Research
Brain Training & Assessment:
Neuromodulation | QEEG
Conditions:
ADD/ADHD | ASD | Learning Disabilities | Migraine | OCD
EEG Biofeedback for the Enhancement of Attentional Processing in Normal College Students
Howard Rasey BA, Joel F. Lubar PhD, Anne McIntyre PhD, Anthony Zoffuto BS, and Paul L. Abbott BA. Journal Of Neurotherapy Vol. 1 , Iss. 3,1995.
Over the past two decades, the use of electroencephalographic (EEG) biofeedback has been shown to be beneficial for the enhancement of attentional processes in children and adults with attentiondeficit disorder (ADD) and attention-deficit hyperactivity disorder (ADHD). For these two groups the EEG biofeedback procedure has been used to help individuals normalize neurological functioning, thereby enabling them to process information and deal with sensory stimulation more effectively (Lubar, 1985, 1991, 1995a, 1995b; Lubar & Lubar, 1984; Lubar, Swartwood, Swartwood, & O’Donnell, 1995; Mann, Lubar, Zimmerman, Miller, & Muenchen, 1992; Senf, 1988; Tansey, 1984, 1990).
Given the effectiveness of using EEG biofeedback for enhancing performance in individuals with ADHD and ADD, the next research question that needs to be answered is whether this EEG training can be used for the enhancement of attentional processing in normal individuals. The objective of this study was to determine whether the EEG biofeedback techniques effectively used to improve attentional processing for individuals with ADHD and ADD will have similar benefits for normal subjects.
Increasing Individual Upper Alpha Power by Neurofeedback Improves Cognitive Performance in Human Subjects
Hanslmayr, S., Sauseng, P., Doppelmayr, M. et al. Appl Psychophysiol Biofeedback (2005) 30: 1. doi:10.1007/s10484-005-2169-8.
The hypothesis was tested of whether neurofeedback training (NFT)–applied in order to increase upper alpha but decrease theta power–is capable of increasing cognitive performance. A mental rotation task was performed before and after upper alpha and theta NFT. Only those subjects who were able to increase their upper alpha power (responders) performed better on mental rotations after NFT. Training success (extent of NFT-induced increase in upper alpha power) was positively correlated with the improvement in cognitive performance. Furthermore, the EEG of NFT responders showed a significant increase in reference upper alpha power (i.e. in a time interval preceding mental rotation). This is in line with studies showing that increased upper alpha power in a prestimulus (reference) interval is related to good cognitive performance.
Neurofeedback Training to Enhance Learning and Memory in Patients with Cognitive Impairment
Traumatic Brain Injury: A Single Case Study. International Journal of Psychosocial Rehabilitation. Vol 14(1). 21-28.
The brain tumours can make cognitive impairment especially when they involve the limbic system, the frontal or temporal lobes. The aim of the present study was to examine neurofeedback training (NFT) to enhance learning and memory in patients with cognitive impairment. Single case pre- and post-intervention study was adopted. The qEEG WISC-IV and CBCL test was compared pre and post NFT. Patient was given 40 sessions of NFT, 45 min / day, 3 days a week. The training incorporated video feedback to increase the frequency of Beta waves (15-18 Hz) and to decrease theta waves (3-7 Hz) in T3 and F3. Also, SMR training was performed in Cz to decrease the seizure attacks. qEEG showed prominent different in the brain activity. Results indicated decrease in theta and increase in Beta waves. The present study puts forward that NFT should be taken into account to plan for rehabilitation of patients with cognitive impairment for enhancement of performance in the school or university.
Sustained excitability elevations induced by transcranial DC motor cortex stimulation in humans
The authors show that in the human transcranial direct current stimulation is able to induce sustained cortical excitability elevations. As revealed by transcranial magnetic stimulation, motor cortical excitability increased approximately 150% above baseline for up to 90 minutes after the end of stimulation. The feasibility of inducing long-lasting excitability modulations in a noninvasive, painless, and reversible way makes this technique a potentially valuable tool in neuroplasticity modulation.
Transcranial Direct Current Stimulation during Sleep Improves Declarative Memory
In humans, weak transcranial direct current stimulation (tDCS) modulates excitability in the motor, visual, and prefrontal cortex. Periods rich in slow-wave sleep (SWS) not only facilitate the consolidation of declarative memories, but in humans, SWS is also accompanied by a pronounced endogenous transcortical DC potential shift of negative polarity over frontocortical areas. To experimentally induce widespread extracellular negative DC potentials, we applied anodal tDCS (0.26 mA) [correction] repeatedly (over 30 min) bilaterally at frontocortical electrode sites during a retention period rich in SWS. Retention of declarative memories (word pairs) and also nondeclarative memories (mirror tracing skills) learned previously was tested after this period and compared with retention performance after placebo stimulation as well as after retention intervals of wakefulness. Compared with placebo stimulation, anodal tDCS during SWS-rich sleep distinctly increased the retention of word pairs (p < 0.005). When applied during the wake retention interval, tDCS did not affect declarative memory. Procedural memory was also not affected by tDCS. Mood was improved both after tDCS during sleep and during wake intervals. tDCS increased sleep depth toward the end of the stimulation period, whereas the average power in the faster frequency bands (,alpha, and beta) was reduced. Acutely, anodal tDCS increased slow oscillatory activity <3 Hz. We conclude that effects of tDCS involve enhanced generation of slow oscillatory EEG activity considered to facilitate processes of neuronal plasticity. Shifts in extracellular ionic concentration in frontocortical tissue (expressed as negative DC potentials during SWS) may facilitate sleep-dependent consolidation of declarative memories.
Assessment of Digital EEG, quantitative EEG, and EEG Brain Mapping
Clinical Advantages of Quantitative Electroencephalogram (QEEG)-Electrical Neuroimaging Application in General Neurology Practice
QEEG-electrical neuroimaging has been underutilized in general neurology practice for uncertain reasons. Recent advances in computer technology have made this electrophysiological testing relatively inexpensive. Therefore, this study was conducted to evaluate the clinical usefulness of QEEG/electrical neuroimaging in neurological practice. Over the period of approximately 6 months, 100 consecutive QEEG recordings were analyzed for potential clinical benefits. The patients who completed QEEG were divided into 5 groups based on their initial clinical presentation. The main groups included patients with seizures, headaches, post-concussion syndrome, cognitive problems, and behavioral dysfunctions. Subsequently, cases were reviewed and a decision was made as to whether QEEG analysis contributed to the diagnosis and/or furthered patient’s treatment. Selected and representative cases from each group are presented in more detail, including electrical neuroimaging with additional low-resolution electromagnetic tomography analysis or using computerized cognitive testing. Statistical analysis showed that QEEG analysis contributed to 95% of neurological cases, which indicates great potential for wider application of this modality in general neurology. Many patients also began neurotherapy, depending on the patient’s desire to be involved in this treatment modality.
Clinical Database Development: Characterization of EEG Phenotypes
Spectrum-weighted EEG Frequency ("Brain-Rate") as a Quantitative of Mental Arousal
A concept of brain-rate is introduced, defining it as the weighted mean frequency of the EEG spectrum. In analogue to the blood pressure, heart-rate and temperature, used as standard preliminary indicators of corresponding general bodily activations, it is proposed to use the brain-rate as a preliminary indicator of general mental activation (mental arousal) level. In addition, along with the more specific fewband biofeedback parameters (theta-beta ratio, relative beta ratio, etc.), the brain-rate could be effectively used as a general multiband biofeedback parameter.
The effect of QEEG-guided neurofeedback treatment in decreasing of OCD symptoms
Barzegary, L., Yaghubi, H., and Rostami, R. (2011). The effect of QEEG-guided neurofeedback treatment in decreasing of OCD symptoms. Procedia – Social and Behavioral Sciences, 30, 2659-2662.
The main purpose of this research is to determine effectiveness of QEEG-Guided Neurofeedback therapy in decreasing OCD symptoms. Twelve patients were selected from Atiyeh institution in Tehran – Iran and they are placed in 3 situations randomly which are neurofeedback, drug therapy and waiting list. Padua Inventory is administered for all patients as pre-test and post – test in 10 weeks. The results of this research using kuruskal – Wallis and Mann-whitney U test were analysed. It’s resulted that neurofeedback treatment may be used as a new treatment approach for treating OCD.
Obsessive compulsive disorder and the efficacy of QEEG-guided neurofeedback treatment: a case series
Surmeli, T., and Ertem, A. (2011). Obsessive compulsive disorder and the efficacy of QEEG-guided neurofeedback treatment: a case series. Clinical EEG and Neuroscience, 42(3), 195-201.
While neurofeedback (NF) has been extensively studied in the treatment of many disorders, there have been only three published reports, by D.C. Hammond, on its clinical effects in the treatment of obsessive compulsive disorder (OCD). In this paper the efficacy of qEEG-guided NF for subjects with OCD was studied as a case series. The goal was to examine the clinical course of the OCD symptoms and assess the efficacy of qEEG guidedNF training on clinical outcome measures. Thirty-six drug resistant subjects with OCD were assigned to 9-84 sessions of QEEG-guided NFtreatment. Daily sessions lasted 60 minutes where 2 sessions with half-hour applications with a 30 minute rest given between sessions were conducted per day. Thirty-three out of 36 subjects who received NF training showed clinical improvement according to the Yale-Brown obsessive-compulsive scale (Y-BOCS). The Minnesota multiphasic inventory (MMPI) was administered before and after treatment to 17 of the subjects. The MMPI results showed significant improvements not only in OCD measures, but all of the MMPI scores showed a general decrease. Finally, according to the physicians’ evaluation of the subjects using the clinical global impression scale (CGI), 33 of the 36 subjects were rated as improved. Thirty-six of the subjects were followed for an average of 26 months after completing the study. According to follow-up interviews conducted with them and/or their family members 19 of the subjects maintained the improvements in their OCD symptoms. This study provides good evidence for the efficacy of NF treatment in OCD. The results of this study encourage further controlled research in this area.
QEEG-Guided neurofeedback in the treatment of obsessive compulsive disorder
Hammond, C. (2003). QEEG-Guided neurofeedback in the treatment of obsessive compulsive disorder. Journal of Neurotherapy, 7, 25-52.
Introduction. Blinded, placebo-controlled research (e.g., Sterman, 2000) has documented the ability of brainwave biofeedback to recondition brain wave patterns. Neurofeedback has been used successfully with uncontrolled epilepsy, ADD/ADHD, learning disabilities, anxiety, and head injuries. However, nothing has been published on the treatment of obsessive-compulsive disorder (OCD) with neurofeedback.
Method. Quantitative EEGs were gathered on two consecutive OCD patients who sought treatment. This assessment guided protocol selection for subsequent neurofeedback training.
Results. Scores on the Yale-Brown Obsessive-Compulsive Scale and the Padua Inventory normalized following treatment. An MMPI was administered pre-post to one patient, and she showed dramatic improvements not only in OCD symptoms, but also in depression, anxiety, somatic symptoms, and in becoming extroverted rather than introverted and withdrawn. Discussion. In follow-ups of the two cases at 15 and 13 months after completion of treatment, both patients were maintaining improvements in OCD symptoms as measured by the Padua Inventory and as externally validated through contacts with family members. Since research has ound that pharmacologic treatment of OCD produces only very modest improvements and behavior therapy utilizing exposure with response prevention is experienced as quite unpleasant and results in treatment dropouts, neurofeedback appears to have potential as a new treatment modality.
Quantitative electoencephalographic subtyping of obsessive-compulsive disorder
Prichep, L. S., Francis, M., Hollander, E., Liebowitz, M., John, E. R., Almas, M., et al. (1993). Quantitative electoencephalographic subtyping of obsessive-compulsive disorder. Psychiatry Research: Neuroimaging, 50, 25-32.
Current neuropsychological, electrophysiological, and other imaging data strongly suggest the existence of a neurobiological basis for obsessive-compulsive disorder (OCD), which was long considered to be exclusively of psychogenic origin. The positive response of some OCD patients to neurosurgery, as well as the efficacy of agents that selectively block serotonin reuptake, lends further support to a biological involvement. However, a survey of the treatment literature reveals that only 45 – 62% of OCD patients improve with these specific medications. In a pilot study using a quantitative electroencephalographic (QEEG) method known as neurometrics, in which QEEG data from OCD patients were compared statistically with those from an age-appropriate normative population, we previously reported the existence of two subtypes of OCD patients within a clinically homogeneous group of patients who met DSM-III-Rcriteria for OCD. Following pharmacological treatment, a clear relationship was found between treatment response and neurometric cluster membership. In this study, we have expanded the OCD population, adding patients from a second site, and have replicated the existence of two clusters of patients in an enlarged, statistically more robust population. Cluster 1 was characterized by excess relative power in theta, especially in the frontal and frontotemporal regions; cluster 2 was characterized by increased relative power in alpha. Further, 80.0% of the members of cluster 1 were found to be nonresponders to drug treatment, while 82.4% of the members of cluster 2 were found to be treatment responders. These findings suggest the existence of at least two pathophysiological subgroups within the OCD population that share a common clinical expression, but show a differential response to treatment with serotonin reuptake inhibitors.
QEEG-Guided neurofeedback for recurrent migraine headaches
Walker, J. E. (2011). QEEG-Guided neurofeedback for recurrent migraine headaches. Clinical EEG and Neuroscience, 42, 59-61.
Seventy-one patients with recurrent migraine headaches, aged 17-62, from one neurological practice, completed a quantitativeelectroencephalogram (QEEG) procedure. All QEEG results indicated an excess of high-frequency beta activity (21-30 Hz) in 1-4 cortical areas. Forty-six of the 71 patients selected neurofeedback training while the remaining 25 chose to continue on drug therapy. Neurofeedback protocols consisted of reducing 21-30 Hz activity and increasing 10 Hz activity (5 sessions for each affected site). All the patients were classified as migraine without aura. For the neurofeedback group the majority (54%) experienced complete cessation of their migraines, and many others (39%) experienced a reduction in migraine frequency of greater than 50%. Four percent experienced a decrease in headache frequency of < 50%. Only one patient did not experience a reduction in headache frequency. The control group of subjects who chose to continue drug therapy as opposed to neurofeedback experienced no change in headache frequency (68%), a reduction of less than 50% (20%), or a reduction greater than 50% (8%). QEEG-guided neurofeedback appears to be dramatically effective in abolishing or significantly reducing headache frequency in patients with recurrent migraine.
Connectivity-guided neurofeedback for autistic spectrum disorder
Coben, R. (2007). Connectivity-guided neurofeedback for autistic spectrum disorder. Biofeedback, 35, 131-135.
Research on autistic spectrum disorder (ASD) has shown related symptoms to be the result of brain dysfunction in multiple brain regions. Functional neuroimaging and electroencephalography research have shown this to be related to abnormal neural connectivity problems. The brains of individuals with ASD show both areas of excessively high connectivity and areas with deficient connectivity. This article reviews emerging evidence that neurofeedback guided by connectivity data can remediate these connectivity anomalies leading to symptom reduction and functional improvement. This evidence raises the hopes for a behavioral, psychophysiological intervention moderating the severity of ASD. Both empirical data and a case example are presented to exemplify this approach.
QEEG-guided neurofeedback: New brain-based individualized evaluation and treatment for autism
Neubrander, J., Linden, M., Gunkelman, J., and Kerson, C. (2013). QEEG-guided neurofeedback: New brain-based individualized evaluation and treatment for autism. Autism Science Digest: The Journal of Autismone, 3, 91-100.
QEEG-guided neurofeedback is based on normalizing dysregulated brain regions that relate to specific clinical presentation. With ASD, this means that the approach is specific to each individual’s QEEG subtype patterns and presentation. The goal of neurofeedback with ASD is to correct amplitude abnormalities and balance brain functioning, while coherence neurofeedback aims to improve the connectivity and plasticity between brain regions. This tailored approach has implications that should not be underestimated. . . . Clinicians, including the authors, have had amazing results with ASD, including significant speech and communication improvements, calmer and less aggressive behavior, increased attention, better eye contact, and improved socialization. Many of our patients have been able to reduce or eliminate their medications after completion of QEEG-guided neurofeedback.
Functional neuroanatomy and the rationale for using EEG biofeedback for clients with Asperger's syndrome
Coben, R. (2007). Connectivity-guided neurofeedback for autistic spectrum disorder. Biofeedback, 35, 131-135.
Research on autistic spectrum disorder (ASD) has shown related symptoms to be the result of brain dysfunction in multiple brain regions. Functional neuroimaging and electroencephalography research have shown this to be related to abnormal neural connectivity problems. The brains of individuals with ASD show both areas of excessively high connectivity and areas with deficient connectivity. This article reviews emerging evidence that neurofeedback guided by connectivity data can remediate these connectivity anomalies leading to symptom reduction and functional improvement. This evidence raises the hopes for a behavioral, psychophysiological intervention moderating the severity of ASD. Both empirical data and a case example are presented to exemplify this approach.
On the application of quantitative EEG for characterizing autistic brain: a systematic review
Billeci, L., Sicca, F., Maharatna, K., Apicella, F., Narzisi, A., Campatelli, G., et al. (2013). On the application of quantitative EEG for characterizing autistic brain: a systematic review. Frontiers in Human Neuroscience, 7, 1-15.
Autism-Spectrum Disorders (ASD) are thought to be associated with abnormalities in neural connectivity at both the global and local levels. Quantitative electroencephalography (QEEG) is a non-invasive technique that allows a highly precise measurement of brain function and connectivity. This review encompasses the key findings of QEEG application in subjects with ASD, in order to assess the relevance of this approach in characterizing brain function and clustering phenotypes. QEEG studies evaluating both the spontaneous brain activity and brain signals under controlled experimental stimuli were examined. Despite conflicting results, literature analysis suggests that QEEG features are sensitive to modification in neuronal regulation dysfunction which characterize autistic brain. QEEG may therefore help in detecting regions of altered brain function and connectivity abnormalities, in linking behavior with brain activity, and subgrouping affected individuals within the wide heterogeneity of ASD. The use of advanced techniques for the increase of the specificity and of spatial localization could allow finding distinctive patterns of QEEG abnormalities in ASD subjects, paving the way for the development of tailored intervention strategies.
The importance of electroencephalogram assessment for autistic disorders
Coben, R. (2009). The importance of electroencephalogram assessment for autistic disorders. Biofeedback, 37, 71-80.
Autistic disorders are a set of complex syndromes that lead to challenges impacting communication, behavior repertoire, and social skills. The etiology of autism is unknown but is likely epigenetic in nature. It is likely associated with an inflammatory process leading to neuroinflammation in early childhood. Autistic disorders include seizures in approximately one-third of the cases and there are often regions of brain dysfunction associated with neural connectivity anomalies. The electroencephalogram (EEG) is presented as a premiere tool to assess these difficulties due to its non-invasive nature, availability and utility in detailing these difficulties. Techniques for seizure detection, monitoring, and tracing their propagation are shown. Similar approaches can then be utilized for assessing EEG oscillations, which are at the heart of these neuronal regulation dysfunctions. Autistic disorders are clearly associated with regions of dysfunction and quantitative electroencephalogram strategies for assessing these impairments are shown. These include techniques for increasing the specificity and spatial resolution of the EEG such as source localization and independent components analysis. Lastly, advanced methods for assessing the neural connectivity problems that underlie the difficulties of these children are presented. EEG assessment, when processed and analyzed with the most advanced techniques, can be invaluable in the evaluation of autistic disorders.
Quantitative electroencephalographic profiles for children with autistic spectrum disorder
Chan, A. S., Sze, S. L., and Cheung, M. C. (2007). Quantitative electroencephalographic profiles for children with autistic spectrum disorder. Neuropsychology, 21, 74-81.
The present study examined quantitative electroencephalographic (QEEG) profile for children with autistic spectrum disorder (ASD). Five-minute QEEG data were obtained from 90 normal controls (NCs) and 66 children with ASD. Spectrum analyses revealed that ASD children showed significantly less relative alpha and more relative delta than NC. Specifically, 26% of ASD children and 2% of NCs showed 1.5 SDs of relative alpha below the normative mean. Children with this QEEG profile had 17 times the risk of having ASD than those without such a profile. Sensitivity and specificity of relative alpha were 91% and 73%, respectively. Split-half cross-validation yielded a sensitivity of 76%.
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EEG abnormalities in adolescent males with AD/HD
Hobbs, M. J., Clarke, A. R., Barry, R. J., McCarthy, R., and Selikowitz, M. (2007). EEG abnormalities in adolescent males with AD/HD. Clinical Neurophysiology, 118, 363-371.
OBJECTIVES: This study investigated EEG abnormalities in adolescents with attention-deficit/hyperactivity disorder (AD/HD).
METHODS: Fifteen AD/HD subjects and 15 control subjects participated in this study. All subjects were between 14 and 17 years of age. The EEGwas recorded from 19 electrode sites and was analysed to provide estimates of both absolute and relative power in the delta, theta, alpha and beta bands. Theta/alpha and theta/beta ratio coefficients were also calculated.
RESULTS: Across the scalp, AD/HD subjects were characterised by greater absolute delta and theta activity, and an increased theta/beta ratio compared to controls. No group differences were found for either absolute or relative alpha, or absolute beta. However, AD/HD subjects demonstrated a reduction in relative beta activity in the posterior regions. CONCLUSIONS: The AD/HD group showed significant deviations from normal CNS development, in particular in posterior regions. This supports previous suggestions that individuals with an EEG profile that is not indicative of a maturational lag are more likely to have AD/HD during adolescence.
SIGNIFICANCE: This is the first study to investigate EEG abnormalities in adolescents with AD/HD during an eyes-closed resting condition.
EEG coherence in children with attention-deficit/hyperactivity disorder and comorbid oppositional defiant disorder
Barry, R. J., Clarke, A. R., McCarthy, R., and Selikowitz, M. (2007). EEG coherence in children with attention-deficit/hyperactivity disorder and comorbid oppositional defiant disorder. Clinical Neurophysiology, 118(2), 356-362.
OBJECTIVES: This study is the first to investigate EEG coherence differences between two groups of children with attention-deficit/hyperactivity disorder combined type (AD/HD), with or without comorbid oppositional defiant disorder (ODD), and normal control subjects.
METHODS: Each group consisted of 20 males. All subjects were between the ages of 8 and 12 years, and groups were matched on age. EEG was recorded during an eyes-closed resting condition from 21 monopolar derivations. Wave-shape coherence was calculated for 8 intrahemispheric electrode pairs (4 in each hemisphere), and 8 interhemispheric electrode pairs, within each of the delta, theta, alpha, and beta bands.
RESULTS: Children with comorbid AD/HD and ODD had intrahemispheric coherences at shorter inter-electrode distances significantly reduced from those apparent in children with AD/HD without comorbid ODD. Such reduced coherences in the comorbid group appeared to wash out coherence elevations previously noted in AD/HD studies. CONCLUSIONS: The present results suggest that, rather than suffering an additional deficit, children with AD/HD and comorbid ODD show significantly less CNS impairment than AD/HD patients without comorbid ODD. SIGNIFICANCE: These results have treatment implications, suggesting that behavioural training, perhaps using family-based cognitive behavioural therapy, could be useful for those children with AD/HD and comorbid ODD. This should focus on the ODD symptoms, in association with a medication regime focussed on the AD/HD symptoms.
EEG-defined subtypes of children with attention-deficit/hyperactivity disorder
Clarke, A. R., Barry, R. J., McCarthy, R., and Selikowitz, M. (2001). EEG-defined subtypes of children with attention-deficit/hyperactivity disorder. Clinical Neurophysiology, 112(11), 2098-2105.
OBJECTIVES: This study investigated the presence of EEG clusters within a sample of children with the combined type of attention-deficit/hyperactivity disorder (ADHD).
METHODS: Subjects consisted of 184 boys with ADHD and 40 age-matched controls. EEG was recorded from 21 sites during an eyes-closed resting condition and Fourier transformed to provide estimates for total power, and relative power in the delta, theta, alpha and beta bands, and for the theta/beta ratio. Factor analysis was used to group sites into 3 regions, covering frontal, central and posterior regions. These data were subjected to cluster analysis.
RESULTS: Three distinct EEG clusters of children with ADHD were found. These were characterized by (a) increased slow wave activity and deficiencies of fast wave, (b) increased high amplitude theta with deficiencies of beta activity, and (c) an excess beta group.
CONCLUSIONS: These results indicate that children with ADHD do not constitute a homogenous group in EEG profile terms. This has important implications for studies of the utility of EEG in the diagnosis of ADHD. Efforts aimed at using EEG as a tool to discriminate ADHD children from normals must recognize the variability within the ADHD population if such a tool is to be valid and reliable in clinical practice.
Peak alpha frequency: An electroencephalographic measure of cognitive preparedness
Angelakis, E. (2003). Peak alpha frequency: An electroencephalographic measure of cognitive preparedness. Journal of Neurotherapy, 7, 27-29.
OBJECTIVES: Electroencephalographic (EEG) peak alpha frequency (PAF) (measured in Hz) has been correlated to cognitive performance between healthy and clinical individuals, and among healthy individuals. PAF also varies within individuals across developmental stages, among different cognitive tasks, and among physiological states induced by administration of various substances. The present study suggests that, among other things, PAF reflects a trait or state of cognitive preparedness.
METHODS: Experiment 1 involved 19-channel EEG recordings from 10 individuals with traumatic brain injury (TBI) and 12 healthy matched controls, before, during, and after tasks of visual and auditory attention. Experiment 2 involved EEG recordings from 19 healthy young adults before and after a working memory task (WAIS-R Digit Span), repeated on 2 different days to measure within-individual differences. RESULTS: Experiment 1 showed significantly lower PAF in individuals with TBI, mostly during post-task rest. Experiment 2 showed PAF during pre-task baseline to be significantly correlated with Digit Span performance of the same day but not with Digit Span performance of another day. Moreover, PAF was significantly increased after Digit Span for those participants whose PAF was lower than the sample median before the task, but not for those who had it higher. Finally, both PAF and Digit Span performance were increased during the second day.
CONCLUSIONS: PAF was shown to detect both trait and state differences in cognitive preparedness, as well as to be affected by cognitive tasks. Traits are better reflected during post-task rest, whereas states are better reflected during initial resting baseline recordings.
Quantitative EEG abnormalities in a sample of dyslexic persons
Evans, J. R., and Park, N. (1996). Quantitative EEG abnormalities in a sample of dyslexic persons. Journal of Neurotherapy, 2, 1-5.
Definitions of terms such as dyslexia and specific reading disability commonly recognize a basis in central nervous system dysfunction. Past research has related this dysfunction to both structural and neural timing abnormalities. The present study used QEEG findings to provide further evidence for neural timing lcoherence abnormalities in reading disabled persons. Eight children and two adults were diagnosed with specific reading disability based on standard psychoeducational assessment. QEEGik were obtained from each using Laicor Neurosearch 24 equipment, and analyzed using the Thatcher Life Span Reference Data Base. Standard print-outs depicting coherence, phase, amplitude asymmetry, and relative power abnormalities of each subject were inspected, and tallies made of the most frequently occurring significant deviations from the norms. The folikwing abnormalities were found in 70% or more of the subjects: (1). abnormal coherence between one or more combination of sites P3, T5, T3, 01; (2) an equal to or greater than 1.4 11 ratio of left to right side coherence abnormalities; (3) coherence abnormalities between posterior sites more ofien involved decreased rather than increased coherence; (4) at least five abnormalities (or any type) involving site P3; (5) at least three abnormalities (coherence, phase, asymmetry) involving fiontal fpari – etal sites. These data appear to have relevance for neurofeedback. Phase lcoherence (neural timing) training and emphasis on site P3 may be especially useful in some cases of reading disability.
Different brain activation patterns in dyslexic children: evidence from EEG power and coherence patterns for the double-deficit theory of dyslexia
Arns, M., Peters, S., Breteler, R., and Verhoeven, L. (2007). Different brain activation patterns in dyslexic children: evidence from EEG power and coherence patterns for the double-deficit theory of dyslexia. Journal of Integrative Neuroscience, 6, 175-190.
AIMS: QEEG and neuropsychological tests were used to investigate the underlying neural processes in dyslexia.
METHODS: A group of dyslexic children were compared with a matched control group from the Brain Resource International Database on measures of cognition and brain function (EEG and coherence).
RESULTS: The dyslexic group showed increased slow activity (Delta and Theta) in the frontal and right temporal regions of the brain. Beta-1 was specifically increased at F7. EEG coherence was increased in the frontal, central and temporal regions for all frequency bands. There was a symmetric increase in coherence for the lower frequency bands (Delta and Theta) and a specific right-temporocentral increase in coherence for the higher frequency bands (Alpha and Beta). Significant correlations were observed between subtests such as Rapid Naming Letters, Articulation, Spelling and Phoneme Deletion and EEG coherence profiles.
DISCUSSION: The results support the double-deficit theory of dyslexia and demonstrate that the differences between the dyslexia and control group might reflect compensatory mechanisms. INTEGRATIVE SIGNIFICANCE: These findings point to a potential compensatory mechanism of brain function in dyslexia and helps to separate real dysfunction in dyslexia from acquired compensatory mechanisms.
