Assessing brain neuroplasticity: Surface morphometric analysis of cortical changes induced by Quadrato motor training.

Morphological markers for brain plasticity are still lacking and their findings are challenged by the extreme variability of cortical brain surface. Trying to overcome the "correspondence problem," we applied a landmark-free method (the generalized procrustes surface analysis (GPSA)) for investigating the shape variation of cortical surface in a group of 40 healthy volunteers (i.e., the practice group) subjected to daily motor training known as Quadrato motor training (QMT). QMT is a sensorimotor walking meditation that aims at balancing body, cognition, and emotion. More specifically, QMT requires coordination and attention and consists of moving in one of three possible directions on corners of a 50 × 50 cm2. Brain magnetic resonance images (MRIs) of practice group (acquired at baseline, as well as after 6 and 12 weeks of QMT), were 3D reconstructed and here compared with brain MRIs of six more volunteers never practicing the QMT (naïve group). Cortical regions mostly affected by morphological variations were visualized on a 3D average color-scaled brain surface indicating from higher (red) to lower (blue) levels of variation. Cortical regions interested in most of the shape variations were as follows: (1) the supplementary motor cortex; (2) the inferior frontal gyrus (pars opercolaris) and the anterior insula; (3) the visual cortex; (4) the inferior parietal lobule (supramarginal gyrus and angular gyrus). Our results show that surface morphometric analysis (i.e., GPSA) can be applied to assess brain neuroplasticity processes, such as those stimulated by QMT.

Anatomical substrates of cognitive and clinical dimensions in first episode schizophrenia.

OBJECTIVE: To explore gray (GM) and white matter (WM) abnormalities and the relationships with neuropsychopathology in first-episode schizophrenia (FES). METHOD: Nineteen patients with first episode of non-affective psychosis and 18 controls underwent a magnetic resonance voxel-based morphometry. Additionally, WM fractional anisotropy (FA) was calculated. For correlative analysis, symptoms and neuropsychological performances were scored by PANSS and by a comprehensive neuropsychological assessment respectively. RESULTS: Patients showed significantly decreased volume of left temporal lobe and disarray of all major WM tracts. Disorganized PANSS factor was inversely related to left cerebellar GM volume (corrected P = 0.03) and to WM FA of the left cerebellum, inferior fronto-occipital fasciculi (IFOF), and inferior longitudinal fasciculi (corrected P < 0.05). PANSS negative factor was inversely related to FA in the IFOF and superior longitudinal fasciculi (corrected P < 0.05). Impairment in facial emotion identification showed associations with temporo-occipital GM volume decrease (corrected P = 0.003) and WM disarray of superior and middle temporal gyri, anterior thalamic radiation, and superior longitudinal fasciculi (corrected P < 0.05). Speed of processing and visual memory correlated with WM abnormalities in fronto-temporal tracts. CONCLUSION: These results confirm how the structural development of key brain regions is related to neuropsychopathological dysfunction in FES, consistently with a neurodevelopmentally derived misconnection syndrome.

Is HCMV vaccine an unmet need? The state of art of vaccine development.

Congenital HCMV infection is the most frequent congenital infection, with an incidence of 0.2- 2.5 percent among all live births. About 11 percent of infected newborns show symptoms at birth, including hepato-splenomegaly, thrombocytopenia, neurologic involvement, hearing impairment and visual deficit. Moreover, 5-25 percent of the asymptomatic congenital HCMV-infected neonates will develop sequelae over months or even years. The relevant social burden, the economic costs of pre-natal screening, post-natal diagnosis, follow-up and possible therapy, although still limited, are the major factors to be considered. Several types of vaccines have been explored in order to develop an effective and safe HCMV vaccine: live attenuated, subunit, vectored, peptide, DNA, and subviral ones, but none are available for use. This review illustrates the different vaccine types studied to date, focusing on the possible vaccination strategy to be implemented once the HCMV vaccine is available, in terms of target population.

Gait analysis and cerebral volumes in Down's syndrome.

The aim of this study was to look for a relationship between cerebral volumes computed using a voxel-based morphometry algorithm and walking patterns in individuals with Down's syndrome (DS), in order to investigate the origin of the motor problems in these subjects with a view to developing appropriate rehabilitation programmes. Nine children with DS underwent a gait analysis (GA) protocol that used a 3D motion analysis system, force plates and a video system, and magnetic resonance imaging (MRI). Analysis of GA graphs allowed a series of parameters to be defined and computed in order to quantify gait patterns. By combining some of the parameters it was possible to obtain a 3D description of gait in terms of distance from normal values. Finally, the results of cerebral volume analysis were compared with the gait patterns found. A strong relationship emerged between cerebellar vermis volume reduction and quality of gait and also between grey matter volume reduction of some cerebral areas and asymmetrical gait. An evaluation of high-level motor deficits, reflected in a lack or partial lack of proximal functions, is important in order to define a correct rehabilitation programme.

Inward versus reward: white matter pathways in extraversion.

The trait of extraversion is one of the longest-standing domains that captures the social dimension of personality and can potentially explain the covariation of a wide variety of behaviors. To date, there is a growing recognition that human behavior should be specified not only through the psychological mechanisms underlying each trait but also through their underlying neurobehavioral systems. While imaging studies have revealed important initial insights into the structural and functional neural correlates of extraversion, current knowledge about the relationships between extraversion and brain structures is still rather limited, especially with regard to the relationship between extraversion and white matter (WM). In this study, we aimed to investigate WM microstructure in extraversion in greater depth. Thirty-five healthy volunteers (21 women; mean age 35) underwent magnetic resonance imaging, as a part of a larger project aimed at investigating the longitudinal effect of motor training. WM integrity was assessed using the diffusion tensor imaging technique combining multiple diffusion tensor measures. Extraversion was assessed by the Eysenck Personality Questionnaire-Revised. Voxelwise correlation analyses between fractional anisotropy, axial diffusivities, and radial diffusivities maps and extraversion score showed decreased connectivity in the right inferior fronto-occipital fasciculus and forceps major among individuals who had high extraversion ratings. In conclusion, individual differences in extraversion may reflect differential organization of the WM tracts connecting frontal cortex, temporal, and occipital areas, which are related to socioemotional and control functions.

Prefrontal [correction of Prefontal] cortex in long-term memory: an "interference" approach using magnetic stimulation.

Neuroimaging 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 performance.

Assessing cortical functional connectivity by linear inverse estimation and directed transfer function: simulations and application to real data.

OBJECTIVE: To test a technique called Directed Transfer Function (DTF) for the estimation of human cortical connectivity, by means of simulation study and human study, using high resolution EEG recordings related to finger movements. METHODS: The method of the Directed Transfer Function (DTF) is a frequency-domain approach, based on a multivariate autoregressive modeling of time series and on the concept of Granger causality. Since the spreading of the potential from the cortex to the sensors makes it difficult to infer the relation between the spatial patterns on the sensor space and those on the cortical sites, we propose the use of the DTF method on cortical signals estimated from high resolution EEG recordings, which exhibit a higher spatial resolution than conventional cerebral electromagnetic measures. The simulation study was followed by an analysis of variance (ANOVA) of the results obtained for different levels of Signal to Noise Ratio (SNR) and temporal length, as they have been systematically imposed on simulated signals. The whole methodology was then applied to high resolution EEG data recorded during a visually paced finger movement. RESULTS: The statistical analysis performed returns that during simulations, DTF is able to estimate correctly the imposed connectivity patterns under reasonable operative conditions, i.e. when data exhibit a SNR of at least 3 and a length of at least 75 s of non-consecutive recordings at 64 Hz of sampling rate, equivalent, more generally, to 4800 data samples. CONCLUSIONS: Functional connectivity patterns of cortical activity can be effectively estimated under general conditions met in any practical EEG recordings, by combining high resolution EEG techniques, linear inverse estimation and the DTF method. SIGNIFICANCE: The estimation of cortical connectivity can be performed not only with hemodynamic measurements, by using functional MRI recordings, but also with modern EEG recordings treated with advanced computational techniques.

Personalizing the Electrode to Neuromodulate an Extended Cortical Region.

BACKGROUND: Among transcranial electric stimulation (tES) parameters, personalizing the electrode geometry might help overcome the individual variability of the induced effects. OBJECTIVE/HYPOTHESIS: To test the need for electrode personalization, instead of a universal electrode for everyone, to induce neuromodulation effects on the bilateral primary motor cortex (M1) devoted to upper and lower limb representation. METHODS: By an ad-hoc neuronavigation procedure, we shaped the personalized electrode and positioned it matching the projection on the scalp of the individual central sulcus by a 2 cm strip, with total area of 35 cm(2). The non-personalized electrode, i.e., equal for all subjects, was a 2 cm wide strip size-matched with the personalized electrode but shaped on a standard model fitting the curve passing through C3-CZ-C4 sites of the electroencephalographic (EEG) 10-20 International System. To test neuromodulation electrode-dependent efficacy, we induced a 20 Hz sinusoidal modulated current (transcranial alternating current stimulation, tACS) because it produces online effects. We simultaneously collected left and right hand and leg motor potentials (MEP) that were evoked by a rounded transcranial magnetic stimulation (TMS) coil. Through each electrode we delivered both real and sham stimulations. RESULTS: While cortical excitability during tACS increased during both the non-personalized and the personalized electrodes for the leg, the hand representation excitability enhancement was induced selectively when using the personalized electrode. The results were consistent bilaterally. CONCLUSIONS: We documented that by using a personalized electrode it is possible to induce the neuromodulation of a predetermined extended cortical target, which did not occur with a non-personalized electrode. Our findings can help in building neuromodulation methods that might compensate for individual alterations across specific brain networks.

Coupling between "hand" primary sensorimotor cortex and lower limb muscles after ulnar nerve surgical transfer in paraplegia.

Previous neuroimaging evidence revealed an "invasion" of "hand" over "lower limb" primary sensorimotor cortex in paraplegic subjects, with the exception of a rare patient who received a surgical motor reinnervation of hip-thigh muscles by the ulnar nerve. Here, the authors show that a functional reorganization of cortico-muscular and cortico-cortical oscillatory coupling was related to the recovery of the rare patient, as a paradigmatic case of long-term plasticity in human sensorimotor cortex after motor reinnervation of paraplegic muscles. This conclusion was based on electroencephalographic and electromyographic data collected while the patient and normal control subjects performed isometric muscle contraction of the left hand or lower limb. Cortico-muscular and cortico-cortical coupling was estimated by electroencephalographic-electromyographic coherence and directed transfer function of a multivariate autoregressive model.

"Gating" of human short-latency somatosensory evoked cortical responses during execution of movement. A high resolution electroencephalography study.

The present study aimed at investigating gating of median nerve somatosensory evoked cortical responses (SECRs), estimated during executed continuous complex ipsilateral and contralateral sequential finger movements. SECRs were modeled with an advanced high resolution electroencephalography technology that dramatically improved spatial details of the scalp recorded somatosensory evoked potentials. Integration with magnetic resonance brain images allowed us to localize different SECRs within cortical areas. The working hypothesis was that the gating effects were time varying and could differently influence SECRs. Maximum statistically significant (p<0. 01) time-varying gating (magnitude reduction) of the short-latency SECRs modeled in the contralateral primary motor and somatosensory and supplementary motor areas was computed during the executed ipsilateral movement. The gating effects were stronger on the modeled SECRs peaking 30-45 ms (N30-P30, N32, P45-N45) than 20-26 ms (P20-N20, P22, N26) post-stimulus. Furthermore, the modeled SECRs peaking 30 ms post-stimulus (N30-P30) were significantly increased in magnitude during the executed contralateral movement. These results may delineate a distributed cortical sensorimotor system responsible for the gating effects on SECRs. This system would be able to modulate activity of SECR generators, based on the integration of afferent somatosensory inputs from the stimulated nerve with outputs related to the movement execution.

Bilateral neuromagnetic activation of human primary sensorimotor cortex in preparation and execution of unilateral voluntary finger movements.

Extracranial magnetoencephalographic activity was separately recorded (25 channels) from bilateral primary sensorimotor cortex (M1-S1) of normal right-handers during unilateral finger movements. Standard dipole analysis indicated only a contralateral M1-S1 source for first movement-evoked field (MEF1) peaking at about 115 ms after electromyographic onset. However, the subtraction of the magnetic field generated by this source from the recorded magnetic field disclosed a low-amplitude ipsilateral central-parietal MEF1 that was explained by an ipsilateral M1-S1 source.

Automatic alignment of EEG/MEG and MRI data sets.

OBJECTIVES: We developed a new technique of fully automatic alignment of brain data acquired with scalp sensors (e.g. electroencephalography/evoked potential (EP) electrodes, magnetoencephalography sensors) with a magnetic resonance imaging (MRI) volume of the head. METHODS: The method uses geometrical features (two sets of head points: digitized from the subject and extracted from MRI) to guide the alignment. It combines matching on 3 dimensional (3D) geometrical moments that perform the initial alignment, and 3D distance-based alignment that provides the final tuning. To reduce errors of the initial guessed computation resulting from digitization of the head surface points we introduced weights to compute geometrical moments, and a procedure to remove outliers to eliminate incorrectly digitized points. RESULTS: The method was tested on simulated (Monte Carlo trials) and on real data sets. The simulations demonstrated that for the number of test points within the range of 0.1-1% of the total number of head surface points and for the digitization error in the range of -2-2 mm the average map error was between 0.7 and 2.1 mm. The average distance error was less than 1 mm. Tests on real data gave the average distance error between 2.1 and 2.5 mm. CONCLUSIONS: The developed technique is fast, robust and comfortable for the patient and for medical personnel. It registers scalp sensor positions with MRI head volume with accuracy that is satisfactory for localization of biological processes examined with a commonly used number of scalp sensors (32, 64, or 128).

Computerized processing of EEG-EOG-EMG artifacts for multi-centric studies in EEG oscillations and event-related potentials.

The aim of this study is to present a package including standard software for the electroencephalographic (EEG), electro-oculographic (EOG) and electromyographic (EMG) preliminary data analysis, which may be suitable to standardize the results of many EEG research centers studies (i.e. multi-centric studies) especially focused on event-related potentials. In particular, our software package includes (semi)automatic procedures for (i) EOG artifact detection and correction, (ii) EMG analysis, (iii) EEG artifact analysis, (iv) optimization of the ratio between artifact-free EEG channels and trials to be rejected. The performances of the software package on EOG-EEG-EMG data related to cognitive-motor tasks were evaluated with respect to the preliminary data analysis performed by two expert electroencephalographists (gold standard). Due to its extreme importance for multi-centric EEG studies, we compared the performances of two representative "regression" methods for the EOG correction in time and frequency domains. The aim was the selection of the most suitable method in the perspective of a multi-centric EEG study. The results showed an acceptable agreement of approximately 95% between the human and software behaviors, for the detection of vertical and horizontal EOG artifacts, the measurement of hand EMG responses for a cognitive-motor paradigm, the detection of involuntary mirror movements, and the detection of EEG artifacts. Furthermore, our results indicated a particular reliability of a 'regression' EOG correction method operating in time domain (i.e. ordinary least squares). These results suggest that such a software package could be used for multi-centric EEG studies.

Integration of high resolution EEG and functional magnetic resonance in the study of human movement-related potentials.

Cortical sources of human movement-related potentials (i.e. unilateral finger extension) were modeled using functional magnetic resonance imaging (fMR) data as a constraint of a linear inverse source estimation from highly sampled (128 channels) EEG data. Remarkably, this estimation was performed within realistic subject's MR-constructed head models by boundary element techniques. An appropriate figure of merit served to set the optimal amount of fMR constraints. With respect to standard linear inverse source estimates, fMR-constrained ones presented increased spatial detail and provided a more reliable timing of activation in bilateral sensorimotor cortical regions of interest.

Independent component analysis compared to Laplacian filtering as "deblurring" techniques for event related desynchronization/synchronization.

OBJECTIVES: The aim of the work was to compare two different approaches - one model-dependent, the other data-dependent - for "deblurring" EEG data, in order to improve the estimation of Event-Related Desynchronization/Synchronization. METHODS: Realistic Surface Laplacian filtering (SL) and Infomax Independent Component Analysis (ICA) were applied on multivariate scalp EEG signals (SL: 128 electrodes with MRI-based realistic modeling; ICA: a subset of 19 electrodes, no MRI) prior to beta Event Related Synchronization (ERS) estimation after finger movement in 8 normal subjects. ERS estimation was performed using standard band-pass filtering. ERS peak amplitudes and latencies in the most responsive channel were calculated and the effect of the two methods above was evaluated by one-way analysis of variance (ANOVA) and Sheffe's test. RESULTS: Both methods and their combination significantly improved ERS estimation (greater ERS peak amplitude, p <0.05). The results obtained after ICA on 19 electrodes were not significantly different than the ones obtained with Realistic SL using 128 electrodes and MRI for scalp modeling (p >0.89). CONCLUSIONS: The "low cost" of ICA (19 electrodes, no MRI) imposes such method as a valid alternative to SL filtering. The employ of ICA after SL filtering suggests that the "ideal EEG deblurring method" would unify the two approaches, depending on both the scalp model and the data.

EEG deblurring techniques in a clinical context.

OBJECTIVES: EEG scalp potential distributions recorded in humans are affected by low spatial resolution and by the dependence on the electrical reference used. High resolution EEG technologies are available to drastically increase the spatial resolution of the raw EEG. Such technologies include the computation of surface Laplacian (SL) of the recorded potentials, as well as the use of realistic head models to estimate the cortical sources via linear inverse procedure (low resolution brain electromagnetic tomography, LORETA). However, these deblurring procedures are generally used in conjunction with EEG recordings with 64-128 scalp electrodes and with realistic head models obtained via sequential magnetic resonance images (MRIs) of the subjects. Such recording setup it is not often available in the clinical context, due to both the unavailability of these technologies and the scarce compliance of the patients with them. In this study we addressed the use of SL and LORETA deblurring techniques to analyze data from a standard 10-20 system (19 electrodes) in a group of Alzheimer disease (AD) patients. METHODS: EEG data related to unilateral finger movements were gathered from 10 patients affected by AD. SL and LORETA techniques were applied for source estimation of EEG data. The use of MRIs for the construction of head models was avoided by using the quasi-realistic head model of the Brain Imaging Neurology Institute of Montreal. RESULTS: A similar cortical activity estimated by the SL and LORETA techniques was observed during an identical time period of the acquired EEG data in the examined population. CONCLUSIONS: The results of the present study suggest that both SL and LORETA approaches can be usefully applied in the clinical context, by using quasi-realistic head modeling and a standard 10-20 system as electrode montage (19 electrodes). These results represent a reciprocal cross-validation of the two mathematically independent techniques in a clinical environment.

Classification of EEG mental patterns by using two scalp electrodes and Mahalanobis distance-based classifiers.

OBJECTIVES: In this paper, we explored the use of quadratic classifiers based on Mahalanobis distance to detect mental EEG patterns from a reduced set of scalp recording electrodes. METHODS: Electrodes are placed in scalp centro-parietal zones (C3, P3, C4 and P4 positions of the international 10-20 system). A Mahalanobis distance classifier based on the use of full covariance matrix was used. RESULTS: The quadratic classifier was able to detect EEG activity related to imagination of movement with an affordable accuracy (97% correct classification, on average) by using only C3 and C4 electrodes. CONCLUSIONS: Such a result is interesting for the use of Mahalanobis-based classifiers in the brain computer interface area.

Cortical source estimate of combined high resolution EEG and fMRI data related to voluntary movements.

OBJECTIVES: In this paper, we employed advanced methods for the modeling of human cortical activity related to voluntary right one-digit movements from combined high-resolution electroencepholography (EEG) and functional magnetic resonance imaging (fMRI). METHODS: Multimodal integration between EEG and fMRI data was performed by using realistic head models, a large number of scalp electrodes (128) and the estimation of current density strengths by linear inverse estimation. RESULTS: Increasing of spatial details of the estimated cortical density distributions has been detected by using the proposed integration method with respect to the estimation using EEG data alone. CONCLUSION: The proposed method of multimodal EEG-fMRI data is useful to increase spatial resolution of movement-related potentials and can also be applied to other kinds of event-related potentials.

Solving the neuroimaging puzzle: the multimodal integration of neuroelectromagnetic and functional magnetic resonance recordings.

In this chapter, advanced methods for the modeling of human cortical activity from combined high-resolution electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data are reviewed. These methods include a subject's multicompartment head model (scalp, skull, dura mater, cortex) constructed from magnetic resonance images, multidipole source model, and regularized linear inverse source estimates. Determination of the priors in the resolution of the linear inverse problem was performed with the use of information from the hemodynamic responses of the cortical areas as revealed by block-designed (strength of activated voxels) and event-related (coupling of activated voxels) fMRI. As an example, these methods were applied to EEG (128 electrodes) and fMRI data, which were recorded in separate sessions while normal subjects executed voluntary right one-digit movements.

High-resolution electro-encephalogram: source estimates of Laplacian-transformed somatosensory-evoked potentials using a realistic subject head model constructed from magnetic resonance images.

A 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.