Neurofeedback (NFB) allows subjects to learn self-regulation of neuronal brain activation based on information about the ongoing activation. The implementation of real-time functional magnetic resonance imaging (rt-fMRI) for NFB training now facilitates the investigation into underlying processes. Our study involved 16 control and 16 training right-handed subjects, the latter performing an extensive rt-fMRI NFB training using motor imagery. A previous analysis focused on the targeted primary somato-motor cortex (SMC). The present study extends the analysis to the supplementary motor area (SMA), the next higher brain area within the hierarchy of the motor system. We also examined transfer-related functional connectivity using a whole-volume psycho-physiological interaction (PPI) analysis to reveal brain areas associated with learning. The ROI analysis of the pre- and post-training fMRI data for motor imagery without NFB (transfer) resulted in a significant training-specific increase in the SMA. It could also be shown that the contralateral SMA exhibited a larger increase than the ipsilateral SMA in the training and the transfer runs, and that the right-hand training elicited a larger increase in the transfer runs than the left-hand training. The PPI analysis revealed a training-specific increase in transfer-related functional connectivity between the left SMA and frontal areas as well as the anterior midcingulate cortex (aMCC) for right- and left-hand trainings. Moreover, the transfer success was related with training-specific increase in functional connectivity between the left SMA and the target area SMC. Our study demonstrates that NFB training increases functional connectivity with non-targeted brain areas. These are associated with the training strategy (i.e., SMA) as well as with learning the NFB skill (i.e., aMCC and frontal areas). This detailed description of both the system to be trained and the areas involved in learning can provide valuable information for further optimization of NFB trainings.
To elucidate basic mechanisms underlying neurofeedback we investigated neural mechanisms of training of slow cortical potentials by considering EEG- and fMRI. Additionally, we analyzed the feasibility of a double-blind, placebo-controlled design in NF research based on regulation performance during treatment sessions and self-assessment of the participants. Twenty healthy adults participated in 16 sessions of SCP training: 9 participants received regular SCP training, 11 participants received sham feedback. At three time points (pre, intermediate, post) fMRI and EEG/ERP-measurements were conducted during a continuous performance test (CPT). Performance-data during the sessions (regulation performance) in the treatment group and the placebo group were analyzed. Analysis of EEG-activity revealed in the SCP group a strong enhancement of the CNV (electrode Cz) at the intermediate assessment, followed by a decrease back to baseline at the post-treatment assessment. In contrast, in the placebo group a continuous but smaller increase of the CNV could be obtained from pre to post assessment. The increase of the CNV in the SCP group at intermediate testing was superior to the enhancement in the placebo group. The changes of the CNV were accompanied by a continuous improvement in the test performance of the CPT from pre to intermediate to post assessment comparable in both groups. The change of the CNV in the SCP group is interpreted as an indicator of neural plasticity and efficiency while an increase of the CNV in the placebo group might reflect learning and improved timing due to the frequent task repetition. In the fMRI analysis evidence was obtained for neuronal plasticity. After regular SCP neurofeedback activation in the posterior parietal cortex decreased from the pre- to the intermediate measurement and increased again in the post measurement, inversely following the U-shaped increase and decrease of the tCNV EEG amplitude in the SCP-trained group. Furthermore, we
To introduce a standardized and automatized method for functional MRI (fMRI) examinations of the cortical sensory somatotopy in large samples for investigations of the fingertip somatotopy in the primary somatosensory cortex.At 3 Tesla, T2* (spin-spin relaxation time) weighted images (gradient-echo echo planar imaging, voxel size 1.5 × 1.5 × 2 mm3) were acquired during stimulation of the finger tips for thumb, index and middle finger on both hands, in a group of 18 healthy participants. In addition, structural T1 weighted (magnetization prepared rapid gradient echo, isotropic voxel size 1 mm) and MR-angiography (time of flight, voxel size 0.26 × 0.26 × 0.5 mm3) images were recorded. Boundary based register served to combine movement correction and registration in FreeSurfer Functional analysis stream (FS-Fast), resulting in fine scale corrections, as revealed with FSL Possum (FSL FMRIB Software Library Physics-Oriented Simulated Scanner for Understanding MRI) simulations. Automated data analysis was achieved by inclusion of cytoarchitectonic probability maps for calculation of functional activation in Brodmann area 3b. Draining vessel artifacts were identified using the peak value approach and the MR-angiography. Distances were computed as the shortest connection within the gray matter.The fMRI somatotopic maps agreed with the expected fingertip somatotopy in 63% of the investigated subjects, an improvement of 34% compared with FS-Fast. Artifacts have been removed completely. Adjacent fingertips showed average distances of 8 ± 4.3 mm, and between thumb and middle finger 13.4 ± 4.8 mm was found. Distances for both hands were similar as expected from the characteristics of the fingertip spatial tactile resolution.The introduced evaluation procedure allowed automated analysis of the fingertip representation in excellent agreement with preceding results.
In 1860 and 1862, the German physiologist Wagner published two studies, in which he compared the cortical surfaces of brain specimens. This provided the first account of a rare anatomical variation – bridges across the central sulci in both hemispheres connecting the forward and backward facing central convolutions in one of the brains. The serendipitous rediscovery of the preserved historic brain specimen in the collections at Göttingen University, being mistaken as the brain of the mathematician C.F. Gauss, allowed us to further investigate the morphology of the bridges Wagner had described with magnetic resonance imaging (MRI). On the historic lithograph, current photographs and MRI surface reconstructions of the brain, a connection across the central sulcus can only be seen in the left hemisphere. In the right hemisphere, contrary to the description of Wagner, a connecting structure is only present across the postcentral sulcus. MRI reveals that the left-hemispheric bridge extends into the depth of the sulcus, forming a transverse connection between the two opposing gyri. This rare anatomical variation, generally not associated with neurological symptoms, would nowadays be categorized as a divided central sulcus. The left-hemispheric connection seen across the postcentral sulcus, represents the very common case of a segmented postcentral sulcus. MRI further disclosed a connection across the right-hemispheric central sulcus, which terminates just below the surface of the brain and is therefore not depicted on the historical lithography. This explains the apparent inconsistency between the bilateral description of bridges across the central sulci and the unilateral appearance on the brain surface. The results are discussed based on the detailed knowledge of anatomists of the late 19th century, who already recognized the divided central sulcus as an extreme variation of a deep convolution within the central sulcus.
Abstract Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large interindividual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta-analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pre-training functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pre-training activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain-based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning.
The tactile digit representations in the primary somatosensory cortex have so far been mapped for either the left or the right hand. This study localized all ten digit representations in right-handed subjects and compared them within and across the left and right hands to assess potential differences in the functional organization of the digit map between hands and in the structural organization between hemispheres. Functional magnetic resonance imaging of tactile stimulation of each fingertip in BA 3b confirmed the expected lateral-anterior-inferior to medial-posterior-superior succession from thumb to little-finger representation, located in the postcentral gyrus opposite to the motor hand knob. While the more functionally related measures, such as the extent and strength of activation as well as the Euclidean distance between neighboring digit representations showed significant differences between the digits, no side difference was detected: the layout of the functional digit-representation map did not consistently differ between the left, non-dominant and the right, dominant hand. Comparing the absolute spatial coordinates also revealed a significant difference for the digits, but not between the left and right hand digits. Estimating the individual subject's digit coordinates of one hand by within-subject mirroring of the other-hand digit coordinates across hemispheres yielded a larger estimation error distance than using averaged across-subjects coordinates from within the same hemisphere. However, both methods should only be used with care for single-subject clinical evaluation, as an average estimation error of around 9 mm was observed, being slightly higher than the average distance between neighboring digits.
Purpose: EMG-triggered electrostimulation (EMG-ES) may improve the motor performance of affected limbs of hemiparetic stroke patients even in the chronic stage. This study was designed to characterize cortical activation changes following intensified
Maps of the body surface in somatosensory cortex have been shown to be highly plastic, altering their configuration in response to changes in use of body parts. The current study investigated alterations in the functional organization of the human somatosensory cortex resulting from massed practice. Over a period of 4 weeks, subjects were given synchronous tactile stimulation of thumb (D1) and little finger (D5) for 1 hr/d. They had to identify the orientation of the stimuli. Neuroelectric source localization based on high-resolution EEG revealed that, when subjects received passive tactile stimulation of D1 or D5, the representations of the fingers in primary somatosensory cortex were closer together after training than before. There was also an apparently correlative tendency to anomalously mislocalize near-threshold tactile stimuli equally to the distant finger costimulated during training rather than preferentially to the finger nearest to the finger stimulated in a post-training test. However, when the stimulus discrimination had to be made, neuroelectric source imaging revealed that the digital representations of D1 and D5 were further apart after training than before. Thus, the same series of prolonged repetitive stimulations produced two different opposite effects on the spatial relationship of the cortical representations of the digits, suggesting that differential activation in the same region of somatosensory cortex is specific to different tasks.
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