Independent component analysis of nondeterministic fMRI signal sources

  title={Independent component analysis of nondeterministic fMRI signal sources},
  author={Vesa J Kiviniemi and Juha-Heikki Kantola and Jukka Jauhiainen and Aapo Hyv{\"a}rinen and Osmo Tervonen},
Resting-state fMRI confounds and cleanup
Independent Component Analysis of fMRI Data
Techniques employed to analyze functional magnetic resonance imaging (fMRI) data typically use some form of univariate data analysis to determine regions of task-related activity. Changes in blood
Independent Component Analysis of Instantaneous Power-Based fMRI
It is concluded that ICA decomposition of ip-fMRI may be used to localize energy signal changes in the brain and may have a potential to be applied to detection of brain activity.
Advantages and Disadvantages of Resting State Functional Connectivity Magnetic Resonance Imaging for Clinical Applications
Investigation of brain fluctuations at resting condition and results demonstrate that spontaneous modulation of the BOLD does not produce randomly, which has been proven very valuable in the clinical area of fMRI applications.
Functional segmentation of the brain cortex using high model order group PICA
It is concluded that the high model order ICA of the group BOLD data enables functional segmentation of the brain cortex and enables new approaches to causality and connectivity analysis with more specific anatomical details.
Synchronous Multiscale Neuroimaging Environment for Critically Sampled Physiological Analysis of Brain Function: Hepta-Scan Concept
A multimodal concept, referred to as Hepta-scan, which incorporates synchronous MREG with scalp electroencephalography, near-infrared spectroscopy, noninvasive blood pressure, and anesthesia monitoring is described, which supports the idea that, in the absence of aliased cardiorespiratory signals, VLFFs in the BOLD signal are affected by vasomotor and electrophysiological sources.


Independent component analysis of fMRI data: Examining the assumptions
The results suggest the ICA model may more accurately represent the data in specific regions of the brain, and that both the activity‐dependent sources of blood flow and noise are non‐Gaussian.
Analysis of fMRI data by blind separation into independent spatial components
This work decomposed eight fMRI data sets from 4 normal subjects performing Stroop color‐naming, the Brown and Peterson word/number task, and control tasks into spatially independent components, and found the ICA algorithm was superior to principal component analysis (PCA) in determining the spatial and temporal extent of task‐related activation.
Mapping functionally related regions of brain with functional connectivity MR imaging.
This work tested the hypothesis that fcMRI maps, based on the synchrony of low-frequency blood flow fluctuations, identify brain regions that show activation on fMRI maps of sensorimotor, visual, language, and auditory tasks.
On the characteristics of functional magnetic resonance imaging of the brain.
In this review we discuss various recent topics that characterize functional magnetic resonance imaging (fMRI). These topics include a brief description of MRI image acquisition, how to cope with
Functional connectivity in the motor cortex of resting human brain using echo‐planar mri
It is concluded that correlation of low frequency fluctuations, which may arise from fluctuations in blood oxygenation or flow, is a manifestation of functional connectivity of the brain.
Frequencies contributing to functional connectivity in the cerebral cortex in "resting-state" data.
Functional connectivity in the auditory, visual, and sensorimotor cortices is characterized predominantly by frequencies slower than those in the cardiac and respiratory cycles, which are characterized by a high degree of temporal coherence.
Slow vasomotor fluctuation in fMRI of anesthetized child brain
It is hypothesized that thiopental alters the feedback in neurovascular coupling leading to an increase in the magnitude and a reduction in the frequency of these fluctuations in fMRI during rest caused by vasomotor fluctuations.
The nature of spatiotemporal changes in cerebral hemodynamics as manifested in functional magnetic resonance imaging
The nature of changes in rapidly acquired magnetic resonance images of the brain was studied by using a denoising method and spectral techniques optimally suited to short time series. It was found
Fractal analysis of spontaneous fluctuations in human cerebral hemoglobin content and its oxygenation level recorded by NIRS.
This study has applied the fractal model as implemented in a combination of the power spectral density (PSD) and the scaled windowed variance (SWV) methods in the analysis of human cerebrocortical hemoglobin signals in an attempt to assess their temporal pattern.