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Empirical validation of directed functional connectivity
[article]
2016
bioRxiv
pre-print
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., 2007; Cole, Bagic, Kass & Schneider, 2010; Supp et al., 2007) , these reports did not seek to address antecedent questions as to the base validity of applying directional methods to brain imaging data ...
doi:10.1101/070979
fatcat:2pxqvzyyjzfklg6zsqxlj57jtu
First population study of the general public awareness and perception of epilepsy in Croatia
2009
Epilepsy & Behavior
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Bagić et al. / Epilepsy & Behavior 15 (2009) 170-178 ...
doi:10.1016/j.yebeh.2009.02.044
pmid:19258048
fatcat:ms5wsi6t6vgc3e7eu4bd55ssn4
Empirical validation of directed functional connectivity
2017
NeuroImage
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., 2007; Cole, Bagic, Kass & Schneider, 2010; Supp et al., 2007) , these reports did not seek to address antecedent questions as to the base validity of applying directional methods to brain imaging data ...
doi:10.1016/j.neuroimage.2016.11.037
pmid:27856312
pmcid:PMC5321749
fatcat:l56jxk6g5fesbb4cczzzw7b3au
Disentanglement of Resting State Brain Networks for Localizing Epileptogenic Zone in Focal Epilepsy
[article]
2022
bioRxiv
pre-print
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AbstractResting state electromagnetic recordings have been analyzed in epilepsy patients aiding presurgical evaluation. However, it has been rarely explored how pathological networks can be separated and thus used for epileptogenic focus localization purpose. We proposed here a resting state EEG/MEG analysis framework, to disentangle brain functional networks represented by electrophysiological oscillations. Firstly, by using an Embedded Hidden Markov Model (EHMM), we constructed a state space
doi:10.1101/2022.06.13.495945
fatcat:sa75lskecrezveda7vmq6hzszm
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... or resting state recordings consisting of brain states with different spatiotemporal patterns. After that, functional connectivity analysis along with graph theory were applied on the extracted brain states to quantify the network features of the extracted brain states, and we determine the source location of pathological states based on these features. The EHMM model was rigorously evaluated using computer simulations. Our simulation results revealed the proposed framework can extract brain states with high accuracy regarding both spatial and temporal profiles. We than validated the entire framework as compared with clinical ground truth in 10 patients with drug-resistant focal epilepsy who underwent MEG recordings. We segmented the resting state MEG recordings into a few brain states with diverse connectivity patterns and extracted pathological brain states by applying graph theory on the constructed functional networks. We showed reasonable localization results using the extracted pathological brain states in 6/10 patients, as compared to the invasive clinical findings. The framework can serve as an objective tool in extracting brain functional networks from noninvasive resting state electromagnetic recordings. It promises to aid presurgical evaluation guiding intracranial EEG electrodes implantation.
Imaging the Extent and Location of Spatiotemporally Distributed Epileptiform Sources from MEG Measurements
[article]
2021
bioRxiv
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., , 2020;; Bagic and Burgess, 2020) . ...
doi:10.1101/2021.11.09.467915
fatcat:vgd6fbw3jze5teylkvlg7sulyu
Turning a New Page in Clinical Magnetoencephalography
2011
Journal of clinical neurophysiology
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American Clinical Magnetoencephalography Society Clinical Practice Guideline 1
2011
Journal of clinical neurophysiology
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T he following are considered "minimum standards" for the routine clinical recording and analysis of spontaneous magnetoencephalography (MEG) and EEG in all age-groups. Practicing at minimum standards should not be the goal of an MEG center but rather a starting level for continued improvement. Minimum standards meet only the most basic responsibilities of the patient and the referring physician. These minimum standards have been put forth to improve standardization of procedures and to
doi:10.1097/wnp.0b013e3182272fed
pmid:21811121
fatcat:ozsvniokgzbshn2ikfizq44xui
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... te interchange of recordings and reports among laboratories (centers) in the United States. Epilepsy is currently the only approved clinical indication for recordings of spontaneous cerebral activity.
American Clinical Magnetoencephalography Society Clinical Practice Guideline 3
2011
Journal of clinical neurophysiology
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Interictal SEEG resting-state connectivity localizes seizure onset zone and predicts seizure outcome
[article]
2022
medRxiv
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Stereotactic-electroencephalography (SEEG) is a common neurosurgical method to localize epileptogenic zone in drug resistant epilepsy patients and inform treatment recommendations. In the current clinical practice, localization of epileptogenic zone typically requires prolonged recordings to capture seizure, which may take days to weeks. Although epilepsy surgery has been proven to be effective in general, the percentage of unsatisfactory seizure outcomes is still concerning. We developed a
doi:10.1101/2021.12.30.21268524
fatcat:ssom3q2kkjccrggmj6dblwfdq4
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... od to identify the seizure onset zone (SOZ) and predict seizure outcome using short-time resting-state SEEG data. In a cohort of 43 drug resistant epilepsy patients, we estimated the information flow via directional connectivity and inferred the excitation-inhibition ratio from the 1/f power slope. We hypothesized that the antagonism of information flow at multiple frequencies between SOZ and non-SOZ underlying the relatively stable epilepsy resting state could be related to the disrupted excitation-inhibition balance. We found higher excitability in non-SOZ regions compared to the SOZ, with dominant information flow from non-SOZ to SOZ regions, probably reflecting inhibitory input from non-SOZ to prevent seizure initiation. Greater differences in information flow between SOZ and non-SOZ regions were associated with favorable seizure outcome. By integrating a balanced random forest model with resting-state connectivity, our method localized the SOZ with an accuracy of 85% and predicted the seizure outcome with an accuracy of 77% using clinically determined SOZ. Overall, our study suggests that brief resting-state SEEG data can significantly facilitate the identification of SOZ and may eventually predict seizure outcomes without requiring long-term ictal recordings.
American Clinical Magnetoencephalography Society Clinical Practice Guideline 4
2011
Journal of clinical neurophysiology
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for the ACMEGS Clinical Practice Guideline Committee** (J Clin Neurophysiol 2011;0: 1-2) T his Clinical Practice Guideline pertains to currently approved, reimbursable, clinical indications for magnetoencephalography (MEG), namely, localization of epileptic foci in surgical candidates with medically refractory epilepsy and functional mapping of eloquent cortices in preparation for surgery of various operable lesions. As new applications are clinically validated and established, the guidelines
doi:10.1097/wno.0b013e3181cde4dc
pmid:21811124
fatcat:y7gtsap5gvgy7cns5c3rkr72fe
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... ll be revised as needed. QUALIFICATIONS OF MEG-EEG PERSONNEL Minimal Qualifications for Physicians Interpreting Clinical Magnetoencephalography and MEG-EEG Studies During the pioneering days of clinical MEG, many highly competent professionals of different background propelled the field, advanced clinically with it through different experiences, and currently interpret clinical MEGs within the team while not individually meeting the requirements listed below. A new phase of clinical MEG requires uniform educational standards proposed for individuals entering the clinical MEG field after 2010. A doctoral-level professional interpreting clinical MEG and/or MEG-EEG studies should be a physician preferably with board eligibility or certification in neurology, pediatric neurology, or neurosurgery. Physicians from other specialties need to obtain additional exposure to clinical neurophysiology equivalent to the requirements for board certification in this subspecialty (see point 2). All physicians interpreting clinical MEG and MEG-EEG studies need to acquire expertise specifically in MEG through additional supervised training (see point 3) and have an appropriate license for the practice of medicine. 2. Additional background training of physicians interpreting clinical MEG and MEG-EEG studies should meet the minimal requirements for examination by the American Board of Clinical Neurophysiology (www.abcn.org) or the American Board of Psychiatry and Neurology Added Qualifications in Clinical Neurophysiology (www.abpn.com). 3. Specific MEG training should also include supervised learning of and practice in clinical MEG recording, reviewing, and source analysis of clinical MEG for at least 6 months and the independent interpretation and reporting of at least 50 MEG studies of epilepsy and 25 MEG studies of evoked fields (auditory, visual, somatosensory, motor, and language). The majority of epilepsy studies should be abnormal and include a mixture of clinical findings. Minimal Qualifications of Magnetoneurodiagnostic Technologists 1. The background qualifications of magnetoneurodiagnostic technologists shall preferably be those set forth for electroneurodiagnostic technologists by the American Clinical Neurophysiology Society and allied organizations. Registries in electroencephalographic or evoked potential technology (REEGT and REPT), administered by the American Board of Registration of Electroneurodiagnostic Technologists (www.abret.org), are preferred for MEG technologists. Technologists of related disciplines need to acquire additional exposure to and training in clinical neurophysiology. 2. At least 6 months of supervised clinical experience in an active MEG center, following formal training, is suggested to record MEG-EEG in an unsupervised capacity. 3. A minimum of 3 of the 6 months should include additional supervised training in the principles of MEG technology, technical aspects of MEG systems with competency in operational routines, including helium filling, tuning procedures (as applicable), standard testing procedures, trouble shooting, artifact prevention and elimination, data storage, and sufficient understanding of source localization to preprocess routine clinical data for the analysis by a physician magnetoencephalographer.
Practical Fundamentals of Clinical MEG Interpretation in Epilepsy
2021
Frontiers in Neurology
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Magnetoencephalography (MEG) is a neurophysiologic test that offers a functional localization of epileptic sources in patients considered for epilepsy surgery. The understanding of clinical MEG concepts, and the interpretation of these clinical studies, are very involving processes that demand both clinical and procedural expertise. One of the major obstacles in acquiring necessary proficiency is the scarcity of fundamental clinical literature. To fill this knowledge gap, this review aims to
doi:10.3389/fneur.2021.722986
pmid:34721261
pmcid:PMC8551575
fatcat:spahs375lrbbvpyjp6o4agfake
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... lain the basic practical concepts of clinical MEG relevant to epilepsy with an emphasis on single equivalent dipole (sECD), which is one the most clinically validated and ubiquitously used source localization method, and illustrate and explain the regional topology and source dynamics relevant for clinical interpretation of MEG-EEG.
American Clinical Magnetoencephalography Society Clinical Practice Guideline 3
2011
Journal of clinical neurophysiology
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Accessing and Processing MEG Signals in Real-Time: Emerging Applications and Enabling Technologies
[chapter]
2011
Magnetoencephalography
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et al. 2011; Bagic et al. 2009; Burgess, Funke, et al. 2011; Stefan et al. 2011) . ...
For clinicians who regularly spend many hours analyzing complex epilepsy cases (Bagic et al. 2011; Burgess, Funke, et al. 2011) , having a software package that can process data online and provide at ...
doi:10.5772/27356
fatcat:pa5rkuozrvfttaddpcxhl4gb7q
American Clinical Magnetoencephalography Society Clinical Practice Guideline 2
2011
Journal of clinical neurophysiology
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Spike detection: Inter-reader agreement and a statistical Turing test on a large data set
2017
Clinical Neurophysiology
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Anto Bagic had no potential conflicts of interest to disclose. ...
doi:10.1016/j.clinph.2016.11.005
pmid:27913148
fatcat:pfwmz3vnvnfgvc4vwx56377pmi
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