Research
Article
Clarification of ADHD - Towards Personalized Medicine Through Biomarkers
Müller, Andreas; Candrian, Gian
Clarification of ADHD - Towards Personalized Medicine Through Biomarkers
IN|FO|Neurology & Psychiatry; VOL. 10, No. 3, 2012.
The main problem in diagnosing ADHD is the lack of objectivity. Incorporating biomarkers and understanding them from the perspective of actions, thoughts, and feelings, within the context of life circumstances and personal history, largely resolves this issue. Electrophysiological biomarkers (quantitative analysis of EEG and event-related potentials) are excellent for understanding neural dynamics, for diagnosis, and for determining interventions in the sense of personalized medicine. Studies demonstrate a high validity of event-related potentials.
The QEEG theta/beta ratio in ADHD and normal controls: Sensitivity, specificity, and behavioral correlates
Ogrim, Geir; Kropotov, Juri D; Hestad, Knut
The QEEG theta/beta ratio in ADHD and normal controls: Sensitivity, specificity, and behavioral correlates
Psychiatry Research, 2012.
The purpose of the present study was to determine whether the theta/beta ratio, as well as theta and beta waves separately, correlate with behavioral parameters, and whether these measures can distinguish 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 under eyes-closed and eyes-open conditions, and during a GO/NOGO task in both groups. Neither the theta/beta ratio at CZ nor theta and beta separately showed significant differences between patients and controls. When each individual was compared with the database, significant elevations in theta were found in 25.81% of the patients and in only one control subject (2.61%). In the ADHD group, theta at CZ was positively correlated with inattention and executive function problems and negatively correlated with hyperactivity/impulsivity. Beta correlated with good attention levels in the control group, but with ADHD symptoms in the patients. Omission errors in the GO/NOGO test distinguished between patients and controls with an accuracy of 85.1%. For theta at CZ, the accuracy was 62.1%. Significantly elevated theta characterized a subgroup of ADHD and correlated with inattention and executive problems.
Discriminating between ADHD adults and controls using independent ERP components and a support vector machine: a validation study
Müller, Andreas; Candrian, Gian; Grane, Venke Arntsberg; Kropotov, Yuri D.; Ponomarev, Valery A.; Baschera, Gian-Marco
Discriminating between ADHD adults and controls using independent ERP components and a support vector machine: a validation study
Nonlinear Biomedical Physics, 5:5, 2011.
Background:
Numerous event-related potential (ERP) studies have been conducted on attention-deficit hyperactivity disorder (ADHD), and a substantial number of ERP correlates of the disorder have been identified. However, most of these 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 to investigate the use of such independent ERP components in differentiating adult ADHD patients from non-clinical controls by selecting the most informative feature set. A second aim was to validate the predictive power of the SVM classifier using an independent ADHD sample recruited at a different laboratory.
Methods:
Two groups of age-matched adults (75 with 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.
Results:
Using a 10-fold cross-validation approach, the classification accuracy was 91.1%. The predictive power of the SVM classifier was verified using an independent ADHD sample (17 ADHD patients), resulting in a classification accuracy of 94.1%. The latency and amplitude measures that, in combination, best distinguished between ADHD patients and non-clinical subjects primarily originated from independent components associated with inhibitory and other executive functions.
Conclusions:
This study shows that ERPs can substantially contribute to the diagnosis of ADHD when combined with up-to-date methods.
Analysis of EEG Characteristics in Early Stages of Depression Using the Independent Components Method
Grin‘-Iatsenko, VA; Baas, Ineke; Ponomarev, Valery A; Kropotov, Juri D
Analysis of EEG Characteristics in Early Stages of Depression Using the Independent Components Method
Human Physiology. Jan-Feb;37(1):45-55, 2011.
Independent Component Analysis (ICA) was used for 19-channel resting EEG analysis of 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, 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 play an important role in the clinical picture of depressive disorder at early stages. The use of the ICA method for comparing the spectral characteristics of EEG in groups of patients with different brain pathologies and healthy subjects allows for more precise localization of discovered differences compared to traditional analysis of EEG spectra.
Dissociating action inhibition, conflict monitoring, and sensory mismatch into independent components of event-related potentials in a Go/No-Go task
Kropotov, Juri D; Ponomarev, Valery A; Hollup, Stig; Müller, Andreas
Dissociating action inhibition, conflict monitoring, and sensory mismatch into independent components of event-related potentials in a Go/No-Go task
NeuroImage 57, 565–575, 2011.
In previous studies, the anterior N2 and P3 waves of event-related potentials (ERPs) in the GO/NOGO paradigm, during trials involving preparatory set violations, were inconsistently associated with either action inhibition or conflict monitoring operations. In the present study, a paired-stimulus GO/NOGO design was used 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 using independent component analysis (ICA). The ICA was performed on a collection of 114 individual ERPs across the three experimental conditions. Three of the independent components were selectively affected by the task manipulations, indicating an 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.
Classification of ADHD patients based on independent ERP components using a machine learning system
Müller, Andreas; Candrian, Gian; Kropotov, Juri D; Ponomarev, Valery A; Baschera, Gian-Marco
Classification of ADHD patients based on independent ERP components using a machine learning system
Nonlinear Biomedical Physics, 4 (Suppl 1): S1, 2010.
Background: In the context of sensory and cognitive processing deficits in ADHD patients, there is considerable evidence of altered event-related potentials (ERPs). However, most studies have been conducted on children with ADHD. Using the independent component analysis (ICA) method, ERPs can be decomposed into functionally different components. This study investigated whether features of independent ERP components can be used to differentiate between adults with ADHD and healthy subjects, employing the support vector machine classification method.
Methods: Two groups of age- and sex-matched adults (74 with ADHD, 74 controls) performed a visual two-stimulus GO/NOGO task. ERP responses were decomposed into independent components using ICA. A feature selection algorithm defined a set of independent component features that were entered into a support vector machine.
Results: The feature set consisted of five latency measures within specific time windows, which were collected from four distinct independent components. The independent components included a novelty component, a sensory-related component, and two executive function-related components. Using a 10-fold cross-validation approach, the classification accuracy was 92.1%.
Conclusions: This study was a first attempt to classify adults with ADHD using a support vector machine, indicating that classification with non-linear methods is feasible within the context of clinical groups. Furthermore, independent ERP components have been shown to provide features that can be used to characterize clinical populations.
Beneficial Effects of Electrostimulation Contingencies on Sustained Attention and Electrocortical Activity
Chen, Max Jean-Lon; Thompson, Trevor; Kropotov, Juri D; Gruzelier, John H
Beneficial Effects of Electrostimulation Contingencies on Sustained Attention and Electrocortical Activity
CNS Neuroscience & Therapeutics 00, 1–16, 2010.
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.
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 mitigated by acustimulation in the experimental groups.
Results: Twenty-seven subjects were divided into three groups (n = 9). d-Prime (d') derived from signal detection theory was used as an index of perceptual sensitivity in the visual continuous performance attention test. Increased d' 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.
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 motor inhibition IC. The activational effects of acustimulation apparently attenuated the across-task habituation that characterized the control group.
A comparison of clustering methods for EEG independent components in healthy subjects and patients with post-concussion syndrome after traumatic brain injury
Ponomarev, Valery A.; Gurskaia, O. E.; Kropotov, Yuri D.; Artiushkova, L. V.; Müller, Andreas
A comparison of clustering methods for EEG independent components in healthy subjects and patients with post-concussion syndrome after traumatic brain injury
Human Physiology. Mar-Apr;36(2):5-14, 2010.
A comparison of three different clustering methods for 19-channel EEG independent components was performed in 518 healthy subjects and 87 patients with post-concussion syndrome after traumatic brain injury to more precisely define the location of pathological brain activity sources. The following grouping methods were used: clustering of independent component topographies, clustering of equivalent dipole source coordinates corresponding to independent component topographies, and sorting of independent components using extremes of equivalent source current density computed by Standardized Low Resolution Electromagnetic Tomography (sLORETA). The comparison of independent component power spectra revealed a statistically significant increase in EEG power located in frontal and temporal brain areas across delta, theta, and alpha frequency bands in patients with post-concussion syndrome after traumatic brain injury. The method of clustering independent component topographies appears to be the most sensitive when compared to the other two methods.
Books
ADHD - Neuro-diagnostic Testing in Practice
Müller, Andreas; Candrian, Gian; Kropotov, Juri D
ADHD - Neuro-diagnostic Testing in Practice
Springer-Verlag, 2011, ISBN: 139783642200618.
The genesis of this book had several starting points. First, there was the growing unease regarding the objectivity and the limits of psychological-psychiatric diagnostics, which had developed over the course of our practical work in the last 30 years. Although the currently available psychometric testing methods have a long tradition and a multitude of studies concerning their validity criteria exist, they contribute little to the diagnosis in most cases. While it is possible to assess cognitive-behavioral functions such as various types of thinking and problem-solving, work tempo, memory, and attention with more or less original instruments and to open up avenues to emotions and behavior through questionnaires, the problem with all these findings is that they mostly have low ecological validity and additionally contribute little to understanding human difference. This leads to the fact that the clinically obtained psychostatus is largely generated by the descriptions of those affected and their relatives. The impressions of the assessor are situationally influenced and essentially dependent on the feelings of the expert themselves. This subjective imprint on diagnostics and the associated variability and inaccuracy were, so to speak, the »driving force« for the search for new possibilities for more objective diagnostics.
Neurofeedback and Neuromodulation Techniques and Applications
Coben, Robert; Evans, James R. (Eds.)
Neurofeedback and Neuromodulation Techniques and Applications
Academic Press, 2010.
It wasn't many years ago that the term „neuromodulation“ would have been considered contradictory by many, at least with regard to modifying a damaged or dysfunctional central nervous system. Although it had generally 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 were basically 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 imagined. Research on neural plasticity is burgeoning, along with a plethora of scientifically unsubstantiated claims by practitioners from many different professions for „brain-based“ methods for remediation of various medical, psychological, and educational problems.
Quantitative EEG, Event-Related Potentials, and Neurotherapy
Academic Press, 2008, 978-0123745125.
While the brain is largely governed by chemical neurotransmitters, it is also a bioelectric organ. The combined study of ‚Quantitative Electroencephalograms (QEEG—the conversion of brainwaves into digital form to enable comparison between neurologically healthy and dysfunctional individuals), Event-Related Potentials (ERPs—electrophysiological responses to stimuli), and neurotherapy (the process of actively retraining brain processes),‘ offers a window into brain physiology and function through computer and statistical analyses of traditional EEG patterns, suggesting innovative approaches to improving attention, anxiety, mood, and behavior. The volume provides a detailed description of the various EEG rhythms and ERPs, conventional analytical 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—conventional EEG-based neurofeedback, brain-computer interfaces, transcranial direct current stimulation, and transcranial magnetic stimulation—are covered in full. Additionally, software for EEG analysis is provided on a companion website so that the theory can be put into practice immediately, and a database of the EEG algorithms described in the book can be combined with algorithms uploaded by the user 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 preeminent 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’s disease; a companion website containing software that analyzes EEG patterns and a database of sample EEGs; and, readers can view actual examples of EEG patterns discussed in the book and upload their own library of EEGs for analysis.
Research reports
New tools for the diagnosis and modulation of brain dysfunction
Kropotov, Yuri D
New tools for the diagnosis and modulation of brain dysfunction
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Suppose a boy comes to your door. His behavior looks like typical ADHD: he is extremely inattentive, impulsive, and hyperactive. He performs poorly on continuous performance tasks.
Resent research in neurophysiology of ADHD shows that there are several reasons why the boy behaves in this way:
1. The 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);
2. The patient may have a lack of overall cortical activation due to dysfunction of the ascending reticular system of the brainstem (Sergeant, 2000);
3. a patient may have genetically determined hyperactive frontal lobes (Clarke et al., 2003);
4. The 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 an increase of dopamine reuptake dopamine transporters in the striatum (Krause et al., 2003).
5. The patient may have hypoactivation of the premotor cortex, which is compensated by an increase in motoric activity (Simmonds et al., 2007).;
6. The patient may have dysfunction in the anterior cingulate gyrus, which produces anxiety, emotional instability, and hyperactivation (Albrecht et al., 2008).