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Available from: Heidi Elyse Kirsch
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    • "The number of time points during which the amplitude was greater in the left hemisphere compared with the right hemisphere and vice versa was calculated. Data between 250–750 ms were used in order to focus on high-order processing (Burgess et al., 2011). LIs were calculated using the following formula: LI = (Left − Right)/(Left + Right). "
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    ABSTRACT: Objective: The aim of this study was to develop a presurgical magnetoencephalography (MEG) protocol to localize and lateralize expressive and receptive language function as well as verbal memory in patients with epilepsy. Two simple language tasks and a different analytical procedure were developed. Methods: Ten healthy participants and 13 epileptic patients completed two language tasks during MEG recording: a verbal memory task and a verbal fluency task. As a first step, principal component analyses (PCA) were performed on source data from the group of healthy participants to identify spatiotemporal factors that were relevant to these paradigms. Averaged source data were used to localize areas activated during each task and a laterality index (LI) was computed on an individual basis for both groups, healthy participants and patients, using sensor data. Results: PCA revealed activation in the left temporal lobe (300ms) during the verbal memory task, and from the frontal lobe (210ms) to the temporal lobe (500ms) during the verbal fluency task in healthy participants. Averaged source data showed activity in the left hemisphere (250-750ms), in Wernicke's area, for all participants. Left hemisphere dominance was demonstrated better using the verbal memory task than the verbal fluency task (F1,19=4.41, p=0.049). Cohen's kappa statistic revealed 93% agreement (k=0.67, p=0.002) between LIs obtained from MEG sensor data and fMRI, the IAT, electrical cortical stimulation or handedness with the verbal memory task for all participants. At 74%, agreement results for the verbal fluency task did not reach statistical significance. Significance: Analysis procedures yielded interesting findings with both tasks and localized language-related activation. However, based on source localization and laterality indices, the verbal memory task yielded better results in the context of the presurgical evaluation of epileptic patients. The verbal fluency task did not add any further information to the verbal memory task as regards language localization and lateralization for most patients and healthy participants that would facilitate decision making prior to surgery.
    Full-text · Article · Jan 2016 · Epilepsy Research
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    • "The recording time can even be decreased to 1 minute, as was reported in a CKC study in which precisely timed passive movements were generated with a movement actuator based on pneumatic artificial muscle (PAM) (Piitulainen et al., 2015). These results show that CKC is a fast and reliable tool to locate the SM1 cortex, worth considering as an addition to somatosensory evoked fields (SEFs) (Bourguignon et al., 2011, 2013), which, so far, constitute the 'gold standard' in MEG mapping of the SM1 cortex (Burgess et al., 2011; Hari and Forss, 1999; Korvenoja et al., 2006; Mäkelä et al., 2001). Besides allowing to locate the SM1 cortex, CKC provides a unique tool to quantify proprioceptive afference to the cortex (Bourguignon et al., 2015; Piitulainen et al., 2013b) with a potential for multiple clinical applications. "
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    ABSTRACT: Corticokinematic coherence (CKC) is the coupling between magnetoencephalographic (MEG) signals and limb kinematics during fast movements. Our objective was to assess the robustness of CKC-based identification of the primary sensorimotor (SM1) cortex of subjects producing strong magnetic artifacts when the MEG signals were cleaned with temporal signal space separation (tSSS). We recorded MEG during active and passive forefinger movements and during median-nerve stimulation in the following conditions: (1) artifact-free, (2) a magnetic wire attached to the scalp at C3 location, and (3) a magnetic wire attached behind the lower central incisors. Data were pre-processed with tSSS and analyzed using standard CKC methods, somatosensory evoked fields (SEFs), and dipole modeling. Artifacts were effectively suppressed by tSSS, enabling successful identification of the SM1 cortex in all subjects based on CKC and SEFs. The sources were in artifact conditions ∼5mm away from the sources identified in artifact-free conditions. tSSS suppressed artifacts strongly enough to enable reliable identification of the SM1 cortex on the basis of CKC mapping, with localization accuracy comparable to SEF-based mapping. The results suggest that CKC can be used for SM1 cortex identification and for studies of proprioception even in patients implanted with magnetic material. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
    Full-text · Article · Aug 2015 · Clinical neurophysiology: official journal of the International Federation of Clinical Neurophysiology
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    • "All methods used in the analysis of spontaneous MEG–EEG and of magnetic evoked fields should be clearly stated in this part of the report. Currently accepted methods of analysis of spontaneous MEG–EEG activity are detailed in ACMEGS Guideline 1, 2011, " Recording and Analysis of Spontaneous Cerebral Activity " (Bagi c, Knowlton, Rose, and Ebersole, 2011), and accepted methods for evoked magnetic field analysis can be found in ACMEGS Guideline 2, 2011, " Presurgical Functional Brain Mapping Using Magnetic Evoked Fields " (Burgess et al, 2011). "

    Full-text · Dataset · Oct 2013
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