1,721,051 research outputs found
TMS-induced virtual lesion of the Frontal Eye Field (FEF) interferes with reflexive shifts of attention triggered by averted gaze
No full textImproved realistic Laplacian estimate of highly-sampled EEG potentials by regularization techniques
No full textIn this study we investigated the effects of λ correction, generalized cross-validation (GCV), and Tikhonov regularization techniques on the realistic Laplacian (RL) estimate of highly-sampled (128 channels) simulated and actual EEG potential distributions. The simulated EEG potential distributions were mathematically generated over a 3-shell spherical head model (analytic potential distributions). Noise was added to the analytic potential distributions to mimic EEG noise. The magnitude of the noise was 20, 40 and 80% that of the analytic potential distributions. Performance of the regularization techniques was evaluated by computing the root mean square error (RMSE) between regularized RL estimates and analytic surface Laplacian solutions. The actual EEG data were human movement-related and short-latency somatosensory-evoked potentials. The RL of these potentials was estimated over a realistically-shaped, magnetic resonance-constructed model of the subject's scalp surface. The RL estimate of the simulated potential distributions was improved with all the regularization techniques. However, the λ correction and Tikhonov regularization techniques provided more precise Laplacian solutions than the GCV computation (P < 0.05); they also improved better than the GCV computation the spatial detail of the movement- related and short-latency somatosensory-evoked potential distributions. For both simulated and actual EEG potential distributions the Tikhonov and λ correction techniques provided nearly equal Laplacian solutions, but the former offered the advantage that no preliminary simulation was required to regularize the RL estimate of the actual EEG data
Increased cerebellar volume and BDNF level following quadrato motor training
No full textUsing whole-brain structural measures coupled to analysis of salivary brain-derived neurotrophic factor (BDNF), we demonstrate sensory motor training-induced plasticity, including cerebellar gray matter volume increment and increased BDNF level. The increase of cerebellar volume was positively correlated with the increase of BDNF level
Prefontal cortex in long-term memory: an "interference" approach using magnetic stimulation
Full text linkNeuroimaging has consistently shown engagement of the prefrontal cortex during episodic memory tasks, but the functional relevance of this metabolic/hemodynamic activation in memory processing is still to be determined. We used repetitive transcranial magnetic stimulation (rTMS) to transiently interfere with either left or right prefrontal brain activity during the encoding or retrieval of pictures showing complex scenes. We found that the right dorsolateral prefrontal cortex (DLPFC) was crucial for the retrieval of the encoded pictorial information, whereas the left DLPFC was involved in encoding operations. This 'interference' approach allowed us to establish whether a cortical area activated by a memory task actually contributes to behavioral performanc
Advanced methods for the estimation of cortical connectivity by Directed Transfer Function and Multimodal Integration of EEG and fMRI recordings
No full textErice, Ital
High-resolution electro-encephalogram: source estimates of Laplacian-transformed somatosensory-evoked potentials using a realistic subject head model constructed from magnetic resonance images
No full textA novel high-resolution electro-encephalographic (EEG) procedure is proposed, including high spatial sampling (128 channels), a realistic magnetic resonance-constructed subject head model, a multi-dipole cortical source model and regularised weighted minimum-norm linear inverse source estimation (WMN). As an innovation, EEG potentials (two healthy subjects; median-nerve, short-latency somatosensory-evoked potentials (SEPs)) are preliminarily Laplacian-transformed (LT) to remove brain electrical activity generated by subcortical sources (i.e. not represented in the source model). LT-WMN estimates are mathematically evaluated by figures of merit (WMN estimates as a reference). Results show higher dipole identifiability (0.69; 0.088), lower dipole localisation error (0.6 mm; 7.8 mm) and lower spatial dispersion (8.6 mm; 24 mm) in LT-WMN than in WMN estimates (Bonferroni corrected p<0.001). These estimates are presented on the subject modelled cortical surface to highlight the increased spatial information content in LT-WMN compared with WMN estimates. The proposed high-resolution EEG technique is useful for the study of somatosensory functions in basic research and clinical applications
Human cortical responses to feed-back stimuli in visuomotor working memory and no working memory tasks: A high resolution EEG study
No full textIntroduction. Gevins' high resolution electroencephalographic (EEG) studies in humans have shown that central executive function of working memory involves a distributed system including several cortical frontoparietal areas of both hemispheres (1). In the present study, EEG rhythms were investigated to elucidate the cortical processing of visual feed-back during working memory (WM) and no working memory (NOWM) tasks. Methods. EEG (128 ch) was recorded in 3 right-handed, informed, normals. The WM task consisted of sequential right finger movements on a keyboard according to a cue visual stimulus (numbers). A visual stimulus (numbers) provided feed-back on performance accuracy. In the NOWM task, cue stimulus was available up to feed-back stimulus delivery. Artifact-free EEG trials were Laplacian transformed over a realistic MRI-constructed subject's head model (2). EEG power spectrum ranging (4-7 Hz), (8-12 Hz) and (13-30 Hz) rhythms was computed for scalp regions modeling roughly the responses of pre-frontal (PF), primary contralateral and ipsilateral sensorimotor (MI), mid-frontal (i.e. supplementary motor area, SMA), and superior posterior parietal (PP) areas. Results and Conclusions. During the visual feed-back period, PF and rhythms were lower and SMA, MIs and PP rhythms were higher for the WM than NOWM (Fig. 1). So higher was SMA rhythm. After the visual feedback, PF, SMA and MIs rhythms were lower for the WM than NOWM. In conclusion, in a distributed cortical frontoparietal system, post-movement updating of visuomotor transformations would occur during the feed-back for the NOWM ("on-line updating") and after the feed-back for the WM ("delayed updating"). PF may play a role in this "delayed updating", possibly matching actively memorized visual instruction and feed-back stimuli
Performances of surface Laplacian estimators: a study on simulated and real scalp potential distributions
No full textThis paper presents a study of the performance of various local and spherical spline methods currently in use for the surface Laplacian (SL) estimate of scalp potential distributions. The SL was estimated from simulated instantaneous event-related scalp potentials generated over a three-shell spherical head model. Laplacian estimators used planar and spherical scalp models. Noise of increasing magnitude and spatial frequency was added to the potential distributions in order to simulate noise presumed to contaminate scalp-recorded event-related potentials. A comparison of noise effects on various Laplacian estimates was made for increasing number of "electrode" positions in variants of the 10-20 system. Furthermore, to evaluate the error due to the use of unrealistic scalp models, the matching between SL estimates of human scalp-recorded movement-related potentials computed on spherical and realistically-shaped MRI-constructed models of the scalp was examined. With all methods the error of the SL estimate increased proportionally with the magnitude and spatial frequency of noise. Increased number of "electrodes" up to 256 significantly reduced the error (p < 0.05). In general, the best SL estimates were computed by second and third order splines including lambda correction, the performances of the second order spline being better with more than 64 "electrodes". Compared with spline Laplacians, the best local methods provided nearly equal estimates with low spatial sampling (19 and 28 "electrodes"), as well as high spatial frequency noise. The error of the SL estimate due to unrealistic scalp model was significant, and it augmented with increased spatial sampling from 64 to 128 electrodes
Spline Laplacian estimate of EEG potentials over a realistic magnetic resonance-constructed scalp surface model
No full textThis paper presents a realistic Laplacian (RL) estimator based on a tensorial formulation of the surface Laplacian (SL) that uses the 2-D thin plate spline function to obtain a mathematical description of a realistic scalp surface. Because of this tensorial formulation, the RL does not need an orthogonal reference frame placed on the realistic scalp surface. In simulation experiments the RL was estimated with an increasing number of ''electrodes'' (up to 256) on a mathematical scalp model, the analytic Laplacian being used as a reference. Second and third order spherical spline Laplacian estimates were examined for comparison. Noise of increasing magnitude and spatial frequency was added to the simulated potential distributions. Movement-related potentials and somatosensory evoked potentials sampled with 128 electrodes were used to estimate the RL on a realistically shaped, MR-constructed model of the subject's scalp surface. The RL was also estimated on a mathematical spherical scalp model computed from the real scalp surface. Simulation experiments showed that the performances of the RL estimator were similar to those of the second and third order spherical spline Laplacians. Furthermore, the information content of scalp-recorded potentials was clearly better when the RL estimator computed the SL of the potential on an MR-constructed scalp surface model
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