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001-es BibID:BIBFORM030124
035-os BibID:(Scopus)83555179190 (WoS)000299761400005 (PMID)21925841
Első szerző:Bessenyei Mónika (neurológus, csecsemő- és gyermekgyógyász)
Cím:EEG background activity is abnormal in the temporal and inferior parietal cortex in benign rolandic epilepsy of childhood : a LORETA study / M. Besenyei, E. Varga, I. Fekete, Sz. Puskás, K. Hollódy, A. Fogarasi, M. Emri, G. Opposits, S. A. Kis, B. Clemens
Dátum:2012
ISSN:0920-1211
Megjegyzések:Benign rolandic epilepsy of childhood (BERS) is an epilepsy syndrome with presumably genetic-developmental etiology. The pathological basis of this syndrome is completely unknown. We postulated that a developmental abnormality presumably results in abnormal EEG background activity findings. PATIENTS AND METHODS: 20 children with typical BERS and an age- and sex-matched group of healthy control children underwent EEG recording and analysis. 60x2 s epochs of waking EEG background activity (without epileptiform potentials and artifacts) were analyzed in the 1-25 Hz frequency range, in very narrow bands (VNB, 1 Hz bandwidth). LORETA (Low Resolution Electromagnetic Tomography) localized multiple distributed sources of EEG background activity in the Talairach space. LORETA activity (current source density) was computed for 2394 voxels and 25 VNBs. Normalized LORETA data were processed to voxel-wise comparison between the BERS and control groups. Bonferroni-corrected p<0.05 Student's t-values were accepted as statistically significant. RESULTS: Increased LORETA activity was found in the BERS group (as compared to the controls) in the left and right temporal lobes (fusiform gyri, posterior parts of the superior, middle and inferior temporal gyri) and in the angular gyri in the parietal lobes, in the 4-6 Hz VNBs, mainly at 5 Hz. DISCUSSION: (1) Areas of abnormal LORETA activity exactly correspond to the temporal and parietal cortical areas that are major components of the Mirsky attention model and also the perisylvian speech network. Thus the LORETA findings may correspond to impaired attention and speech in BERS patients. (2) The LORETA findings may contribute to delineating the epileptic network in BERS. SIGNIFICANCE: The novel findings may contribute to investigating neuropsychological disturbances and organization of the epileptic network in BERS.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
egyetemen (Magyarországon) készült közlemény
Megjelenés:Epilepsy Research. - 98 : 1 (2012), p. 44-49. -
További szerzők:Varga Edit (Kenézy Kórház) Fekete István (1951-) (neurológus, pszichiáter) Puskás Szilvia (1979-) (neurológus) Hollódy Katalin (1955-) (csecsemő- és gyermekgyógyász) Fogarasi András Emri Miklós (1962-) (fizikus) Opposits Gábor (1974-) (fizikus, szoftver fejlesztő) Kis Sándor Attila (1973-) (fizikus) Clemens Béla (1950-) (neurológus)
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DOI
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2.

001-es BibID:BIBFORM056215
Első szerző:Clemens Béla (neurológus)
Cím:Valproate treatment normalizes EEG functional connectivity in successfully treated idiopathic generalized epilepsy patients / B. Clemens, S. Puskás, M. Besenyei, N. Zs. Kovács, T. Spisák, S. A. Kis, M. Emri, K. Hollody, A. Fogarasi, I. Kondákor, I. Fekete
Dátum:2014
Megjegyzések:To investigate the effect of chronic VPA treatment of EEG functional connectivity in successfully treated idiopathic generalized epilepsy (IGE) patients. PATIENTS AND METHODS: 19-channel waking, resting-state EEG records of 26 IGE patients were analyzed before treatment (IGE) and after the 90th day of treatment (VPA), in seizure-free condition. Three minutes of artifact-free EEG background activity (without epileptiform potentials) was analyzed for each patient in both conditions. A group of 26 age-matched healthy normative control persons (NC) was analyzed in the same way. All the EEG samples were processed to LORETA (Low Resolution Electromagnetic Tomography) to localize multiple distributed sources of EEG activity. Current source density time series were generated for 33 regions of interest (ROI) in each hemisphere for four frequency bands. Pearson correlation coefficients (R) were computed between all ROIs in each hemisphere, for four bands across the investigated samples. R values corresponded to intrahemispheric, cortico-cortical functional EEG connectivity (EEGfC). Group and condition differences were analyzed by statistical parametric network method. MAIN RESULTS: p<0.05, corrected for multiple comparisons: (1) The untreated IGE group showed increased EEGfC in the delta and theta bands, and decreased EEGfC in the alpha band (as compared to the NC group); (2) VPA treatment normalized EEGfC in the delta, theta and alpha bands; and (3) degree of normalization depended on frequency band and cortical region. CONCLUSIONS: VPA treatment normalizes EEGfC in IGE patients.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Megjelenés:Epilepsy Research. - 108 : 10 (2014), p. 1896-1903. -
További szerzők:Puskás Szilvia (1979-) (neurológus) Bessenyei Mónika (1970-) (neurológus, csecsemő- és gyermekgyógyász) Kovács N. Zs. Spisák Tamás (1986-) (programtervező matematikus, informatikus) Kis Sándor Attila (1973-) (fizikus) Emri Miklós (1962-) (fizikus) Hollódy Katalin (1955-) (csecsemő- és gyermekgyógyász) Fogarasi András Kondákor István (1950-) (neurológus) Fekete István (1951-) (neurológus, pszichiáter)
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DOI
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3.

001-es BibID:BIBFORM030126
Első szerző:Clemens Béla (neurológus)
Cím:EEG-LORETA endophenotypes of the common idiopathic generalized epilepsy syndromes / B. Clemens, Sz. Puskás, M. Besenyei, M. Emri, G. Opposits, S. A. Kis, K. Hollódy, A. Fogarasi, I. Kondákór, K. Füle, K. Bense, I. Fekete
Dátum:2012
Megjegyzések:We tested the hypothesis that the cortical areas with abnormal local EEG synchronization are dissimilar in the three common idiopathic generalized epilepsy (IGE) phenotypes: IGE patients with absence seizures (ABS), juvenile myoclonic epilepsy (JME) and epilepsy with generalized tonic-clonic seizures exclusively (EGTCS). PATIENTS AND METHODS: Groups of unmedicated ABS, JME and EGTCS patients were investigated. Waking EEG background activity (without any epileptiform potentials) was analyzed by a source localization method, LORETA (Low Resolution Electromagnetic Tomography). Each patient group was compared to a separate, age-matched group of healthy control persons. Voxel-based, normalized broad-band (delta, theta, alpha, and beta) and very narrow band (VNB, 1Hz bandwidth, from 1 to 25Hz) LORETA activity (=current source density, A/m(2)) were computed for each person. Group comparison included subtraction (average patient data minus average control data) and group statistics (multiple t-tests, where Bonferroni-corrected p<0.05 values were accepted as statistically significant). RESULTS: Statistically not significant main findings were: overall increased delta and theta broad band activity in the ABS and JME groups; decrease of alpha and beta activity in the EGTCS group. Statistically significant main findings were as follows. JME group: bilaterally increased theta activity in posterior (temporal, parietal, and occipital) cortical areas; bilaterally increased activity in the medial and basal prefrontal area in the 8Hz VNB; bilaterally decreased activity in the precuneus, posterior cingulate and superior parietal lobule in the 11Hz and 21-22Hz VNBs. ABS group: bilaterally increased theta activity emerged in the basal prefrontal and medial temporal limbic areas. Decreased activity was found at 19-21Hz in the right postcentral gyrus and parts of the right superior and medial temporal gyri. EGTCS group: decreased activity was found in the frontal cortex and the postcentral gyrus at 10-11Hz, increased activity in the right parahippocampal gyrus at 16-18Hz. DISCUSSION: Increased theta activity in the posterior parts of the cortex is the endophenotype for JME. Increased theta activity in the fronto-temporal limbic areas is the endophenotype for ABS. Statistically not significant findings might indicate diffuse biochemical abnormality of the cortex in JME and ABS.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Megjelenés:Epilepsy Research. - 99 : 3 (2012), p. 281-292. -
További szerzők:Puskás Szilvia (1979-) (neurológus) Bessenyei Mónika (1970-) (neurológus, csecsemő- és gyermekgyógyász) Emri Miklós (1962-) (fizikus) Opposits Gábor (1974-) (fizikus, szoftver fejlesztő) Kis Sándor Attila (1973-) (fizikus) Hollódy Katalin (1955-) (csecsemő- és gyermekgyógyász) Fogarasi András Kondákor István (1950-) (neurológus) Füle K. Bense Katalin Fekete István (1951-) (neurológus, pszichiáter)
Internet cím:Intézményi repozitóriumban (DEA) tárolt változat
DOI
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4.

001-es BibID:BIBFORM046012
Első szerző:Spisák Tamás (programtervező matematikus, informatikus)
Cím:BrainCON : graph theory based multimodal brain connectivity analysis and visualization software / Spisák Tamás, Opposits Gábor, Kis Sándor Attila, Pohubi László, Jakab András, Puskás Szilvia, Clemens Béla, Emri Miklós
Dátum:2013
Megjegyzések:PURPOSE Graph theory based structural and functional brain connectivity analysis is a novel method providingnew insights into the dynamics and complexity of the brain by modeling it's regional interactions [1].Due to the heterogeneity and dynamic development of the applied mathematical models and analysistechniques the software support of this field is still poorly accomplished [2].Our purpose was to develop a user friendly software system dedicated for the analysis andvisualization of multimodal brain connectivity data based on EEG, fMRI and DTI data.METHODSReconstruction of brain networks is modality dependent and can be performed with various state-of-the-art software tools, eg. BrainMOD (www.minipetct.com/brainmod) [3], Matlab and R for fMRI, FSL or DTI and NeuroGuide for EEG-LORETA data. With the aid of the BrainNET Utils software package, these software tools can be easily fitted into a processing pipeline and the resulting connectivity matrices can be loaded into BrainCON. Reconstructed brain networks can be displayed and thresholded interactively. Cost based adaptive techniques, soft-thresholding and cost-integration [5] method was implemented to solve the problem of thresholding and allow population based comparisons. Various methods are present for global (small worldness, efficiency, clustering coefficient, characteristic path length, etc.), modular (community detection) and nodal (strength, efficiency, betweenness centrality, hub scores) analysis of binary and weighted graphs in both individual and population level [4]. Interpreting the results is aided by real-time 2D and 3D "glass brain" visualization techniques and various plots. The software system was implemented mainly in C++ and partly in R.RESULTS AND CONCLUSIONThe software encapsulates state-of-the-art mathematical graph analysis methods and enhanced real-time network visualization techniques and provides a new user friendly tool in the field of brain connectivity research. The program is built upon the MultiModal Medical Imaging (M3I) software library system (www.minipetct.com/m3i) and runs on Windows 7 and Windows Xp operation systems and various Linux distributions (www.minipetct.com/braincon). The hardware requirements of the application match the current average PC configurations used in medical image analysis.
Tárgyszavak:Orvostudományok Klinikai orvostudományok előadáskivonat
software
medical imaging
brain connectivity
graph theory
complex network
Megjelenés:Electronic presentation online system : ECR Congress 2013 / [ed. ESR]. - p. C-2588.
További szerzők:Opposits Gábor (1974-) (fizikus, szoftver fejlesztő) Kis Sándor Attila (1973-) (fizikus) Pohubi László (1959-) (fizikus) Jakab András (1953-) Puskás Szilvia (1979-) (neurológus) Clemens Béla (1950-) (neurológus) Emri Miklós (1962-) (fizikus)
Pályázati támogatás:TÁMOP-4.2.2.C-11/1/KONV-2012-0001
TÁMOP
TÁMOP-4.2.2/B-10/1-2010-0024
TÁMOP
Internet cím:DOI
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