Brain Mapping: QEEG & Peak Agency
Quantitative EEG analysis, brain mapping techniques, and assessment protocols.
Research Library
We've curated 126 research papers for this use case. Dr. Hill and the Peak Brain team are reviewing and summarizing these papers to provide accessible, actionable insights.
Citations and abstracts shown below. Detailed summaries, key findings, and clinical applications will be added as reviews are completed.
Real-Time fMRI in Neuroscience Research and Its Use in Studying the Aging Brain
Cognitive decline is a major concern in the aging population. It is normative to experience some deterioration in cognitive abilities with advanced age such as related to memory performance, attention distraction to interference, task switching, and processing speed. However, intact cognitive functioning in old age is important for leading an independent day-to-day life. Thus, studying ways to counteract or delay the onset of cognitive decline in aging is crucial. The literature offers various explanations for the decline in cognitive performance in aging; among those are age-related gray and white matter atrophy, synaptic degeneration, blood flow reduction, neurochemical alterations, and change in connectivity patterns with advanced age. An emerging literature on neurofeedback and Brain Computer Interface (BCI) reports exciting results supporting the benefits of volitional modulation of brain activity on cognition and behavior. Neurofeedback studies based on real-time functional magnetic resonance imaging (rtfMRI) have shown behavioral changes in schizophrenia and behavioral benefits in nicotine addiction. This article integrates research on cognitive and brain aging with evidence of brain and behavioral modification due to rtfMRI neurofeedback. We offer a state-of-the-art description of the rtfMRI technique with an eye towards its application in aging. We present preliminary results of a feasibility study exploring the possibility of using rtfMRI to train older adults to volitionally control brain activity. Based on these first findings, we discuss possible implementations of rtfMRI neurofeedback as a novel technique to study and alleviate cognitive decline in healthy and pathological aging.
View Full Paper →High-Definition tDCS of Noun and Verb Retrieval in Naming and Lexical Decision
High-definition transcranial direct current stimulation (HD-tDCS) is a novel brain stimulation method that has high potential for use in language therapy for speakers with aphasia, due to its safety and focality. This study aimed to obtain foundational data on using HD-tDCS to modulate language processing in healthy speakers. Participants received stimulation either of Broca's area or of the left angular gyrus (20 min of anodal, cathodal, and sham stimulation on separate days), followed by naming and lexical decision tasks with single-word verb and noun stimuli. We found that cathodal stimulation over both Broca's area and the left angular gyrus increased naming speed for both verbs and nouns, challenging the traditional view of cathodal stimulation as suppressive or leading to decreased performance. The effect did not extend to the lexical decision task. Additionally, effects of specific stimulation types depended on the order of their administration, suggesting possible physiological carry-over and/or task novelty effects. These results are relevant to the application of HD-tDCS to enhance and direct neural plasticity in patients with neurogenic language disorders.
View Full Paper →Area-specific information processing in prefrontal cortex during a probabilistic inference task: a multivariate fMRI BOLD time series analysis
INTRODUCTION: Discriminating spatiotemporal stages of information processing involved in complex cognitive processes remains a challenge for neuroscience. This is especially so in prefrontal cortex whose subregions, such as the dorsolateral prefrontal (DLPFC), anterior cingulate (ACC) and orbitofrontal (OFC) cortices are known to have differentiable roles in cognition. Yet it is much less clear how these subregions contribute to different cognitive processes required by a given task. To investigate this, we use functional MRI data recorded from a group of healthy adults during a "Jumping to Conclusions" probabilistic reasoning task. METHODS: We used a novel approach combining multivariate test statistics with bootstrap-based procedures to discriminate between different task stages reflected in the fMRI blood oxygenation level dependent signal pattern and to unravel differences in task-related information encoded by these regions. Furthermore, we implemented a new feature extraction algorithm that selects voxels from any set of brain regions that are jointly maximally predictive about specific task stages. RESULTS: Using both the multivariate statistics approach and the algorithm that searches for maximally informative voxels we show that during the Jumping to Conclusions task, the DLPFC and ACC contribute more to the decision making phase comprising the accumulation of evidence and probabilistic reasoning, while the OFC is more involved in choice evaluation and uncertainty feedback. Moreover, we show that in presumably non-task-related regions (temporal cortices) all information there was about task processing could be extracted from just one voxel (indicating the unspecific nature of that information), while for prefrontal areas a wider multivariate pattern of activity was maximally informative. CONCLUSIONS/SIGNIFICANCE: We present a new approach to reveal the different roles of brain regions during the processing of one task from multivariate activity patterns measured by fMRI. This method can be a valuable tool to assess how area-specific processing is altered in psychiatric disorders such as schizophrenia, and in healthy subjects carrying different genetic polymorphisms.
View Full Paper →Fusion and Fission of Cognitive Functions in the Human Parietal Cortex
How is higher cognitive function organized in the human parietal cortex? A century of neuropsychology and 30 years of functional neuroimaging has implicated the parietal lobe in many different verbal and nonverbal cognitive domains. There is little clarity, however, on how these functions are organized, that is, where do these functions coalesce (implying a shared, underpinning neurocomputation) and where do they divide (indicating different underlying neural functions). Until now, there has been no multi-domain synthesis in order to reveal where there is fusion or fission of functions in the parietal cortex. This aim was achieved through a large-scale activation likelihood estimation (ALE) analysis of 386 studies (3952 activation peaks) covering 8 cognitive domains. A tripartite, domain-general neuroanatomical division and 5 principles of cognitive organization were established, and these are discussed with respect to a unified theory of parietal functional organization.
View Full Paper →Bluetooth Communication Interface for EEG Signal Recording in Hyperbaric Chambers
Recording biological signals inside a hyperbaric chamber poses technical challenges (the steel walls enclosing it greatly attenuate or completely block the signals as in a Faraday cage), practical (lengthy cables creating eddy currents), and safety (sparks hazard from power supply to the electronic apparatus inside the chamber) which can be overcome with new wireless technologies. In this technical report we present the design and implementation of a Bluetooth system for electroencephalographic (EEG) recording inside a hyperbaric chamber and describe the feasibility of EEG signal transmission outside the chamber. Differently from older systems, this technology allows the online recording of amplified signals, without interference from eddy currents. In an application of this technology, we measured EEG activity in professional divers under three experimental conditions in a hyperbaric chamber to determine how oxygen, assumed at a constant hyperbaric pressure of 2.8 ATA , affects the bioelectrical activity. The EEG spectral power estimated by fast Fourier transform and the cortical sources of the EEG rhythms estimated by low-resolution brain electromagnetic analysis were analyzed in three different EEG acquisitions: breathing air at sea level; breathing oxygen at a simulated depth of 18 msw, and breathing air at sea level after decompression.
View Full Paper →Z-score LORETA Neurofeedback as a Potential Therapy in Depression/Anxiety and Cognitive Dysfunction1www.TallahasseeNeuroBalanceCenter.com
Introduction of quantitative electroencephalogram low-resolution electromagnetic tomography (QEEG/LORETA) electrical brain imaging has improved our diagnostic ability in neuropsychiatric practice by enhancing identification of dysregulated (defined as two standard deviations above or below the norm) cortical areas implicated in patient symptoms. Additional use of LORETA Z-score neurofeedback (NFB) enables us to directly target these areas of dysregulation in order to improve associated symptoms. Out of 235 neuropsychiatric patients treated in our clinic with Z-score LORETA NFB, a detailed analysis of 35 cases of depression, anxiety, and cognitive dysfunction is presented. Specific areas of dysregulation attributed to particular conditions identified by LORETA are discussed. Follow-up findings of QEEG/LORETA electrical imaging after NFB therapy (including computerized cognitive testing results) are shown. This chapter summarizes our experience with LORETA Z-score NFB as a tool for therapy of depression and associated anxiety. In addition, this form of NFB is able to improve cognitive functions of individuals suffering from memory, information processing, and other cognitive dysfunctions. Extensive presentations of selected cases are used for demonstration of results from our practice. 25 out of 35 patients (71%) were identified as having an objective improvement (on average 10 points) through cognitive testing. In addition, with NFB subjective cognitive improvement and an objective reduction of QEEG abnormalities were also achieved in most of the patients. Detailed analysis of our patients diagnosed with depression and/or anxiety showed that out of 31 included in the study, 24 (77%) were found to have both subjective and objective (improvement of QEEG abnormalities) improvement of the symptoms within 10 sessions of LORETA Z-score NFB. These results are very promising and indicate good effectiveness of LORETA Z-score NFB in therapy of depression, anxiety, and cognitive enhancement.
Real-time fMRI processing with physiological noise correction - Comparison with off-line analysis
BACKGROUND: While applications of real-time functional magnetic resonance imaging (rtfMRI) are growing rapidly, there are still limitations in real-time data processing compared to off-line analysis. NEW METHODS: We developed a proof-of-concept real-time fMRI processing (rtfMRIp) system utilizing a personal computer (PC) with a dedicated graphic processing unit (GPU) to demonstrate that it is now possible to perform intensive whole-brain fMRI data processing in real-time. The rtfMRIp performs slice-timing correction, motion correction, spatial smoothing, signal scaling, and general linear model (GLM) analysis with multiple noise regressors including physiological noise modeled with cardiac (RETROICOR) and respiration volume per time (RVT). RESULTS: The whole-brain data analysis with more than 100,000voxels and more than 250volumes is completed in less than 300ms, much faster than the time required to acquire the fMRI volume. Real-time processing implementation cannot be identical to off-line analysis when time-course information is used, such as in slice-timing correction, signal scaling, and GLM. We verified that reduced slice-timing correction for real-time analysis had comparable output with off-line analysis. The real-time GLM analysis, however, showed over-fitting when the number of sampled volumes was small. COMPARISON WITH EXISTING METHODS: Our system implemented real-time RETROICOR and RVT physiological noise corrections for the first time and it is capable of processing these steps on all available data at a given time, without need for recursive algorithms. CONCLUSIONS: Comprehensive data processing in rtfMRI is possible with a PC, while the number of samples should be considered in real-time GLM.
View Full Paper →The Coordinated Allocation of Resource (CAR) Electrophysiological Patterns of Recalling Names of Faces in Children, Adolescents and Adults and the Central Processing Unit (CPU) of the Brain
The quantitative EEG (QEEG) has proven to be an important methodology in the understanding of brain functioning. The Coordinated Allocation of Resource (CAR) model maintains that cognitive effectiveness depends on the employment of a specific set of resources for specific cognitive tasks, which overlap in some situations. The model employs the flashlight metaphor in understanding the coherence and phase relations between locations. The metaphor asserts that each location can function as a flashlight that sends out a “beam” to the other locations within a frequency. The “beam” can involve all the other locations or be a mini-flashlight that involves only selected locations. The task of recalling names of faces was examined in the context of the CAR model. The developmental changes that occur during the encoding of names of faces include increases in diffusely located communication connections involving theta (4–8 Hz) and alpha (8–13 Hz), increases in the relative power values of the beta variables (13–64 Hz), peak frequency of beta1 (13–32 Hz) and alpha, decreases in communication patterns involving the beta2 (32–64 Hz) and delta (0–4 Hz) frequencies as well as decreasing values of variables involving the lower frequencies (delta, theta), relative power values of alpha and magnitudes of alpha, beta2 and peak amplitudes of beta2.The face-name task is both a verbal and visual task as the participant is hearing the name while he looks at the photograph. Variables that relate to success during the encoding task involve diffuse increases in flashlight activity from F7 and T3 across all frequencies to and between central locations. The QEEG variables that relate to immediate and delayed recall success involve flashlights from T3 across 4 frequencies, F7 involving 3 frequencies and the appearance of a heuristic “central processing unit” involving frontal (F3, Fz, F4), central (C3, Cz, C4) and posterior (P3, Pz, P4) locations.
View Full Paper →Resting state functional connectivity predicts neurofeedback response
Tailoring treatments to the specific needs and biology of individual patients—personalized medicine—requires delineation of reliable predictors of response. Unfortunately, these have been slow to emerge, especially in neuropsychiatric disorders. We have recently described a real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback protocol that can reduce contamination-related anxiety, a prominent symptom of many cases of obsessive-compulsive disorder (OCD). Individual response to this intervention is variable. Here we used patterns of brain functional connectivity, as measured by baseline resting-state fMRI (rs-fMRI), to predict improvements in contamination anxiety after neurofeedback training. Activity of a region of the orbitofrontal cortex (OFC) and anterior prefrontal cortex, Brodmann area (BA) 10, associated with contamination anxiety in each subject was measured in real time and presented as a neurofeedback signal, permitting subjects to learn to modulate this target brain region. We have previously reported both enhanced OFC/BA 10 control and improved anxiety in a group of subclinically anxious subjects after neurofeedback. Five individuals with contamination-related OCD who underwent the same protocol also showed improved clinical symptomatology. In both groups, these behavioral improvements were strongly correlated with baseline whole-brain connectivity in the OFC/BA 10, computed from rs-fMRI collected several days prior to neurofeedback training. These pilot data suggest that rs-fMRI can be used to identify individuals likely to benefit from rt-fMRI neurofeedback training to control contamination anxiety
EEG alpha power and creative ideation
► EEG Alpha activity is sensitive to different creativity-related demands. ► Creativity is associated with alpha increases at frontal and right parietal sites. ► Alpha increases during creative cognition reflect internal processing demands., Neuroscientific studies revealed first insights into neural mechanisms underlying creativity, but existing findings are highly variegated and often inconsistent. Despite the disappointing picture on the neuroscience of creativity drawn in recent reviews, there appears to be robust evidence that EEG alpha power is particularly sensitive to various creativity-related demands involved in creative ideation. Alpha power varies as a function of creativity-related task demands and the originality of ideas, is positively related to an individuals’ creativity level, and has been observed to increase as a result of creativity interventions. Alpha increases during creative ideation could reflect more internally oriented attention that is characterized by the absence of external bottom-up stimulation and, thus, a form of top-down activity. Moreover, they could indicate the involvement of specific memory processes such as the efficient (re-)combination of unrelated semantic information. We conclude that increased alpha power during creative ideation is among the most consistent findings in neuroscientific research on creativity and discuss possible future directions to better understand the manifold brain mechanisms involved in creativity.
View Full Paper →QEEG and 19-Channel Neurofeedback as a Clinical Evaluation Tool for Children with Attention, Learning and Emotional Problems
Attention, learning and emotional problems can have different causes that cannot be easily and clearly distinguished by clinical testing methods. But, QEEG and, even more so, live 19-channel Z-score training under different task conditions can both give very detailed insights about the specific functioning and dysregulations of an individual’s brain. The clinical intake evaluation of the child is optimized by including a quantitative, neurometric analysis of an eyes open (EO) and eyes closed (EC) EEG acquisition combined with a real-time analysis of the child’s (in vivo) brain functioning during a specific set of conditions, as described below. This method was developed and refined with more than 300 children who were tested between June 2012 and April 2014. The goal is to get as much information as possible in only one session lasting 45 to 60 minutes. The different parts of the evaluation consist of: eyes open (EO) and eyes closed (EC) collection of data, display of the actual brain waves, listing of the Z-score values (also presented as plots or instant brain maps with different task conditions), followed by games to play with a challenge condition. In addition, current source density (CSD) sLORETA of the different wave frequencies (usually delta, theta, alpha, beta, and gamma bands), distribution and velocity are shown as they change, as well as when the brain evaluates emotions. The session ends with a brief, individual 19-channel training with video feedback. Because of the usefulness of the information obtained from using this QEEG method, the author recommends that QEEG and an interactive neurofeedback session be included as a standard component in the diagnosis of and treatment planning for children with attention, learning and emotional problems.
View Full Paper →Near-Infrared Spectroscopy in Schizophrenia: A Possible Biomarker for Predicting Clinical Outcome and Treatment Response
Functional near-infrared spectroscopy (fNIRS) is a relatively new technique that can measure hemoglobin changes in brain tissues, and its use in psychiatry has been progressing rapidly. Although it has several disadvantages (e.g., relatively low spatial resolution and the possibility of shallow coverage in the depth of brain regions) compared with other functional neuroimaging techniques (e.g., functional magnetic resonance imaging and positron emission tomography), fNIRS may be a candidate instrument for clinical use in psychiatry, as it can measure brain activity in naturalistic position easily and non-invasively. fNIRS instruments are also small and work silently, and can be moved almost everywhere including schools and care units. Previous fNIRS studies have shown that patients with schizophrenia have impaired activity and characteristic waveform patterns in the prefrontal cortex during the letter version of the verbal fluency task, and part of these results have been approved as one of the Advanced Medical Technologies as an aid for the differential diagnosis of depressive symptoms by the Ministry of Health, Labor and Welfare of Japan in 2009, which was the first such approval in the field of psychiatry. Moreover, previous studies suggest that the activity in the frontopolar prefrontal cortex is associated with their functions in chronic schizophrenia and is its next candidate biomarker. Future studies aimed at exploring fNIRS differences in various clinical stages, longitudinal changes, drug effects, and variations during different task paradigms will be needed to develop more accurate biomarkers that can be used to aid differential diagnosis, the comprehension of the present condition, the prediction of outcome, and the decision regarding treatment options in schizophrenia. Future fNIRS researches will require standardized measurement procedures, probe settings, analytical methods and tools, manuscript description, and database systems in an fNIRS community.
View Full Paper →Brain's reward circuits mediate itch relief. a functional MRI study of active scratching
Previous brain imaging studies investigating the brain processing of scratching used an exogenous intervention mimicking scratching, performed not by the subjects themselves, but delivered by an investigator. In real life, scratching is a conscious, voluntary, controlled motor response to itching, which is directed to the perceived site of distress. In this study we aimed to visualize in real-time by brain imaging the core mechanisms of the itch-scratch cycle when scratching was performed by subjects themselves. Secondly, we aimed to assess the correlations between brain patterns of activation and psychophysical ratings of itch relief or pleasurability of scratching. We also compared the patterns of brain activity evoked by self-scratching vs. passive scratching. We used a robust tridimensional Arterial Spin Labeling fMRI technique that is less sensitive to motion artifacts: 3D gradient echo and spin echo (GRASE)--Propeller. Active scratching was accompanied by a higher pleasurability and induced a more pronounced deactivation of the anterior cingulate cortex and insula, in comparison with passive scratching. A significant involvement of the reward system including the ventral tegmentum of the midbrain, coupled with a mechanism deactivating the periaqueductal gray matter (PAG), suggests that itch modulation operates in reverse to the mechanism known to suppress pain. Our findings not only confirm a role for the central networks processing reward in the pleasurable aspects of scratching, but also suggest they play a role in mediating itch relief.
View Full Paper →Meditation states and traits: EEG, ERP, and neuroimaging studies.
Neuroelectric and imaging studies of meditation are reviewed. Electroencephalographic measures indicate an overall slowing subsequent to meditation, with theta and alpha activation related to proficiency of practice. Sensory evoked potential assessment of concentrative meditation yields amplitude and latency changes for some components and practices. Cognitive event-related potential evaluation of meditation implies that practice changes attentional allocation. Neuroimaging studies indicate increased regional cerebral blood flow measures during meditation. Taken together, meditation appears to reflect changes in anterior cingulate cortex and dorsolateral prefrontal areas. Neurophysiological meditative state and trait effects are variable but are beginning to demonstrate consistent outcomes for research and clinical applications. Psychological and clinical effects of meditation are summarized, integrated, and discussed with respect to neuroimaging data.
View Full Paper →Latest Developments in Live Z-Score Training: Symptom Check List, Phase Reset, and Loreta Z-Score Biofeedback
Advances in neuroscience are applied to the clinical applications of EEG neurofeedback by linking symptoms to functional networks in the brain. This is achieved by reviews of the last 20 years of functional neuroimaging studies of brain networks related to clinical disorders based on positron emission tomography, functional MRI, diffusion tensor imaging, and EEG/MEG inverse solutions. Considerable consistency exists between different imaging modalities because of the property of functional localization and the existence of large clusters of connections in the brain representing network modules and hubs. Reviewed here is new method of EEG neurofeedback called Z-Score Neurofeedback, and it is demonstrated how real-time comparison to an age-matched population of healthy subjects simplifies protocol generation and allows clinicians to target modules and hubs that indicate dysregulation and instability in networks related to symptoms. Z-score neurofeedback, by measuring the distance from the center of the healthy age-matched population, increases specificity in operant conditioning and provides a guide by which extreme Z-score outliers are linked to symptoms and then reinforced toward states of greater homeostasis and stability. The goal is increased efficiency of information processing in brain networks related to the patient's symptoms. The unique advantage of EEG over other neuroimaging methods is high temporal resolution in which the fine temporal details of phase lock and phase shift between large masses of neurons is quantified and can be modified by Z-score neurofeedback to address the patient's symptoms. The latest developments in Z-score neurofeedback are a harbinger of a bright future for clinicians and, most important, patients that suffer from a variety of brain dysfunctions.
Spatially aggregated multiclass pattern classification in functional MRI using optimally selected functional brain areas
In previous works, boosting aggregation of classifier outputs from discrete brain areas has been demonstrated to reduce dimensionality and improve the robustness and accuracy of functional magnetic resonance imaging (fMRI) classification. However, dimensionality reduction and classification of mixed activation patterns of multiple classes remain challenging. In the present study, the goals were (a) to reduce dimensionality by combining feature reduction at the voxel level and backward elimination of optimally aggregated classifiers at the region level, (b) to compare region selection for spatially aggregated classification using boosting and partial least squares regression methods and (c) to resolve mixed activation patterns using probabilistic prediction of individual tasks. Brain activation maps from interleaved visual, motor, auditory and cognitive tasks were segmented into 144 functional regions. Feature selection reduced the number of feature voxels by more than 50%, leaving 95 regions. The two aggregation approaches further reduced the number of regions to 30, resulting in more than 75% reduction of classification time and misclassification rates of less than 3%. Boosting and partial least squares (PLS) were compared to select the most discriminative and the most task correlated regions, respectively. Successful task prediction in mixed activation patterns was feasible within the first block of task activation in real-time fMRI experiments. This methodology is suitable for sparsifying activation patterns in real-time fMRI and for neurofeedback from distributed networks of brain activation.
View Full Paper →The Relation Between Memory Improvement and QEEG Changes in Three Clinical Groups as a Result of EEG Biofeedback Treatment
It is important to understand the relation between changes in the quantitative EEG (QEEG) variables and memory changes as a result of the EEG biofeedback treatment. With this goal in mind, the senior author reviewed his clinical files from the last 5 years and examined the QEEG data addressing relative power and coherence changes and memory (auditory and reading) improvements. The groups involved included (a) normal individuals wanting to improve their cognitive functioning, (b) traumatic brain injured (TBI) subjects, and (c) + (d) subjects who can best be classified as having a specific learning disability (SLD). The SLD group was divided between those who are (c) older than 14 (adults) and those who are (d) younger than 14 (children) in order to reference the appropriate age-related normative group values. The analysis revealed significant improvements in auditory and reading memory across all groups as well as changes on the QEEG variables. All of the groups were performing above the normative reference group on measures of auditory and reading memory in terms of percentage differences (24-97%) and standard deviations (+1.28-1.85). The average auditory memory SD improvement was +1.52, whereas the average percentage change was 82%. For the reading task the average memory standard deviation improvement was 1.38, whereas the percentage improvement was 154%. The experimental group was performing 1.66 SD (68%) above the control group on auditory memory and.90 SD (52%) above the control group on reading memory measures. For the QEEG variables, the average raw value of the Spectral Correlation Coefficient (SCC) change for alpha was 6.1 points (2.09 SD), for SCC beta1 (13-32 Hz) 6.53 points (1.81 SD), and for beta2 (32-64 Hz) 7.5 points (1.77 SD). The changes on the relative power measures were less dramatic, albeit significant. These results underlie the importance of addressing the SCC values in EEG biofeedback treatment protocols.
View Full Paper →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.
View Full Paper →EEG-Based Personalized Medicine in ADHD: Individual Alpha Peak Frequency as an Endophenotype Associated with Nonresponse
This review article summarizes some recent developments in psychiatry such as personalized medicine, employing biomarkers and endophenotypes, and developments collectively referred to as neuromodulation with a focus on ADHD. Several neurophysiological subtypes in ADHD and their relation to treatment outcome are reviewed. In older research the existence of an "abnormal EEG" or "paroxysmal EEG" was often reported, most likely explained by the high occurrence of this EEG subtype in autism, as the diagnosis of autism was not coined until 1980. This subgroup might respond best to anticonvulsant treatments, which requires more specific research. A second subgroup is a beta-excess or beta-spindling subgroup. This group responds well to stimulant medication, albeit several studies suggesting that neurophysiologically this might represent a different subgroup. The third subgroup consists of the "impaired vigilance" subgroup with the often-reported excess frontal theta or excess frontal alpha. This subgroup responds well to stimulant medication. Finally, it is proposed that a slow individual alpha peak frequency is an endophenotype related to treatment resistance in ADHD. Future studies should incorporate this endophenotype in clinical trials to further investigate new treatments for this substantial subgroup of patients, such as NIRS-biofeedback, transcranial Doppler sonography biofeedback, hyperbaric oxygen therapy, or medications such as nicotine and piracetam
View Full Paper →Application of Neurofeedback in General Neurology Practice
Neurofeedback (NFB), also called EEG biofeedback, is infrequently applied in general neurology practice. Therefore, this study was conducted to evaluate the clinical usefulness of NFB in neurological settings. Over the period of approximately 15 months, 25 subsequent patients who were interested in NFB therapy and completed at least 20 sessions of NFB treatment were analyzed for potential clinical benefits. Patients’ subjective responses were collected after NFB treatment to see if any improvement of symptoms was accomplished with NFB therapy. Quantitative electroencephalography (QEEG) was completed before and after NFB therapy initiation and analyzed for any major changes in frequency bands expression. Patients’ analysis revealed 84% subjective improvement rate and 75% objective QEEG improvement after completion of NFB therapy. These encouraging results indicate the need for more broad utilization of NFB in general neurology practice.
View Full Paper →Neurofeedback to improve neurocognitive functioning of children treated for a brain tumor: design of a randomized controlled double-blind trial
BACKGROUND: Neurotoxicity caused by treatment for a brain tumor is a major cause of neurocognitive decline in survivors. Studies have shown that neurofeedback may enhance neurocognitive functioning. This paper describes the protocol of the PRISMA study, a randomized controlled trial to investigate the efficacy of neurofeedback to improve neurocognitive functioning in children treated for a brain tumor. METHODS/DESIGN: Efficacy of neurofeedback will be compared to placebo training in a randomized controlled double-blind trial. A total of 70 brain tumor survivors in the age range of 8 to 18 years will be recruited. Inclusion also requires caregiver-reported neurocognitive problems and being off treatment for more than two years. A group of 35 healthy siblings will be included as the control group. On the basis of a qEEG patients will be assigned to one of three treatment protocols. Thereafter patients will be randomized to receive either neurofeedback training (n=35) or placebo training (n=35). Neurocognitive tests, and questionnaires administered to the patient, caregivers, and teacher, will be used to evaluate pre- and post-intervention functioning, as well as at 6-month follow-up. Siblings will be administered the same tests and questionnaires once. DISCUSSION: If neurofeedback proves to be effective for pediatric brain tumor survivors, this can be a valuable addition to the scarce interventions available to improve neurocognitive and psychosocial functioning. TRIAL REGISTRATION: ClinicalTrials.gov NCT00961922.
View Full Paper →Evaluating Prefrontal Activation and Its Relationship with Cognitive and Emotional Processes by Means of Hemoencephalography (HEG)
The main aim of this study is to determine the efficacy of the method of diagnosis known as hemoencephalography (HEG), which measures hemodynamic changes in the prefrontal cortex by determining differences in oxygen flow to show patterns of neuronal activity. Of the 5 tests designed for this purpose, 2 are strictly cognitive, while the other 3 have primarily emotional or sensitive content. The tests were applied to a sample of 70 university students. The Wilcoxon nonparametric signed rank test was applied to test the paired differences between the HEG baseline result and the HEG result of the task. Results show, first, that the HEG method successfully determines oxygen flow to the prefrontal cortex and clearly differentiates the subject's baseline from HEG activation during the task (Wilcoxon, p < .05); second, that HEG results vary depending on the type of activity, whether cognitive (low emotional load) or emotional (high emotional load) in such a way that cognitive areas, those located higher in the cortex (dorsolateral prefrontal), show less activity during emotional tests and more activity during cognitive tests, thus associating higher areas (dorsolateral prefrontal) with cognition and deeper areas (medial temporal, medial prefrontal, and cingulate) with emotion. The HEG procedure is effective in detecting states or situations of ailment or suffering not always accompanied by evident external manifestations. Furthermore, the procedure can differentiate between cognitive and emotional processing. The HEG method can help diagnosis in clinical settings due to its ability to detect painful-feeling processing independently of both body and verbal language.
View Full Paper →Amygdala lesions disrupt modulation of functional MRI activity evoked by facial expression in the monkey inferior temporal cortex
We previously showed that facial expressions modulate functional MRI activity in the face-processing regions of the macaque monkey’s amygdala and inferior temporal (IT) cortex. Specifically, we showed that faces expressing emotion yield greater activation than neutral faces; we term this difference the “valence effect.” We hypothesized that amygdala lesions would disrupt the valence effect by eliminating the modulatory feedback from the amygdala to the IT cortex. We compared the valence effects within the IT cortex in monkeys with excitotoxic amygdala lesions (n = 3) with those in intact control animals (n = 3) using contrast agent-based functional MRI at 3 T. Images of four distinct monkey facial expressions--neutral, aggressive (open mouth threat), fearful (fear grin), and appeasing (lip smack)--were presented to the subjects in a blocked design. Our results showed that in monkeys with amygdala lesions the valence effects were strongly disrupted within the IT cortex, whereas face responsivity (neutral faces > scrambled faces) and face selectivity (neutral faces > non-face objects) were unaffected. Furthermore, sparing of the anterior amygdala led to intact valence effects in the anterior IT cortex (which included the anterior face-selective regions), whereas sparing of the posterior amygdala led to intact valence effects in the posterior IT cortex (which included the posterior face-selective regions). Overall, our data demonstrate that the feedback projections from the amygdala to the IT cortex mediate the valence effect found there. Moreover, these modulatory effects are consistent with an anterior-to-posterior gradient of projections, as suggested by classical tracer studies.
View Full Paper →Impact of in-scanner head motion on multiple measures of functional connectivity: relevance for studies of neurodevelopment in youth
It has recently been reported (Van Dijk et al., 2011) that in-scanner head motion can have a substantial impact on MRI measurements of resting-state functional connectivity. This finding may be of particular relevance for studies of neurodevelopment in youth, confounding analyses to the extent that motion and subject age are related. Furthermore, while Van Dijk et al. demonstrated the effect of motion on seed-based connectivity analyses, it is not known how motion impacts other common measures of connectivity. Here we expand on the findings of Van Dijk et al. by examining the effect of motion on multiple types of resting-state connectivity analyses in a large sample of children and adolescents (n=456). Following replication of the effect of motion on seed-based analyses, we examine the influence of motion on graphical measures of network modularity, dual-regression of independent component analysis, as well as the amplitude and fractional amplitude of low frequency fluctuation. In the entire sample, subject age was highly related to motion. Using a subsample where age and motion were unrelated, we demonstrate that motion has marked effects on connectivity in every analysis examined. While subject age was associated with increased within-network connectivity even when motion was accounted for, controlling for motion substantially attenuated the strength of this relationship. The results demonstrate the pervasive influence of motion on multiple types functional connectivity analysis, and underline the importance of accounting for motion in studies of neurodevelopment.
View Full Paper →Clinical Efficacy of a New Automated Hemoencefalographic Neurofeedback Protocol
Among the ongoing attempts to enhance cognitive performance, an emergent and yet underrepresented venue is brought by hemoencefalographic neurofeedback (HEG). This paper presents three related advances in HEG neurofeedback for cognitive enhancement: a) a new HEG protocol for cognitive enhancement, as well as b) the results of independent measures of biological efficacy (EEG brain maps) extracted in three phases, during a one year follow up case study; c) the results of the first controlled clinical trial of HEG, designed to assess the efficacy of the technique for cognitive enhancement of an adult and neurologically intact population. The new protocol was developed in the environment of a software that organizes digital signal algorithms in a flowchart format. Brain maps were produced through 10 brain recordings. The clinical trial used a working memory test as its independent measure of achievement. The main conclusion of this study is that the technique appears to be clinically promising. Approaches to cognitive performance from a metabolic viewpoint should be explored further. However, it is particularly important to note that, to our knowledge, this is the world's first controlled clinical study on the matter and it is still early for an ultimate evaluation of the technique., Entre los intentos en curso para mejorar el rendimiento cognitivo, uno emergente y todavía insuficientemente representado es el neurofeedback hemoencefalográphico (HEG). Este trabajo presenta tres avances relacionados con HEG neurofeedback para la mejora cognitiva: a) un nuevo protocolo HEG para la mejora cognitiva, así como b) los resultados de las medidas independientes de la eficacia biológica (mapas cerebrales EEG) extraídos en tres fases durante un año estudio de seguimiento de casos; c) los resultados del primer ensayo clínico controlado de HEG, diseñado para evaluar la eficacia de la técnica para la mejora cognitiva de población adulta y neurológicamente sana. El nuevo protocolo fue desarrollado en el marco de un software que organiza algoritmos de señales digitales en un formato de diagrama de flujo. Los mapas de cerebro fueron producidos a través de 10 registros cerebrales. El ensayo clínico utilizó un test de memoria de trabajo como medida independiente de sus logros. La principal conclusión de este estudio es que la técnica parece ser clínicamente prometedora. Los enfoques para el rendimiento cognitivo desde un punto de vista metabólico deben investigarse más a fondo. Sin embargo, es particularmente importante tener en cuenta que, a nuestro entender, este es el primer estudio clínico controlado sobre el tema en el mundo, y aún es pronto para una evaluación final de la técnica.
View Full Paper →Symbol Digit and the Quantitative EEG
The coordination of allocation resource model of brain functioning examines the relations between quantitative EEG (QEEG) variables and cognitive performance on specific tasks. The Digit Symbol (DS) subtest of the Wechsler Adult Intelligence Scales has proven to be a sensitive measure in a variety of clinical conditions. A conceptually and empirically similar task (Symbol Digit [SD]) was employed to examine the QEEG correlates of successful functioning. A sample of 119 participants engaged in a modified SD test for 200 seconds while QEEG data were obtained. The participant verbally provided the matching number to the examiner to avoid any motor component of the task. There were negative relations between performance and magnitudes across almost all locations and across a wide bandwidth (0-64 Hz). Negative relations to SD performance were also observed for increased relative power of beta1, whereas positive relations were found for absolute values of coherences of alpha, beta1 (13-32 Hz), and beta2 (32-64 Hz). The results showed the importance of spectral correlation coefficients (SCC) in cognitive functioning, in particular the SCC values within the frontal region and in the 13-64 frequency range.
EVENT-RELATED POTENTIAL STUDY OF ATTENTION REGULATION DURING ILLUSORY FIGURE CATEGORIZATION TASK IN ADHD, AUTISM SPECTRUM DISORDER, AND TYPICAL CHILDREN
Autism spectrum disorders (ASD) and attention deficit/hyperactivity disorder (ADHD) are very common developmental disorders which share some similar symptoms of social, emotional, and attentional deficits. This study is aimed to help understand the differences and similarities of these deficits using analysis of dense-array event-related potentials (ERP) during an illusory figure recognition task. Although ADHD and ASD seem very distinct, they have been shown to share some similarities in their symptoms. Our hypothesis was that children with ASD will show less pronounced differences in ERP responses to target and non-target stimuli as compared to typical children, and to a lesser extent, ADHD. Participants were children with ASD (N=16), ADHD (N=16), and controls (N=16). EEG was collected using a 128 channel EEG system. The task involved the recognition of a specific illusory shape, in this case a square or triangle, created by three or four inducer disks. There were no between group differences in reaction time (RT) to target stimuli, but both ASD and ADHD committed more errors, specifically the ASD group had statistically higher commission error rate than controls. Post-error RT in ASD group was exhibited in a post-error speeding rather than corrective RT slowing typical for the controls. The ASD group also demonstrated an attenuated error-related negativity (ERN) as compared to ADHD and controls. The fronto-central P200, N200, and P300 were enhanced and less differentiated in response to target and non-target figures in the ASD group. The same ERP components were marked by more prolonged latencies in the ADHD group as compared to both ASD and typical controls. The findings are interpreted according to the “minicolumnar” hypothesis proposing existence of neuropathological differences in ASD and ADHD, specifically minicolumnar number/width morphometry spectrum differences. In autism, a model of local hyperconnectivity and long-range hypoconnectivity explains many of the behavioral and cognitive deficits present in the condition, while the inverse arrangement of local hypoconnectivity and long-range hyperconnectivity in ADHD explains some deficits typical for this disorder. The current ERP study supports the proposed suggestion that some between group differences could be manifested in the frontal ERP indices of executive functions during performance on an illusory figure categorization task.
The use of functional neuroimaging to evaluate psychological and other non-pharmacological treatments for clinical pain
A large number of studies have provided evidence for the efficacy of psychological and other non-pharmacological interventions in the treatment of chronic pain. While these methods are increasingly used to treat pain, remarkably few studies focused on the exploration of their neural correlates. The aim of this article was to review the findings from neuroimaging studies that evaluated the neural response to distraction-based techniques, cognitive behavioral therapy (CBT), clinical hypnosis, mental imagery, physical therapy/exercise, biofeedback, and mirror therapy. To date, the results from studies that used neuroimaging to evaluate these methods have not been conclusive and the experimental methods have been suboptimal for assessing clinical pain. Still, several different psychological and non-pharmacological treatment modalities were associated with increased pain-related activations of executive cognitive brain regions, such as the ventral- and dorsolateral prefrontal cortex. There was also evidence for decreased pain-related activations in afferent pain regions and limbic structures. If future studies will address the technical and methodological challenges of today's experiments, neuroimaging might have the potential of segregating the neural mechanisms of different treatment interventions and elucidate predictive and mediating factors for successful treatment outcomes. Evaluations of treatment-related brain changes (functional and structural) might also allow for sub-grouping of patients and help to develop individualized treatments.
View Full Paper →Covert waking brain activity reveals instantaneous sleep depth
The neural correlates of the wake-sleep continuum remain incompletely understood, limiting the development of adaptive drug delivery systems for promoting sleep maintenance. The most useful measure for resolving early positions along this continuum is the alpha oscillation, an 8-13 Hz electroencephalographic rhythm prominent over posterior scalp locations. The brain activation signature of wakefulness, alpha expression discloses immediate levels of alertness and dissipates in concert with fading awareness as sleep begins. This brain activity pattern, however, is largely ignored once sleep begins. Here we show that the intensity of spectral power in the alpha band actually continues to disclose instantaneous responsiveness to noise--a measure of sleep depth--throughout a night of sleep. By systematically challenging sleep with realistic and varied acoustic disruption, we found that sleepers exhibited markedly greater sensitivity to sounds during moments of elevated alpha expression. This result demonstrates that alpha power is not a binary marker of the transition between sleep and wakefulness, but carries rich information about immediate sleep stability. Further, it shows that an empirical and ecologically relevant form of sleep depth is revealed in real-time by EEG spectral content in the alpha band, a measure that affords prediction on the order of minutes. This signal, which transcends the boundaries of classical sleep stages, could potentially be used for real-time feedback to novel, adaptive drug delivery systems for inducing sleep.
View Full Paper →QEEG-guided neurofeedback for recurrent migraine headaches
Seventy-one patients with recurrent migraine headaches, aged 17-62, from one neurological practice, completed a quantitative electroencephalogram (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.
View Full Paper →A continuous mapping of sleep states through association of EEG with a mesoscale cortical model
Here we show that a mathematical model of the human sleep cycle can be used to obtain a detailed description of electroencephalogram (EEG) sleep stages, and we discuss how this analysis may aid in the prediction and prevention of seizures during sleep. The association between EEG data and the cortical model is found via locally linear embedding (LLE), a method of dimensionality reduction. We first show that LLE can distinguish between traditional sleep stages when applied to EEG data. It reliably separates REM and non-REM sleep and maps the EEG data to a low-dimensional output space where the sleep state changes smoothly over time. We also incorporate the concept of strongly connected components and use this as a method of automatic outlier rejection for EEG data. Then, by using LLE on a hybrid data set containing both sleep EEG and signals generated from the mesoscale cortical model, we quantify the relationship between the data and the mathematical model. This enables us to take any sample of sleep EEG data and associate it with a position among the continuous range of sleep states provided by the model; we can thus infer a trajectory of states as the subject sleeps. Lastly, we show that this method gives consistent results for various subjects over a full night of sleep and can be done in real time.
View Full Paper →Validity and Reliability of Quantitative Electroencephalography
Reliability and validity are statistical concepts that are reviewed and then applied to the field of quantitative electroencephalography (qEEG). The review of the scientific literature demonstrated high levels of split-half and test–retest reliability of qEEG and convincing content and predictive validity as well as other forms of validity. QEEG is distinguished fromnonquantitative EEG (“eyeball” examination of EEG traces), with the latter showing low reliability (e.g., 0.2–0.29) and poor interrater agreement for nonepilepsy evaluation. In contrast, qEEG is greater than 0.9 reliable with as little as 40-s epochs and remains stable with high test–retest reliability over many days and weeks. Predictive validity of qEEG is established by significant and replicable correlations with clinical measures and accurate predictions of outcome and performance on neuropsychological tests. In contrast, non-qEEG or eyeball visual examination of the EEG traces in cases of nonepilepsy has essentially zero predictive validity. Content validity of qEEG is established by correlations with independent measures such as the MRI, PET and SPECT, the Glasgow Coma Score, neuropsychological tests, and so on, where the scientific literature again demonstrates significant correlations between qEEG and independent measures known to be related to various clinical disorders. The ability to test and evaluate the concepts of reliability and validity are demonstrated by mathematical proof and simulation where one can demonstrate test–retest reliability as well as zero physiological validity of coherence and phase differences when using an average reference and Laplacian montage.
View Full Paper →Post WISC-R and TOVA Improvement with QEEG Guided Neurofeedback Training in Mentally Retarded: A Clinical Case Series of Behavioral Problems
According to the DSM-IV, Mental Retardation is significantly subaverage general intellectual functioning accompanied by significant limitations in adaptive functioning in at least two of the following skill areas: communication, self-care, home living, social/interpersonal skills, use of community resources, self-direction, functional academic skills, work, leisure, health and safety. In pilot work, we have seen positive clinical effects of Neurofeedback (NF) applied to children with Trisomy 21 (Down Syndrome) and other forms of mental retardation. Given that many clinicians use NF in Attention Deficit Hyperactivity Disorder and Generalized Learning Disability cases, we studied the outcomes of a clinical case series using Quantitative EEG (QEEG) guided NF in the treatment of mental retardation. All 23 subjects received NF training. The QEEG data for most subjects had increased theta, alpha, and coherence abnormalities. A few showed increased delta over the cortex. Some of the subjects were very poor in reading and some had illegible handwriting, and most subjects had academic failures, impulsive behavior, and very poor attention, concentration, memory problems, and social skills. This case series shows the impact of QEEG-guided NF training on these clients' clinical outcomes. Fourteen out of 23 subjects formerly took medications without any improvement. Twenty-three subjects ranging from 7–16 years old attending private learning centers were previously diagnosed with mental retardation (severity of degree: from moderate to mild) at various university hospitals. Evaluation measures included QEEG analysis, WISC-R (Wechsler Intelligence Scale for Children-Revised) IQ test, TOVA (Test of Variables of Attention) test, and DPC-P (Developmental Behaviour Checklist) were filled out by the parents. NF trainings were performed by Lexicor Biolex software. NX-Link was the commercial software reference database used to target the treatment protocols, along with the clinical judgment of the first author. QEEG signals were sampled at 128 samples per second per channel and electrodes were placed according to the International 10–20 system. Between 80 and 160 NF training sessions were completed, depending on the case. None of the subjects received any special education during NF treatment. Two subjects with the etiology of epilepsy were taking medication, and the other 21 subjects were medication-free at the baseline. Twenty-two out of 23 patients who received NF training showed clinical improvement according to the DPC-P with QEEG reports. Nineteen out of 23 patients showed significant improvement on the WISC-R, and the TOVA. For the WISC-R test, 2 showed decline on total IQ due to the decline on some of the subtests, 2 showed no improvement on total IQ although improvement was seen on some of the subtests, however even these cases showed improvement on QEEG and DPC-P. This study provides the first evidence for positive effects of NF treatment in mental retardation. The results of this study encourage further research.
View Full Paper →Neurotherapy of fibromyalgia?
OBJECTIVE: To evaluate the efficacy of a novel variant of electroencephalograph biofeedback, the Low Energy Neurofeedback System (LENS), that utilizes minute pulses of electromagnetic stimulation to change brainwave activity for the amelioration of fibromyalgia (FM) symptoms. DESIGN: Randomized, double-blind, placebo-controlled clinical trial. SETTING: Tertiary referral academic medical center, outpatient. PATIENTS: Thirty-four patients diagnosed with FM according to 1990 American College of Rheumatology classification criteria. INTERVENTIONS: Active or sham LENS, depending on randomization, for 22 treatment sessions. OUTCOME MEASURES: Primary outcome measure was the Fibromyalgia Impact Questionnaire total score. Secondary outcome measures included number of tender points (TPs) and pressure required to elicit TPs on physical examination, quantitative sensory testing heat pain threshold, and self-reported cognitive dysfunction, fatigue, sleep problems, global psychological distress, and depression obtained at baseline, immediate post-treatment, and 3- and 6-month follow-up. RESULTS: Participants who received the active or sham interventions improved (Ps < 0.05) on the primary and a variety of secondary outcome measures, without statistically significant between group differences in evidence at post-treatment or 3- or 6-month follow-up. Individual session self-reported ratings of specific symptoms (cognitive dysfunction, fatigue, pain, and sleep, and overall activity level) over the course of the 22 intervention sessions indicated significant linear trends for improvement for the active intervention condition only (Ps < 0.05). CONCLUSION: LENS cannot be recommended as a single modality treatment for FM. However, further study is warranted to investigate the potential of LENS to interact synergistically with other pharmacologic and nonpharmacologic therapies for improving symptoms in FM.
View Full Paper →The clinical use of quantitative EEG in cognitive disorders
The primary diagnosis of most cognitive disorders is clinically based, but the EEG plays a role in evaluating, classifying and following some of these disorders. There is an ongoing debate over routine use of qEEG. Although many findings regarding the clinical use of quantitative EEG are awaiting validation by independent investigators while confirmatory clinical follow-up studies are also needed, qEEG can be cautiously used by a skilled neurophysiologist in cognitive dysfunctions to improve the analysis of background activity, slow/fast focal activity, subtle asymmetries, spikes and waves, as well as in longitudinal follow-ups.
View Full Paper →Functional Neuroanatomy and the Rationale for Using EEG Biofeedback for Clients with Asperger’s Syndrome
This paper reviews the symptoms of Asperger’s Syndrome (AS), a disorder along the autism continuum, and highlights research findings with an emphasis on brain differences. Existing theories concerning AS are described, including theory of mind (Hill and Frith in Phil Trans Royal Soc Lond, Bull 358:281–289, 2003), mirror neuron system (Ramachandran and Oberman in Sci Am 295(5):62–69, 2006), and Porges’ (Ann N Y Acad Sci 1008:31–47, 2003, The neurobiology of autism, Johns Hopkins University Press, Baltimore, 2004) polyvagal theory. (A second paper, Outcomes using EEG Biofeedback Training in Clients with Asperger’s Syndrome, summarizes clinical outcomes obtained with more than 150 clients.) Patterns seen with QEEG assessment are then presented. Single channel assessment at the vertex (CZ) reveals patterns similar to those found in Attention-Deficit/Hyperactivity Disorder. Using 19-channel data, significant differences (z-scores > 2) were found in the amplitude of both slow waves (excess theta and/or alpha) and fast waves (beta) at various locations. Differences from the norm were most often found in mirror neuron areas (frontal, temporal and temporal-parietal). There were also differences in coherence patterns, as compared to a normative database (Neuroguide). Low Resolution Electromagnetic Tomography Analysis (Pascual-Marqui et al. in Methods Find Exp Clin Pharmacol 24C:91–95, 2002) suggested the source of the abnormal activity was most often the anterior cingulate. Other areas involved included the amygdala, uncus, insula, hippocampal gyrus, parahippocampal gyrus, fusiform gyrus, and the orbito-frontal and/or ventromedial areas of the prefrontal cortex. Correspondence between symptoms and the functions of the areas found to have abnormalities is evident and those observations are used to develop a rationale for using EEG biofeedback, called neurofeedback (NFB), intervention. NFB training is targeted to improve symptoms that include difficulty reading and mirroring emotions, poor attention to the outside world, poor self-regulation skills, and anxiety. Porges’ polyvagal theory is used to emphasize the need to integrate NFB with biofeedback (BFB), particularly heart rate variability training. We term this emerging understanding the Systems Theory of Neural Synergy. The name underscores the fact that NFB and BFB influence dynamic circuits and emphasizes that, no matter where we enter the nervous system with an intervention, it will seek its own new balance and equilibrium.
View Full Paper →QEEG-Based Protocol Selection: A Study of Level of Agreement on Sites, Sequences, and Rationales Among a Group of Experienced QEEG-Based Neurofeedback Practitioners
Background. The history of neurofeedback is marked by a diversity of theoretical bases and specific protocol development approaches, including standard protocols based on research, symptom/neurophysiological function-based approaches, and approaches based on quantitative electroencephalography (QEEG) assessment (Budzynski, 1999; Demos, 2005). Although this diversity of approaches currently characterizes clinical practice within the field, one might assume that a certain degree of uniformity exists among practitioners who follow one particular treatment model. That is, clinicians who follow a symptom/function-based approach might be expected to select similar protocols for a given client, and practitioners who base their protocols largely on QEEG likewise would develop similar protocols for the same client. Method. To test this latter assumption, 13 neurofeedback practitioners having 5 to 20 years of experience using QEEG and neurofeedback were sent the same QEEG data and presenting problems of a female adult who had previously sought neurofeedback treatment. The participant's data were edited in both NeuroReport and NeuroGuide, and both edits were provided to the survey participants. The practitioners were asked to provide treatment protocols covering sites, frequencies, sequences, and so on, as well as rationales that supported their protocol selections. Results. Ten of the 13 professionals contacted responded to the survey. Respondents were in general agreement as to which sites and frequencies to treat. However, they diverged in their sequencing of treatment sites; in whether to inhibit, reinforce, or both; in cautioning about reference contamination in the QEEG record; and in their theoretical rationales for their protocol selections. Conclusions. Although further research will have to document the efficacy of the various protocols recommended by the experienced QEEG-based practitioners surveyed for this study, it can be assumed that these practitioners are finding some consistent success using them in their practices. Therefore, the primary implication of this study appears to be that as long as appropriate treatment sites and frequencies are addressed for a given client, competently applied neurofeedback seems to be robust enough to tolerate a relatively wide diversity in specific protocol configurations.
View Full Paper →Eyes-Closed and Activation QEEG Databases in Predicting Cognitive Effectiveness and the Inefficiency Hypothesis
Background. Quantitative electroencephalography (QEEG) databases have been developed for the eyes closed (EC) condition. The development of a cognitive activation database is a logical and necessary development for the field. Method. Brain activation was examined by QEEG during several tasks including EC rest, visual attention (VA), auditory attention (AA), listening to paragraphs presented auditorily and reading silently. The QEEG measures obtained in the EC and simple, non-cognitive attention task that were significantly related to subsequent cognitive performance were not the same variables which accounted for success during the cognitive task. Results. There were clear differences between relative power, microvolt, coherence and phase values across these different tasks. Conclusions. The conclusions reached are (1) the associations among QEEG variables are complex and vary by task; (2) the QEEG variables which predict cognitive performance under task demands are not the same as the variables which predict to subsequent performance from the EC or simple, non-cognitive attention tasks; (3) a cognitive activation database is clinically useful; and (4) an hypothesis of brain functioning is proposed to explain the findings. The coordinated allocation of resources (CAR) hypothesis states that cognitive effectiveness is a product of multiple specific activities in the brain, which vary according to the task; and (5) the average response pattern does not involve the variables that are critical to success at the task, thus indicating an inefficiency of the normal human brain.
Introduction to Advances in EEG Connectivity
This special issue of the Journal of Neurotherapy has been devoted to Advances in EEG Connectivities. These purposes include providing education to our readers and collaboration among the scientists and authors. Multiple connectivity metrics have been defined with an emphasis on coherence and multivariate connectivity measures. The goals of connectivity measurements should include accuracy compared to known neurological networks and utility in assessment and application for intervention (e.g., EEG coherence training). It is hoped that the information contained in this special issue will form the basis for future advancements in EEG connectivity assessment and intervention.
View Full Paper →Connectivity Assessment and Training: A Partial Directed Coherence Approach
Background. The multivariate autoregressive (MVAR) method to generate a linear model of multichannel signal processes has been employed in many fields but not applied to the assessment of quantitative electroencephalographic (QEEG) connectivity neurofeedback. A measure known as Partial Directed Coherence (PDC) derived in the MVAR framework can offer insensitivity to volume conduction and ability to provide information relating to the direction of information flow between electrode locations, as a function of frequency during QEEG assessment and neurofeedback. Method. This article outlines a variety of reasons why PDC and other related metrics could play a more fundamental role in elucidating the causal relationships underlying EEG connectivity than can be provided though a multivariate analysis of coherence alone. Results. Real-time PDC neurofeedback implementation issues are discussed, technical challenges are outlined, and research questions are proposed. Conclusion. MVAR-based methods are an additional means of relating global to local EEG activity as well as helping to bridge QEEG assessment and neurofeedback protocol generation and treatment.
View Full Paper →Infrared Imaging and Neurofeedback: Initial Reliability and Validity
Introduction. The neurological correlates underlying positive treatment outcomes for neurofeedback have been either unavailable or difficult to demonstrate. Assessment of brain-related changes associated with neurofeedback is needed to further establish its empirical basis. Infrared (IR) imaging is a noninvasive assessment of brain activity with high spatial and temporal resolution. Method. Study 1, a reliability study, assessed the test-retest stability of IR imaging. In Validity Study 2 and 3, IR imaging assessed brain-related changes prior to and following neurofeedback and passive infrared hemoencephalography (pir HEG) training, respectively. Results. In Study 1, high correlations occurred in pre-post comparisons for IR measures unrelated to treatment. Lower correlation between measures of IR imaging indicated changes in brain activation associated with thermoregulation following neurofeedback training. In Study 2, changes in thermal regulation occurred both within and across sessions. The change in metabolic regulation was enduring and associated with a reduction in core Autistic Spectrum Disorder symptomatology and improved cerebral connectivity. In Study 3, a significant percentage of patients with Traumatic Brain Injury increased thermal readings following pir HEG training and the change in thermal readings was associated with EEG connectivity. Conclusion. Findings indicated that IR imaging may be a reliable and valid measure of treatment outcomes with clinical utility and sensitivity.
Atlas-based multichannel monitoring of functional MRI signals in real-time: automated approach
We report an automated method to simultaneously monitor blood-oxygenation-level-dependent (BOLD) MR signals from multiple cortical areas in real-time. Individual brain anatomy was normalized and registered to a pre-segmented atlas in standardized anatomical space. Subsequently, using real-time fMRI (rtfMRI) data acquisition, localized BOLD signals were measured and displayed from user-selected areas labeled with anatomical and Brodmann's Area (BA) nomenclature. The method was tested on healthy volunteers during the performance of hand motor and internal speech generation tasks employing a trial-based design. Our data normalization and registration algorithm, along with image reconstruction, movement correction and a data display routine were executed with enough processing and communication bandwidth necessary for real-time operation. Task-specific BOLD signals were observed from the hand motor and language areas. One of the study participants was allowed to freely engage in hand clenching tasks, and associated brain activities were detected from the motor-related neural substrates without prior knowledge of the task onset time. The proposed method may be applied to various applications such as neurofeedback, brain-computer-interface, and functional mapping for surgical planning where real-time monitoring of region-specific brain activity is needed.
View Full Paper →Functional Connectivity and Aging: Comodulation and Coherence Differences
Introduction. Misconceptions about coherence and comodulation has hindered their simultaneous use in assessing electroencephalography (EEG). Coherence refers to phase synchrony, whereas comodulation refers to magnitude synchrony. Child and adult EEG data were analyzed for age functions to demonstrate coherence and comodulation differences. Method. Eyes closed resting EEG was analyzed for 101 children and adults between ages of 5 and 35 years (34 female, 67 male; M age = 17.5 years). Spectral analysis focused on site-centered connectivity of 10 frequency bands. Site-centered connectivity refers to averaged coherence or comodulation associated with a site, an estimate of its network traffic. Results. Site-centered coherence and comodulation increased with age for frequencies below 30 Hz in most sites. Age-related changes in anterior connectivity occurred for adults but not for children. The strongest age function was found for alpha comodulation at electrode site T5. Differences in coherence and comodulation results are also reported. Conclusion. Functional connectivity increases steadily with age. Anterior EEG connectivity increased during adulthood but not during childhood. This finding parallels previous research on anterior callosal myelination and suggests that EEG connectivity measures may in part reflect myelination patterns. A model that associates coherence and comodulation with feedforward and feedback activity of the brain is proposed. A Periodicity Table for creating new and potentially relevant psychophysiological coefficients was described.
View Full Paper →An open-source hardware and software system for acquisition and real-time processing of electrophysiology during high field MRI
Simultaneous recording of electrophysiology and functional magnetic resonance imaging (fMRI) is a technique of growing importance in neuroscience. Rapidly evolving clinical and scientific requirements have created a need for hardware and software that can be customized for specific applications. Hardware may require customization to enable a variety of recording types (e.g., electroencephalogram, local field potentials, or multi-unit activity) while meeting the stringent and costly requirements of MRI safety and compatibility. Real-time signal processing tools are an enabling technology for studies of learning, attention, sleep, epilepsy, neurofeedback, and neuropharmacology, yet real-time signal processing tools are difficult to develop. We describe an open-source system for simultaneous electrophysiology and fMRI featuring low-noise (<0.6microV p-p input noise), electromagnetic compatibility for MRI (tested up to 7T), and user-programmable real-time signal processing. The hardware distribution provides the complete specifications required to build an MRI-compatible electrophysiological data acquisition system, including circuit schematics, print circuit board (PCB) layouts, Gerber files for PCB fabrication and robotic assembly, a bill of materials with part numbers, data sheets, and vendor information, and test procedures. The software facilitates rapid implementation of real-time signal processing algorithms. This system has been used in human EEG/fMRI studies at 3 and 7T examining the auditory system, visual system, sleep physiology, and anesthesia, as well as in intracranial electrophysiological studies of the non-human primate visual system during 3T fMRI, and in human hyperbaric physiology studies at depths of up to 300 feet below sea level.
View Full Paper →Towards a Coherent View of Brain Connectivity
Background. The electroencephalogram provides a myriad of opportunities to detect and assess brain function and brain connectivity. Method. This article describes the relationship between local and non-local brain activation and synchrony, and discusses the use of appropriate connectivity measures to study and train functional brain connectivity. Specific connectivity measures are described including coherence, phase, synchrony, correlation, and comodulation. The measures are contrasted and compared in terms of their ability to detect particular aspects of connectivity and their usefulness for neurofeedback training. Results. Connectivity metrics for example EEG data are calculated and shown graphically, to illustrate relevant principles. Conclusion. It is possible to assess brain connectivity and integrated function for both assessment and training, through the use of appropriate metrics and display methods.
View Full Paper →Test–retest reliability of resting EEG spectra validates a statistical signature of persons
Objective When EEG is recorded in humans, the question arises whether the resting EEG remains stable. We compared the inter-individual variation in spectral observables to the intra-individual stability over more than a year. Methods We recorded resting EEG in 55 healthy adults with eyes closed. In 20 persons EEG was recorded in a second session with retest intervals 12–40 months. For electrodes AFz, Cz and Pz α peak frequency and α peak height were transformed into Z-scores. We compared the curve shape of power spectra by first aligning α peaks to 10Hz and then regressing spectra pairwise onto each other to calculate a t-value. The t-value and differences of Z-scores for all pairs of sessions were entered into a generalized linear model (GLM) where binary output represents the recognition probability. The results were cross-validated by out-of-sample testing. Results Of the 40 sessions, 35 were correctly matched. The shape of power spectra contributed most to recognition. Out of all 2960 pairwise comparisons 99.5% were correct, with sensitivity 88% and specificity 99.5%. Conclusions Our statistical apparatus allows to identify those spectral EEG observables which qualify as statistical signature of a person. Significance The effect of external factors on EEG observables can be contrasted against their normal variability over time.
View Full Paper →What Is Quantitative EEG?
This article provides a basic description of quantitative electroencephalography (EEG) in the context of neurotherapeutic application. Issues associated with spectral analysis of human EEG are discussed and an example quantitative EEG assessment report is provided.
View Full Paper →A Modular Activation/Coherence Approach to Evaluating Clinical/QEEG Correlations and for Guiding Neurofeedback Training: Modular Insufficiencies, Modular Excesses, Disconnections, and Hyperconnections
Current approaches to QEEG-guided neurofeedback involve efforts to normalize the abnormalities seen, without reference to the functional localization of the cortical areas involved. Recent advances in cortical neurophysiology indicate that specific brain areas are developed to perform certain functions (cortical modules). Complex brain functions require cooperation between modules, particularly during a learning situation. For example, the left prefrontal “activation module” must cooperate with one or both occipital “visual modules” to attend and see something on a chalkboard. To remember what has been seen, both temporal “memory modules” must cooperate with the visual modules for the image to be retained in short-term memory. If the connections between these modules are not functioning optimally, visual learning will be impaired. Decreased coherence (hypocoherence) indicates a decrease in functional connectivity between these modules, and increased coherence (hypercoherence) indicates an increase in functional connectivity between the modules. Neurofeedback can be used to normalize coherence between these modules, thereby improving the efficiency of their cooperation in the learning process. If coherence is less than normal, it is trained up. If coherence is more than normal, it is trained down. Three cases are presented where this approach has succeeded in remediating the client's symptoms.
View Full Paper →Effects of Electrode Placement Upon EEG Biofeedback Training: The Monopolar-Bipolar Controversy
Roles of tradition, convenience, and noise or artifact rejection are discussed with regard to the referential versus bipolar electrode placement controversy in electroencephalography (EEG). Particular emphasis is placed on the relevance to neurofeedback. The crucial interactions between the differential amplifier, brain waves, and referential/bipolar placements are discussed. Through logical analysis and empirical observation, it is demonstrated how the very nature of the EEG differential amplifier must destroy those elements of brain activity which are common (synchronous) to the recording electrodes. Controlled experiments further illustrate the critical importance of electrode placements. Various methods, including preferred electrode placements, are presented to help resolve recording problems that frequently arise. It is concluded that there are serious implications for researchers, EEG clinicians, neurofeedback providers, and their clients in preferring one type of electrode placement technique over another. EEG recording information is affected by this choice.
View Full Paper →EEG alpha oscillations: The inhibition–timing hypothesis
The traditional belief is that the event-related alpha response can solely be described in terms of suppression or event-related desynchronization (ERD). Recent research, however, has shown that under certain conditions alpha responds reliably with an increase in amplitudes (event-related synchronization or ERS). ERS is elicited in situations, where subjects withhold or control the execution of a response and is obtained over sites that probably are under, or exert top-down control. Thus, we assume that alpha ERS reflects top-down, inhibitory control processes. This assumption leads over to the timing aspect of our hypothesis. By the very nature of an oscillation, rhythmic amplitude changes reflect rhythmic changes in excitation of a population of neurons. Thus, the time and direction of a change – described by phase – is functionally related to the timing of neuronal activation processes. A variety of findings supports this view and shows, e.g., that alpha phase coherence increases between task-relevant sites and that phase lag lies within a time range that is consistent with neuronal transmission speed. Another implication is that phase reset will be a powerful mechanism for the event-related timing of cortical processes. Empirical evidence suggests that the extent of phase locking is a functionally sensitive measure that is related to cognitive performance. Our general conclusion is that alpha ERS plays an active role for the inhibitory control and timing of cortical processing whereas ERD reflects the gradual release of inhibition associated with the emergence of complex spreading activation processes.
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