{"id":191,"date":"2020-09-10T20:32:25","date_gmt":"2020-09-10T18:32:25","guid":{"rendered":"http:\/\/www.hbimed.com\/wp-enfold-aug2020\/?page_id=191"},"modified":"2020-09-10T20:32:25","modified_gmt":"2020-09-10T18:32:25","slug":"forschung","status":"publish","type":"page","link":"https:\/\/hbimed.com\/?page_id=191","title":{"rendered":"Forschung"},"content":{"rendered":"<div id='av_section_1'  class='avia-section av-1m486-c4ba37123efc5011fae03206ec432ee7 main_color avia-section-default avia-no-border-styling  avia-builder-el-0  el_before_av_section  avia-builder-el-first  avia-bg-style-scroll container_wrap sidebar_right'  ><div class='container av-section-cont-open' ><main  role=\"main\" itemprop=\"mainContentOfPage\"  class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-191'><div class='entry-content-wrapper clearfix'>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-15y6f-39312c453ec97aabad9ecafe7ad5e6d4\">\n#top .av-special-heading.av-15y6f-39312c453ec97aabad9ecafe7ad5e6d4{\npadding-bottom:10px;\n}\nbody .av-special-heading.av-15y6f-39312c453ec97aabad9ecafe7ad5e6d4 .av-special-heading-tag .heading-char{\nfont-size:25px;\n}\n.av-special-heading.av-15y6f-39312c453ec97aabad9ecafe7ad5e6d4 .av-subheading{\nfont-size:15px;\n}\n<\/style>\n<div  class='av-special-heading av-15y6f-39312c453ec97aabad9ecafe7ad5e6d4 av-special-heading-h1 blockquote modern-quote  avia-builder-el-1  el_before_av_one_half  avia-builder-el-first '><h1 class='av-special-heading-tag '  itemprop=\"headline\"  >Forschung<\/h1><div class=\"special-heading-border\"><div class=\"special-heading-inner-border\"><\/div><\/div><\/div>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-s82i-5e70d99c8233c51b6166d65407b030cd\">\n.flex_column.av-s82i-5e70d99c8233c51b6166d65407b030cd{\nborder-radius:0px 0px 0px 0px;\npadding:0px 0px 0px 0px;\n}\n<\/style>\n<div  class='flex_column av-s82i-5e70d99c8233c51b6166d65407b030cd av_one_half  avia-builder-el-2  el_after_av_heading  el_before_av_one_half  first flex_column_div av-zero-column-padding  '     ><section  class='av_textblock_section av-kdoek3vo-272befba42fc51414855ade34c25da1f '   itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div class='avia_textblock'  itemprop=\"text\" ><h2>Artikel<\/h2>\n<\/div><\/section><br \/>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-kex5kljy-40686d73d7d9a4f8362914a9905570cf\">\n#top .togglecontainer.av-kex5kljy-40686d73d7d9a4f8362914a9905570cf p.toggler{\nborder-color:#96c11f;\n}\n#top .togglecontainer.av-kex5kljy-40686d73d7d9a4f8362914a9905570cf .toggle_wrap .toggle_content{\nborder-color:#96c11f;\n}\n<\/style>\n<div  class='togglecontainer av-kex5kljy-40686d73d7d9a4f8362914a9905570cf av-minimal-toggle  avia-builder-el-4  el_after_av_textblock  avia-builder-el-last  toggle_close_all' >\n<section class='av_toggle_section av-nrb1j-8fed4d9cbbd34df673f2121156b34491'  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div role=\"tablist\" class=\"single_toggle\" data-tags=\"{Alle} \"  ><p id='toggle-toggle-id-1' data-fake-id='#toggle-id-1' class='toggler  av-title-above av-inherit-border-color'  itemprop=\"headline\"  role='tab' tabindex='0' aria-controls='toggle-id-1' data-slide-speed=\"200\" data-title=\"Abkl\u00e4rung des ADHS - Durch Biomarker zu personalisierter Medizin\" data-title-open=\"\" data-aria_collapsed=\"Click to expand: Abkl\u00e4rung des ADHS - Durch Biomarker zu personalisierter Medizin\" data-aria_expanded=\"Click to collapse: Abkl\u00e4rung des ADHS - Durch Biomarker zu personalisierter Medizin\">Abkl\u00e4rung des ADHS - Durch Biomarker zu personalisierter Medizin<span class=\"toggle_icon\"><span class=\"vert_icon\"><\/span><span class=\"hor_icon\"><\/span><\/span><\/p><div id='toggle-id-1' aria-labelledby='toggle-toggle-id-1' role='region' class='toggle_wrap  av-title-above'  ><div class='toggle_content invers-color av-inherit-border-color'  itemprop=\"text\" ><p><em>M\u00fcller, Andreas; Candrian, Gian<\/em><br \/>\n<strong>Abkl\u00e4rung des ADHS &#8211; Durch Biomarker zu personalisierter Medizin<\/strong><\/p>\n<p>IN|FO|Neurologie &amp; Psychatrie; VOL. 10, Nr. 3, 2012.<\/p>\n<p>Das Problem bei der Diagnose ADHS ist vorwiegend durch das Fehlen von Objektivit\u00e4t definiert. Das Beiziehen von Biomarkern und das Verstehen derselben unter dem Aspekt von Handeln, Denken und F\u00fchlen und auf dem Hintergrund des Lebensfeldes und der Lebensgeschichte l\u00f6st das Problem weitgehend. Elektrophysiologische Biomarker (Quantitative Analyse des EEGs und ereigniskorrelierte Potentiale) eignen sich ausgezeichnet f\u00fcr das Verstehen der neuronalen Dynamik, f\u00fcr die Diagnosestellung und zuer Festlegung der Intervention im Sinne der personalisierte Medizin. Untersuchungen bekegen eine Hohe Validit\u00e4t der ereigniskorrelierten Potenziale.<\/p>\n<\/div><\/div><\/div><\/section>\n<section class='av_toggle_section av-gl3in-8e9784e2d62ffbb8a2eb320dc8ad9692'  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div role=\"tablist\" class=\"single_toggle\" data-tags=\"{Alle} \"  ><p id='toggle-toggle-id-2' data-fake-id='#toggle-id-2' class='toggler  av-title-above av-inherit-border-color'  itemprop=\"headline\"  role='tab' tabindex='0' aria-controls='toggle-id-2' data-slide-speed=\"200\" data-title=\"The QEEG theta\/beta ratio in ADHD and normal controls: Sensitivity, specificity, and behavioral correlates \" data-title-open=\"\" data-aria_collapsed=\"Click to expand: The QEEG theta\/beta ratio in ADHD and normal controls: Sensitivity, specificity, and behavioral correlates \" data-aria_expanded=\"Click to collapse: The QEEG theta\/beta ratio in ADHD and normal controls: Sensitivity, specificity, and behavioral correlates \">The QEEG theta\/beta ratio in ADHD and normal controls: Sensitivity, specificity, and behavioral correlates <span class=\"toggle_icon\"><span class=\"vert_icon\"><\/span><span class=\"hor_icon\"><\/span><\/span><\/p><div id='toggle-id-2' aria-labelledby='toggle-toggle-id-2' role='region' class='toggle_wrap  av-title-above'  ><div class='toggle_content invers-color av-inherit-border-color'  itemprop=\"text\" ><p><em>Ogrim, Geir; Kropotov, Juri D; Hestad, Knut<\/em><br \/>\n<strong>The QEEG theta\/beta ratio in ADHD and normal controls: Sensitivity, specificity, and behavioral correlates<\/strong><\/p>\n<p>Psychiatry Research, 2012.<\/p>\n<p>The purpose of the present study was to determine if the theta\/beta ratio, and theta and beta separately, correlate with behavioral parameters, and if these measures discriminate between children and adolescents with ADHD and normal gender- and age-matched controls. Sixty-two patients and 39 controls participated in the study. A continuous performance test (CPT), a GO\/NOGO test and two rating scales were used to measure behavior in the patient group. EEG spectra were analyzed in eyes-closed and eyes-opened conditions, and in a GO\/NOGO task in both groups. Neither the theta\/beta ratio at CZ, nor theta and beta separately discriminated significantly between patients and controls. When each person was compared with the database significant elevations of theta were found in 25.8% of the patients and in only one control subject (2.6%). In the ADHD group, theta at CZ was positively correlated with inattention and executive problems and negatively correlated with hyperactivity\/impulsivity. Beta correlated with good attention level in the control group, but with ADHD symptoms in the patients. Omission errors in the GO\/NOGO test discriminated between patients and controls with an accuracy of 85%. For theta at CZ, the accuracy was 62%. Significantly elevated theta characterized a subgroup of ADHD and correlated with inattention and executive problems.<\/p>\n<\/div><\/div><\/div><\/section>\n<section class='av_toggle_section av-zr6n-172c56512c2bbf06ebee60957c80e0f5'  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div role=\"tablist\" class=\"single_toggle\" data-tags=\"{Alle} \"  ><p id='toggle-toggle-id-3' data-fake-id='#toggle-id-3' class='toggler  av-title-above av-inherit-border-color'  itemprop=\"headline\"  role='tab' tabindex='0' aria-controls='toggle-id-3' data-slide-speed=\"200\" data-title=\"Discriminating between ADHD adults and controls using independent ERP components and a support vector machine: a validation study\" data-title-open=\"\" data-aria_collapsed=\"Click to expand: Discriminating between ADHD adults and controls using independent ERP components and a support vector machine: a validation study\" data-aria_expanded=\"Click to collapse: Discriminating between ADHD adults and controls using independent ERP components and a support vector machine: a validation study\">Discriminating between ADHD adults and controls using independent ERP components and a support vector machine: a validation study<span class=\"toggle_icon\"><span class=\"vert_icon\"><\/span><span class=\"hor_icon\"><\/span><\/span><\/p><div id='toggle-id-3' aria-labelledby='toggle-toggle-id-3' role='region' class='toggle_wrap  av-title-above'  ><div class='toggle_content invers-color av-inherit-border-color'  itemprop=\"text\" ><p><em>M\u00fcller, Andreas; Candrian, Gian; Grane, Venke Arntsberg; Kropotov, Juri D; Ponomarev, Valery A; Baschera, Gian-Marco<\/em><br \/>\n<strong>Discriminating between ADHD adults and controls using independent ERP components and a support vector machine: a validation study<\/strong><\/p>\n<p>Nonlinear Biomedical Physics, 5:5, 2011.<\/p>\n<p><strong>Background:<\/strong><br \/>\nThere are numerous event-related potential (ERP) studies in relation to attention-deficit hyperactivity disorder (ADHD), and a substantial number of ERP correlates of the disorder have been identified. However, most of the studies are limited to group differences in children. Independent component analysis (ICA) separates a set of mixed event-related potentials into a corresponding set of statistically independent source signals, which are likely to represent different functional processes. Using a support vector machine (SVM), a classification method originating from machine learning, this study aimed at investigating the use of such independent ERP components in differentiating adult ADHD patients from non-clinical controls by selecting a most informative feature set. A second aim was to validate the predictive power of the SVM classifier by means of an independent ADHD sample recruited at a different laboratory.<\/p>\n<p><strong>Methods:<\/strong><br \/>\nTwo groups of age-matched adults (75 ADHD, 75 controls) performed a visual two stimulus go\/no-go task. ERP responses were decomposed into independent components, and a selected set of independent ERP component features was used for SVM classification.<\/p>\n<p><strong>Results:<\/strong><br \/>\nUsing a 10-fold cross-validation approach, classification accuracy was 91%. Predictive power of the SVM classifier was verified on the basis of the independent ADHD sample (17 ADHD patients), resulting in a classification accuracy of 94%. The latency and amplitude measures which in combination differentiated best between ADHD patients and non-clinical subjects primarily originated from independent components associated with inhibitory and other executive operations.<\/p>\n<p><strong>Conclusions:<br \/>\n<\/strong>This study shows that ERPs can substantially contribute to the diagnosis of ADHD when combined with up-to-date methods.<\/p>\n<\/div><\/div><\/div><\/section>\n<section class='av_toggle_section av-fkguf-9d48716a1bc33293d64b837be2f1d4be'  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div role=\"tablist\" class=\"single_toggle\" data-tags=\"{Alle} \"  ><p id='toggle-toggle-id-4' data-fake-id='#toggle-id-4' class='toggler  av-title-above av-inherit-border-color'  itemprop=\"headline\"  role='tab' tabindex='0' aria-controls='toggle-id-4' data-slide-speed=\"200\" data-title=\"Analysis of EEG characteristic at early stages of depression using method of independent components\" data-title-open=\"\" data-aria_collapsed=\"Click to expand: Analysis of EEG characteristic at early stages of depression using method of independent components\" data-aria_expanded=\"Click to collapse: Analysis of EEG characteristic at early stages of depression using method of independent components\">Analysis of EEG characteristic at early stages of depression using method of independent components<span class=\"toggle_icon\"><span class=\"vert_icon\"><\/span><span class=\"hor_icon\"><\/span><\/span><\/p><div id='toggle-id-4' aria-labelledby='toggle-toggle-id-4' role='region' class='toggle_wrap  av-title-above'  ><div class='toggle_content invers-color av-inherit-border-color'  itemprop=\"text\" ><p><em>Grin&#8216;-Iatsenko, VA; Baas, Ineke; Ponomarev, Valery A; Kropotov, Juri D<\/em><br \/>\n<strong>Analysis of EEG characteristic at early stages of depression using method of independent components<\/strong><\/p>\n<p>Fiziol Cheloveka. Jan-Feb;37(1):45-55, 2011.<\/p>\n<p>Independent Component Analysis (ICA) was used for 19-channel resting EEG analysis 111 patients at early stages of depressive disorder and 526 age-matched healthy subjects. Comparison of independent components power spectra in depressed patients and healthy subjects in two states: Eyes closed and Eyes open, has revealed significant differences between groups for three frequency bands: Theta (4-7.5 Hz), Alpha (7.5-14 Hz), and Beta (14-20 Hz). Increased power of alpha and theta activity in depressed patients at parietal and occipital sites may be caused by decreased cortical activation of these regions. Diffuse enhancement of beta activity level can correlate with anxiety symptoms which take an important place in clinical picture of depressive disorder at early stages. Using of ICA method for comparison of spectral characteristics of EEG in groups of patients with different brain pathology and healthy subjects gives a possibility to localize more precisely the discovered differences as compare to traditional analysis of EEG spectra.<\/p>\n<\/div><\/div><\/div><\/section>\n<section class='av_toggle_section av-p3p3-0af4162a63a13b67699c90efa181d3ad'  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div role=\"tablist\" class=\"single_toggle\" data-tags=\"{Alle} \"  ><p id='toggle-toggle-id-5' data-fake-id='#toggle-id-5' class='toggler  av-title-above av-inherit-border-color'  itemprop=\"headline\"  role='tab' tabindex='0' aria-controls='toggle-id-5' data-slide-speed=\"200\" data-title=\"Dissociating action inhibition, conflict monitoring and sensory mismatch into independent components of event related potentials in GO\/NOGO task\" data-title-open=\"\" data-aria_collapsed=\"Click to expand: Dissociating action inhibition, conflict monitoring and sensory mismatch into independent components of event related potentials in GO\/NOGO task\" data-aria_expanded=\"Click to collapse: Dissociating action inhibition, conflict monitoring and sensory mismatch into independent components of event related potentials in GO\/NOGO task\">Dissociating action inhibition, conflict monitoring and sensory mismatch into independent components of event related potentials in GO\/NOGO task<span class=\"toggle_icon\"><span class=\"vert_icon\"><\/span><span class=\"hor_icon\"><\/span><\/span><\/p><div id='toggle-id-5' aria-labelledby='toggle-toggle-id-5' role='region' class='toggle_wrap  av-title-above'  ><div class='toggle_content invers-color av-inherit-border-color'  itemprop=\"text\" ><p><em>Kropotov, Juri D; Ponomarev, Valery A; Hollup, Stig; M\u00fcller, Andreas<\/em><br \/>\n<strong>Dissociating action inhibition, conflict monitoring and sensory mismatch into independent components of event related potentials in GO\/NOGO task<\/strong><\/p>\n<p>NeuroImage 57, 565\u2013575, 2011.<\/p>\n<p>The anterior N2 and P3 waves of event related potentials (ERPs) in the GO\/NOGO paradigm in trials related to preparatory set violations in previous studies were inconsistently associated either with action inhibition or conflict monitoring operations. In the present study a paired stimulus GO\/NOGO design was used in order to experimentally control the preparatory sets. Three variants of the same stimulus task manipulated sensory mismatch, action inhibition and conflict monitoring operations by varying stimulus-response associations. The anterior N2 and P3 waves were decomposed into components by means of independent component analysis (ICA). The ICA was performed on collection of 114 individual ERPs in the three experimental conditions. Three of the independent components were selectively affected by the task manipulations indicating association of these components with sensory mismatch, action inhibition and conflict monitoring operations. According to sLORETA the sensory mismatch component was generated in the left and right temporal areas, the action suppression component was generated in the supplementary motor cortex, and the conflict monitoring component was generated in the anterior cingulate cortex.<\/p>\n<\/div><\/div><\/div><\/section>\n<section class='av_toggle_section av-a2iav-88d82f2e4841f5146ecb47ca7ecbd5d2'  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div role=\"tablist\" class=\"single_toggle\" data-tags=\"{Alle} \"  ><p id='toggle-toggle-id-6' data-fake-id='#toggle-id-6' class='toggler  av-title-above av-inherit-border-color'  itemprop=\"headline\"  role='tab' tabindex='0' aria-controls='toggle-id-6' data-slide-speed=\"200\" data-title=\"Classification of ADHD patients on the basis of independent ERP components using a machine learning system\" data-title-open=\"\" data-aria_collapsed=\"Click to expand: Classification of ADHD patients on the basis of independent ERP components using a machine learning system\" data-aria_expanded=\"Click to collapse: Classification of ADHD patients on the basis of independent ERP components using a machine learning system\">Classification of ADHD patients on the basis of independent ERP components using a machine learning system<span class=\"toggle_icon\"><span class=\"vert_icon\"><\/span><span class=\"hor_icon\"><\/span><\/span><\/p><div id='toggle-id-6' aria-labelledby='toggle-toggle-id-6' role='region' class='toggle_wrap  av-title-above'  ><div class='toggle_content invers-color av-inherit-border-color'  itemprop=\"text\" ><p><em>M\u00fcller, Andreas; Candrian, Gian; Kropotov, Juri D; Ponomarev, Valery A; Baschera, Gian-Marco<\/em><br \/>\n<strong>Classification of ADHD patients on the basis of independent ERP components using a machine learning system<\/strong><\/p>\n<p>Nonlinear Biomedical Physics, 4 (Suppl 1) :S1, 2010.<\/p>\n<p>Background: In the context of sensory and cognitive-processing deficits in ADHD patients, there is considerable evidence of altered event related potentials (ERP). Most of the studies, however, were done on ADHD children. Using the independent component analysis (ICA) method, ERPs can be decomposed into functionally different components. Using the classification method of support vector machine, this study investigated whether features of independent ERP components can be used for discrimination of ADHD adults from healthy subjects.<\/p>\n<p>Methods: Two groups of age- and sex-matched adults (74 ADHD, 74 controls) performed a visual two stimulus GO\/NOGO task. ERP responses were decomposed into independent components by means of ICA. A feature selection algorithm defined a set of independent component features which was entered into a support vector machine.<\/p>\n<p>Results: The feature set consisted of five latency measures in specific time windows, which were collected from four different independent components. The independent components involved were a novelty component, a sensory related and two executive function related components. Using a 10-fold cross-validation approach, classification accuracy was 92%.<\/p>\n<p>Conclusions: This study was a first attempt to classify ADHD adults by means of support vector machine which indicates that classification by means of non-linear methods is feasible in the context of clinical groups. Further, independent ERP components have been shown to provide features that can be used for characterizing clinical populations.<\/p>\n<\/div><\/div><\/div><\/section>\n<section class='av_toggle_section av-e4arb-372acf51276ffbc771c35d0510283743'  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div role=\"tablist\" class=\"single_toggle\" data-tags=\"{Alle} \"  ><p id='toggle-toggle-id-7' data-fake-id='#toggle-id-7' class='toggler  av-title-above av-inherit-border-color'  itemprop=\"headline\"  role='tab' tabindex='0' aria-controls='toggle-id-7' data-slide-speed=\"200\" data-title=\"Beneficial Effects of Electrostimulation Contingencies on Sustained Attention and Electrocortical Activity\" data-title-open=\"\" data-aria_collapsed=\"Click to expand: Beneficial Effects of Electrostimulation Contingencies on Sustained Attention and Electrocortical Activity\" data-aria_expanded=\"Click to collapse: Beneficial Effects of Electrostimulation Contingencies on Sustained Attention and Electrocortical Activity\">Beneficial Effects of Electrostimulation Contingencies on Sustained Attention and Electrocortical Activity<span class=\"toggle_icon\"><span class=\"vert_icon\"><\/span><span class=\"hor_icon\"><\/span><\/span><\/p><div id='toggle-id-7' aria-labelledby='toggle-toggle-id-7' role='region' class='toggle_wrap  av-title-above'  ><div class='toggle_content invers-color av-inherit-border-color'  itemprop=\"text\" ><p><em>Chen, Max Jean-Lon; Thompson, Trevor; Kropotov, Juri D; Gruzelier, John H<\/em><br \/>\n<strong>Beneficial Effects of Electrostimulation Contingencies on Sustained Attention and Electrocortical Activity<\/strong><\/p>\n<p>CNS Neuroscience &amp; Therapeutics 00, 1\u201316, 2010.<\/p>\n<p>Introduction: Chinese acupuncture therapy has been practiced for more than 3000 years. According to neuroimaging studies, electroacupuncture has been demonstrated to be effective via control of the frequency parameter of stimulation, based on the theory of frequency modulation of brain function.<\/p>\n<p>Aims: To investigate the following: (1) possible sustained effects of acustimulation in improving perceptual sensitivity in attention by comparing before, during, and 5 min following stimulation; (2) relations between commission errors and the motor inhibition event-related potential (ERP) component measured with independent component analysis (ICA); (3) whether habituation would be demonstrated in the sham control group and would be militated by acustimulation in the experimental groups.<\/p>\n<p>Results: Twenty-seven subjects were divided into three groups (n = 9). d-Prime (d\u0002) derived from signal detection theory was used as an index of perceptual sensitivity in the visual continuous performance attention test. Increased d\u0002 was found during both alternating frequency (AE) and low frequency (LE) stimulation, but with no change in the sham control group (SE). However, only following AE was there a sustained poststimulation effect. Spatial filtration-based independent components (ICs) in the AE group revealed significantly decreased amplitudes of the motor inhibition ICs both during and poststimulation. There was a significant habituation effect from task repetition in the sham group with decreased amplitudes of ICs as follows: the visual comparison component difference between go (correct response) and nogo cues (correct withheld response), the P400 action monitoring and the working memory component in the nogo condition, and the passive auditory component on control trials.<\/p>\n<p>Conclusion: The results showed associations between acustimulation and improved perceptual sensitivity with sustained improvements following AE, but not LE stimulation. Improvements in commission errors in the AE group were related to the motor inhibition IC. The activational effects of acustimulation apparently attenuated the acrosstask habituation that characterized the control group.<\/p>\n<\/div><\/div><\/div><\/section>\n<section class='av_toggle_section av-bu2vr-db514295a14a4878ea9ab2225c2becf1'  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div role=\"tablist\" class=\"single_toggle\" data-tags=\"{Alle} \"  ><p id='toggle-toggle-id-8' data-fake-id='#toggle-id-8' class='toggler  av-title-above av-inherit-border-color'  itemprop=\"headline\"  role='tab' tabindex='0' aria-controls='toggle-id-8' data-slide-speed=\"200\" data-title=\"The comparison of clustering methods of EEG independent components in healthy subjects and patients with post concussion syndrome after traumatic brain injury\" data-title-open=\"\" data-aria_collapsed=\"Click to expand: The comparison of clustering methods of EEG independent components in healthy subjects and patients with post concussion syndrome after traumatic brain injury\" data-aria_expanded=\"Click to collapse: The comparison of clustering methods of EEG independent components in healthy subjects and patients with post concussion syndrome after traumatic brain injury\">The comparison of clustering methods of EEG independent components in healthy subjects and patients with post concussion syndrome after traumatic brain injury<span class=\"toggle_icon\"><span class=\"vert_icon\"><\/span><span class=\"hor_icon\"><\/span><\/span><\/p><div id='toggle-id-8' aria-labelledby='toggle-toggle-id-8' role='region' class='toggle_wrap  av-title-above'  ><div class='toggle_content invers-color av-inherit-border-color'  itemprop=\"text\" ><p><em>Ponomarev, Valery A; Gurskaia, OE; Kropotov, Juri D; Artiushkova, LV; M\u00fcller, Andreas<\/em><br \/>\n<strong>The comparison of clustering methods of EEG independent components in healthy subjects and patients with post concussion syndrome after traumatic brain injury<\/strong><\/p>\n<p>Fiziol Cheloveka. Mar-Apr;36(2):5-14, 2010.<\/p>\n<p>The comparison of three different clustering methods of 19-channels EEG independent components in 518 healthy subjects and 87 patients with post concussion syndrome after traumatic brain injury was performed to define more exact the location of sources of pathologic brain activity. Following methods of grouping were used: clustering of independent components topographies, clustering of coordinates of equivalent dipole sources corresponding to independent components topographies and sorting of independent components using extremes of equivalent source current density computed by Standardized Low Resolution Electromagnetic Tomography (sLORETA).The comparison of power spectra of independent components revealed statically significant increase of EEG power located in frontal and temporal brain areas in delta, theta and alpha frequency bands in patients with post concussion syndrome after traumatic brain injury. The method of clustering of independent components topographies seems to be most sensitive in comparison with other two methods.<\/p>\n<\/div><\/div><\/div><\/section>\n<\/div><\/p><\/div>\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-s82i-b7ee1b49f4240284e23b34917aff6499\">\n.flex_column.av-s82i-b7ee1b49f4240284e23b34917aff6499{\nborder-radius:0px 0px 0px 0px;\npadding:0px 0px 0px 0px;\n}\n<\/style>\n<div  class='flex_column av-s82i-b7ee1b49f4240284e23b34917aff6499 av_one_half  avia-builder-el-5  el_after_av_one_half  el_before_av_hr  flex_column_div av-zero-column-padding  '     ><section  class='av_textblock_section av-kdoek3vo-272befba42fc51414855ade34c25da1f '   itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div class='avia_textblock'  itemprop=\"text\" ><h2>B\u00fccher<\/h2>\n<\/div><\/section><br \/>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-kex5kljy-40686d73d7d9a4f8362914a9905570cf\">\n#top .togglecontainer.av-kex5kljy-40686d73d7d9a4f8362914a9905570cf p.toggler{\nborder-color:#96c11f;\n}\n#top .togglecontainer.av-kex5kljy-40686d73d7d9a4f8362914a9905570cf .toggle_wrap .toggle_content{\nborder-color:#96c11f;\n}\n<\/style>\n<div  class='togglecontainer av-kex5kljy-40686d73d7d9a4f8362914a9905570cf av-minimal-toggle  avia-builder-el-7  el_after_av_textblock  el_before_av_hr  toggle_close_all' >\n<section class='av_toggle_section av-hcbgf-1af4d83aaa4ed45edf9aca1092e73c20'  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div role=\"tablist\" class=\"single_toggle\" data-tags=\"{Alle} \"  ><p id='toggle-toggle-id-9' data-fake-id='#toggle-id-9' class='toggler  av-title-above av-inherit-border-color'  itemprop=\"headline\"  role='tab' tabindex='0' aria-controls='toggle-id-9' data-slide-speed=\"200\" data-title=\"ADHS \u2013 Neurodiagnostik in der Praxis\" data-title-open=\"\" data-aria_collapsed=\"Click to expand: ADHS \u2013 Neurodiagnostik in der Praxis\" data-aria_expanded=\"Click to collapse: ADHS \u2013 Neurodiagnostik in der Praxis\">ADHS \u2013 Neurodiagnostik in der Praxis<span class=\"toggle_icon\"><span class=\"vert_icon\"><\/span><span class=\"hor_icon\"><\/span><\/span><\/p><div id='toggle-id-9' aria-labelledby='toggle-toggle-id-9' role='region' class='toggle_wrap  av-title-above'  ><div class='toggle_content invers-color av-inherit-border-color'  itemprop=\"text\" ><p><em>M\u00fcller, Andreas; Candrian, Gian; Kropotov, Juri D<\/em><br \/>\n<strong>ADHS \u2013 Neurodiagnostik in der Praxis<\/strong><\/p>\n<p>Springer-Verlag, 2011, ISBN: 139783642200618.<\/p>\n<p>Die Entstehung des vorliegenden Buches hatte verschiedene Ausgangspunkte. Zun\u00e4chst war da das zunehmende Unbehagen in Bezug auf Objektivit\u00e4t und Aussagem\u00f6glichkeiten psychologisch- psychiatrischer Diagnostik, das sich w\u00e4hrend unserer praktischen T\u00e4tigkeit im Verlauf der letzten 30 Jahre entwickelt hatte. Obwohl die derzeit zur Verf\u00fcgung stehenden psychometrischen Testmethoden eine lange Tradition haben und eine Vielzahl von Untersuchungen zu den G\u00fctekriterien vorliegen, tragen sie in den meisten F\u00e4llen wenig zur Diagnose bei. Es ist zwar m\u00f6glich, kognitiv-verhaltensm\u00e4\u00dfige Funktionen wie verschiedene Arten des Denkens und Probleml\u00f6sens, Arbeitstempo, Ged\u00e4chtnis sowie Aufmerksamkeit mit mehr oder weniger originellen Instrumenten zu erfassen und Zug\u00e4nge zu den Emotionen und zum Verhalten mittels Fragebogen zu er\u00f6ff nen. Das Problem bei allen diesen Erkenntnissen liegt aber darin, dass sie meist eine geringe \u00f6kologische Validit\u00e4t haben und zus\u00e4tzlich wenig zum Verstehen menschlicher Andersartigkeit beitragen. Das f\u00fchrt dazu, dass der klinisch erhobene Psychostatus weitgehend durch die Schilderungen der Betroff enen und deren Angeh\u00f6rigen zustande kommt. Die Eindr\u00fccke des Beurteilers sind situativ gepr\u00e4gt und im Wesentlichen abh\u00e4ngig vom Empfi nden der Fachperson selbst. Diese subjektive Pr\u00e4gung der Diagnostik und die damit verbundene Variabilit\u00e4t und Ungenauigkeit war sozusagen die \u00bbTriebfeder \u00ab f\u00fcr das Suchen nach neuen M\u00f6glichkeiten f\u00fcr eine objektivere Diagnostik.<\/p>\n<\/div><\/div><\/div><\/section>\n<section class='av_toggle_section av-7sdif-b43f2f7232397a05292100a8e4d76df8'  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div role=\"tablist\" class=\"single_toggle\" data-tags=\"{Alle} \"  ><p id='toggle-toggle-id-10' data-fake-id='#toggle-id-10' class='toggler  av-title-above av-inherit-border-color'  itemprop=\"headline\"  role='tab' tabindex='0' aria-controls='toggle-id-10' data-slide-speed=\"200\" data-title=\"Neurofeedback and Neuromodulation Techniques and Applications\" data-title-open=\"\" data-aria_collapsed=\"Click to expand: Neurofeedback and Neuromodulation Techniques and Applications\" data-aria_expanded=\"Click to collapse: Neurofeedback and Neuromodulation Techniques and Applications\">Neurofeedback and Neuromodulation Techniques and Applications<span class=\"toggle_icon\"><span class=\"vert_icon\"><\/span><span class=\"hor_icon\"><\/span><\/span><\/p><div id='toggle-id-10' aria-labelledby='toggle-toggle-id-10' role='region' class='toggle_wrap  av-title-above'  ><div class='toggle_content invers-color av-inherit-border-color'  itemprop=\"text\" ><p><em>Coben, Robert; Evans, James R (Hrsg.)<\/em><br \/>\n<strong>Neurofeedback and Neuromodulation Techniques and Applications<\/strong><\/p>\n<p>Academic Press, 2010.<\/p>\n<p>It was not many years ago that the term &#8222;neuromodulation&#8220; would have been considered a contradictory term by many\u0001 at least in regard to modification of a damaged or dysfunctional central nervous system. Although it generally had been assumed that learning and memory somehow resulted in relatively permanent modifications of brain structure and\/or function, the notion persisted that neural function and structure basically were set by genetics and were relatively immune to change. However, within the past couple of decades developments in neuroimaging have enabled scientific research providing evidence of neural plasticity far greater than previously had been imagined. Research on neural plasticity is burgeoning, along with a plethora of scientifically unsubstantiated claims by practitioners from many different professions for &#8222;brain-based&#8220; methods for remediation of various medical, psychological, and educational problems.<\/p>\n<\/div><\/div><\/div><\/section>\n<section class='av_toggle_section av-a5vfz-d6fb71ecf1274ae16e21e6f57b127b54'  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div role=\"tablist\" class=\"single_toggle\" data-tags=\"{Alle} \"  ><p id='toggle-toggle-id-11' data-fake-id='#toggle-id-11' class='toggler  av-title-above av-inherit-border-color'  itemprop=\"headline\"  role='tab' tabindex='0' aria-controls='toggle-id-11' data-slide-speed=\"200\" data-title=\"Quantitative EEG, Event-Related Potentials and Neurotherapy\" data-title-open=\"\" data-aria_collapsed=\"Click to expand: Quantitative EEG, Event-Related Potentials and Neurotherapy\" data-aria_expanded=\"Click to collapse: Quantitative EEG, Event-Related Potentials and Neurotherapy\">Quantitative EEG, Event-Related Potentials and Neurotherapy<span class=\"toggle_icon\"><span class=\"vert_icon\"><\/span><span class=\"hor_icon\"><\/span><\/span><\/p><div id='toggle-id-11' aria-labelledby='toggle-toggle-id-11' role='region' class='toggle_wrap  av-title-above'  ><div class='toggle_content invers-color av-inherit-border-color'  itemprop=\"text\" ><p class=\"tp_pub_author\"><em>Kropotov, Juri D<\/em><br \/>\n<strong>Quantitative EEG, Event-Related Potentials and Neurotherapy<\/strong><\/p>\n<p class=\"tp_pub_additional\"><span class=\"tp_pub_additional_publisher\">Academic Press,\u00a0<\/span><span class=\"tp_pub_additional_year\">2008<\/span>,\u00a0<span class=\"tp_pub_additional_isbn\">ISBN: 978-0123745125<\/span>.<\/p>\n<p>While the brain is ruled to a large extent by chemical neurotransmitters, it is also a bioelectric organ. The collective study of &#8218;Quantitative ElectroEncephaloGraphs (QEEG &#8211; the conversion of brainwaves to digital form to allow for comparison between neurologically normative and dysfunctional individuals), Event Related Potentials (ERPs &#8211; electrophysiological response to stimulus) and Neurotherapy (the process of actually retraining brain processes to)&#8216; offers a window into brain physiology and function via computer and statistical analyses of traditional EEG patterns, suggesting innovative approaches to the improvement of attention, anxiety, mood and behavior. The volume provides detailed description of the various EEG rhythms and ERPs, the conventional analytic methods such as spectral analysis, and the emerging method utilizing QEEG and ERPs. This research is then related back to practice and all existing approaches in the field of Neurotherapy &#8211; conventional EEG-based neurofeedback, brain-computer interface, transcranial Direct Current Stimulation, and Transcranial Magnetic Stimulation &#8211; are covered in full. Additionally, software for EEG analysis is provided on a companion web site so that the theory can be practically utilized on the spot, and a database of the EEG algorithms described in the book can be combined with algorithms uploaded by the user in order to compare dysfunctional and normative data. While it does not offer the breadth provided by an edited work, this volume does provide a level of depth and detail that a single author can deliver, as well as giving readers insight into the personal theories of one of the pre-eminent leaders in the field. Features and benefits include: provides a holistic picture of quantitative EEG and event related potentials as a unified scientific field; presents a unified description of the methods of quantitative EEG and event related potentials; gives a scientifically based overview of existing approaches in the field of neurotherapy; provides practical information for the better understanding and treatment of disorders, such as ADHD, Schizophrenia, Addiction, OCD, Depression, and Alzheimer&#8217;s Disease; companion web site containing software which analyzes EEG patterns and database sample EEGs; and, reader can see actual examples of EEG patterns discussed in book and can upload their own library of EEGs for analysis.<\/p>\n<\/div><\/div><\/div><\/section>\n<\/div><br \/>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-kex65max-5e473eb3fb2656aa86ac10eb2603cbd1\">\n#top .hr.hr-invisible.av-kex65max-5e473eb3fb2656aa86ac10eb2603cbd1{\nheight:25px;\n}\n<\/style>\n<div  class='hr av-kex65max-5e473eb3fb2656aa86ac10eb2603cbd1 hr-invisible  avia-builder-el-8  el_after_av_toggle_container  el_before_av_textblock '><span class='hr-inner '><span class=\"hr-inner-style\"><\/span><\/span><\/div><br \/>\n<section  class='av_textblock_section av-kdoek3vo-272befba42fc51414855ade34c25da1f '   itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div class='avia_textblock'  itemprop=\"text\" ><h2>Forschungsberichte<\/h2>\n<\/div><\/section><br \/>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-kex5kljy-40686d73d7d9a4f8362914a9905570cf\">\n#top .togglecontainer.av-kex5kljy-40686d73d7d9a4f8362914a9905570cf p.toggler{\nborder-color:#96c11f;\n}\n#top .togglecontainer.av-kex5kljy-40686d73d7d9a4f8362914a9905570cf .toggle_wrap .toggle_content{\nborder-color:#96c11f;\n}\n<\/style>\n<div  class='togglecontainer av-kex5kljy-40686d73d7d9a4f8362914a9905570cf av-minimal-toggle  avia-builder-el-10  el_after_av_textblock  avia-builder-el-last  toggle_close_all' >\n<section class='av_toggle_section av-7xeu7-f270ef92626cf5ef1bf1658ae5581477'  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div role=\"tablist\" class=\"single_toggle\" data-tags=\"{Alle} \"  ><p id='toggle-toggle-id-12' data-fake-id='#toggle-id-12' class='toggler  av-title-above av-inherit-border-color'  itemprop=\"headline\"  role='tab' tabindex='0' aria-controls='toggle-id-12' data-slide-speed=\"200\" data-title=\"New tools for diagnosis and modulation of brain dysfunction\" data-title-open=\"\" data-aria_collapsed=\"Click to expand: New tools for diagnosis and modulation of brain dysfunction\" data-aria_expanded=\"Click to collapse: New tools for diagnosis and modulation of brain dysfunction\">New tools for diagnosis and modulation of brain dysfunction<span class=\"toggle_icon\"><span class=\"vert_icon\"><\/span><span class=\"hor_icon\"><\/span><\/span><\/p><div id='toggle-id-12' aria-labelledby='toggle-toggle-id-12' role='region' class='toggle_wrap  av-title-above'  ><div class='toggle_content invers-color av-inherit-border-color'  itemprop=\"text\" ><p><em>Kropotov, Juri D<\/em><br \/>\n<strong>New tools for diagnosis and modulation of brain dysfunction<\/strong><\/p>\n<p>0000.<\/p>\n<p>Suppose a boy comes to your door. His behavior looks like typical ADHD: he is extremely inattentive, impulsive and hyperactive. He performs poorly in continuous performance tasks.<\/p>\n<p><strong>Recent research in neurophysiology of ADHD shows that there are several reasons why the boy behaves in this way:<\/strong><\/p>\n<p>1. patient may have a focus in his cortex , which without any overt symptoms of epilepsy impairs information processing and, consequently, mimics attention deficit (see Aldenkamp, Arends, 2004);<br \/>\n2. patient may have a lack of overall cortical activation due to dysfunction of the ascending reticular system of the brain stem (Sergeant , 2000);<br \/>\n3. patient may have genetically determined hyperactive frontal lobes (Clarke et al., 2003);<br \/>\n4. patient may have dysfunction of the prefrontal-striato-thalamic system due to structural abnormality (Silk et al., 2009; Busch et al., 2005; Castellanos et al., 1996); or increase of dopamine reuptake dopamine transporters in the striatum (Krause et al., 2003)<br \/>\n5. patient may have hypoactivation of the premotor cortex of the brain, which is compensated by increase of motoric activity (Simmonds et al., 2007);<br \/>\n6. patient may have dysfunctioning in the anterior gyrus cingulus which produces anxiety, emotional instability and hyperactivation (Albrecht et al., 2008).<\/p>\n<\/div><\/div><\/div><\/section>\n<\/div><\/p><\/div><div  id=\"aposapos\"  class='hr &apos;av-kgkiedt6&apos;-6e09bbdc0abbbc35ecda3588a92a569a hr-&apos;invisible&apos; 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