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One of the most challenging questions open in Neuroscience today is the characterization of the brain responses during social interaction. A major limitation of the approaches used in most of the studies performed so far is that only one of the participating brains is measured each time. The "interaction" between cooperating, competing or communicating brains is thus not measured directly, but inferred by independent observations aggregated by cognitive models and assumptions that link behavior and neural activation. In this paper, we present the results of the simultaneous neuroelectric recording of 5 couples of subjects engaged in cooperative games (EEG hyperscanning). The simultaneous recordings of couples of interacting subjects allows to observe and model directly the neural signature of human interactions in order to understand the cerebral processes generating and generated by social cooperation or competition. We used a paradigm called Prisoner's dilemma derived from the game theory. Results collected in a population of 10 subjects suggested that the most consistently activated structure in social interaction paradigms is the orbitofrontal region (roughly described by the Brodmann area 10) during the condition of competition. more...

We investigated brain activity during the observation of TV commercials by tracking the cortical activity and the functional connectivity changes in normal subjects. The aim was to elucidate if the TV commercials that were remembered by the subjects several days after their first observation elicited particular brain activity and connectivity compared with those generated during the observation of TV commercials that were quickly forgotten. High-resolution electroencephalogram (EEG) recordings were performed in a group of healthy subjects and the cortical activity during the observation of TV commercials was evaluated in several regions of interest coincident with the Brodmann areas (BAs). The patterns of cortical connectivity were obtained in the four principal frequency bands, Theta (3-7 Hz), Alpha (8-12 Hz), Beta (13-30 Hz), Gamma (30-40 Hz) and the directed influences between any given pair of the estimated cortical signals were evaluated by use of a multivariate spectral technique known as partial directed coherence. The topology of the cortical networks has been identified with tools derived from graph theory. Results suggest that the cortical activity and connectivity elicited by the viewing of the TV commercials that were remembered by the experimental subjects are markedly different from the brain activity elicited during the observation of the TV commercials that were forgotten. In particular, during the observation of the TV commercials that were remembered, the amount of cortical spectral activity from the frontal areas (BA 8 and 9) and from the parietal areas (BA 5, 7, and 40) is higher compared with the activity elicited by the observation of TV commercials that were forgotten. In addition, network analysis suggests a clear role of the parietal areas as a target of the incoming flow of information from all the other parts of the cortex during the observation of TV commercials that have been remembered. The techniques presented here shed new light on all the cortical networks and their behavior during the memorization of TV commercials. Such techniques could also be relevant in neuroeconomics and neuromarketing for the investigation of the neural substrates subserving other decision-making and recognition tasks. more...

In the present study, we estimated the cortical networks were from high-resolution EEG recordings in a group of spinal cord injured patients and in a group of healthy subjects, during the preparation of a limb movement. Then, we use the Markov Clustering method to analyse the division of the network into community structures. The results indicate large differences between the injured patients and the healthy subjects. In particular, the networks of spinal cord injured patient exhibited a higher density of clusters. In the Alpha (7-12 Hz) frequency band, the two observed largest communities were mainly composed by the cingulate motor areas with the supplementary motor areas, and by the pre-motor areas with the right primary motor area of the foot. This functional separation could reflect the partial alteration in the primary motor areas because of the effects of the spinal cord injury. more...

The present work intends to evaluate the functional characteristics of the cerebral network during the successful memory encoding of TV commercials. We estimated the functional networks in the frequency domain from a set of high-resolution EEG data. High resolution EEG recordings were performed in a group of healthy subjects and the cortical activity during the observation of TV commercials was evaluated in several regions of interest coincident with the Brodmann areas (BAs). Summarizing the main results of the present study, a sign of the memorization of a particular set of TV commercials have been found in a group of investigated subjects with the aid of advanced modern tools for the acquisition and the processing of EEG data. The cerebral processes involved during the observation of TV commercials that were remembered successively by the population examined (RMB dataset) are generated by the posterior parietal cortices and the prefrontal areas, rather bilaterally and are irrespective of the frequency bands analyzed. Such results are compatible with previously results obtained from EEG recordings with superficial electrodes as well as with the brain activations observed with the use of MEG and fMRI devices. more...

In this study we estimated time-varying cortical connectivity patterns from a group of Spinal Cord Injured (SCI) patients during the attempt to move a paralyzed limb. This data were compared with the time-varying connectivity patterns estimated in a control group during the effective execution of the movement. Connectivity was estimated from high resolution EEG recordings with the use of realistic head modelling and the linear inverse estimation of the cortical activity. Time-varying PDC was obtained by the adaptive recursive fit of an MVAR model with time-dependent parameters, by means of a generalized recursive least-square (RLS) algorithm, taking into consideration a set of EEG epochs. Such estimator is able to follow rapid changes in the connectivity between cortical areas during an experimental task. The obtained experimental evidences support the conclusion that the SCI population involved a larger cortical network than those generated by the healthy subjects during the task performance. Such network differs for the involvement of the parietal cortices, which increases in strength near to the EMG onset. more...

In the present work, we estimated the functional networks in the frequency domain from a set of high-resolution EEG data in a group of healthy subjects during the showing of commercial spots within a neutral documentary. Then, we evaluated the differences in the cortical network associated with later remembered and not-remembered commercials by calculating the global- E(g) and local-efficiency E(l) indexes. During the visualization of the video-clips that will be forgotten (FRG), the cortical network exhibited high values of global- and local-efficiency, reflecting a small-world configuration. During the visualization of the video-clips that will be remembered (RMB), the same indexes appeared significantly lower. Such a difference seems not depending on the spectral content of the cortical activity. This result shows how the network communication efficiency would be affected by the presence of attentional and semantic processes that are behind a successful memory encoding in a lifelike situation. more...

In this paper we propose the use of an adaptive multivariate approach to define time-varying multivariate estimators based on the Directed Transfer Function (DTF) and the Partial Directed Coherence (PDC). DTF and PDC are frequency-domain estimators that are able to describe interactions between cortical areas in terms of the concept of Granger causality. Time-varying DTF and PDC were obtained by the adaptive recursive fit of an MVAR model with time-dependent parameters, by means of a generalized recursive least-square (RLS) algorithm, taking into consideration a set of EEG epochs. Such estimators are able to follow rapid changes in the connectivity between cortical areas during an experimental task. We provide an application to the cortical estimations obtained from high resolution EEG data, recorded from a group of healthy subject during a combined foot-lips movement, and present the time-varying connectivity patterns resulting from the application of both DTF and PDC. Two different cortical networks were detected, one constant across the task and the other evolving during the preparation of the joint movement. more...

In this work, a novel approach is proposed in order to capture relevant features related to the structure and organization of the functional brain networks estimated in the time-frequency domain. To achieve this, we used a cascade of computational tools able to estimate first the electrical activity of the cortical surface by using high resolution EEG techniques. Then, on the cortical signals from different regions of interests we estimated the time-varying functional connectivity patterns by means of the adaptive Partial Directed Coherence. Such time-varying connectivity estimation returns a series of causality patterns evolving during the examined task which can be summarized and interpreted with the aid of mathematical indexes based on the graph theory. The combination of all these methods is demonstrated on a set of high resolution EEG data recorded from a healthy subject performing a simple foot movement. more...

The aim of this paper is to test a technique called partial directed coherence (PDC) and its modification (squared PDC; sPDC) for the estimation of human cortical connectivity by means of simulation study, in which both PDC and sPDC were studied by analysis of variance. The statistical analysis performed returned that both PDC and sPDC are able to estimate correctly the imposed connectivity patterns when data exhibit a signal-to-noise ratio of at least 3 and a length of at least 27 s of nonconsecutive recordings at 250 Hz of sampling rate, equivalent, more generally, to 6750 data samples. more...

The Directed Transfer Function (DTF) and the Partial Directed Coherence (PDC) are frequency-domain estimators, based on the multivariate autoregressive modelling (MVAR) of time series, that are able to describe interactions between cortical areas in terms of the concept of Granger causality. However, the classical estimation of these methods requires the stationary of the signals. In this way, transient pathways of information transfer remains hidden. The objective of this study is to test a time-varying multivariate method for the estimation of rapidly changing connectivity relationships between cortical areas of the human brain, based on DTF/PDC and on the use of adaptive MVAR modelling (AMVAR). This approach will allow the observation of transient influences between the cortical areas during the execution of a task. Time-varying DTF and PDC were obtained by the adaptive recursive fit of an MVAR model with time-dependent parameters, by means of a generalized recursive least-square (RLS) algorithm, taking into consideration a set of EEG epochs. Simulations were performed under different levels of Signal to Noise Ratio (SNR), number of trials (TRIALS) and frequency bands (BAND), and of different values of the RLS adaptation factor adopted (factor C). The results indicated that time-varying DTF and PDC are able to estimate correctly the imposed connectivity patterns under reasonable operative conditions of SNR ad number of trials. Moreover, the capability of follow the rapid changes in connectivity is highly increased by the number of trials at disposal, and by the right choice of the value adopted for the adaptation factor C. The results of the simulation study indicate that DTF and PDC computed on adaptive MVAR can be effectively used to estimate time-varying patterns of functional connectivity between cortical activations, under general conditions met in practical EEG recordings. more...

Objective: We investigated the effect of bilateral subthalamic nucleus (STN) and internal globus pallidus (GPi) deep brain stimulation (DBS) on intracortical inhibition (ICI) in patients with advanced Parkinson's disease (PD)., Methods: The activity of intracortical inhibitory circuits was studied in 4 PD patients implanted with stimulating electrodes both in STN and GPi by means of paired-pulse transcranial magnetic stimulation, delivered in a conditioning-test design at short (1-6 ms) interstimulus intervals (ISI). The effect of apomorphine on the same PD patients was also investigated., Results: We observed that implanted PD patients showed a significant increase in ICI during either bilateral STN or GPi DBS at 3 ms ISI, and during bilateral STN DBS at 2 ms ISI in comparison to their off DBS condition. The same statistical improvement was observed during apomorphine infusion at 3 and 2 ms ISI. In each condition, the electrophysiological changes were associated with a significant clinical improvement as measured by the Unified Parkinson's Disease Rating Scale motor examination., Conclusions: These results are consistent with the hypothesis that basal ganglia DBS can mimic the effects of pharmacological dopaminergic therapy on PD patients cortical activity. We propose that in PD patients, the basal ganglia DBS-induced improvement of ICI may be related to a recovery in modulation of thalamo-cortical motor pathway. more...

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. more...

GP 47779, the active metabolite of oxcarbazepine (OCBZ) inhibits glutamatergic excitatory postsynaptic potentials (EPSPs) in rat striatum (described in the accompanying article). This effect was presumed to involve the modulation of the calcium (Ca2+) signals at either pre- or postsynaptic level. Therefore, we directly tested whether GP 47779 could modulate Ca2+ conductances in cortical as well as in striatal neurons. GP 47779 produced a reversible dose-dependent decrease in high-voltage-activated (HVA) Ca2+ currents evoked by membrane depolarization in isolated cortical pyramidal cells. GP 47779-mediated reduction in HVA Ca2+ currents, if occurring also at corticostriatal axon terminals, might explain the reduction of glutamate release in the striatum. An inhibitory action of GP 47779 on HVA Ca2+ currents was also observed in isolated striatal neurons. The effect of HVA Ca2+ currents in cortical and striatal neurons persisted in the presence of nifedipine, suggesting that dihydropyridine-sensitive channels were not involved in the GP 47779-mediated responses. We propose that the modulation of HVA Ca2+ channels by this carbamazepine (CBZ) analogue may account for its inhibitory action on transmitter release. more...

The action of glycine (Gly) intravenously injected on rat epileptic foci induced by strychnine or penicillin topically applied, was compared with that of GABA. Gly (450 mg/kg i.v.) produced a complete block of the spiking activity. The inhibitory action of GABA (80 mg/kg), in terms of threshold and duration, was stronger than the action of Gly. The same inhibitory effect was also observed if these amino acids were applied topically or intracisternally. These results are consistent with the possibility that Gly has a role in the rat cortical inhibition. more...

In the present study we analyze whether glycine satisfies some electrophysiological and biochemical criteria to consider it as a putative transmitter in the rat cerebral cortex. Intracellular recordings from rat sensory-motor cortex showed that in 15-20% of the tested neurons glycine hyperpolarized the cell membrane, decreased the firing rate and flattened the evoked EPSP-IPSP sequence by increasing the membrane conductance. The iontophoretic application of strychnine antagonized the block of 'spontaneous' firing and the membrane hyperpolarization induced by glycine. Moreover, in a group of neurons, strychnine decreased the amplitude and duration of the IPSP and brought back the membrane potential to resting values. Previously accumulated [3H]glycine and endogenous glycine were released from cortical synaptosomal preparations by depolarizing stimuli in a Ca2+-dependent way. The release pattern of glycine was qualitatively similar in cortical and in spinal synaptosomes. [14C]Glycine was rapidly synthetized from [14C]serine in cortical synaptosomal preparations, and the newly formed [14C]glycine was released by depolarizing stimuli in a Ca2+-dependent way. It is concluded that glycine, which is generally considered as an inhibitory neurotransmitter in the spinal cord, medulla and pons, may also have a transmitter role in a discrete number of cortical neurons of some mammalian species.U more...

The action of glycine (Gly) on rat cortical neurons was studied. Gly, iontophoretically applied, hyperpolarized the membrane potential, blocked the firing rate and decreased the amplitude of EPSP-IPSP sequences. Generally the membrane resistance during the aminoacid ejection decreased. The role of Gly in the rat cortical inhibition is discussed. more...

The actions of GABA and glycine (Gly), iontophoretically applied to rat cortical neurons, were compared. These amino acids hyperpolarized the membrane cell, decreasing the membrane resistance. The results show that the ionic mechanisms involved in the inhibitory actions of GABA and Gly are probably the same in contrast with the results obtained in cat cortical neurons. more...

In this paper, different linear and nonlinear methodologies for the estimation of cortical connectivity from neuroelectric and hemodynamic measurements are reviewed and applied on common data set in order to highlight similarities and differences in the results. Different effective and functional connectivity methods were applied to motor and cognitive data sets, including structural equation modeling (SEM), directed transfer function (DTF), partial directed coherence (PDC), and direct directed transfer function (dDTF). Comparisons were made between the results in order to understand if, for a same dataset, effective and functional connectivity estimators can return the same cortical connectivity patterns. An application of a nonlinear method [phase synchronization index (PSI)] to similar executed and imagined movements was also reviewed. Connectivity patterns estimated with the use of the neuroelectric information and of the information from the multimodal integration of neuroelectric and hemodynamic data were also compared. Results suggests that the estimation of the cortical connectivity patterns performed with the linear methods (SEM, DTF, PDC, dDTF) or with the nonlinear method (PSI) on movement related potentials returned similar cortical networks. Differences in cortical connectivity were noted between the patterns estimated with the use of multimodal integration and those estimated by using only the neuroelectric data. [ABSTRACT FROM AUTHOR] more...

Abstract-The extraction of the salient characteristics from brain connectivity patterns is an open challenging topic since often the estimated cerebral networks have a relative large size and complex structure. Since a graph is a mathematical representation of a network, which is essentially reduced to nodes and connections between them, the use of a theoretical graph approach would extract significant information from the functional brain networks estimated through different neuroimaging techniques. The present work intends to support the development of the "brain network analysis:" a mathematical tool consisting in a body of indexes based on the graph theory able to improve the comprehension of the complex interactions within the brain. In the present work, we applied for demonstrative purpose some graph indexes to the time-varying networks estimated from a set of high-resolution EEG data in a group of healthy subjects during the performance of a motor task. The comparison with a random benchmark allowed extracting the significant properties of the estimated networks in the representative Alpha (7-12 Hz) band. Altogether, our findings aim at proving how the brain network analysis could reveal important information about the time-frequency dynamics of the functional cortical networks. [ABSTRACT FROM AUTHOR] more...