NeuroImage
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The objective of the present study was to assess the spatiotemporal scenario of brain activity associated with sensory stimulation of the abductor pollicis brevis muscle. Spatiotemporal dipole models, using realistic individual boundary element head models, were built from somatosensory evoked potentials (SEPs; 64 Ch. EEG) to nonpainful and painful intramuscular electrostimulation (IMES) as well as to cutaneous electrostimulation delivered to the distal phalanx of the thumb. ⋯ This source was unmasked by the lower stimulus intensity; (4) a source for IMES was located in the contralateral caudal CMA rather than being located in the cingulate gyrus. Cerebral sensory processing of input from the muscle involved several sensory and motor areas and likely occurs in two parallel streams subserving higher order somatosensory processing as well as sensory-motor integration. The two streams might on one hand involve sensory discrimination via SI and SII and on the other hand integration of sensory feedback for further motor processing via MI, lateral PM area, and caudal CMA.
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Functional magnetic resonance imaging (fMRI) was used to investigate the effects of inspired hypoxic, hyperoxic, and hypercapnic gases on baseline and stimulus-evoked changes in blood oxygenation level-dependent (BOLD) signals, cerebral blood flow (CBF), and the cerebral metabolic rate of oxygen (CMRO2) in spontaneously breathing rats under isoflurane anesthesia. Each animal was subjected to a baseline period of six inspired gas conditions (9% O2, 12% O2, 21% O2, 100% O2, 5% CO2, and 10% CO2) followed by a superimposed period of forepaw stimulation. Significant stimulus-evoked fMRI responses were found in the primary somatosensory cortices. ⋯ However, under 9% O2 and 10% CO2, stimulus-evoked CBF and BOLD were substantially reduced and the CMRO2 formalism appeared invalid, likely due to attenuated neurovascular coupling and/or a failure of the model under extreme physiological perturbations. These findings demonstrate that absolute fMRI measurements help distinguish neural from non-neural contributions to the fMRI signals and may lend a more accurate measure of brain activity during states of altered basal physiology. Moreover, since numerous pharmacologic agents, pathophysiological states, and psychiatric conditions alter baseline physiology independent of neural activity, these results have implications for neuroimaging studies using relative fMRI changes to map brain activity.
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Independent component analysis (ICA) is a data-driven approach utilizing high-order statistical moments to find maximally independent sources that has found fruitful application in functional magnetic resonance imaging (fMRI). Being a blind source separation technique, ICA does not require any explicit constraints upon the fMRI time courses. However, for some fMRI data analysis applications, such as for the analysis of an event-related paradigm, it would be useful to flexibly incorporate paradigm information into the ICA analysis. ⋯ Compared with a traditional GLM approach, the sbICA approach provides a flexible way to analyze fMRI data that reduces the assumptions placed upon the hemodynamic response of the brain. The advantages and limitations of our technique are discussed in detail in the manuscript to provide guidelines to the reader for developing useful applications. The use of prior time course information in a spatial ICA analysis, which combines elements of both a regression approach and a blind ICA approach, may prove to be a useful tool for fMRI analysis.