Clinical EEG and neuroscience最新文献

Introduction: The aim was to examine the differences in electroencephalography (EEG) findings by visual and automated quantitative analyses between Alzheimer's disease (AD) and dementia with Lewy bodies (DLB) and Parkinson's disease with dementia (PDD). Methods: EEG data of 20 patients with AD and 24 with DLB/PDD (12 DLB and 12 PDD) were retrospectively analyzed. Based on the awake EEG, the posterior dominant rhythm frequency and proportion of patients who showed intermittent focal and diffuse slow waves (IDS) were visually and automatically compared between the AD and DLB/PDD groups. Results: On visual analysis, patients with DLB/PDD showed a lower PDR frequency than patients with AD. In patients with PDR <8 Hz and occipital slow waves or patients with PDR <8 Hz and IDS, DLB/PDD was highly suspected (PPV 100%) and AD was unlikely (PPV 0%). On automatic analysis, the findings of the PDR were similar to those on visual analysis. Comparisons between visual and automatic analysis showed an overlap in the focal slow wave commonly detected by both methods in 10 of 44 patients, and concordant presence or absence of IDS in 29 of 43 patients. With respect to PDR <8 Hz and the combination of PDR <8 Hz and IDS, PPV and NPV in DLB/PDD and AD were not different between visual and automatic analysis. Conclusions: As the noninvasive, widely available clinical tool of low expense, visual analysis of EEG findings provided highly sufficient information to delineate different brain dysfunction in AD and DLB/PDD, and automatic EEG analysis could support visual analysis especially about PD.

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.

Objectives: Evaluate the diagnostic yield of 24-h video-EEG monitoring in a group of children admitted in our epilepsy monitoring unit (EMU). Methods: 232 children who underwent 24-h video-EEG monitoring was analysed. We divided each patient's monitoring duration into the first 1, 2, 4, 8, 16 h, relative to the whole 24 h monitoring period. The detection of the first interictal epileptiform discharges (IEDs), epileptic seizures (ES), and psychogenic non-epileptic seizures (PNES) were analysed relative to the different monitoring time subdivision. Results: Our findings revealed that: (1) there was no significant difference in the prevalence of detecting initial IEDs between the first 4-h and 24-h monitoring periods (73.7% vs 81%); (2) clinical events detection rate was statistically similar between the first 8-h and 24-h monitoring periods (15.5% vs 19.3%); (4) an 8-h monitoring was sufficient to capture IEDs, ES and PNES in focal epilepsy children; (5) a 1-h monitoring was sufficient to capture IEDs, ES and PNES in generalized epilepsy children; and (6) IEDs were detected within the first 1-h of monitoring in 96.7% self-limited focal epilepsies (SeLFEs) patient. Conclusion: Our study suggests that a 4-h monitoring has more value in increasing the detection rate of IEDs compared to the traditional shorter routine EEG. And in the case of SeLFEs, a 1-h of monitoring might be sufficient in detecting IEDs. A 24-h VEEG monitoring can detect clinical events in 19.3% of patients. Overall, the yield of IEDs and clinical events detection is adequate in children in children undergoing 24-h video-EEG monitoring.

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: Holmes tremor (HT) is a rare motor disorder characterized by high-amplitude and low-frequency resting, intentional, and postural tremors. HT typically arises from disruptions in neural pathways, including the dopaminergic system. Its causes include cerebrovascular incidents, neoplasms, demyelination, and infections. Diagnosis involves thorough clinical, neurophysiological, and neuroimaging assessments. Our report details the clinical profile, neuroimaging and EEG results and levodopa treatment response of an HT patient after cerebral arteriovenous malformation (AVM) surgery. Case Report: A female patient who underwent AVM surgery developed head tremor and dystonia. Neuroimaging revealed left thalamus involvement. Video electroencephalography (EEG) revealed high-amplitude, low-frequency tremors. The patient responded well to levodopa treatment. Conclusions: Involuntary rhythmic or non-rhythmic movements are a primary clinical feature of HT. A differential diagnosis of epilepsy and HT can be achieved through neurophysiological monitoring, avoiding the overuse of antiepileptic drugs. Symptoms can be alleviated with levodopa intervention.

Objectives: To perform spectral analysis on previously recorded electroencephalograms (EEGs) containing hypsarrhythmia in an initial recording and to assess changes in spectral power (µV²) in a follow-up recording after a period of 10-25 days. Methods: Fifty participants, aged 2-39 months, with hypsarrhythmia in an initial recording (R1), were compared with regard to their spectral findings in a later recording (R2). Typically, anticonvulsant therapy was initiated or modified after R1. Average delta, theta, alpha, and beta power was derived from approximately 3 min of artifact-free EEG data recorded from 19 electrode derivations. Group and individual changes in delta power between R1 and R2 formed the main analyses. Results: Delta accounted for 84% of the total power. In group comparisons, median delta power decreased statistically significantly between R1 and R2 in all 19 derivations, for example, from 3940 µV² in R1 to 1722 µV² in R2, Cz derivation. When assessing individual participants, delta power decreases in R2 were >50% in 60% of the participants, but <25% in 24% of the participants. Conclusion: Spectral analysis may be used as an additional tool for providing a potential biomarker in the assessment of short-term changes in hypsarrhythmia, including the effects of treatment.

Background. Epilepsy is prevalent in the elderly, whose brain morphologies and skull electrical characteristics differ from those of younger adults. Here, using a multivariate definition of signal-to-noise ratio (SNR), we explored the detectability of epileptic spikes in scalp EEG measurements in elderly by forward simulations of hypersynchronous spikes generated at 78 cortical regions of interest (ROIs) in the presence of background noise. Methods. Simulated electric potentials were measured at 18, 35, and 70 standard 10-20 electrode positions using three reference methods: infinity reference (INF), common average reference (CAR), and average mastoid reference (M1M2). MRIs of six elderly subjects were used to construct finite element method (FEM) models with age-adjusted skull conductivities. Results. SNRs of epileptic spikes increased with increasing sizes of the brain electrical source areas, although medial and deep brain regions such as the hippocampus showed lower SNRs, consistent with clinical findings. The SNRs were greater in the 70-channel dataset than in the 18-channel and 35-channel datasets, especially for ROIs located closer to the head surface. In addition, the SNRs were lower for the CAR and M1M2 references than for the ideal INF reference. Moreover, we found comparable results in the standard FEM heads with age-adjusted skull conductivities. Conclusions. The results provide insights for evaluating scalp EEG data in elderly patients with suspected epilepsy, and suggest that age-adjusted skull conductivity is an important factor for forward models in elderly adults, and that the standard FEM head with age-adjusted skull conductivity can be used when MRIs are not available.

Objective: Substance use disorders (SUD) still represent a huge worldwide health problem, as, despite withdrawal, medication, social support and psychotherapy, the relapse rate (around 80% at one year following treatment) remains tremendously high. Therefore, an important challenge consists in finding new complementary add-on tools to enhance quality of care. Methods and Results: In this report we focus on new insights reported through the use of three electrophysiological tools (quantitative electroencephalography (EEG), QEEG; cognitive event-related potentials, ERPs; and neurofeedback) suggesting that their use might be helpful at the clinical level in the management of various forms of SUDs. Empirical evidence were presented. Conclusion: In light of encouraging results obtained highlighting how these electrophysiological tools may be used in the treatment of SUDs, further studies are needed in order to facilitate the implementation of such procedures in clinical care units.

Dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD) are synucleinopathy syndromes with similar symptom profiles that are distinguished clinically based on the arbitrary rule of the time of symptom onset. Identifying reliable electroencephalographic (EEG) biomarkers would provide a precise method for better diagnosis, treatment, and monitoring of treatment response in these two types of dementia. From April 2015 to March 2021, the records of new referrals to a neurology clinic were retrospectively reviewed and 28 DLB(70.3% male) and 20 PDD (80.8% male) patients with appropriate EEG were selected for this study. Artifact-free 60-s EEG signals (21 channels) at rest with eyes closed were analyzed using EEGLAB, and regional spectral power ratios were extracted. Marked diffuse slowing was found in DLB patients compared to PDD patients in all regions in terms of decrease in alpha and increase in theta band. Although, these findings demean between groups after adjusting for MMSE scores, the significant difference still remained in terms of the mean relative alpha powers, particularly in the anterior and central regions. QEEG measures may have the potential to discriminate between these two syndromes. However, further prospective and longitudinal studies are required to improve the early differentiation of these dementia syndromes and to elucidate the underlying causes and pathogenesis and specific treatment.

Psychogenic non-epileptic seizures (PNES) are complex episodes that outwardly resemble epileptic seizures but are not caused by any underlying neurological disease. Unlike true epileptic seizures, PNES are more likely to be linked to psychological factors and do not show any abnormal activity on electroencephalography (EEG) recordings. This differentiation is crucial for accurate diagnosis and treatment, as misdiagnosing can lead to unnecessary treatments.Diagnosis of PNES might become difficult in the presence of particular benign EEG variants such as Rhythmic Midtemporal Discharges (RMTD). RMTD is a rare benign variant of normal EEG, characterized by rhythmic 5-7 Hz discharges in the temporal regions. This pattern could be present in normal individuals, in patients with psychiatric disorders or epilepsy. It could mimic interictal epileptiform discharges. Recognition of this pattern is essential to avoid misinterpretation of EEG findings that might eventuate in inappropriate treatment and adverse effects on a patient's medical condition, especially when there is a recent suspicious event in terms of an epileptic seizure. Among patients with PNES, the occurrence of benign variants might be much harder to interpret and physicians may mistakenly interpret RMTD on the EEG as indicative for epilepsy, especially in the absence of clear clinical criteria for PNES. This report is the first to document RMTD in first-degree relatives with PNES, suggesting a possible genetic predisposition and the need for further research into the interaction between RMTD and PNES.Our aim is to raise awareness that will enable accurate EEG reading and correct diagnosis.