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Five-dimensional neuroimaging: localization of the time-frequency dynamics of cortical activity.

ABSTRACT: The spatiotemporal dynamics of cortical oscillations across human brain regions remain poorly understood because of a lack of adequately validated methods for reconstructing such activity from noninvasive electrophysiological data. In this paper, we present a novel adaptive spatial filtering algorithm optimized for robust source time-frequency reconstruction from magnetoencephalography (MEG) and electroencephalography (EEG) data. The efficacy of the method is demonstrated with simulated sources and is also applied to real MEG data from a self-paced finger movement task. The algorithm reliably reveals modulations both in the beta band (12-30 Hz) and high gamma band (65-90 Hz) in sensorimotor cortex. The performance is validated by both across-subjects statistical comparisons and by intracranial electrocorticography (ECoG) data from two epilepsy patients. Interestingly, we also reliably observed high frequency activity (30-300 Hz) in the cerebellum, although with variable locations and frequencies across subjects. The proposed algorithm is highly parallelizable and runs efficiently on modern high-performance computing clusters. This method enables the ultimate promise of MEG and EEG for five-dimensional imaging of space, time, and frequency activity in the brain and renders it applicable for widespread studies of human cortical dynamics during cognition.

SUBMITTER: Dalal SS

PROVIDER: S-EPMC2426929 | biostudies-literature | 2008 May

REPOSITORIES: biostudies-literature

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Five-dimensional neuroimaging: localization of the time-frequency dynamics of cortical activity.

Dalal Sarang S SS Guggisberg Adrian G AG Edwards Erik E Sekihara Kensuke K Findlay Anne M AM Canolty Ryan T RT Berger Mitchel S MS Knight Robert T RT Barbaro Nicholas M NM Kirsch Heidi E HE Nagarajan Srikantan S SS

NeuroImage 20080131 4

The spatiotemporal dynamics of cortical oscillations across human brain regions remain poorly understood because of a lack of adequately validated methods for reconstructing such activity from noninvasive electrophysiological data. In this paper, we present a novel adaptive spatial filtering algorithm optimized for robust source time-frequency reconstruction from magnetoencephalography (MEG) and electroencephalography (EEG) data. The efficacy of the method is demonstrated with simulated sources ...[more]

PMID: 18356081

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Project description:Accurate localization of the epileptogenic zone (EZ) is a key factor to obtain good surgical outcome for refractory epilepsy patients. However, no technique, so far, can precisely locate the EZ, and there are barely any reports on the combined application of multiple technologies to improve the localization accuracy of the EZ. In this study, we aimed to explore the use of a multimodal method combining PET-MRI, fluid and white matter suppression (FLAWS)-a novel MRI sequence, and high-frequency oscillation (HFO) automated analysis to delineate EZ. We retrospectively collected 15 patients with refractory epilepsy who underwent surgery and used the above three methods to detect abnormal brain areas of all patients. We compared the PET-MRI, FLAWS, and HFO results with traditional methods to evaluate their diagnostic value. The sensitivities, specificities of locating the EZ, and marking extent removed versus not removed [RatioChann(ev)] of each method were compared with surgical outcome. We also tested the possibility of using different combinations to locate the EZ. The marked areas in every patient established using each method were also compared to determine the correlations among the three methods. The results showed that PET-MRI, FLAWS, and HFOs can provide more information about potential epileptic areas than traditional methods. When detecting the EZs, the sensitivities of PET-MRI, FLAWS, and HFOs were 68.75, 53.85, and 87.50%, and the specificities were 80.00, 33.33, and 100.00%. The RatioChann(ev) of HFO-marked contacts was significantly higher in patients with good outcome than those with poor outcome (p< 0.05). When intracranial electrodes covered all the abnormal areas indicated by neuroimaging with the overlapping EZs being completely removed referred to HFO analysis, patients could reach seizure-free (p < 0.01). The periphery of the lesion marked by neuroimaging may be epileptic, but not every lesion contributes to seizures. Therefore, approaches in multimodality can detect EZ more accurately, and HFO analysis may help in defining real epileptic areas that may be missed in the neuroimaging results. The implantation of intracranial electrodes guided by non-invasive PET-MRI and FLAWS findings as well as HFO analysis would be an optimized multimodal approach for locating EZ.

Dataset Information

Five-dimensional neuroimaging: localization of the time-frequency dynamics of cortical activity.

Publications

Five-dimensional neuroimaging: localization of the time-frequency dynamics of cortical activity.

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