Clinical EEG and Neuroscience最新文献

We report the first case of deep brain stimulator (DBS) artifact in the EEG of a pediatric patient. Our case is a 7-year-old male with bilateral globus pallidus interna (GPi) DBS for whom the EEG recorded a rhythmic 7.5 Hz theta activity on EEG related to DBS artifact. This artifact was also appreciated as a monochromatic invariable frequency band over 7.5 Hz on density spectral array (DSA). This rhythmic artifact may mimic an ictal pattern and should be recognized as artifact in order to avoid unnecessary treatment with anti-seizure medications (ASM).

Motor imagery (MI) signals recorded by electroencephalography provide the most practical basis for conceiving brain-computer interfaces (BCI). These interfaces offer a high degree of freedom. This helps people with motor disabilities communicate with the device by tackling a sequence of motor imagery tasks. However, the extracting user-specific features and increasing the accuracy of the classifier remain as difficult tasks in MI-based BCI. In this work, we propose a new method using artificial neural network (ANN) enhancing the performance of the motor imagery classification. Feature extraction techniques, like time domain parameters, band power features, signal power features, and wavelet packet decomposition (WPD), are studied and compared. Four classification algorithms are implemented which are Quadratic Discriminant Analysis, k-Nearest Neighbors, Linear Discriminant Analysis, and proposed ANN architecture. We added Batch Normalization layers to the proposed ANN architecture to improve the learning time and accuracy of the neural network. These layers also alleviate the effect of weight initialization and the addition of a regularization effect on the network. Our proposed method using ANN architecture achieves 0.5545 of kappa and 58.42% of accuracy on the BCI Competition IV-2a dataset. Our results show that the modified ANN method, with frequency and spatial features extracted by WPD and Common Spatial Pattern, respectively, offers a better classification compared to other current methods.

Background. Cue-reactivity as a characteristic symptom of substance use disorders (SUD) is highly context dependent. Paradigms with high context validity need to be established for the investigation of underlying neurobiological mechanisms. While craving can be assessed by self-report as one aspect of cue-reactivity (CR), the assessment of biological measures such as the autonomous response and EEG promises a holistic perspective including CR at an automatized level. In a multimodal approach, smoking cue exposure (CE) effects on heart rate variability (HRV), EEG frequency power, and craving as well as their interrelation were assessed. This pilot study focused on the validity of CR measurements in a naturalistic CE paradigm. Methods. EEG frequency power, HRV, and craving were assessed during resting state (RS) and smoking CE in smokers (n = 14) and nonsmoking controls (n = 10) to investigate the psychophysiological and subjective reactions to CE. Results. Increased beta power was found only in smokers during CE compared to the control condition. There was an inverse correlation of beta power and maximum craving. Likewise, HRV correlated negatively with maximum smoking urges in smokers immediately after the measurements, without differentiation between CE and control condition. Conclusion. The increased beta power in smokers during CE is discussed as increased inhibitory control related to reduced craving in smokers. Furthermore, increased craving during CE seems to be associated to decreased vagal activity. The multimodal measurements during the CE showed ecological validity to be fundamental for CE assessment in clinical populations to evaluate its predictive value.

Objective. To analyze the EEG features of four subacute sclerosing panencephalitis cases in North China. Methods. We retrospectively analyzed the EEG features in four patients with subacute sclerosing panencephalitis and 12 patients in control group from North China. Results. The periodic long-interval diffuse discharges were found in all of the four cases with subacute sclerosing panencephalitis. The morphology and component of periodic complexes were varied in different patients and different wakefulness states. Some EEG parameter settings help to identify periodic long-interval diffuse discharges including the slowed sweep speed, decreased sensitivity and reduced number of montages. In each patient with subacute sclerosing panencephalitis, the periodic long-interval diffuse discharges associated with two types of brief episodes (1:1) during awake period were found and none of the patients in the control group had this EEG pattern. The score system based on the periodic discharges and brief episodes also shows that all the patients with SSPE reached score 5 while none of the patients in the control group has a score greater than 3, which suggests that this EEG pattern may have diagnostic value. Conclusions. In subacute sclerosing panencephalitis, the morphology and component of periodic long-interval diffuse discharges were varied in different patients and different wakefulness states. Specific EEG parameter settings help to identify periodic long-interval diffuse discharges. Periodic long-interval diffuse discharges associated with two types of brief episodes (1:1) during awake period may strongly suggest the diagnosis of subacute sclerosing panencephalitis.

Purpose: The present study which addressed adults who stutter (AWS) attempted to investigate power spectral dynamics in the stuttering state by answering the questions using quantitative electroencephalography (qEEG). Method: A 64-channel electroencephalography (EEG) setup was used for data acquisition at 20 AWS. Since the speech, especially stuttering, causes significant noise in the EEG, 2 conditions of speech preparation (SP) and imagined speech (IS) were considered. EEG signals were decomposed into 6 bands. The corresponding sources were localized using the standard low-resolution electromagnetic tomography (sLORETA) tool in both fluent and dysfluent states. Results: Significant differences were noted after analyzing the time-locked EEG signals in fluent and dysfluent utterances. Consistent with previous studies, poor alpha and beta suppression in SP and IS conditions were localized in the left frontotemporal areas in a dysfluent state. This was partly true for the right frontal regions. In the theta range, disfluency was concurrence with increased activation in the left and right motor areas. Increased delta power in the left and right motor areas as well as increased beta2 power over left parietal regions was notable EEG features upon fluent speech. Conclusion: Based on the present findings and those of earlier studies, explaining the neural circuitries involved in stuttering probably requires an examination of the entire frequency spectrum involved in speech.

Background. Migraine headache may have a substantial bearing on the brain functions and rhythms. Electrophysiological methods can detect changes in brain oscillation. The present work examined the frequency band power through quantitative electroencephalogram (qEEG) and density spectral array (DSA) to elucidate the resting state neuronal oscillations in migraine. Methods. Clinical details were inquired, and EEG was recorded in migraineurs and healthy controls. The acquired data were analyzed to determine power spectral density values and obtain DSA graphs. The absolute and relative powers for the alpha, theta, and delta frequencies in frontocentral, parieto-occipital, and temporal regions were determined. A correlation of significant EEG findings with clinical features of migraine was sought. Results. Forty-five participants were enrolled in the study. The spectrum analysis revealed an increase in the relative theta power (P < .001) and a reduction in relative alpha power (P < .001) in the observed cortical areas among the migraineurs as compared to the healthy controls. Relative delta power was increased over the frontocentral region (P = .001), slightly more on the symptomatic side of the head. In addition, frontocentral delta power had a moderate positive correlation (r = .697, n = 22, P = .000) with migraine severity. Conclusion. The study supports the evidence of a neuronal dysfunction existing in the resting state during the ictal phase of migraine. qEEG can reveal these aberrant oscillations. Utility of DSA to depict the changes in brain activity in migraine is a potential area for research. The information can help formulate new therapeutic strategies towards alteration in cortical excitability using brain stimulation techniques.

Objective.The pathophysiology of amnestic mild cognitive impairment (aMCI) and Alzheimer disease (AD) is still a matter of debate. Visual system might be precociously altered, especially for its cholinergic connections. We thus studied patients with aMCI compared to AD with paired-pulse flash-visual evoked potentials (paired-F-VEPs), a putative marker of cholinergic function. Methods. We enrolled 12 adult patients with aMCI and 12 with AD. 14 normal age- and sex-matched subjects acted as controls (HS). Stimuli were single flashes, with interspersed random flash pairs at critical interstimulus intervals (ISIs, 16.5 to 125 ms) with closed eyes. The "single" (unconditioned) F-VEP was split into a "main complex" (50 to 200 ms after the flash) and a "late response" (200 to 400 ms). As for paired stimulation, the "test" F-VEP emerged from electronic subtraction of the "single" F-VEP from the "paired"-F-VEP. Results. In the single F-VEP, P2 latency was prolonged in patients (aMCI and AD) compared to HS (p < .05). As to the paired F-VEPs, in aMCI the "late response" normal inhibition was abolished at ISIs 50-62.5 ms (p ≤ .016), compared to AD and controls. No changes were detected for the "main complex". Conclusions. Paired-F-VEPs demonstrate a defective neural inhibition in the visual system of patients with aMCI at critical intervals. It may represent a compensatory mechanism against neuronal loss, the failure of which may be involved in AD development. Paired-F-VEPs may warrant inclusion in future preclinical/clinical studies, to evaluate its potential role in the pathophysiology and management of aMCI.

EEG neurofeedback (EEG-NFB) is a promising tool for the treatment of depressive disorders. However, many methods for the presentation of neurobiological reactions are available and it is widely unknown which of these feedback options are preferrable. Moreover, the influence of motivation on NFB training success is insufficiently studied. This study analyzed the efficacy of a novel EEG protocol (FC3/Pz) based on findings for NFB in depression. The role of four feedback options (Rumination, Anxiety, Meditation Master, Moving Art) from the NFB software "Brain Assistant" and motivation in EEG-based NFB performance was studied. Regarding "Anxiety" and "Rumination" visual feedback was used to evoke emotions; reinforcement (both negative and positive operant conditioning) was continuous. Regarding "Meditation Master" visual feedback was combined with continuous positive reinforcement. Regarding "Moving Art" 20-min calm nature films with neutral character were used; both visual and auditive feedback were applied. The reinforcement was positive and continuous. 13 healthy participants completed 15 EEG sessions over four months combining simultaneous frontal (aims: reduction of theta-, alpha- and high beta-activity, increase of low and mid beta-activity) and parietal training (aims: reduction of theta-, alpha 1-, mid and high beta-activity, increase of alpha 2- and low beta-activity). We observed significantly more pronounced percentage change in the expected direction for Anxiety than Moving Art (mean difference = 3.32; p = 0.003). The association between motivation and performance was non-significant. Based on these results we conclude that feedback with both negative and positive operant conditioning and emotion evoking effects should be preferred.