Effectiveness of Low-Resolution Brain Electromagnetic Tomography Z Score Neurofeedback Comparison with Cognitive Rehabilitation in Depression and Anxiety in Opioid Use Disorder.

Background: Previous studies have shown that conventional neurofeedback (NFB) and cognitive rehabilitation can improve psychological outcomes in people with opioid use disorders (OUDs). However, the effectiveness of Low-Resolution Brain Electromagnetic Tomography (LORETA) Z-score neurofeedback (LZNFB) and attention bias modification training (ABMT) on depression and anxiety of these people has not been investigated yet. The present study aims to compare the effect of these two methods on depression and anxiety of men with OUD under methadone maintenance therapy (MMT). Methods: In this randomized controlled clinical trial with a pre-test, post-test, and follow-up design, 30 men with OUD under MMT were randomly assigned into three groups of LZNFB, ABMT, and control (MMT alone). The LZNFB group underwent LZNFB at 20 sessions. The ABMT using the dot-probe task was provided individually to the second group for 2 weeks at 15 sessions. The Beck Anxiety Inventory and the Beck Depression Inventory were completed by the participants before, immediately after, and 1-month after interventions. The collected data were analyzed in SPSS v.22 software. Results: Both intervention groups showed a significant reduction in anxiety and depression at the post-test phase (p < 0.05), where LZNFB group showed more decrease in anxiety and depression than the ABMT group. This decrease continued in the follow-up period. Conclusion: Both LZNFB and ABMT with the dot-robe task are effective in reducing depression and anxiety of men with OUD under MMT. However, LZNFB is more effective. These findings add to the growing body of literature supporting the effectiveness of NFB and cognitive rehabilitation therapy in treating addiction-related comorbidities.

Comparing LORETA Z Score Neurofeedback and Cognitive Rehabilitation Regarding Their Effectiveness in Reducing Craving in Opioid Addicts.

Introduction: Previous studies have shown that conventional neurofeedback and cognitive modification treatments have numerous psychological benefits for patients with substance use disorders. However, the effectiveness of LORETA (Low-Resolution Brain Electromagnetic Tomography) Z Score Neurofeedback (LZNFB) and cognitive rehabilitation therapy in reducing opioid craving has not been investigated. Thus, the present study aimed to compare the effectiveness of LZNFB and cognitive rehabilitation therapy with Methadone Maintenance Treatment (MMT) in reducing craving in patients with opioid use disorder. Methods: Thirty patients with opioid use disorder undergoing MMT were randomly assigned into three groups: LZNFB with MMT, cognitive rehabilitation with MMT (as experimental groups), and MMT alone control group. The LZNFB and cognitive rehabilitation groups received 20 and 15 sessions of treatment, respectively. The three groups were assessed using several questionnaires and dot-probe task at pretest, posttest, and one-month follow-up. Results: The results showed that both experimental groups accomplished a significantly greater reduction in opioid craving than MMT alone group at posttest and follow-up (P<0.05). The LZNFB plus MMT group showed a greater decrease in opioid craving than the cognitive rehabilitation plus MMT group. In addition, the cognitive rehabilitation plus MMT group experienced greater improvement in attentional bias towards craving cues than the LZNFB with MMT group at posttest and follow-up. Finally, the LZNFB plus MMT group and cognitive rehabilitation plus MMT group got higher scores on the recovery assessment scale than MMT alone group at posttest and follow-up. According to study results, LZNFB training is more effective than cognitive rehabilitation in decreasing cravings and improving the quality of life in addiction to opioids. Conclusion: The current study's findings provided preliminary support for the effectiveness of LZNFB and cognitive rehabilitation in reducing opioid craving, improving attentional bias towards craving cues, and the quality of life among Iranian opioid use patients. Highlights: LZNFB training showed higher decrease in opioid craving than the Cognitive rehabilitation in opioid addicts.Cognitive rehabilitation group experienced greater improvement on attentional bias towards craving cues than LZNFB.LZNFB and Cognitive rehabilitation with MMT group got higher scores on the recovery assessment scale than MMT alone group.LZNFB training is more effective than Cognitive Rehabilitation in decreasing of craving in addiction. opioids. Plain Language Summary: Addiction is a chronic relapsing disease that makes many problems for human society. Routine medical treatments are not completely effective and they have relapse. New forms of non-medical treatments such as neurofeedback and cognitive rehabilitation are effective and safe without impressive side effects . This article shows the efficacy of above mentioned interventions for decrease craving and control of this problem.

Neuroscience20 (BRAIN20, SPINE20, and MENTAL20) Health Initiative: A Global Consortium Addressing the Human and Economic Burden of Brain, Spine, and Mental Disorders Through Neurotech Innovations and Policies.

Neurological disorders significantly impact the world's economy due to their often chronic and life-threatening nature afflicting individuals which, in turn, creates a global disease burden. The Group of Twenty (G20) member nations, which represent the largest economies globally, should come together to formulate a plan on how to overcome this burden. The Neuroscience-20 (N20) initiative of the Society for Brain Mapping and Therapeutics (SBMT) is at the vanguard of this global collaboration to comprehensively raise awareness about brain, spine, and mental disorders worldwide. This paper aims to provide a comprehensive review of the various brain initiatives worldwide and highlight the need for cooperation and recommend ways to bring down costs associated with the discovery and treatment of neurological disorders. Our systematic search revealed that the cost of neurological and psychiatric disorders to the world economy by 2030 is roughly $16T. The cost to the economy of the United States is $1.5T annually and growing given the impact of COVID-19. We also discovered there is a shortfall of effective collaboration between nations and a lack of resources in developing countries. Current statistical analyses on the cost of neurological disorders to the world economy strongly suggest that there is a great need for investment in neurotechnology and innovation or fast-tracking therapeutics and diagnostics to curb these costs. During the current COVID-19 pandemic, SBMT, through this paper, intends to showcase the importance of worldwide collaborations to reduce the population's economic and health burden, specifically regarding neurological/brain, spine, and mental disorders.

LORETA EEG phase reset of the default mode network.

OBJECTIVES: The purpose of this study was to explore phase reset of 3-dimensional current sources in Brodmann areas located in the human default mode network (DMN) using Low Resolution Electromagnetic Tomography (LORETA) of the human electroencephalogram (EEG). METHODS: The EEG was recorded from 19 scalp locations from 70 healthy normal subjects ranging in age from 13 to 20 years. A time point by time point computation of LORETA current sources were computed for 14 Brodmann areas comprising the DMN in the delta frequency band. The Hilbert transform of the LORETA time series was used to compute the instantaneous phase differences between all pairs of Brodmann areas. Phase shift and lock durations were calculated based on the 1st and 2nd derivatives of the time series of phase differences. RESULTS: Phase shift duration exhibited three discrete modes at approximately: (1) 25 ms, (2) 50 ms, and (3) 65 ms. Phase lock duration present primarily at: (1) 300-350 ms and (2) 350-450 ms. Phase shift and lock durations were inversely related and exhibited an exponential change with distance between Brodmann areas. CONCLUSIONS: The results are explained by local neural packing density of network hubs and an exponential decrease in connections with distance from a hub. The results are consistent with a discrete temporal model of brain function where anatomical hubs behave like a "shutter" that opens and closes at specific durations as nodes of a network giving rise to temporarily phase locked clusters of neurons for specific durations.

Quantitative EEG and neurofeedback in children and adolescents: anxiety disorders, depressive disorders, comorbid addiction and attention-deficit/hyperactivity disorder, and brain injury.

This article explores the science surrounding neurofeedback. Both surface neurofeedback (using 2-4 electrodes) and newer interventions, such as real-time z-score neurofeedback (electroencephalogram [EEG] biofeedback) and low-resolution electromagnetic tomography neurofeedback, are reviewed. The limited literature on neurofeedback research in children and adolescents is discussed regarding treatment of anxiety, mood, addiction (with comorbid attention-deficit/hyperactivity disorder), and traumatic brain injury. Future potential applications, the use of quantitative EEG for determining which patients will be responsive to medications, the role of randomized controlled studies in neurofeedback research, and sensible clinical guidelines are considered.

The psychological and neurological bases of leader self-complexity and effects on adaptive decision-making.

Complex contexts and environments require leaders to be highly adaptive and to adjust their behavioral responses to meet diverse role demands. Such adaptability may be contingent upon leaders having requisite complexity to facilitate effectiveness across a range of roles. However, there exists little empirical understanding of the etiology or basis of leader complexity. To this end, we conceptualized a model of leader self-complexity that is inclusive of both the mind (the complexity of leaders' self-concepts) and the brain (the neuroscientific basis for complex leadership). We derived psychometric and neurologically based measures, the latter based on quantitative electroencephalogram (qEEG) profiles of leader self-complexity, and tested their separate effects on the adaptive decision-making of 103 military leaders. Results demonstrated that both measures accounted for unique variance in external ratings of adaptive decision-making. We discuss how these findings provide a deeper understanding of the latent and dynamic mechanisms that underpin leaders' self-complexity and their adaptability.

Integration of XNAT/PACS, DICOM, and Research Software for Automated Multi-modal Image Analysis.

Traumatic brain injury (TBI) is an increasingly important public health concern. While there are several promising avenues of intervention, clinical assessments are relatively coarse and comparative quantitative analysis is an emerging field. Imaging data provide potentially useful information for evaluating TBI across functional, structural, and microstructural phenotypes. Integration and management of disparate data types are major obstacles. In a multi-institution collaboration, we are collecting electroencephalogy (EEG), structural MRI, diffusion tensor MRI (DTI), and single photon emission computed tomography (SPECT) from a large cohort of US Army service members exposed to mild or moderate TBI who are undergoing experimental treatment. We have constructed a robust informatics backbone for this project centered on the DICOM standard and eXtensible Neuroimaging Archive Toolkit (XNAT) server. Herein, we discuss (1) optimization of data transmission, validation and storage, (2) quality assurance and workflow management, and (3) integration of high performance computing with research software.

Coherence, phase differences, phase shift, and phase lock in EEG/ERP analyses.

Electroencephalogram (EEG) coherence is a mixture of phase locking interrupted by phase shifts in the spontaneous EEG. Average reference, Laplacian transforms, and independent component (ICA) reconstruction of time series can distort physiologically generated phase differences and invalidate the computation of coherence and phase differences as well as in the computation of directed coherence and phase reset. Time domain measures of phase shift and phase lock are less prone to artifact and are independent of volume conduction. Cross-frequency synchrony in the surface EEG and in Low Resolution Electromagnetic Tomography (LORETA) provides insights into dynamic functions of the brain.

Diffusion spectral imaging modules correlate with EEG LORETA neuroimaging modules.

OBJECTIVES: The purpose of this study was to test the hypothesis that the highest temporal correlations between 3-dimensional EEG current source density corresponds to anatomical Modules of high synaptic connectivity. METHODS: Eyes closed and eyes open EEG was recorded from 19 scalp locations with a linked ears reference from 71 subjects age 13-42 years. LORETA was computed from 1 to 30 Hz in 2,394 cortical gray matter voxels that were grouped into six anatomical Modules corresponding to the ROIs in the Hagmann et al.'s [2008] diffusion spectral imaging (DSI) study. All possible cross-correlations between voxels within a DSI Module were compared with the correlations between Modules. RESULTS: The Hagmann et al. [ 2008] Module correlation structure was replicated in the correlation structure of EEG three-dimensional current source density. CONCLUSIONS: EEG Temporal correlation between brain regions is related to synaptic density as measured by diffusion spectral imaging.

Subgenual cingulate theta activity predicts treatment response of repetitive transcranial magnetic stimulation in participants with vascular depression.

Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for depression. Increased metabolism in the anterior cingulate cortex (ACC) is a known predictor for antidepressant response. The authors assessed whether increased theta power within the ACC predicts rTMS response in participants with vascular depression. Sixty-five participants were randomized to active or sham rTMS. Outcome was assessed using the Hamilton Depression Rating Scale. Electroencephalography was obtained, and comparisons were made among each group with a normative database using low-resolution electromagnetic tomography. Results suggest that vascular depression participants respond well to rTMS and that increased low-theta power in the subgenual ACC predicts response to rTMS.

Antipsychotic effect of electroconvulsive therapy is related to normalization of subgenual cingulate theta activity in psychotic depression.

OBJECTIVE: Electroconvulsive therapy (ECT) is one of the most effective options available for treating depressive and psychotic symptoms in a variety of disorders. While the exact mechanism of ECT is unclear, it is known to increase metabolism and blood flow specifically in the anterior cingulate cortex (ACC). The ACC is a cortical generator of theta rhythms, which are abnormal in patients with depression and psychotic disorders. Since patients with psychotic depression are known to respond particularly robustly to ECT, we investigated whether the therapeutic effect of ECT in this population was related to normalization of abnormal theta activity in the ACC. METHOD: We obtained 19-lead electroencephalography (EEG) data from 17 participants with psychotic depression before and 2-3 weeks after a full course of ECT. EEG data was analyzed with quantitative measures and low-resolution electromagnetic tomography (LORETA) compared to an age-adjusted normative database. RESULTS: Quantitative EEG analyses revealed that theta band (4-7 Hz) activity was the only frequency band that changed with ECT. LORETA analyses revealed that the primary site of theta activity change was within the subgenual ACC (Brodmann area 25). There was a positive association between increased subgenual ACC theta activity and decreased psychotic symptoms. The degree of low theta activity in the subgenual ACC prior to ECT predicted the antipsychotic response of ECT. CONCLUSIONS: The antipsychotic effect of ECT is related to normalization of subgenual ACC theta hypoactivity.

Autism and EEG phase reset: deficient GABA mediated inhibition in thalamo-cortical circuits.

The purpose of this study was to explore the relationship between electroencephalogram (EEG) phase reset in autism spectrum disorder (ASD) subjects as compared to age matched control subjects. The EEG was recorded from 19 scalp locations from 54 autistic subjects and 241 control subjects ranging in age from 2.6 years to 11 years. Complex demodulation was used to compute instantaneous phase differences between all pairs of electrodes and the 1st and 2nd derivatives were used to measure phase reset by phase shift duration and phase lock duration. In both short (6 cm) and long (21-24 cm) inter-electrode distances phase shift duration in ASD subjects was significantly shorter in all frequency bands but especially in the alpha-1 frequency band (8-10 Hz) (p < .0001). Phase lock duration was significantly longer in the alpha-2 frequency band (10-12 Hz) in ASD subjects (p < .0001). An anatomical gradient was present with the occipital-parietal regions the most significant. The findings in this study support the hypothesis that neural resource recruitment occurs in the lower frequency bands and especially the alpha-1 frequency band while neural resource allocation occurs in the alpha-2 frequency band. The results are consistent with a general GABA inhibitory neurotransmitter deficiency resulting in reduced number and/or strength of thalamo-cortical connections in autistic subjects.

Development of cortical connections as measured by EEG coherence and phase delays.

The purpose of this study was to explore human development of EEG coherence and phase differences over the period from infancy to 16 years of age. The electroencephalogram (EEG) was recorded from 19 scalp locations from 458 subjects ranging in age from 2 months to 16.67 years. EEG coherence and EEG phase differences were computed for the left and right hemispheres in the posterior-to-anterior direction (O1/2-P3/4, O1/2-C3/4, O1/2-F3/4, and O1/2-Fp1/2) and the anterior-to- posterior direction (Fp1/2-F3/4, Fp1/2-C3/4, Fp1/2-P3/4, and Fp1/2-O1/2) in the beta frequency band (13-25 Hz). Sliding averages of EEG coherence and phase were computed using 1 year averages and 9 month overlapping that produced 64 means from 0.44 years of age to 16.22 years of age. Rhythmic oscillations in coherence and phase were noted in all electrode combinations. Different developmental trajectories were present for coherence and phase differences and for anterior-to-posterior and posterior-to-anterior directions and inter-electrode distance. Large changes in EEG coherence and phase were present from approximately 6 months to 4 years of age followed by a significant linear trend to higher coherence in short distance inter-electrode distances and longer phase delays in long inter-electrode distances. The results are consistent with a genetic model of rhythmic long term connection formation that occurs in cycles along a curvilinear trajectory toward adulthood. Competition for dendritic space, development of complexity, and nonlinear dynamic oscillations are discussed.

Quantitative EEG and the Frye and Daubert standards of admissibility.

The 70-year-old Frye standards of "general acceptance" were replaced by the Supreme Court's 1993 Daubert criteria of the scientific method, which established the standards for admissibility of evidence in Federal Court. The four Daubert criteria were: 1- Hypothesis testing, 2- Estimates of error rates, 3- Peer reviewed publication and 4- General acceptance (Daubert v. Merrell Dow Pharmaceuticals, 61 U.S.LW 4805 (U.S. June 29, 1993)). The present paper starts with the Daubert four factors and then matches them, step by step, to the scientific peer reviewed literature of quantitative EEG (QEEG) in relation to different clinical evaluations. This process shows how the peer reviewed science of the Digital EEG and the Quantitative EEG (QEEG) meet all of the Daubert standards of scientific knowledge. Furthermore, the science and technical aspects of QEEG in measuring the effects of neurological and psychiatric dysfunction also match the recent Supreme Court standards of "technical" and "other specialized" knowledge (General Electric Co v. Joiner, 1997, Kumho Tire Company, Ltd. v. Carmichael, 1999). Finally, it is shown that QEEG scientific knowledge and QEEG "technical" and "other specialized" knowledge meet the trilogy standards of the Supreme Court rulings in support of QEEG's admissibility as a clinically valid method in the evaluation of the nature and extent of neurological and psychiatric disorders.