PubMed Health⌕ Search

Biomedical subjects

F Babiloni

Publications and source records attributed to F Babiloni.

At least 19 recordsLinked to original sources
PubMed2004

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.

Adult↗
PubMed2003

Influence of the supplementary motor area on primary motor cortex excitability during movements triggered by neutral or emotionally unpleasant visual cues.

The stronger anatomo-functional connections of the supplementary motor area (SMA), as compared with premotor area (PM), with regions of the limbic system, suggest that SMA could play a role in the control of movements triggered by visual stimuli with emotional content. We addressed this issue by analysing the modifications of the excitability of the primary motor area (M1) in a group of seven healthy subjects, studied with transcranial magnetic stimulation (TMS), after conditioning TMS of SMA, during emotional and non-emotional visually cued movements. Conditioning TMS of the PM or of contralateral primary motor cortex (cM1) were tested as control conditions. Single-pulse TMS over the left M1 was randomly intermingled with paired TMS, in which a conditioning stimulation of the left SMA, left PM or right M1 preceded test stimulation over the left M1. The subjects carried out movements in response to computerised visual cues (neutral pictures and pictures with negative emotional content). The amplitudes of motor-evoked potentials (MEPs) recorded from the right first dorsal interosseous muscle after paired TMS were measured and compared with those obtained after single-pulse TMS of the left M1 under the various experimental conditions. Conditioning TMS of the SMA in the paired-pulse paradigm selectively enhanced MEP amplitudes in the visual-emotional triggered movement condition, compared with single-pulse TMS of M1 alone or with paired TMS during presentation of neutral visual cues. On the other hand, conditioning TMS of the PM or cM1 did not differentially influence MEP amplitudes under visual-emotional triggered movement conditions. This pattern of effects was related to the intensity of the conditioning TMS over the SMA, being most evident with intensities ranging from 110% to 80% of motor threshold. These results suggest that the SMA in humans could interface the limbic and the motor systems in the transformation of emotional experiences into motor actions.

Adult↗
PubMed2003

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.

Algorithms↗
PubMed2003

Multimodal integration of high-resolution EEG and functional magnetic resonance imaging data: a simulation study.

Previous simulation studies have stressed the importance of the use of fMRI priors in the estimation of cortical current density. However, no systematic variations of signal-to-noise ratio (SNR) and number of electrodes were explicitly taken into account in the estimation process. In this simulation study we considered the utility of including information as estimated from fMRI. This was done by using as the dependent variable both the correlation coefficient and the relative error between the imposed and the estimated waveforms at the level of cortical region of interests (ROI). A realistic head and cortical surface model was used. Factors used in the simulations were the different values of SNR of the scalp-generated data, the different inverse operators used to estimated the cortical source activity, the strengths of the fMRI priors in the fMRI-based inverse operators, and the number of scalp electrodes used in the analysis. Analysis of variance results suggested that all the considered factors significantly afflict the correlation and the relative error between the estimated and the simulated cortical activity. For the ROIs analyzed with simulated fMRI hot spots, it was observed that the best estimation of cortical source currents was performed with the inverse operators that used fMRI information. When the ROIs analyzed do not present fMRI hot spots, both standard (i.e., minimum norm) and fMRI-based inverse operators returned statistically equivalent correlation and relative error values.

Analysis of Variance↗
PubMed2003

Introducing BF++: AC++ framework for cognitive bio-feedback systems design.

OBJECTIVE: This paper addressed the issue of building-up a framework for the realization of several cognitive bio-feedback (CBF) systems. It minimizes the programming effort and maximizes the efficiency and the cross-platform portability so that it can be used with many platforms (either software or hardware). METHODS: A generic CBF system was decomposed into six modules: acquisition, kernel, feedback rule, patient feedback, operator user interface and persistent storage. The way in which these modules interact was defined by immutable software interfaces in a way that allows to completely substitute a module without the need to modify the others. RESULTS: Three Brain Computer Interface engines were developed with less than 40 lines of C++ code each. They can also be used under virtually any platform that supports an ANSI C++ compiler. CONCLUSION: A framework for the implementation of a wide range of CBF systems was developed. Compared to the other approaches that are described in the literature, the proposed one is the most efficient, the most protable across different platforms, the most generic and the one that allows the realization of the cheapest final systems.

Cognition↗
PubMed2002

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.

Biomedical Engineering↗
PubMed2002

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.

Brain Mapping↗
PubMed2001

Mapping of early and late human somatosensory evoked brain potentials to phasic galvanic painful stimulation.

In the present study, we modeled the spatiotemporal evolution of human somatosensory evoked cortical potentials (SEPs) to brief median-nerve galvanic painful stimulation. SEPs were recorded (-50 to +250 ms) from 12 healthy subjects following nonpainful (reference), slight painful, and moderate painful stimulations (subjective scale). Laplacian transformation of scalp SEPs reduced head volume conduction effects and annulled electric reference influence. Typical SEP components to the galvanic nonpainful stimulation were contralateral frontal P20-N30-N60-N120-P170, central P22-P40, and parietal N20-P30-P60-P120 (N = negativity, P = positivity, number = latency in ms). These components were observed also with the painful stimulations, the N60, N120, P170 having a longer latency with the painful than nonpainful stimulations. Additional SEP components elicited by the painful stimulations were parietomedian P80 as well as central N125, P170 (cP170), and P200. These additional SEP components included the typical vertex negative-positive complex following transient painful stimulations. Latency of the SEP components exclusively elicited by painful stimulation is highly compatible with the involvement of A delta myelinated fibers/spinothalamic pathway. The topography of these components is in line with the response of both nociceptive medial and lateral systems including bilateral primary sensorimotor and anterior cingulate cortical areas. The role of attentive, affective, and motor aspects in the modulation of the reported SEP components merits investigation in future experiments.

Adult↗
PubMed2001

Linear inverse source estimate of combined EEG and MEG data related to voluntary movements.

A method for the modeling of human movement-related cortical activity from combined electroencephalography (EEG) and magnetoencephalography (MEG) data is proposed. This method includes a subject's multi-compartment head model (scalp, skull, dura mater, cortex) constructed from magnetic resonance images, multi-dipole source model, and a regularized linear inverse source estimate based on boundary element mathematics. Linear inverse source estimates of cortical activity were regularized by taking into account the covariance of background EG and MEG sensor noise. EEG (121 sensors) and MEG (43 sensors) data were recorded in separate sessions whereas normal subjects executed voluntary right one-digit movements. Linear inverse source solution of EEG, MEG, and EEG-MEG data were quantitatively evaluated by using three performance indexes. The first two indexes (Dipole Localization Error [DLE] and Spatial Dispersion [SDis]) were used to compute the localization power for the source solutions obtained. Such indexes were based on the information provided by the column of the resolution matrix (i.e., impulse response). Ideal DLE values tend to zero (the source current was correctly retrieved by the procedure). In contrast, high DLE values suggest severe mislocalization in the source reconstruction. A high value of SDis at a source space point mean that such a source will be retrieved by a large area with the linear inverse source estimation. The remaining performance index assessed the quality of the source solution based on the information provided by the rows of the resolution matrix R, i.e., resolution kernels. The i-th resolution kernels of the matrix R describe how the estimation of the i-th source is distorted by the concomitant activity of all other sources. A statistically significant lower dipole localization error was observed and lower spatial dispersion in source solutions produced by combined EEG-MEG data than from EEG and MEG data considered separately (P < 0.05). These effects were not due to an increased number of sensors in the combined EEG-MEG solutions. They result from the independence of source information conveyed by the multimodal measurements. From a physiological point of view, the linear inverse source solution of EEG-MEG data suggested a contralaterally preponderant bilateral activation of primary sensorimotor cortex from the preparation to the execution of the movement. This activation was associated with that of the supplementary motor area. The activation of bilateral primary sensorimotor cortical areas was greater during the processing of afferent information related to the ongoing movement than in the preparation for the motor act. In conclusion, the linear inverse source estimate of combined MEG and EEG data improves the estimate of movement-related cortical activity.

Dura Mater↗
PubMed2001

Recognition of imagined hand movements with low resolution surface Laplacian and linear classifiers.

EEG-based Brain Computer Interfaces (BCIs) require on-line detection of mental states from spontaneous EEG signals. In this framework, it was suggested that EEG patterns can be better detected with EEG data transformed with Surface Laplacian computation (SL) than with the unprocessed raw potentials. However, accurate SL estimates require the use of many EEG electrodes, when local estimation methods are used. Since BCI devices have to use a limited number of electrodes for practical reasons, we investigated the performances of spline methods for SL estimates using a limited number of electrodes (low resolution SL). Recognition of mental activity was attempted on both raw and SL-transformed EEG data from five healthy people performing two mental tasks, namely imagined right and left hand movements. Linear classifiers were used including Signal Space Projection (SSP) and Fisher's linear discriminant. Results showed an acceptable average correlation between the waveforms obtained with the low resolution SL and these obtained with the SL computed from 26 electrodes (full resolution SL). More importantly, satisfactorily recognition scores for mental EEG-patterns were obtained with the low-resolution surface Laplacian transformation of the recorded potentials when compared with those obtained by using full resolution SL (82%). These results demonstrated also the utility of linear classifiers for the detection of mental patterns in the BCI field.

Biomedical Engineering↗
PubMed2001

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.

Adult↗
PubMed2000

Comparison between human and artificial neural network detection of Laplacian-derived electroencephalographic activity related to unilateral voluntary movements.

A back-propagation artificial neural network (ANN) was tested to verify its capacity to select different classes of single trials (STs) based on the spatial information content of electroencephalographic activity related to voluntary unilateral finger movements. The rationale was that ipsilateral and contralateral primary sensorimotor cortex can be involved in a nonstationary way in the control of unilateral voluntary movements. The movement-related potentials were surface Laplacian-transformed (SL) to reduce head volume conductor effects and to model the response of the primary sensorimotor cortex. The ANN sampled the SL from four or two central channels overlying the primary motor area of both sides in the period of 80 ms preceding the electromyographic response onset in the active muscle. The performance of the ANN was evaluated statistically by calculating the percentage value of agreement between the STs classified by the ANN and those of two investigators (used as a reference). The results showed that both investigator and ANN were capable of selecting STs with the SL maximum in the central area contralateral to the movement (contralateral STs, about 25%), STs with considerable SL values also in the ipsilateral central area (bilateral STs, about 50%), and STs with neither the contralateral nor bilateral pattern ("spatially incoherent" single trials; about 25%). The maximum agreement (64-84%) between the ANN and the investigator was obtained when the ANN used four spatial inputs (P < 0.0000001). Importantly, the common means of all single trials showed a weak or absent ipsilateral response. These results may suggest that a back-propagation ANN could select EEG single trials showing stationary and nonstationary responses of the primary sensorimotor cortex, based on the same spatial criteria as the experimenter.

Electroencephalography↗
PubMed2000

Movement-related electroencephalographic reactivity in Alzheimer disease.

Event-related desynchronization/synchronization (ERD/ERS) of alpha and beta electroencephalographic (EEG) rhythms was investigated in normal subjects and mild Alzheimer Disease patients (AD), performing unilateral right finger movements (about 10 s intermovement interval). Electroencephalographic data were sampled based on 10-20 system electrode montage. Surface Laplacian estimate of the potential reduced the head-volume conductor effects and annulled electrode reference variations. Results showed that EEG reactivity (i.e., ERD/ERS) of modeled contralateral rolandic cortex and motor performance were preserved in mild to moderate AD. In contrast, modeled activity (i.e., ERD/ERS) of frontolateral, centromedial, and ipsilateral rolandic areas was abnormal. Furthermore, interrelatedness of cortical response and movement timing was abnormal in AD patients. These results would support the working hypothesis that mild to moderate AD is a global brain network disease, including processing of sensorimotor information (despite no overt movement disorder). Further investigations will ascertain the clinical relevance of these results.

Aged↗
PubMed2000

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.

Electroencephalography↗
PubMed2000

Linear classification of low-resolution EEG patterns produced by imagined hand movements.

Electroencephalograph (EEG)-based brain-computer interfaces (BCI's) require on-line detection of mental states from spontaneous EEG signals. In this framework, surface Laplacian (SL) transformation of EEG signals has proved to improve the recognition scores of imagined motor activity. The results we obtained in the first year of an European project named adaptive brain interfaces (ABI) suggest that: 1) the detection of mental imagined activity can be obtained by using the signal space projection (SSP) method as a classifier and 2) a particular type of electrodes can be used in such a BCI device, reconciling the benefits of SL waveforms and the need for the use of few electrodes. Recognition of mental activity was attempted on both raw and SL-transformed EEG data from five healthy people performing two mental tasks, namely imagined right and left hand movements.

Adult↗
PubMed2000

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.

Adult↗