Clinical EEG and neuroscience最新文献

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.

We report two cases of temporo-perisylvian epilepsy with habitual seizures consistently inducible by hyperventilation (HV). One case was non-lesional, while the other was a lesional temporo-perisylvian epilepsy. Both underwent surgical resection and were seizure-free or nearly seizure-free thereafter. We discuss the pathophysiological changes evoked by HV in healthy brains, and those with generalized and focal epilepsy. We provide a comprehensive and critical review of the literature on the role of HV in focal epilepsy. We suggest HV should be considered an activation method for patients with focal epilepsy during epilepsy monitoring unit admissions and may help in the localization of the epileptogenic network/zone.

As depressive symptom is considered a prodrome, a risk factor for progression from mild cognitive impairment (MCI) to dementia, improving depressive symptoms should be considered a clinical priority in patients with MCI undergoing transcranial direct current stimulation (tDCS) intervention. We aimed to comprehensively evaluate the efficacy of the home-based and remotely monitored tDCS in patients with both MCI and depression, by integrating cognitive, psychological, and electrophysiological indicators. In a 6-week, randomized, double blind, and sham-controlled study, 37 community-dwelling patients were randomly assigned to either an active or a sham stimulation group, and received 30 home-based sessions of 2 mA tDCS for 30 min with the anode located over the left and cathode over the right dorsolateral prefrontal cortex. We measured depressive symptoms, neurocognitive function, and resting-state electroencephalography. In terms of effects of both depressive symptoms and cognitive functions, active tDCS was not significantly different from sham tDCS. However, compared to sham stimulation, active tDCS decreased and increased the activation of delta and beta frequencies, respectively. Moreover, the increase in beta activity was correlated with the cognitive enhancement only in the active group. It was not possible to reach a definitive conclusion regarding the efficacy of tDCS on depression and cognition in patients with both MCI and depression. Nevertheless, the relationship between the changes of electrophysiology and cognitive performance suggests potential neuroplasticity enhancement implicated in cognitive processes by tDCS.

Objective: Obsessive-compulsive disorder (OCD) is a highly common psychiatric disorder. The symptoms of this condition overlap and co-occur with those of other psychiatric illnesses, making diagnosis difficult. The availability of biomarkers could be useful for aiding in diagnosis, although prior neuroimaging studies were unable to provide such biomarkers. Method: In this study, patients with OCD were classified from healthy controls using 2 different hybrid deep learning models: one-dimensional convolutional neural networks (1DCNN) together with long-short term memory (LSTM) and gradient recurrent units (GRU), respectively. Results: Both models exhibited exceptional classification accuracies in cross-validation and external validation phases. The mean classification accuracies in the cross-validation stage were 90.88% and 85.91% for the 1DCNN-LSTM and 1DCNN-GRU models, respectively. The inferior frontal, temporal, and occipital electrodes were predominant in providing discriminative features. Conclusion: Our findings underscore the potential of hybrid deep learning architectures utilizing EEG data to effectively differentiate patients with OCD from healthy controls. This promising approach holds implications for advancing clinical decision-making by offering valuable insights into diagnostic markers for OCD.

Background: Deficits in problem-solving may be related to vulnerability to suicidal behavior. We aimed to identify the electroencephalographic (EEG) power spectrum associated with the performance of the Raven as a reasoning/problem-solving task among individuals with recent suicide attempts. Methods: This study with the case-control method, consisted of 61 participants who were assigned to three groups: Suicide attempt + Major Depressive Disorder (SA + MDD), Major Depressive Disorder (MDD), and Healthy Control (HC). All participants underwent clinical evaluations and problem-solving abilities. Subsequently, EEG signals were recorded while performing the Raven task. Results: The SA + MDD and MDD groups were significantly different from the HC group in terms of anxiety, reasons for life, and hopelessness. Regarding brain oscillations in performing the raven task, increased theta, gamma, and betha power extending over the frontal areas, including anterior prefrontal cortex, dlPFC, pre-SMA, inferior frontal cortex, and medial prefrontal cortex, was significant in SA + MDD compared with other groups. The alpha wave was more prominent in the left frontal, particularly in dlPFC in SA + MDD. Compared to the MDD group, the SA + MDD group had a shorter reaction time, while their response accuracy did not differ significantly. Conclusions: Suicidal patients have more frontal activity in planning and executive function than the two other groups. Nevertheless, it seems that reduced activity in the left frontal region, which plays a crucial role in managing emotional distress, can contribute to suicidal tendencies among vulnerable individuals. Limitation The small sample size and chosen difficult trials for the Raven task were the most limitations of the study.

Introduction. Chronic pain is a percept due to an imbalance in the activity between sensory-discriminative, motivational-affective, and descending pain-inhibitory brain regions. Evidence suggests that electroencephalography (EEG) infraslow fluctuation neurofeedback (ISF-NF) training can improve clinical outcomes. It is unknown whether such training can induce EEG activity and functional connectivity (FC) changes. A secondary data analysis of a feasibility clinical trial was conducted to determine whether EEG ISF-NF training can significantly alter EEG activity and FC between the targeted cortical regions in people with chronic painful knee osteoarthritis (OA). Methods. A parallel, two-arm, double-blind, randomized, sham-controlled clinical trial was conducted. People with chronic knee pain associated with OA were randomized to receive sham NF training or source-localized ratio ISF-NF training protocol to down-train ISF bands at the somatosensory (SSC), dorsal anterior cingulate (dACC), and uptrain pregenual anterior cingulate cortices (pgACC). Resting state EEG was recorded at baseline and immediate post-training. Results. The source localization mapping demonstrated a reduction (P = .04) in the ISF band activity at the left dorsolateral prefrontal cortex (LdlPFC) in the active NF group. Region of interest analysis yielded significant differences for ISF (P = .008), slow (P = .007), beta (P = .043), and gamma (P = .012) band activities at LdlPFC, dACC, and bilateral SSC. The FC between pgACC and left SSC in the delta band was negatively correlated with pain bothersomeness in the ISF-NF group. Conclusion. The EEG ISF-NF training can modulate EEG activity and connectivity in individuals with chronic painful knee osteoarthritis, and the observed EEG changes correlate with clinical pain measures.

Background. EEG is an effective tool due to its ability to capture and interpret the changes in brain activity under different situations. Quantitative EEG (qEEG) can be essential in evaluating and treating children's learning problems. Methods and procedure. Fifty school-going children with difficulty in learning were studied. Analysis of the difference between pre-intervention and postintervention EEG power ratio of frequency bands, including Theta to Beta and Theta to Alpha, while eyes-closed, eyes-open, hyperventilation, writing, and reading conditions and the values for relative powers were calculated. The study correlated postintervention theta/beta ratio (TBR) and theta/alpha ratio (TAR) values with behavioral measures. Results. The findings suggested that there was a significant difference in pre-intervention and postintervention relative TAR and TBR power values. A significant increase of TAR and TBR power values was observed in eyes-closed (resting), hyperventilation, writing, and reading task conditions, indicative of a state of arousal at FP1FP2, T3T4, and O1O2 scalp locations. During eye open conditions, the TAR and TBR were significantly low at all 3 scalp locations, indicating a relaxed, conscious, and aware state of mind. Postintervention TAR and TBR values were significantly correlated with behavioral measures during 5 task conditions on several scalp locations. Conclusion. These quantitative electroencephalogram findings in children with learning problems indicate that with the increased complexity of the cognitive tasks, TAR and TBR increase, while postintervention, children could attain a relaxed and conscious state of mind during eyes-open condition.

Aim: Deviant visual processing has been observed in autism spectrum disorder (ASD), manifesting as decreased P1 and P2 components of visual event-related potentials (ERPs). Alterations have been attributed to a failure of Bayesian inference, characterized by hypo-activation of top-down predictive abilities. To test this hypothesis, we measured the visual negativity (vN) as an ERP index of visual preparation hypothesized to mirror predictive brain activity. Method: ERPs in a cued visual GO/NOGO task in 63 adolescents with ASD (IQ > 70, attention-deficit hyperactivity disorder excluded) were compared with ERPs in a sex- and age-matched group of 60 typically developing (TD) controls. Results: The behavioral variables (omissions, commissions, reaction time, and reaction time variability), as well as ERP components reflecting, among other processes, cognitive control (contingent negative variation, P3 GO, P3 NOGO, N2 NOGO) did not differ between the groups. There were group differences in visually based ERPs. Besides P1 and P2 differences, the vN component differentiated the 2 groups with the highest effect size (d  =  0.74).Conclusion: This ERP study lends support to the hypothesis suggesting that a Bayesian hypo-prediction could underlie unique perceptual experiences in individuals with ASD. This could lead to a predisposition to perceive the world with reduced influence and modulation from contextual cues, prior experiences, and pre-existing expectations.

Introduction. Nonlinear EEG provides information about dynamic properties of the brain. This study aimed to compare nonlinear EEG parameters estimated from patients with Long COVID in different cognitive and motor tasks. Materials and Methods. This 12-month prospective cohort study included 83 patients with Long COVID: 53 symptomatic and 30 asymptomatic. Brain electrical activity was evaluated by EEG in 4 situations: (1) at rest, (2) during the Trail Making Test Part A (TMT-A), (3) during the TMT Part B (TMT-B), and (4) during a coordination task: the Box and Blocks Test (BBT). Nonlinear EEG parameters were estimated in the time domain (activity and complexity). Assessments were made at 0 to 3, 3 to 6, and 6 to 12 months after inclusion. Results. There was a decrease in activity and complexity during the TMT-A and TMT-B, and an increase of these parameters during the BBT in both groups. There was an increase in activity at rest and during the TMT-A in the COVID-19 group at 0 to 3 months compared to the control, an increase in activity in the TMT-B in the COVID-19 group at 3 to 6 months compared to the control, and reduced activity and complexity at rest and during the TMT-A at 6 to 12 months compared to the control. Conclusion. The tasks followed a pattern of increased activity and complexity in cognitive tasks, which decreased during the coordination task. It was also observed that an increase in activity at rest and during cognitive tasks in the early stages, and reduced activity and complexity at rest and during cognitive tasks in the late phases of Long COVID.

Despite different etiologies, people with schizophrenia (SCZ) or with traumatic brain injury (TBI) both show aberrant neuroplasticity. One neuroplastic mechanism that may be affected is prediction error coding. We used a roving mismatch negativity (rMMN) paradigm which uses different lengths of standard tone trains and is optimized to assess predictive coding. Twenty-five SCZ, 22 TBI (mild to moderate), and 25 healthy controls were assessed. We used a frequency-deviant rMMN in which the number of standards preceding the deviant was either 2, 6, or 36. We evaluated repetition positivity to the standard tone immediately preceding a deviant tone (repetition positivity [RP], to assess formation of the memory trace), deviant negativity to the deviant stimulus (deviant negativity [DN], which reflects signaling of a prediction error), and the difference wave between the 2 (the MMN). We found that SCZ showed reduced DN and MMN compared with healthy controls and with people with mild to moderate TBI. We did not detect impairments in any index (RP, DN, or MMN) in people with TBI compared to controls. Our findings suggest that prediction error coding assessed with rMMN is aberrant in SCZ but intact in TBI, though there is a suggestion that severity of head injury results in poorer prediction error coding.