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L Astolfi,
F Cincotti,
D Mattia,
C Babiloni,
F Carducci,
A Basilisco,
P M Rossini,
S Salinari,
L Ding, Y Ni,
B He,
F Babiloni
[show abstract]
[hide abstract]
ABSTRACT: 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.
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.
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.
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.
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.
Clinical Neurophysiology 05/2005; 116(4):920-32. · 3.41 Impact Factor
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F Babiloni,
F Cincotti,
C Babiloni,
F Carducci,
D Mattia,
L Astolfi,
A Basilisco,
P M Rossini,
L Ding, Y Ni,
J Cheng,
K Christine,
J Sweeney,
B He
[show abstract]
[hide abstract]
ABSTRACT: 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.
NeuroImage 02/2005; 24(1):118-31. · 5.89 Impact Factor
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L. Astolfi,
F. Babiloni,
C. Babiloni,
F. Carducci,
F. Cincotti,
A. Basilisco,
P.M. Rossini,
S. Salinari,
L. Ding, Y. Ni,
B. He
[show abstract]
[hide abstract]
ABSTRACT: 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.
Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE; 10/2004
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L Astolfi,
F Babiloni,
C Babiloni,
F Carducci,
F Cincotti,
A Basilisco,
P M Rossini,
S Salinari, Y Ni,
B He,
L Ding
[show abstract]
[hide abstract]
ABSTRACT: 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.
Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 02/2004; 6:4405-8.
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[show abstract]
[hide abstract]
ABSTRACT: The present study aims to identify the anatomic substrate locations of neural generators behind self-paced fast repetitive finger movement, by dipole analysis and cortical current density imaging from scalp-recorded movement-related potentials. Both methods demonstrated that the contralateral premotor cortex was preponderantly activated in relation to movement performance. The present results therefore suggest that premotor cortex is involved in the precise control of sequential timed movement based on the motor field (MF) of the movement related potentials. In addition, the cortical current density imaging results demonstrate increased activity in ipsilateral premotor cortex as well.
Neural Engineering, 2003. Conference Proceedings. First International IEEE EMBS Conference on; 04/2003
