Estimation of cortical activity from noninvasive high-resolution EEG recordings

2004 ◽  
Vol 1270 ◽  
pp. 245-248 ◽  
Author(s):  
Donatella Mattia ◽  
Marco Mattiocco ◽  
Alessandro Timperi ◽  
Serenella Salinari ◽  
Maria Grazia Marciani ◽  
...  
2010 ◽  
Vol 24 (2) ◽  
pp. 83-90 ◽  
Author(s):  
Laura Astolfi ◽  
Febo Cincotti ◽  
Donatella Mattia ◽  
Fabrizio De Vico Fallani ◽  
Giovanni Vecchiato ◽  
...  

Objective: In this paper, we propose a body of techniques for the estimation of rapidly changing connectivity relationships between EEG signals estimated in cortical areas, based on the use of adaptive multivariate autoregressive modeling (AMVAR) for the estimation of a time-varying partial directed coherence (PDC). This approach allows the observation of rapidly changing influences between the cortical areas during the execution of a task, and does not require the stationarity of the signals. Methods: High resolution EEG data were recorded from a group of spinal cord injured (SCI) patients during the attempt to move a paralyzed limb. These data were compared with the time-varying connectivity patterns estimated in a control group during the real execution of the movement. Connectivity was estimated with the use of realistic head modeling and the linear inverse estimation of the cortical activity in a series of regions of interest by using time-varying PDC. Results: The SCI population involved a different cortical network than those generated by the healthy subjects during the task performance. Such a network differs for the involvement of the parietal cortices, which increases in strength near to the movement imagination onset for the SCI when compared to the normal population. Conclusions: The application of time-varying PDC allows tracking the evolution of the connectivity between cortical areas in the analyzed populations during the proposed tasks. Such details about the temporal evolution of the connectivity patterns estimated cannot be obtained with the application of the standard estimators of connectivity.


2007 ◽  
Vol 19 (3) ◽  
pp. 125-136 ◽  
Author(s):  
Fabrizio De Vico Fallani ◽  
Laura Astolfi ◽  
Febo Cincotti ◽  
Donatella Mattia ◽  
Andrea Tocci ◽  
...  

Neuroreport ◽  
1996 ◽  
Vol 8 (1) ◽  
pp. 203-206 ◽  
Author(s):  
Antonio Urbano ◽  
C Babiloni ◽  
P Onorati ◽  
F Babiloni

2007 ◽  
Vol 28 (2) ◽  
pp. 143-157 ◽  
Author(s):  
Laura Astolfi ◽  
Febo Cincotti ◽  
Donatella Mattia ◽  
M. Grazia Marciani ◽  
Luiz A. Baccala ◽  
...  

2010 ◽  
Vol 2010 ◽  
pp. 1-7 ◽  
Author(s):  
Giovanni Vecchiato ◽  
Laura Astolfi ◽  
Alessandro Tabarrini ◽  
Serenella Salinari ◽  
Donatella Mattia ◽  
...  

The use of modern brain imaging techniques could be useful to understand what brain areas are involved in the observation of video clips related to commercial advertising, as well as for the support of political campaigns, and also the areas of Public Service Announcements (PSAs). In this paper we describe the capability of tracking brain activity during the observation of commercials, political spots, and PSAs with advanced high-resolution EEG statistical techniques in time and frequency domains in a group of normal subjects. We analyzed the statistically significant cortical spectral power activity in different frequency bands during the observation of a commercial video clip related to the use of a beer in a group of 13 normal subjects. In addition, a TV speech of the Prime Minister of Italy was analyzed in two groups of swing and “supporter” voters. Results suggested that the cortical activity during the observation of commercial spots could vary consistently across the spot. This fact suggest the possibility to remove the parts of the spot that are not particularly attractive by using those cerebral indexes. The cortical activity during the observation of the political speech indicated a major cortical activity in the supporters group when compared to the swing voters. In this case, it is possible to conclude that the communication proposed has failed to raise attention or interest on swing voters. In conclusions, high-resolution EEG statistical techniques have been proved to able to generate useful insights about the particular fruition of TV messages, related to both commercial as well as political fields.


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