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Methods based on the multivariate autoregressive (MVAR) approach are commonly used for effective connectivity estimation as they allow to include all available sources into a unique model. To ensure high levels of accuracy for high model dimensions, all the observations are used to provide a unique estimation of the model, and thus of the network and its properties. The unavailability of a distribution...
One of the main limitations commonly encountered when dealing with the estimation of brain connectivity is the difficulty to perform a statistical assessment of significant changes in brain networks at a single-subject level. This is mainly due to the lack of information about the distribution of the connectivity estimators at different conditions. While group analysis is commonly adopted to perform...
In BCI applications for stroke rehabilitation, BCI systems are used with the aim of providing patients with an instrument that is capable of monitoring and reinforcing EEG patterns generated by motor imagery (MI). In this study we proposed an offline analysis on data acquired from stroke patients subjected to a BCI-assisted MI training in order to define an index for the evaluation of MI-BCI training...
Recent studies have investigated changes in the human brain network organization during the normal aging. A reduction of the connectivity between brain areas was demonstrated by combining neuroimaging technologies and graph theory. Clustering, characteristic path length and small-worldness are key topological measures and they are widely used in literature. In this paper we propose a new methodology...
Partial Directed Coherence (PDC) is a spectral multivariate estimator for effective connectivity, relying on the concept of Granger causality. Even if its original definition derived directly from information theory, two modifies were introduced in order to provide better physiological interpretations of the estimated networks: i) normalization of the estimator according to rows, ii) squared transformation...
Memory processes are based on large cortical networks characterized by non-stationary properties and time scales which represent a limitation to the traditional connectivity estimation methods. The recent development of connectivity approaches able to consistently describe the temporal evolution of large dimension connectivity networks, in a fully multivariate way, represents a tool that can be used...
Graph theory is a powerful mathematical tool recently introduced in neuroscience field for quantitatively describing the main properties of investigated connectivity networks. Despite the technical advancements provided in the last few years, further investigations are needed for overcoming actual limitations in the field. In fact, the absence of a common procedure currently applied for the extraction...
The “Default Mode Network” concept was defined, in fMRI field, as a consistent pattern, involving some regions of the brain, which is active during resting state activity and deactivates during attention demanding or goal-directed tasks. Several fMRI studies described its features also correlating the deactivations with the attentive load required for the task execution. Despite the efforts in EEG...
One of the main limitations of the brain functional connectivity estimation methods based on Autoregressive Modeling, like the Granger Causality family of estimators, is the hypothesis that only stationary signals can be included in the estimation process. This hypothesis precludes the analysis of transients which often contain important information about the neural processes of interest. On the other...
Controlling an aircraft during a flight is a compelling condition, which requires a strict and well coded interaction between the crew. The interaction level between the Captain and the First Officer changes during the flight, ranging from a maximum (during takeoff and landing, as well as in case of a failure of the instrumentation or other emergency situations) to a minimum during quiet mid-flight...
Episodes of complete failure to respond during attentive tasks — lapses of responsiveness (‘lapses’) — accompanied by behavioral signs of sleep such as slow-eye-closure are known as behavioral microsleeps (BMs). The occurrence of BMs can have serious/fatal consequences, particularly in the transport sectors, and therefore further investigations on neurophysiological correlates of BMs are highly desirable...
Partial Directed Coherence (PDC) is a powerful tool to estimate a frequency domain description of Granger causality between multivariate time series. One of the main limitation of this estimator, however, has been so far the criteria used to assess the statistical significance, which have been obtained through surrogate data approach or arbitrarily imposed thresholds. The aim of this work is to test...
Brain Hyperscanning, i.e. the simultaneous recording of the cerebral activity of different human subjects involved in interaction tasks, is a very recent field of Neuroscience aiming at understanding the cerebral processes generating and generated by social interactions. This approach allows the observation and modeling of the neural signature specifically dependent on the interaction between subjects,...
In this paper we show how the possibility of recording simultaneously the cerebral neuroelectric activity in different subjects (EEG hyperscanning) during the execution of different tasks can return useful information about the “internal” cerebral state of the subjects. We present the results obtained by EEG hyperscannings during ecological task (such as the execution of a card game) as well as those...
This paper presents some considerations about the use of adequate statistical techniques in the framework of the neuroelectromagnetic brain mapping. With the use of advanced EEG/MEG recording setup involving hundred of sensors, the issue of the protection against the type I errors that could occur during the execution of hundred of univariate statistical tests, has gained interest. In the present...
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