16 healthy controls underwent fMRI scanning at 1.5 T. The fMRI d...

Correction: Nonlinear Complexity Analysis of Brain fMRI Signals in Schizophrenia