Search results for "Infomax"
showing 4 items of 4 documents
Testing different ICA algorithms and connectivity analyses on MS patients.
2015
Multiple sclerosis (MS) is a progressive neurological disorder that affects the central nervous system. Functional magnetic resonance imaging (fMRI) has been employed to track the course and disease progression in patients with MS. The two main aims of this study were to apply in a data-driven approach the independent component analysis (ICA) in the spatial domain to depict the active sources and to look at the effective connectivity between the identified spatial sources. Several ICA algorithms have been proposed for fMRI data analysis. In this study, we aimed to test two well characterized algorithms, namely, the fast ICA and the complex infomax algorithms, followed by two effective conne…
ERP qualification exploiting waveform, spectral and time-frequency infomax
2008
The present contribution briefly introduces an event related potential (ERP) detector. The specified detector includes three kinds of features of ERP. They are the ERP waveform feature, ERP spectral feature and ERP time-frequency feature respectively. According to these characteristics, two parameters are defined to reflect the timing feature of ERP. The mismatch negativity (MMN) is taken as the example to design an exact qualification detector. The experiment validates that the computer can automatically detect the raw trace to reflect the quality of the dataset, qualify the filtered trace to test whether the artifacts have been filtered out, and select the ERP-like component to reject art…
ICA of full complex-valued fMRI data using phase information of spatial maps.
2015
Background ICA of complex-valued fMRI data is challenging because of the ambiguous and noisy nature of the phase. A typical solution is to remove noisy regions from fMRI data prior to ICA. However, it may be more optimal to carry out ICA of full complex-valued fMRI data, since any filtering or voxel-based processing may disrupt information that can be useful to ICA. New method We enable ICA of the full complex-valued fMRI data by utilizing phase information of estimated spatial maps (SMs). The SM phases are first adjusted to properly represent spatial phase changes of all voxels based on estimated time courses (TCs), and then these are used to segment the voxels into BOLD-related and unwant…
Empirical Mode Decomposition on Mismatch Negativity
2008
Empirical mode decomposition (EMD) has been applied in the various disciplines to extract the desired signal. The basic principle is to decompose a time series into intrinsic mode functions (IFMs) and each IFM corresponds to an oscillation phenomenon. A statistical description of the oscillatory activities of the EEG has been well known. It is desired to extract single oscillatory process from the EEG by EMD. Mismatch negativity (MMN) can be automatically elicited by the deviant stimulus in an oddball paradigm, in which physically the deviant stimulus occurs among repetitive and homogeneous stimuli. MMN thus reflects the ability of the brain to detect changes in auditory stimuli. So, the MM…