The introduction of BCI technology in assisting MI practice demonstrates the rehabilitative potential of MI, contributing to significantly better motor functional outcomes in subacute stroke patients with severe motor impairments.

In recent years, new research has brought the field of electroencephalogram (EEG)-based brain–computer interfacing (BCI) out of its infancy and into a phase of relative maturity through many demonstrated prototypes such as brain-controlled wheelchairs, keyboards, and computer games. With this proof-of-concept phase in the past, the time is now ripe to focus on the development of practical BCI technologies that can be brought out of the lab and into real-world applications. In particular, we focus on the prospect of improving the lives of countless disabled individuals through a combination of BCI technology with existing assistive technologies (AT). In pursuit of more practical BCIs for use outside of the lab, in this paper, we identify four application areas where disabled individuals could greatly benefit from advancements in BCI technology, namely, “Communication and Control”, “Motor Substitution”, “Entertainment”, and “Motor Recovery”. We review the current state of the art and possible future developments, while discussing the main research issues in these four areas. In particular, we expect the most progress in the development of technologies such as hybrid BCI architectures, user–machine adaptation algorithms, the exploitation of users’ mental states for BCI reliability and confidence measures, the incorporation of principles in human–computer interaction (HCI) to improve BCI usability, and the development of novel BCI technology including better EEG devices.

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Abstract:The aim of this work is to characterize quantitatively the performance of a body of techniques in the frequency domain for the estimation of cortical connectivity from high-resolution EEG recordings in different operative conditions commonly encountered in practice. Connectivity pattern estimators investigated are the Directed Transfer Function (DTF), its modification known as direct DTF (dDTF) and the Partial Directed Coherence (PDC). Predefined patterns of cortical connectivity were simulated and then retrieved by the application of the DTF, dDTF, and PDC methods. Signal-to-noise ratio (SNR) and length (LENGTH) of EEG epochs were studied as factors affecting the reconstruction of the imposed connectivity patterns. Reconstruction quality and error rate in estimated connectivity patterns were evaluated by means of some indexes of quality for the reconstructed connectivity pattern. The error functions were statistically analyzed with analysis of variance (ANOVA). The whole methodology was then applied to high-resolution EEG data recorded during the well-known Stroop paradigm. Simulations indicated that all three methods correctly estimated the simulated connectivity patterns under reasonable conditions. However, performance of the methods differed somewhat as a function of SNR and LENGTH factors. The methods were generally equivalent when applied to the Stroop data. In general, the amount of available EEG affected the accuracy of connectivity pattern estimations. Analysis of 27 s of nonconsecutive recordings with an SNR of 3 or more ensured that the connectivity pattern could be accurately recovered with an error below 7% for the PDC and 5% for the DTF. In conclusion, functional connectivity patterns of cortical activity can be effectively estimated under general conditions met in most EEG recordings by combining high-resolution EEG techniques, linear inverse estimation of the cortical activity, and frequency domain multivariate methods such as PDC, DTF, and dDTF. Hum Brain Mapp 28:143-157, 2007.

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In this study we were interested to analyse the brain activity occurring during the "naturalistic" observation of commercial ads intermingled in a random order within a documentary. In order to measure both the brain activity and the emotional engage of the 15 healthy subjects investigated, we used simultaneous EEG, Galvanic Skin Response (GSR), Heart Rate (HR) recordings during the whole experiment. We would like to link significant variation of EEG, GSR, HR and Heart Rate Variability (HRV) measurements with the memory and pleasantness of the stimuli presented, as resulted successively from the subject's verbal interview. In order to do that, different indexes were employed to summarize the cerebral and autonomic measurements performed. Such indexes were used in the statistical analysis, performed with the use of Analysis of Variance (ANOVA) and z-score transformation of the estimated cortical activity by solving the associated EEG inverse problem. The results are summarized as follows: (1) in the population analyzed, the cortical activity in the theta band elicited during the observation of the TV commercials that were remembered is higher and localized in the left frontal brain areas when compared to the activity elicited during the vision of the TV commercials that were forgotten (p< 0.048). Same increase in the theta activity occurred during the observation of commercials that were judgment pleasant when compared with the other (p < 0.042). Differences in cortical activity were also observed for the gamma activity, bilaterally in frontal and prefrontal areas. (2) the HR and HRV activity elicited during the observation of the TV commercials that were remembered or judged pleasant is higher than the same activity during the observation of commercials that will be forgotten (p < 0.001 and p < 0.048, respectively for HR and HRV) or were judged unpleasant (p < 0.042 and p < 0.04, respectively for HR and HRV). No statistical differences between the level of the GSR values were observed across the experimental conditions. In conclusion, the TV commercials proposed to the population analyzed have increased the HR values and the cerebral activity mainly in the theta band in the left hemisphere when they will be memorized and judged pleasant. Further research with an extended set of subjects will be necessary to further validate the observations reported in this paper. However, these conclusions seems reasonable and well inserted in the already existing literature on this topic related to the HERA model.

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The aim of this research is to analyze the changes in the EEG frontal activity during the observation of commercial videoclips. In particular, we aimed to investigate the existence of EEG frontal asymmetries in the distribution of the signals' power spectra related to experienced pleasantness of the video, as explicitly rated by the eleven experimental subjects investigated. In the analyzed population, maps of Power spectral density (PSD) showed an asymmetrical increase of theta and alpha activity related to the observation of pleasant (unpleasant) advertisements in the left (right) hemisphere. A correlation analysis revealed that the increase of PSD at left frontal sites is negatively correlated with the degree of pleasantness perceived. Conversely, the de-synchronization of left alpha frontal activity is positively correlated with judgments of high pleasantness. Moreover, our data presented an increase of PSD related to the observation of unpleasant commercials, which resulted higher with respect to the one elicited by pleasant advertisements.