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.

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.

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.

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 electroencephalography (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.

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.

Clinical and biomarker profiling of prodromal Alzheimer's disease in workpackage 5 of the Innovative Medicines Initiative PharmaCog project: a 'European ADNI study'

BACKGROUND

In the field of Alzheimer's disease (AD), the validation of biomarkers for early AD diagnosis and for use as a surrogate outcome in AD clinical trials is of considerable research interest.

OBJECTIVE

To characterize the clinical profile and genetic, neuroimaging and neurophysiological biomarkers of prodromal AD in amnestic mild cognitive impairment (aMCI) patients enrolled in the IMI WP5 PharmaCog (also referred to as the European ADNI study).

METHODS

A total of 147 aMCI patients were enrolled in 13 European memory clinics. Patients underwent clinical and neuropsychological evaluation, magnetic resonance imaging (MRI), electroencephalography (EEG) and lumbar puncture to assess the levels of amyloid β peptide 1-42 (Aβ42), tau and p-tau, and blood samples were collected. Genetic (APOE), neuroimaging (3T morphometry and diffusion MRI) and EEG (with resting-state and auditory oddball event-related potential (AO-ERP) paradigm) biomarkers were evaluated.

RESULTS

Prodromal AD was found in 55 aMCI patients defined by low Aβ42 in the cerebrospinal fluid (Aβ positive). Compared to the aMCI group with high Aβ42 levels (Aβ negative), Aβ positive patients showed poorer visual (P = 0.001), spatial recognition (P < 0.0005) and working (P = 0.024) memory, as well as a higher frequency of APOE4 (P < 0.0005), lower hippocampal volume (P = 0.04), reduced thickness of the parietal cortex (P < 0.009) and structural connectivity of the corpus callosum (P < 0.05), higher amplitude of delta rhythms at rest (P = 0.03) and lower amplitude of posterior cingulate sources of AO-ERP (P = 0.03).

CONCLUSION

These results suggest that, in aMCI patients, prodromal AD is characterized by a distinctive cognitive profile and genetic, neuroimaging and neurophysiological biomarkers. Longitudinal assessment will help to identify the role of these biomarkers in AD progression.

Evaluation of symptomatic drug effects in Alzheimer's disease: strategies for prediction of efficacy in humans

In chronic diseases such as Alzheimer's disease (AD), the arsenal of biomarkers available to determine the effectiveness of symptomatic treatment is very limited. Interpretation of the results provided in literature is cumbersome and it becomes difficult to predict their standardization to a larger patient population. Indeed, cognitive assessment alone does not appear to have sufficient predictive value of drug efficacy in early clinical development of AD treatment. In recent years, research has contributed to the emergence of new tools to assess brain activity relying on innovative technologies of imaging and electrophysiology. However, the relevance of the use of these newer markers in treatment response assessment is waiting for validation. This review shows how the early clinical assessment of symptomatic drugs could benefit from the inclusion of suitable pharmacodynamic markers. This review also emphasizes the importance of re-evaluating a step-by-step strategy in drug development.

Effects of dietary resveratrol on the sleep-wake cycle in the non-human primate gray mouse lemur (Microcebus murinus)

Converging evidence shows that the non-human primate gray mouse lemur (Microcebus murinus) is ideal for the study of the aging process and for testing the effects of new therapies and dietary interventions on age-associated pathologies. One such dietary supplement is resveratrol (RSV), a dietary polyphenolic compound with several positive effects on metabolic functions and longevity. However, little is known about the effect of RSV on the lemur sleep-wake cycle, which reflects mammalian brain function and health. In the present study, the authors investigated this effect by comparing sleep-wake cycles in adult lemurs based on electroencephalographic (EEG) rhythms. The effect of short-term RSV supplementation on the sleep-wake cycle of mouse lemurs was evaluated in entrained conditions (long-day photoperiods, light:dark 14:10). After 3 wks of RSV supplementation, the animals exhibited a significantly increased proportion of active-wake time, occurring mainly during the resting phase of the sleep-wake cycle (+163%). The increase in active-wake time with RSV supplementation was accompanied by a significant reduction of both paradoxical sleep (-95%) and slow-wave sleep (-38%). These changes mainly occurred during the resting phase of the sleep-wake cycle (RSV supplementation induced negligible changes in active-wake time during the active phase of the sleep-wake cycle). The present data suggest that RSV may be a potent regulator of sleep-wake rhythms and could be of major interest in the study of sleep perturbations associated with aging and neuropathology.

Functional coupling of parietal α rhythms is enhanced in athletes before visuomotor performance: a coherence electroencephalographic study

It has been shown that elite pistol shooters are characterized by a power increase of wide cortical electroencephalographic (EEG) alpha (about 8-12 Hz) and beta (about 14-35 Hz) rhythms during the preparation of air pistol shots, possibly related to selective attentional and "neural efficiency" processes [Del Percio C, Babiloni C, Bertollo M, Marzano N, Iacoboni M, Infarinato F, Lizio R, Stocchi M, Robazza C, Cibelli G, Comani S, Eusebi F (2009a) Hum Brain Mapp 30(11):3527-3540; Del Percio C, Babiloni C, Marzano N, Iacoboni M, Infarinato F, Vecchio F, Lizio R, Aschieri P, Fiore A, Toràn G, Gallamini M, Baratto M, Eusebi F (2009b) Brain Res Bull 79(3-4):193-200]. Here, we tested the hypothesis that such processes are associated with an enhanced functional coupling of posterior cortical regions involved in task-relevant attentional processes and visuo-motor transformations. To this aim, between-electrodes spectral coherence was computed from spatially enhanced EEG data collected during a previous study (i.e. right handed 18 elite air pistol shooters and 10 matched non-athletes; augmented 10-20 system; surface Laplacian estimation). Theta (about 4-6 Hz), low-frequency alpha (about 8-10 Hz), high-frequency alpha (about 10-12 Hz), low-frequency beta (14-22 Hz), high-frequency beta (23-35 Hz), and gamma (36-44 Hz) bands were considered. Statistical results showed that intra-hemispheric low-frequency alpha (parietal-temporal and parietal-occipital regions), high-frequency alpha (parietal-temporal and parietal-occipital regions), high-frequency beta, and gamma (parietal-temporal regions) coherence values were stable in amplitude in the elite athletes but not in the non-athletes during the preparation of pistol shots. The same applies to inter-hemispheric low-frequency alpha (parietal regions), high-frequency alpha (parietal regions), high-frequency beta and gamma coherence values. These findings suggest that under the present experimental conditions, elite athletes are characterized by the stabilization of functional coupling of preparatory EEG rhythms between "visuo-spatial" parietal area and other posterior cortical areas.

The I.F.A.S.T. model allows the prediction of conversion to Alzheimer disease in patients with mild cognitive impairment with high degree of accuracy

This paper presents the results obtained with the innovative use of special types of artificial neural networks (ANNs) assembled in a novel methodology named IFAST (implicit function as squashing time) capable of compressing the temporal sequence of electroencephalographic (EEG) data into spatial invariants. The aim of this study is to test the potential of this parallel and nonlinear EEG analysis technique in providing an automatic classification of mild cognitive impairment (MCI) subjects who will convert to Alzheimer's disease (AD) with a high degree of accuracy. Eyes-closed resting EEG data (10-20 electrode montage) were recorded in 143 amnesic MCI subjects. Based on 1-year follow up, the subjects were retrospectively classified to MCI converted to AD and MCI stable. The EEG tracks were successively filtered according to four different frequency ranges, in order to evaluate the hypotheses that a specific range, corresponding to specific brain wave type, could provide a better classification (0.12 Hz, 12.2 - 29.8 Hz; 30.2 - 40 Hz, and finally Notch Filter 48 - 50 Hz). The spatial content of the EEG voltage was extracted by IFAST step-wise procedure using ANNs. The data input for the classification operated by ANNs were not the EEG data, but the connections weights of a nonlinear auto-associative ANN trained to reproduce the recorded EEG tracks. These weights represented a good model of the peculiar spatial features of the EEG patterns at scalp surface. The classification based on these parameters was binary and performed by a supervised ANN. The best results distinguishing between MCI stable and MCI/AD reached to 85.98%.(012 Hz band). And confirmed the working hypothesis that a correct automatic classification can be obtained extracting spatial information content of the resting EEG voltage by ANNs and represent the basis for research aimed at integrating spatial and temporal information content of the EEG. These results suggest that this low-cost procedure can reliably distinguish eyes-closed resting EEG data in individual MCI subjects who will have different prognosis at 1-year follow up, and is promising for a large-scale periodic screening of large populations at amnesic MCI subjects at risk of AD.

Effects of tiredness on visuo-spatial attention processes in elite karate athletes and non-athletes

"Attentional" adaptations are fundamental effects for sport performance. We tested the hypothesis that tiredness and muscular fatigue poorly affect visuo-spatial attentional processes in elite karate athletes. To this aim, 14 elite karate athletes and 11 non-athletes were involved in an isometric contraction exercise protocol up to muscular fatigue. Blood lactate and attention measurements were taken. Posner's test probed "endogenous" (i.e., internally planned allocation of spatial attention) and "reflexive" (i.e., brisk variation of endogenous spatial attention due to unexpected external stimuli) attention. Lactate and attentional measurements were performed before (Block 1, B1) and after the fatiguing exercise (B2) and at the end of a recovery period (B3). Compared to the non-athletes, the athletes showed a better performance in the fatigue protocol, confirmed by the higher absolute lactate values in B2. The correct responses in the "valid trials" probing "endogenous" attention were 92.4% (B1), 93.9% (B2), and 95.8% (B3) in the non-athletes, and 98.5%, 96.4%, 95.5% in the elite karate athletes. The correct responses in the "invalid trials" probing "reflexive" attention were 95.4%, 89.7%, 93.2% in the non-athletes, and 96.4%, 97.3%, 98.5% in the elite karate athletes. The percentage of correct responses in the "invalid" trials significantly decreased from B1 to B2 in the non-athletes but not in the elite karate athletes. In conclusion, tiredness and muscular fatigue do not affect "reflexive" attentional processes of elite karate athletes, which is crucial to contrast attacks coming from an unexpected spatial region.

Conditioning transcutaneous electrical nerve stimulation induces delayed gating effects on cortical response: A magnetoencephalographic study

The present study was undertaken to investigate after-effects of 7 Hz non-painful prolonged stimulation of the median nerve on somatosensory-evoked fields (SEFs). The working hypothesis that conditioning peripheral stimulations might produce delayed interfering ("gating") effects on the response of somatosensory cortex to test stimuli was evaluated. In the control condition, electrical thumb stimulation induced SEFs in ten subjects. In the experimental protocol, a conditioning median nerve stimulation at wrist preceded 6 electrical thumb stimulations. Equivalent current dipoles fitting SEFs modeled responses of contralateral primary area (SI) and bilateral secondary somatosensory areas (SII) following control and experimental conditions. Compared to the control condition, conditioning stimulation induced no amplitude modulation of SI response at the initial stimulus-related peak (20 ms). In contrast, later response from SI (35 ms) and response from SII were significantly weakened in amplitude. Gradual but fast recovery towards control amplitude levels was observed for the response from SI-P35, while a slightly slower cycle was featured from SII. These findings point to a delayed "gating" effect on the synchronization of somatosensory cortex after peripheral conditioning stimulations. This effect was found to be more lasting in SII area, as a possible reflection of its integrative role in sensory processing.

Inhibitory effect of voluntary movement preparation on cutaneous heat pain and laser-evoked potentials

In our study, preparation of voluntary movement was used to physiologically activate the motor cortex areas and the effect of this activation on CO(2) laser-evoked potentials (LEPs) was explored. LEPs were recorded from 31 scalp electrodes in 10 healthy subjects after painful stimulation of the right C6-C7 skin dermatomes. LEP stimuli were delivered in the time interval between a visual warning stimulus followed after 1 s. by an imperative stimulus. The imperative stimulus triggered: (i) no task in the baseline condition (Pain); (ii) flexion-extension movements of the second finger of the right hand in the movement condition (Pain + Movement); (iii) cognitive task (mathematic computation) in the distraction condition (Pain + Cognition). The experimental conditions were also repeated during application of laser stimuli on the left C6-C7 skin dermatomes. Compared with the baseline condition (no task required), during preparation of right-hand voluntary movement there was a significant reduction in LEP amplitude and subjective pain rating after right- but not after left-hand stimulation, which suggests that the observed effect cannot be attributed to a nonspecific reduction in attention toward painful stimulus. During preparation of a cognitive task, LEP amplitude was reduced compared to baseline. Our results represent the first neurophysiological suggestion that physiological activation of the motor cortex, occurring during movement preparation, inhibits cortical pain processing by a centrifugal mechanism.

Time-varying cortical connectivity by high resolution EEG and directed transfer function: simulations and application to finger tapping data

The problem of the definition and evaluation of brain connectivity has become a central one in neuroscience during the latest years, as a way to understand the organization and interaction of cortical areas during the execution of cognitive or motor tasks. The method of the directed transfer function (DTF) is a frequency-domain approach to this problem, based on a multivariate autoregressive modeling of time series and on the concept of Granger causality. So far, all the connectivity estimations performed on cerebral electromagnetic signals were computed between signals gathered from the electric or magnetic sensors. However, 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. In this paper 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. As main contributions of this work, we present the results of a wide simulation study, aiming to evaluate performances of DTF application on this kind of data, and a statistical analysis (via the ANOVA, analysis of variance) of the results obtained for different levels of signal to noise ratio and temporal length, as they have been systematically imposed on simulated signals. Finally, we provide an application to the estimation of cortical connectivity from high resolution EEG recordings related to finger tapping movements.

Conversion from mild cognitive impairment to Alzheimer's disease is predicted by sources and coherence of brain electroencephalography rhythms

Objective. Can quantitative electroencephalography (EEG) predict the conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD)? Methods. Sixty-nine subjects fulfilling criteria for MCI were enrolled; cortical connectivity (spectral coherence) and (low resolution brain electromagnetic tomography) sources of EEG rhythms (delta=2-4 Hz; theta=4-8 Hz; alpha 1=8-10.5 Hz; alpha 2=10.5-13 Hz: beta 1=13-20 Hz; beta 2=20-30 Hz; and gamma=30-40) were evaluated at baseline (time of MCI diagnosis) and follow up (about 14 months later). At follow-up, 45 subjects were still MCI (MCI Stable) and 24 subjects were converted to AD (MCI Converted). Results. At baseline, fronto-parietal midline coherence as well as delta (temporal), theta (parietal, occipital and temporal), and alpha 1 (central, parietal, occipital, temporal, limbic) sources were stronger in MCI Converted than stable subjects (P<0.05). Cox regression modeling showed low midline coherence and weak temporal source associated with 10% annual rate AD conversion, while this rate increased up to 40% and 60% when strong temporal delta source and high midline gamma coherence were observed respectively. Interpretation. Low-cost and diffuse computerized EEG techniques are able to statistically predict MCI to AD conversion.

Somatotopy of anterior cingulate cortex (ACC) and supplementary motor area (SMA) for electric stimulation of the median and tibial nerves: an fMRI study

In this study, we tested whether there is a somatotopic sensory organization in human anterior cingulate cortex (ACC) and supplementary motor area (SMA), as a reflection of central feed-back sensory processing for motor control. To this aim, fMRI recordings were performed in 15 normal young adults during nonpainful and painful electric stimulation of median nerve at the wrist and tibial nerve at the medial malleolus. Results showed that the representation of median nerve area was more anterior in the ACC and more inferior in the SMA than the one of tibial nerve area. This was true for both nonpainful and painful stimulation intensities. These results point to a somatotopic sensory organization of human ACC and SMA.

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.

Nociceptive and non-nociceptive sub-regions in the human secondary somatosensory cortex: An MEG study using fMRI constraints

Previous evidence from functional magnetic resonance imaging (fMRI) has shown that a painful galvanic stimulation mainly activates a posterior sub-region in the secondary somatosensory cortex (SII), whereas a non-painful sensory stimulation mainly activates an anterior sub-region of SII [Ferretti, A., Babiloni, C., Del Gratta, C., Caulo, M., Tartaro, A., Bonomo, L., Rossini, P.M., Romani, G.L., 2003. Functional topography of the secondary somatosensory cortex for non-painful and painful stimuli: an fMRI study. Neuroimage 20 (3), 1625-1638.]. The present study, combining fMRI with magnetoencephalographic (MEG) findings, assessed the working hypothesis that the activity of such a posterior SII sub-region is characterized by an amplitude and temporal evolution in line with the bilateral functional organization of nociceptive systems. Somatosensory evoked magnetic fields (SEFs) recordings after alvanic median nerve stimulation were obtained from the same sample of subjects previously examined with fMRI [Ferretti, A., Babiloni, C., Del Gratta, C., Caulo, M., Tartaro, A., Bonomo, L., Rossini, P.M., Romani, G.L., 2003. Functional topography of the secondary somatosensory cortex for non-painful and painful stimuli: an fMRI study. Neuroimage 20 (3), 1625-1638.]. Constraints for dipole source localizations obtained from MEG recordings were applied according to fMRI activations, namely, at the posterior and the anterior SII sub-regions. It was shown that, after painful stimulation, the two posterior SII sub-regions of the contralateral and ipsilateral hemispheres were characterized by dipole sources with similar amplitudes and latencies. In contrast, the activity of anterior SII sub-regions showed statistically significant differences in amplitude and latency during both non-painful and painful stimulation conditions. In the contralateral hemisphere, the source activity was greater in amplitude and shorter in latency with respect to the ipsilateral. Finally, painful stimuli evoked a response from the posterior sub-regions peaking significantly earlier than from the anterior sub-regions. These results suggested that both ipsi and contra posterior SII sub-regions process painful stimuli in parallel, while the anterior SII sub-regions might play an integrative role in the processing of somatosensory stimuli.

Decrease of functional coupling between left and right auditory cortices during dichotic listening: An electroencephalography study

The present study focused on functional coupling between human bilateral auditory cortices and on possible influence of right over left auditory cortex during dichotic listening of complex non-verbal tones having near (competing) compared with distant non-competing fundamental frequencies. It was hypothesized that dichotic stimulation with competing tones would induce a decline of functional coupling between the two auditory cortices, as revealed by a decrease of electroencephalography coherence and an increase of directed transfer function from right (specialized for the present stimulus material) to left auditory cortex. Electroencephalograph was recorded from T3 and T4 scalp sites, overlying respectively left and right auditory cortices, and from Cz scalp site (vertex) for control purposes. Event-related coherence between T3 and T4 scalp sites was significantly lower for all electroencephalography bands of interest during dichotic listening of competing than non-competing tone pairs. This was a specific effect, since event-related coherence did not differ in a monotic control condition. Furthermore, event-related coherence between T3 and Cz and between T4 and Cz scalp sites showed no significant effects. Conversely, the directed transfer function results showed negligible influence at group level of right over left auditory cortex during dichotic listening. These results suggest a decrease of functional coupling between bilateral auditory cortices during competing dichotic stimuli as a possible neural substrate for the lateralization of auditory stimuli during dichotic listening.

Estimation of the cortical functional connectivity with the multimodal integration of high-resolution EEG and fMRI data by directed transfer function

Nowadays, several types of brain imaging device are available to provide images of the functional activity of the cerebral cortex based on hemodynamic, metabolic, or electromagnetic measurements. However, static images of brain regions activated during particular tasks do not convey the information of how these regions communicate with each other. In this study, advanced methods for the estimation of cortical connectivity from combined high-resolution electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data are presented. These methods include a subject's multicompartment head model (scalp, skull, dura mater, cortex) constructed from individual magnetic resonance images, multidipole source model, and regularized linear inverse source estimates of cortical current density. 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) fMRI. We estimate functional cortical connectivity by computing the directed transfer function (DTF) on the estimated cortical current density waveforms in regions of interest (ROIs) on the modeled cortical mantle. The proposed method was able to unveil the direction of the information flow between the cortical regions of interest, as it is directional in nature. Furthermore, this method allows to detect changes in the time course of information flow between cortical regions in different frequency bands. The reliability of these techniques was further demonstrated by elaboration of high-resolution EEG and fMRI signals collected during visually triggered finger movements in four healthy subjects. Connectivity patterns estimated for this task reveal an involvement of right parietal and bilateral premotor and prefrontal cortical areas. This cortical region involvement resembles that revealed in previous studies where visually triggered finger movements were analyzed with the use of separate EEG or fMRI measurements.

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.

Temporal dynamics of alpha and beta rhythms in human SI and SII after galvanic median nerve stimulation. A MEG study

In this MEG study, we investigated cortical alpha/sigma and beta ERD/ERS induced by median nerve stimulation to extend previous evidence on different resonant and oscillatory behavior of SI and SII (NeuroImage 13 [2001] 662). Here, we tested whether simple somatosensory stimulation could induce a distinctive sequence of alpha/sigma and beta ERD/ERS over SII compared to SI. We found that for both alpha/sigma (around 10 Hz) and beta (around 20 Hz) rhythms, the latencies of ERD and ERS were larger in bilateral SII than in contralateral SI. In addition, the peak amplitude of alpha/sigma and beta ERS was smaller in bilateral SII than in contralateral SI. These results indicate a delayed and prolonged activation of SII responses, reflecting a protracted information elaboration possibly related to SII higher order role in the processing of somatosensory information. This temporal dynamics of alpha/sigma and beta rhythms may be related to a sequential activation scheme of SI and SII during the somatosensory information processes. Future studies should evaluate in SII the possible different functional significance of alpha/sigma with respect to beta rhythms during somatosensory processing.

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.

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.