Age-related changes in event-related potentials in visual discrimination tasks

Visual event-related potentials and reaction times in physical and semantic discrimination tasks were studied in 29 normal subjects between the ages of 21 and 74 years. The NA, N2 and P3 components of the evoked potential, and simple and GO/NOGO reaction times were observed in both kinds of discrimination. Significant age-related slowing of the GO/NOGO reaction time was observed only in the semantic discrimination task. The N2 and P3 latencies elicited by both the physical and semantic stimuli were significantly and positively correlated with age, although there was no significant correlation between the NA latency and age. The interpeak latency between N2 and P3 showed no age-related changes. The decline of cognitive information processing with advancing age was evident from the classification of a perceived event as reflected by the N2 component.     

Classification of ADHD patients on the basis of independent ERP components using a machine learning system

Background

In the context of sensory and cognitive-processing deficits in ADHD patients, there is considerable evidence of altered event related potentials (ERP). Most of the studies, however, were done on ADHD children. Using the independent component analysis (ICA) method, ERPs can be decomposed into functionally different components. Using the classification method of support vector machine, this study investigated whether features of independent ERP components can be used for discrimination of ADHD adults from healthy subjects.

Methods

Two groups of age- and sex-matched adults (74 ADHD, 74 controls) performed a visual two stimulus GO/NOGO task. ERP responses were decomposed into independent components by means of ICA. A feature selection algorithm defined a set of independent component features which was entered into a support vector machine.

Results

The feature set consisted of five latency measures in specific time windows, which were collected from four different independent components. The independent components involved were a novelty component, a sensory related and two executive function related components. Using a 10-fold cross-validation approach, classification accuracy was 92%.

Conclusions

This study was a first attempt to classify ADHD adults by means of support vector machine which indicates that classification by means of non-linear methods is feasible in the context of clinical groups. Further, independent ERP components have been shown to provide features that can be used for characterizing clinical populations.

     

Operant conditioning of small birds for acoustic discrimination

Standard operant conditioning techniques have been successfully applied to the problem of call discrimination in small birds. Budgerigars (Melopsittacus undulatus) and canaries (Serinus canarius) were trained with a GO/NOGO procedure using positive reinforcement to discriminate between both conspecific contact calls and contact calls of the other species. Budgerigars showed equal facility at each task. By contrast, canaries learned the task involving conspecific contact calls but failed, as a group, to discriminate between budgerigar contact calls. These results show that conditioning techniques can be used to study perceptual learning of species typical calls in small birds.     

The effect of selective attention on pattern-specific visual evoked potentials

In a complex choice reaction time experiment, patterned stimuli without luminance change were presented, and pattern-specific visual evoked potentials to lower half-field stimulation were recorded. Two experimental conditions were used. The first was the between-field selection, where square patterns were presented in either the lower or the upper half of the visual field. In a given stimulus run one of the half-fields was task-relevant, and the subjects' task was to press a microswitch to stimuli of higher duration value (GO stimuli), while they had to ignore shorter ones, i. e. stimuli of lower apparent spatial contrast (NOGO stimuli). They had to ignore the stimuli appearing in the irrelevant half-field (IRR stimuli). In order to ensure proper fixation, the subjects had to press another microswitch at the onset of a dim light at the fixation point (CRT stimuli). Our second experimental condition was the within-field selection, where the GO, NOGO, and IRR stimuli appeared in the lower half of the visual field. GO and NOGO were square patterns while IRR stimuli were constructed of circles, or vice versa. (The CRT stimuli were the same as in the previous condition.) Three pattern-specific visual evoked potential components were identified, i. e. CI (70 ms latency), CII (100 ms latency), and CIII (170 ms latency). There were marked selective attention effects on both the CI-CII and CII-CIII peak-to-peak amplitudes. In both experimental conditions, responses with the highest amplitude were evoked by the GO type of stimuli, while the IRR stimuli evoked the smallest responses. According to these results, attention effects on the pattern-specific visual evoked potentials in the first 200 ms cannot be attributed to a simple stimulus set kind of selection.     

Does one hour of bright or short-wavelength filtered tablet screenlight have a meaningful effect on adolescents’ pre-bedtime alertness,sleep, and daytime functioning?

Electronic media use is prevalent among adolescent populations, as is the frequency of sleeplessness. One mechanism proposed for technology affecting adolescents’ sleep is the alerting effects from bright screens. Two explanations are provided. First, screens emit significant amounts of short-wavelength light (i.e. blue), which produces acute alertness and alters sleep timing. Second, later chronotypes are hypothesised to be hypersensitive to evening light. This study analysed the pre-sleep alertness (GO/NOGO task speed, accuracy; subjective sleepiness), sleep (sleep diary, polysomnography), and morning functioning of 16 healthy adolescents (M?=?17.4?±?1.9?yrs, 56% f) who used a bright tablet screen (80?lux), dim screen (1?lux) and a filtered short-wavelength screen (f.lux; 50?lux) for 1?hr before their usual bedtime in a within-subjects protocol. Chronotype was analysed as a continuous between-subjects factor; however, no significant interactions occurred. Significant effects occurred between bright and dim screens for GO/NOGO speed and accuracy. However, the magnitude of these differences was small (e.g. GO/NOGO speed?=?23?ms, accuracy?=?13%), suggesting minimal clinical significance. No significant effects were found for sleep onset latency, slow-rolling eye movements, or the number of SWS and REM minutes in the first two sleep cycles. Future independent studies are needed to test short (1?hr) vs longer (>2?hrs) screen usage to provide evidence for safe-to-harmful levels of screenlight exposure before adolescents’ usual bedtime.     

Improved Diagnosis in Children with Partial Epilepsy Using a Multivariable Prediction Model Based on EEG Network Characteristics

Background

Electroencephalogram (EEG) acquisition is routinely performed to support an epileptic origin of paroxysmal events in patients referred with a possible diagnosis of epilepsy. However, in children with partial epilepsies the interictal EEGs are often normal. We aimed to develop a multivariable diagnostic prediction model based on electroencephalogram functional network characteristics.

Methodology/Principal Findings

Routinely performed interictal EEG recordings at first presentation of 35 children diagnosed with partial epilepsies, and of 35 children in whom the diagnosis epilepsy was excluded (control group), were used to develop the prediction model. Children with partial epilepsy were individually matched on age and gender with children from the control group. Periods of resting-state EEG, free of abnormal slowing or epileptiform activity, were selected to construct functional networks of correlated activity. We calculated multiple network characteristics previously used in functional network epilepsy studies and used these measures to build a robust, decision tree based, prediction model. Based on epileptiform EEG activity only, EEG results supported the diagnosis of with a sensitivity and specificity of 0.77 and 0.91 respectively. In contrast, the prediction model had a sensitivity of 0.96 [95% confidence interval: 0.78–1.00] and specificity of 0.95 [95% confidence interval: 0.76–1.00] in correctly differentiating patients from controls. The overall discriminative power, quantified as the area under the receiver operating characteristic curve, was 0.89, defined as an excellent model performance. The need of a multivariable network analysis to improve diagnostic accuracy was emphasized by the lack of discriminatory power using single network characteristics or EEG''s power spectral density.

Conclusions/Significance

Diagnostic accuracy in children with partial epilepsy is substantially improved with a model combining functional network characteristics derived from multi-channel electroencephalogram recordings. Early and accurate diagnosis is important to start necessary treatment as soon as possible and inform patients and parents on possible risks and psychosocial aspects in relation to the diagnosis.     

Pattern classification of large-scale functional brain networks: identification of informative neuroimaging markers for epilepsy

The accurate prediction of general neuropsychiatric disorders, on an individual basis, using resting-state functional magnetic resonance imaging (fMRI) is a challenging task of great clinical significance. Despite the progress to chart the differences between the healthy controls and patients at the group level, the pattern classification of functional brain networks across individuals is still less developed. In this paper we identify two novel neuroimaging measures that prove to be strongly predictive neuroimaging markers in pattern classification between healthy controls and general epileptic patients. These measures characterize two important aspects of the functional brain network in a quantitative manner: (i) coordinated operation among spatially distributed brain regions, and (ii) the asymmetry of bilaterally homologous brain regions, in terms of their global patterns of functional connectivity. This second measure offers a unique understanding of brain asymmetry at the network level, and, to the best of our knowledge, has not been previously used in pattern classification of functional brain networks. Using modern pattern-recognition approaches like sparse regression and support vector machine, we have achieved a cross-validated classification accuracy of 83.9% (specificity: 82.5%; sensitivity: 85%) across individuals from a large dataset consisting of 180 healthy controls and epileptic patients. We identified significantly changed functional pathways and subnetworks in epileptic patients that underlie the pathophysiological mechanism of the impaired cognitive functions. Specifically, we find that the asymmetry of brain operation for epileptic patients is markedly enhanced in temporal lobe and limbic system, in comparison with healthy individuals. The present study indicates that with specifically designed informative neuroimaging markers, resting-state fMRI can serve as a most promising tool for clinical diagnosis, and also shed light onto the physiology behind complex neuropsychiatric disorders. The systematic approaches we present here are expected to have wider applications in general neuropsychiatric disorders.     

Multivariate EEG spectral analysis evidences the functional link between motor and visual cortex during integrative sensorimotor tasks

The identification of the networks connecting brain areas and the understanding of their role in executing complex tasks is a crucial issue in cognitive neuroscience. In this study, specific visuomotor tasks were devised to reveal the functional network underlying the cooperation process between visual and motor regions. Electroencephalography (EEG) data were recorded from twelve healthy subjects during a combined visuomotor task, which integrated precise grip motor commands with sensory visual feedback (VM). This condition was compared with control tasks involving pure motor action (M), pure visual perception (V) and visuomotor performance without feedback (V + M). Multivariate parametric cross-spectral analysis was applied to ten EEG derivations in each subject to assess changes in the oscillatory activity of the involved cortical regions and quantify their coupling. Spectral decomposition was applied to precisely and objectively determine the power associated with each oscillatory component of the spectrum, while surrogate data analysis was performed to assess the statistical significance of estimated coherence values. A significant decrease of the alpha and/or beta power in EEG spectra with respect to rest values was assumed as indicative of specific cortical area activation during task execution. Indeed alpha band coherence increased in proximity of task-involved areas, while it was suppressed or remained unchanged in other regions, suggesting the activation of a specific network for each task. According to our coherence analysis, a direct link between visual and motor areas was activated during V + M and VM tasks. The effect of visual feedback was evident in the beta band, where the increase of coherence was observed only during the VM task. Multivariate analysis suggested the presence of a functional link between motor and visual cortex subserving sensorimotor integration. Furthermore, network activation was related to the sum of single task (M and V) local effects in the alpha band, and to the presence of visual feedback in the beta band.     

Functional Brain Dysfunction in Patients with Benign Childhood Epilepsy as Revealed by Graph Theory

There is growing evidence that brain networks are altered in epileptic subjects. In this study, we investigated the functional connectivity and brain network properties of benign childhood epilepsy with centrotemporal spikes using graph theory. Benign childhood epilepsy with centrotemporal spikes is the most common form of idiopathic epilepsy in young children under the age of 16 years. High-density EEG data were recorded from patients and controls in resting state with eyes closed. Data were preprocessed and spike and spike-free segments were selected for analysis. Phase locking value was calculated for all paired combinations of channels and for five frequency bands (δ, θ, α, β₁ and β₂). We computed the degree and small-world parameters—clustering coefficient (C) and path length (L)—and compared the two patient conditions to controls. A higher degree at epileptic zones during interictal epileptic spikes (IES) was observed in all frequency bands. Both patient conditions reduced connection at the occipital and right frontal regions close to the epileptic zone in the α band. The “small-world” features (high C and short L) were deviated in patients compared to controls. A changed from an ordered network in the δ band to a more randomly organized network in the α band was observed in patients compared to healthy controls. These findings show that the benign epileptic brain network is disrupted not only at the epileptic zone, but also in other brain regions especially frontal regions.     

托吡酯与丙戊酸钠对癫痫患儿脑电活动及糖脂代谢的影响

目的:探讨托吡酯与丙戊酸钠对癫痫患儿脑电活动及相关代谢指标的影响。方法:选择66例癫痫患儿进行研究,并采用随机方法分为两组,其中观察组予托吡酯治疗,对照组予丙戊酸钠治疗。比较治疗前后患儿脑电活动及糖脂代谢指标差异。结果:治疗后,观察组患儿癫痫样放电(6.77±1.04)次、δ(12.77±2.32)次、θ(21.63±2.77)次、α(20.54±2.55)次、β(11.18±1.72)次均较治疗前和对照组明显减少(P0.05)。观察组患儿经治疗后体质指数(BMI)(14.43±1.29)kg/m2、空腹血糖(FPG)(4.53±0.51)mmol/L较治疗前和对照组明显减少(P0.05),空腹胰岛素(FINS)(9.78±1.44)m U/L较治疗前和对照组明显增加(P0.05)。两组患者经治疗后脂代谢各项指标甘油三酯(TG)、总胆固醇(TC)、低密度脂蛋白(L-DLD)、高密度脂蛋白(H-DLD)均较治疗前无明显变化(P0.05),且两组间比较无显著差异(P0.05)。结论:托吡酯能更有效控制癫痫患儿的脑电活动,但会导致糖代谢异常及患儿体质量指数减少,而丙戊酸钠对癫痫患儿糖脂代谢及体质量指数的影响较小,临床应根据具体情况合理选择用药。     

Altered Retinal Perfusion in Patients with Inactive Graves Ophthalmopathy Using Optical Coherence Tomography Angiography

Objective: The aim of this study was to evaluate retinal and optic nerve head (ONH) perfusion in patients with inactive Graves ophthalmopathy (GO) and compare it to healthy controls using optical coherence tomography angiography (OCTA).Methods: Twenty-nine eyes of 29 patients with inactive GO (study group) and 29 eyes of 29 healthy subjects (control group) were included in this study. The vessel density (VD) data in the superficial and deep retinal OCT angiogram of the macula and the radial peripapillary capillary network (RPC) were extracted and analyzed. OCTA was performed using RTVue XR Avanti with AngioVue (Optovue Inc, Fremont, CA). Clinical activity was evaluated using the clinical activity score, the severity assessment using the NOSPECS classification.Results: The VD in the superficial OCT angiogram and in the OCT angiogram of the ONH was significantly lower in the GO group when compared to the control group (whole en face, P = .016; parafovea, P = .026; RPC peripapillary, P = .027). There was no significant correlation between VD and functional parameters or the NOSPECS classification.Conclusion: Macular VD and ONH capillary density measured using OCTA were significantly lower in the study group compared to healthy controls. Noninvasive quantitative analysis of retinal perfusion using OCTA could be useful in monitoring patients with GO.Abbreviations: CAS = clinical activity score; GO = Graves ophthalmopathy; OCTA = optical coherence tomography angiography; ONH = optic nerve head; RPC = radial peripapillary capillary; rSp = Spearman's correlation coefficient; VD = vessel density     

白血病融合基因EVI1的多态性与白血病发生风险的相关性

目的:探讨白血病融合基因亲嗜性病毒整合位点1(ecotropic viral integration site-1,EVI1)的多态性与白血病发生风险的相关性。方法:选取本院2017年2月～2019年2月收治的骨刺患儿90例作为研究组,同期选择健康人群83例作为对照组。清晨空腹抽取两组入选者的外周静脉血2 mL,采用PCR方法检测两组入选者EVI1的多态性情况,调查一般资料并进行相关性分析。结果:EVI1 rs17561基因共有CC、CA、AA三种基因型,两组入选者的EVI1 rs17561基因分布均符合Hardy-Weinberg平衡定律,研究对象具有群体代表性。两组入选者EVI1 rs17561基因型分布差异具有统计学意义(P0.05),研究组的EVI1 rs17561基因CC基因型显著高于对照组(90.0%vs. 75.9%, P0.05),研究组的等位基因C频率(显著高于对照组(96.7%vs. 80.7%, P0.05)。在90例骨刺患儿中,6例患儿确诊为白血病,检出率为6.7%,均为CC基因型。研究组患儿EVI1 rs17561基因的CC基因型与血小板计数、危险度分层、诊断分型显著相关(P0.05)。多元Logistic回归分析显示血小板计数、危险度分层、诊断分型为影响EVI1rs17561CC基因型的主要因素(P0.05)。结论:白血病患儿融合基因EVI1多态性比较常见,多表现为rs17561CC等位基因,此等位基因可能与白血病患者的血小板计数、危险度分层、诊断分型显著相关,其中血小板计数、危险度分层、诊断分型为影响EVI1rs17561CC基因型的主要因素。     

癫痫发作间期alpha波的窄带相位同步分析

神经元同步化放电是癫痫发作的一个重要特征,作者提出并运用窄带相位同步技术对比分析了54个癫痫病人和10个正常成年人的脑电信号(EEG)数据.结果表明,相对于对照组,癫痫组的Alpha波的平均窄带相位同步值有显著下降(P=0.02058).为了更准确地刻画和衡量癫痫组和其对照组在同步模式上的差异,提出了一个新的具体的量化指标,即alpha波的窄带相位同步发散率.分析结果显示,对照组的窄带相位同步发散率明显低于癫痫组(P=0.003060),说明对照组的alpha波振子间互诱导强度更高.这可能反映了癫痫组窄带相位同步发散率的升高及所代表的alpha振子间互诱导强度的减弱与患者在癫痫发作间期的状态有密切的联系.     

菜心和水稻绿叶中不同等电点的乙醇酸氧化酶

The proteins with glycolate oxidase activity from B.parachinensis Bailey and rice( Oryza sativa )green leaves were prepared respectively.From the second protein peak on DEAE\|Cellulose column,two glycolate oxidases,expressed as B.parachinensis Bailey GO Ⅲ(specific activity natove 13 2 U·mg -1 ·min -1 )and rice GOⅢ(specific activity 8 8 U·mg -1 ·min -1 ),could not migrate anywhere in 4%～20% native\|PAGE under a pH8.3 buffer system.GOⅢ's p I was about pH8.3. The protein containing B.parachinensis Bailey GOⅢ showed 67±2,43±2,and 38±2 kD in SDS PAGE,band 43±2 kD was the subunit of B.parachinensis Bailey GOⅢ.From the two proteins above,another group of glycolate oxidases,expressed as B.parachinensis Beiley GOⅠ(specific activity 5 U·mg -1 ·min -1 )and rice GOⅠ(specific activity 1 2 U·mg -1 ·min -1 ),showed only one 43±2 kD band in SDS\|PAGE,and was purified on the Sepharose\|6B column which migrated towards anode in the same native\|PAGE showing the M r about 420 kD,or 460 kD and 260 kD respectively.GOⅠ's p I was smaller than pH8.3.Antibody against B.parachinensis Bailey GOⅠ was prepared and its efficacy was about 1/1600 in ELISA.By native\|PAGE,Western blot and rocket immunoelectrophoresis,the third group of glycolate oxidases,expressed as B.parachinensis Bailey GOⅡ and rice G0Ⅱ,were confirmed in crude protein of green leaves and migrated towards cathode under the same native\|PAGE,so GOⅡ's p I was higher than pH8.3.The M r of B.parachinensis Bailey GOⅡ was about 669 kD determined by native\|PAGE Western blot.Rice GOⅠ,rice GOⅢ and rice GOⅡ showed different quantitation under different physiological conditions.Rice GOⅡ could be induced by glycolate.     

Multiple characteristics analysis of Alzheimer’s electroencephalogram by power spectral density and Lempel–Ziv complexity

To investigate the electroencephalograph (EEG) background activity in patients with Alzheimer’s disease (AD), power spectrum density (PSD) and Lempel–Ziv (LZ) complexity analysis are proposed to extract multiple effective features of EEG signals from AD patients and further applied to distinguish AD patients from the normal controls. Spectral analysis based on autoregressive Burg method is first used to quantify the power distribution of EEG series in the frequency domain. Compared with the control group, the relative PSD of AD group is significantly higher in the theta frequency band while lower in the alpha frequency bands. In order to explore the nonlinear information, Lempel–Ziv complexity (LZC) and multi-scale LZC is further applied to all electrodes for the four frequency bands. Analysis results demonstrate that the group difference is significant in the alpha frequency band by LZC and multi-scale LZC analysis. However, the group difference of multi-scale LZC is much more remarkable, manifesting as more channels undergo notable changes, particularly in electrodes O1 and O2 in the occipital area. Moreover, the multi-scale LZC value provided a better classification between the two groups with an accuracy of 85.7 %. In addition, we combine both features of the relative PSD and multi-scale LZC to discriminate AD patients from the normal controls by applying a support vector machine model in the alpha frequency band. It is indicated that the two groups can be clearly classified by the combined feature. Importantly, the accuracy of the classification is higher than that of any one feature, reaching 91.4 %. The obtained results show that analysis of PSD and multi-scale LZC can be taken as a potential comprehensive measure to distinguish AD patients from the normal controls, which may benefit our understanding of the disease.     

Is He Being Bad? Social and Language Brain Networks during Social Judgment in Children with Autism

Individuals with autism often violate social rules and have lower accuracy in identifying and explaining inappropriate social behavior. Twelve children with autism (AD) and thirteen children with typical development (TD) participated in this fMRI study of the neurofunctional basis of social judgment. Participants indicated in which of two pictures a boy was being bad (Social condition) or which of two pictures was outdoors (Physical condition). In the within-group Social–Physical comparison, TD children used components of mentalizing and language networks [bilateral inferior frontal gyrus (IFG), bilateral medial prefrontal cortex (mPFC), and bilateral posterior superior temporal sulcus (pSTS)], whereas AD children used a network that was primarily right IFG and bilateral pSTS, suggesting reduced use of social and language networks during this social judgment task. A direct group comparison on the Social–Physical contrast showed that the TD group had greater mPFC, bilateral IFG, and left superior temporal pole activity than the AD group. No regions were more active in the AD group than in the group with TD in this comparison. Both groups successfully performed the task, which required minimal language. The groups also performed similarly on eyetracking measures, indicating that the activation results probably reflect the use of a more basic strategy by the autism group rather than performance disparities. Even though language was unnecessary, the children with TD recruited language areas during the social task, suggesting automatic encoding of their knowledge into language; however, this was not the case for the children with autism. These findings support behavioral research indicating that, whereas children with autism may recognize socially inappropriate behavior, they have difficulty using spoken language to explain why it is inappropriate. The fMRI results indicate that AD children may not automatically use language to encode their social understanding, making expression and generalization of this knowledge more difficult.     

高原肺水肿易感基因多态性的全基因组关联分析

目的：高原肺水肿严重影响高原人群的健康。筛选高原肺水肿易感基因以用于高原肺水肿易感者的评估及防护。方法：利用Affymetrix SNP Array6．0芯片对23例高原肺水肿患者和17个健康对照进行全基因组SNP分型,利用PLINK软件进行了全基因组关联分析,利用Go和Pathway软件进行分析及作图。结果：全基因组关联分析获得39个相对显著的SNPs位点（P〈10^-4）。通过对这些SNP位点附近27个基因的c0和Pathway富集分析,发现这些基因主要参与细胞增殖调控过程、氮代谢过程和G蛋白耦联受体蛋白信号转导通路等。结论：本文发现的多态性位点及相关基因可能与高原肺水肿易感性相关。     

Transcriptome Analysis of the Hippocampus in Novel Rat Model of Febrile Seizures

Febrile seizures (FS) are the most common type of convulsive events in infants and young children, but the precise underlying genetic mechanism remains to be explored. To investigate the underlying pathogenic factors in FS and subsequent epilepsy, alterations in gene expression between the two new strains of rats (hyperthermia-prone [HP] vs hyperthermia-resistant [HR]), were investigated by using the Whole Rat Genome Oligo Microarray. This process identified 1,140 differentially expressed genes (DEGs; 602 upregulated and 538 downregulated), which were analyzed to determine significant Gene Ontology (GO) categories, signaling pathways and gene networks. Based on the GO analyses, the modified genes are closely related to various FS pathogenesis factors, including immune and inflammatory responses and ion transport. Certain DEGs identified have not been previously examined in relation to FS pathogenesis. Among these genes is dipeptidyl peptidase 4 (DPP4), a gene closely linked to interleukin 6 (IL-6), which played a key role in the gene network analysis. Furthermore, sitagliptin, a DPP4 inhibitor significantly decreased epileptic discharge in rats, observed via electroencephalogram, suggesting an important role for DPP4 in FS. The effectiveness of sitagliptin in reducing seizure activity may occur through a mechanism that stabilizes cellular Ca²⁺ homeostasis. In addition, DPP4 expression may be regulated by DNA methylation. The hippocampal gene expression profiles in novel rat models of FS provides a large database of candidate genes and pathways, which will be useful for researchers interested in disorders of neuronal excitability.     

Features of Autonomic Regulation and the Character of Convulsions in Stammering Children

The neurophysiological mechanisms of convulsions were studied in the stammering syndrome. Electrophysiological, neurological, neuropsychological, and logopedic examinations were performed for 23 children aged 9–10 years with stammering. For comprehensive analysis, a neurophysiological classification was used to divide the stammering children into two groups: group I, which included patients with paroxysmal patterns recorded in the EEG, and group II, which included patients without paroxysmal EEG patterns. The analysis revealed a correlation of specific features of the autonomic regulation with the character of convulsions. Predominant malfunction of the parasympathetic part of the autonomic nervous system and tonic convulsions in stammering were found in the group I children. Malfunction of the sympathetic part of the autonomic nervous system and clonic convulsions in stammering were characteristic of group II children.