Reliable detection of bilateral activation in human primary somatosensory cortex by unilateral median nerve stimulation

In non-human primates, a bilateral representation of unilaterally presented somatosensory information can be found at the lowest level of cortical processing as indicated by the presence of neurons with bilateral receptive fields in the hand region of primary somatosensory (SI) cortex. In humans, such bilateral activation of SI is considered controversial due to highly variable detection rates for the much weaker ipsilateral response across different studies (ranging from 3% to 100%). Second-order blind identification (SOBI) is a blind source separation algorithm that has been successfully used to isolate neuronal signals from functionally distinct brain regions, including the left- and right-SI. SOBI-aided extraction of left- and right-SI responses to median nerve stimulation from high-density EEG has been previously validated against the fMRI and MEG literature. Here, we applied SOBI to EEG data and examined whether relatively weaker ipsilateral activations could be reliably detected across subjects. In single subject analysis, statistically significant somatosensory evoked potentials (SEPs) in response to unilateral stimulation were detected from both SI contralateral to and SI ipsilateral to the side of stimulation. Furthermore, these ipsilateral responses were observed in both the left and right hemispheres of all 10 subjects studied. Together these results demonstrate that unilateral stimulation of the median nerve, whether applied to the left or right wrist, can activate both the left- and right-SI, raising the possibility that in humans, unilateral sensory input may be bilaterally represented at the lowest level of cortical processing.     

Validation of SOBI components from high-density EEG

Second-order blind identification (SOBI) is a blind source separation (BSS) algorithm that can be used to decompose mixtures of signals into a set of components or putative recovered sources. Previously, SOBI, as well as other BSS algorithms, has been applied to magnetoencephalography (MEG) and electroencephalography (EEG) data. These BSS algorithms have been shown to recover components that appear to be physiologically and neuroanatomically interpretable. While some proponents of these algorithms suggest that fundamental discoveries about the human brain might be made through the application of these techniques, validation of BSS components has not yet received sufficient attention. Here we present two experiments for validating SOBI-recovered components. The first takes advantage of the fact that noise sources associated with individual sensors can be objectively validated independently from the SOBI process. The second utilizes the fact that the time course and location of primary somatosensory (SI) cortex activation by median nerve stimulation have been extensively characterized using converging imaging methods. In this paper, using both known noise sources and highly constrained and well-characterized neuronal sources, we provide validation for SOBI decomposition of high-density EEG data. We show that SOBI is able to (1) recover known noise sources that were either spontaneously occurring or artificially induced; (2) recover neuronal sources activated by median nerve stimulation that were spatially and temporally consistent with estimates obtained from previous EEG, MEG, and fMRI studies; (3) improve the signal-to-noise ratio (SNR) of somatosensory-evoked potentials (SEPs); and (4) reduce the level of subjectivity involved in the source localization process.     

Independent components of magnetoencephalography: single-trial response onset times

Werecently demonstrated that second-order blind identification (SOBI), an independent component analysis (ICA) method, can separate the mixture of neuronal and noise signals in magnetoencephalographic (MEG) data into neuroanatomically and neurophysiologically meaningful components. When the neuronal signals had relatively higher trial-to-trial variability, SOBI offered a particular advantage in identifying and localizing neuronal source activations with increased source detectability (A. C. Tang et al., 2002, Neural Comput. 14, 1827-1858). Here, we explore the utility of SOBI in the analysis of temporal aspects of neuromagnetic signals from MEG data. From SOBI components, we were able to measure single-trial response onset times of neuronal populations in visual, auditory, and somatosensory modalities during cognitive and sensory activation tasks, with a detection rate as high as 96% under optimal conditions. Comparing the SOBI-aided detection results with those obtained directly from the sensors, we found that with SOBI preprocessing, we were able to measure, among a greater proportion of trials, single-trial response onset times that are above background neuronal activity. We suggest that SOBI ICA can improve our current capability in measuring single-trial responses from human subjects using the noninvasive brain imaging method MEG.     

From neurovascular coupling to neurovascular cascade: a study on neural, autonomic and vascular transients in attention

Mental processes bring about neural, vascular and autonomic changes in the brain cortex. Due to the different nature of these modifications, their onsets show no synchrony and time dynamics is often strongly dissimilar. After acquiring data from a group of 16 subjects, we estimated temporal correlation between task and signals in order to assess possible influences induced by an attentive task on electroencephalographic (EEG), heart rate variability (HRV), oxy- and deoxy-haemoglobin concentration signals. We also investigated correlations and time delays between couples of different biological signals. This allowed for the isolation of a subgroup of subjects showing similar tracks. Cardiac frequency and deoxy-haemoglobin signals displayed a strong positive correlation with the task design, while EEG alpha rhythm and oxygenation showed a negative correlation. Neural electrical response was nearly instantaneous with respect to the task progression, and autonomic response showed a mean delay of about 15 s and a slower hemodynamic response (mean delay above 20 s) was finally induced. Globally, the task elicited a cascade of responses, in which delays can be quantified.     

Detection of very high correlation in the alpha band between temporal regions of the human brain using MEG

It is generally believed that alpha band (8-12 Hz) electric and magnetic activity in the area of the left and right temporal regions in the human brain are at best poorly correlated. There are no previous reports of very high alpha band correlation between left and right temporal regions by magnetoencephalography (MEG) or electroencephalography (EEG). We present whole head magnetoencephalography (MEG) results that demonstrate that, for temporal channels in the majority of healthy subjects tested, the alpha band signals are highly to very highly correlated and are antiparallel in direction. A correlation as high as -0.97 was found for a limited time in one subject. We suggest that the correlation found may be the consequence of strong direct or indirect coupling between homologue areas in left and right temporal regions rather than a common source. The correlation may provide a valuable index of loss of connectivity in the brain due to disease as well providing valuable insight to brain function and deserves further investigation.     

Comprehension of degraded speech sounds with m-sequence modulation: An fMRI study

In a recent electroencephalography (EEG) study (Takeichi et al., 2007a), we developed a new technique for assessing speech comprehension using speech degraded by m-sequence modulation and found a correlation peak with a 400-ms delay. This peak depended on the comprehensibility of the modulated speech sounds. Here we report the results of a functional magnetic resonance imaging (fMRI) experiment comparable to our previous EEG experiment. We examined brain areas related to verbal comprehension of the modulated speech sound to examine which neural system processes this modulated speech. A non-integer, alternating-block factorial design was used with 23 Japanese-speaking participants, with time reversal and m-sequence modulation as factors. A main effect of time reversal was found in the left temporal cortex along the superior temporal sulcus (BA21 and BA39), left precentral gyrus (BA6) and right inferior temporal gyrus (BA21). A main effect of modulation was found in the left postcentral gyrus (BA43) and the right medial frontal gyri (BA6) as an increase by modulation and in the left temporal cortex (BA21, 39), parahippocampal gyrus (BA34), posterior cingulate (BA23), caudate and thalamus and right superior temporal gyrus (BA38) as a decrease by modulation. An interaction effect associated specifically with non-modulated speech was found in the left frontal gyrus (BA47), left occipital cortex in the cuneus (BA18), left precuneus (BA7, 31), right precuneus (BA31) and right thalamus (forward > reverse). The other interaction effect associated specifically with modulation of speech sound was found in the inferior frontal gyrus in the opercular area (BA44) (forward > reverse). Estimated scalp projection of the component correlation function (Cao et al., 2002) for the corresponding EEG data (Takeichi et al., 2007a, showed leftward dominance. Hence, activities in the superior temporal sulcus (BA21 and BA39), which are commonly observed for speech processing, as well as left precentral gyrus (BA6) and left inferior frontal gyrus in the opercular area (BA44) is suggested to contribute to the comprehension-related EEG signal.     

Measuring temporal dynamics of functional networks using phase spectrum of fMRI data

We present a novel method to measure relative latencies between functionally connected regions using phase-delay of functional magnetic resonance imaging data. Derived from the phase component of coherency, this quantity estimates the linear delay between two time-series. In conjunction with coherence, derived from the magnitude component of coherency, phase-delay can be used to examine the temporal properties of functional networks. In this paper, we apply coherence and phase-delay methods to fMRI data in order to investigate dynamics of the motor network during task and rest periods. Using the supplementary motor area (SMA) as a reference region, we calculated relative latencies between the SMA and other regions within the motor network including the dorsal premotor cortex (PMd), primary motor cortex (M1), and posterior parietal cortex (PPC). During both the task and rest periods, we measured significant delays that were consistent across subjects. Specifically, we found significant delays between the SMA and the bilateral PMd, bilateral M1, and bilateral PPC during the task condition. During the rest condition, we found that the temporal dynamics of the network changed relative to the task period. No significant delays were measured between the SMA and the left PM and left M1; however, the right PM, right M1, and bilateral PPC were significantly delayed with respect to the SMA. Additionally, we observed significant map-wise differences in the dynamics of the network at task compared to the network at rest. These differences were observed in the interaction between the SMA and the left M1, left superior frontal gyrus, and left middle frontal gyrus. These temporal measurements are important in determining how regions within a network interact and provide valuable information about the sequence of cognitive processes within a network.     

Biomagnetic and bioelectric detection of gastric slow wave activity in normal human subjects--a correlation study

We measured gastric slow wave activity simultaneously with a Superconducting Quantum Interference Device (SQUID) magnetometer, mucosal electrodes and cutaneous electrodes in 18 normal human subjects (11 women and 7 men). We processed signals with Fourier spectral analysis and SOBI blind-source separation techniques. We observed a high waveform correlation between the mucosal electromyogram (EMG) and multichannel SQUID magnetogastrogram (MGG). There was a lower waveform correlation between the mucosal EMG and cutaneous electrogastrogram (EGG), but the correlation improved with the application of SOBI. There was also a high correlation between the frequency of the electrical activity recorded in the MGG and in mucosal electrodes (r = 0.97). We concluded that SQUID magnetometers noninvasively record gastric slow wave activity that is highly correlated with the activity recorded by invasive mucosal electrodes.     

基于频带能量和小波包熵的运动意识任务分类研究

目的探讨脑电信号频带能量和小波包熵在识别左右手想象运动中的作用。方法采用脑-计算机接口2003竞赛中Graz科技大学提供的脑电数据,用小波包分解获取8～16Hz脑电信号,计算C₃、C₄电极脑电信号的频带能量和小波包熵,将其结合作为反应想象左右手运动的特征量,对大脑想象左右手运动任务进行分类。结果对140次实验的测试样本数据分析,最大分类正确率可达87.14%。结论脑电信号频带能量和小波包熵随时间的变化与事件相关去同步和事件相关同步现象相一致,可在线识别左右手想象运动。     

脑机接口在线识别左右手运动想象的脑电信号分析

采用脑机接口2003竞赛中Graz科技大学提供的脑电数据,用小波包分解获取8～16 Hz脑电信号,计算C3,C4电极脑电信号的功率谱峰值和对应频率作为组合脑电特征向量,运用时变线性分类算法对运动意识任务运行分类.对140次实验的测试样本数据分析,最大分类正确率可达89.29%,最大互信息和信噪比分别为0.622 8 bit和1.371 3.提示C3,C4电极8～16 Hz脑电信号功率谱峰值和对应的频率能很好地反映左右手运动想象脑电特征的变化,与事件相关去同步/事件相关同步现象变化一致,可在线识别左右手想象运动.     

Proposal of a Method for Automatic Optimization of Left Heart Atrioventricular Interval Applicable to DDD Pacemakers

Electrical pacing of the right heart is known to cause delays in the depolarization of left heart chambers, leading to abnormal left heart AV sequence. Interatrial conduction time, defined as the time from the right atrial pacing pulse or intrinsic P to the onset of left atrial P wave, and P wave sensing delay cause a shorter left heart AV interval during atrial pacing-ventricular sensing and atrial sense-ventricular pace. Interventricular conduction time (the time from the right ventricular pacing pulse to the onset of left ventricular depolarization), lengthens left heart AV interval during atrial sensing-ventricular pacing. These delays may add up or partly cancel out, depending on pacing mode. Thus, an algorithm for DDD pacemakers to optimize left heart AV interval by compensating for the above delays is proposed. This algorithm takes into account pacing and sensing delays to deliver a certain AV sequence to the right heart, aimed at producing a physiological left heart AV interval. The optimization of left heart AV interval is achieved by automatically changing right heart AV interval and pacing mode in accordance with known interatrial and interventricular conduction delays, and P wave sense offset.     

三维超声联合剪切波弹性成像评估压力性尿失禁绝经女性耻骨直肠肌功能北大核心CSCD

目的观察三维超声联合剪切波弹性成像(SWE)评估压力性尿失禁(SI)绝经女性耻骨直肠肌功能的价值。方法收集57例SI绝经女性(SI组)和30名查体未见明显异常的绝经女性(对照组),采用经会阴三维超声测量其静息及最大缩肛状态下肛提肌裂孔(LH)参数(面积、前后径、左右径),以高频超声及SWE测量其静息及最大缩肛状态下耻骨直肠肌厚度及杨氏模量平均值(E_(mean)),比较组间各参数差异。结果静息状态下,SI组与对照组LH面积、前后径及左右径差异均无统计学意义(P均>0.05);最大缩肛状态下,SI组LH面积、前后径及左右径均大于对照组(P均<0.05)。SI组双侧耻骨直肠肌厚度及E_(mean)均小于对照组(P均<0.05);最大缩肛状态下,SI组与对照组双侧耻骨直肠肌厚度及E_(mean)均大于静息状态(P均<0.05)。静息状态下,SI组LH面积与双侧耻骨直肠肌E_(mean)均无明显相关(左侧r=-0.182,P=0.108;右侧r=-0.274,P=0.053),最大缩肛状态下,SI组LH面积与双侧耻骨直肠肌E_(mean)均呈低度负相关(左侧r=-0.349,P=0.002;右侧r=-0.329,P=0.003)。结论三维超声联合SWE可通过观察LH形态和耻骨直肠肌厚度及E_(mean)评估绝经女性耻骨直肠肌功能,有助于早期诊断及治疗SI。     

EEG correlates of haptic feedback in a visuomotor tracking task

This study investigates the temporal brain dynamics associated with haptic feedback in a visuomotor tracking task. Haptic feedback with deviation-related forces was used throughout tracking experiments in which subjects' behavioral responses and electroencephalogram (EEG) data were simultaneously measured. Independent component analysis was employed to decompose the acquired EEG signals into temporally independent time courses arising from distinct brain sources. Clustering analysis was used to extract independent components that were comparable across participants. The resultant independent brain processes were further analyzed via time-frequency analysis (event-related spectral perturbation) and event-related coherence (ERCOH) to contrast brain activity during tracking experiments with or without haptic feedback. Across subjects, in epochs with haptic feedback, components with equivalent dipoles in or near the right motor region exhibited greater alpha band power suppression. Components with equivalent dipoles in or near the left frontal, central, left motor, right motor, and parietal regions exhibited greater beta-band power suppression, while components with equivalent dipoles in or near the left frontal, left motor, and right motor regions showed greater gamma-band power suppression relative to non-haptic conditions. In contrast, the right occipital component cluster exhibited less beta-band power suppression in epochs with haptic feedback compared to non-haptic conditions. The results of ERCOH analysis of the six component clusters showed that there were significant increases in coherence between different brain networks in response to haptic feedback relative to the coherence observed when haptic feedback was not present. The results of this study provide novel insight into the effects of haptic feedback on the brain and may aid the development of new tools to facilitate the learning of motor skills.     

Transmission of Facial Expressions of Emotion Co-Evolved with Their Efficient Decoding in the Brain: Behavioral and Brain Evidence

Competent social organisms will read the social signals of their peers. In primates, the face has evolved to transmit the organism's internal emotional state. Adaptive action suggests that the brain of the receiver has co-evolved to efficiently decode expression signals. Here, we review and integrate the evidence for this hypothesis. With a computational approach, we co-examined facial expressions as signals for data transmission and the brain as receiver and decoder of these signals. First, we show in a model observer that facial expressions form a lowly correlated signal set. Second, using time-resolved EEG data, we show how the brain uses spatial frequency information impinging on the retina to decorrelate expression categories. Between 140 to 200 ms following stimulus onset, independently in the left and right hemispheres, an information processing mechanism starts locally with encoding the eye, irrespective of expression, followed by a zooming out to processing the entire face, followed by a zooming back in to diagnostic features (e.g. the opened eyes in “fear”, the mouth in “happy”). A model categorizer demonstrates that at 200 ms, the left and right brain have represented enough information to predict behavioral categorization performance.     

基于多通道自适应自回归模型脑-机接口系统特征的提取

背景:由于脑电图信号的非平稳特性,脑-机接口系统至今仍然没有走出实验室,制约脑-机接口实用的主要原因之一是由于被试生理或心理状态的干扰下,脑电特征信号动态变化,难以得到稳定可靠的分类特征。目的:观察动态提取基于左手、右手和脚3种运动想象时的脑电信号分类特征,提高在线脑-机接口系统分类准确率和反应速度。方法:共有3位自愿受试者参加了实验,按照屏幕上的提示分别想象左手、右手和脚3种运动,对采集到的脑电图信号,首先通过带通及拉普拉斯滤波,去除眼电等干扰;其次提取改进的多变量自适应自回归模型模型参数作为分类特征;最后与传统的自适应自回归模型和自回归模型方法进行了比较。结果与结论:结果表明改进的多通道自适应自回归模型算法能够比较稳定的提取出对应左手、右手和脚的分类特征,有利于进一步改进在线脑-机接口数据分析算法的自适应能力,促进脑-机接口系统的实际应用。     

首发抑郁症伴自杀意念患者大脑功能连接时间动力学改变

目的 观察伴自杀意念(SI)首发抑郁症患者大脑功能连接(FC)的时间动力学改变。方法 前瞻性纳入57例首发抑郁症伴SI患者(SI组)、42例首发抑郁症不伴SI患者(NSI组)及48名健康志愿者(HC组),行脑功能MRI和抑郁症相关量表评估;根据FC密度(FCD)标准差量化整个大脑、大脑半球间及半球内动态FCD(dFCD)的时间变异性,分析FC时间动力学改变。结果 SI组汉密尔顿抑郁量表24项(HAMD-24)总分大于NSI组(P<0.05)。SI组左侧颞中回的全脑dFCD方差值高于NSI组和HC组(P均<0.05),SI组右侧颞中回半球内dFCD方差值高于HC组(P<0.05),而SI组和NSI组右侧额中回/额下回半球间dFCD方差值均低于HC组(P均<0.05)。结论 首发抑郁症伴SI患者额、颞叶FC存在动态改变。     

卒中后失语非损伤侧脑电功率谱网络特征研究

目的 探索左侧损伤卒中后失语(PSA)患者右脑脑电(EEG)功率谱网络效应特点。方法 2018年12月至2019年6月,招募12例仅左脑半球损伤的PSA患者(PSA组)以及相匹配的健康成年人12例(健康对照组)。采用中国康复研究中心失语症检查(CRRCAE)评价语言功能,并采集脑电数据。对比Alpha和Theta功率谱功能连接特点,与语言亚项进行相关分析。结果 PSA患者右侧脑功能网络在中央区与额、顶及额顶联合区的Alpha与Theta频段功能连接增强,在颞顶、顶枕区与额、额顶、额中央区的Theta频段功能连接减弱。右侧顶枕区至中央区Alpha频段功能连接增强与患者语言表达能力降低相关(P < 0.05),而顶、顶枕与前额、额中央的Theta频段功能连接减弱与患者语言的说、读、抄写、听写和计算等能力相关( r= -0.676~-0.717, P < 0.05)。 结论 EEG功率谱网络可反映右脑功能网络重组情况,右脑额-顶-中央网络功能连接变化可能与PSA语言功能损伤密切相关,可作为PSA疗效评价客观指征。     

脑静息态功能磁共振局部一致性分析在轻度认知障碍患者中的初步研究

目的利用局部一致性(regional homogeneity,ReHo)分析方法来探讨轻度认知障碍(mild cognitive impairment,MCI)患者局部自发脑活动特点,并进一步探讨相应脑区ReHo值改变与认知功能及临床生理指标的相关性。材料与方法39例被试入组,其中临床诊断的MCI患者17例,年龄、性别及受教育年限相匹配的健康志愿者22例,所有受试者均行静息态功能磁共振成像(resting-state fMRI,rs-fMRI)扫描,采用rs-fMRI的ReHo分析方法,比较静息状态下MCI患者与健康志愿者ReHo值存在差异的脑区,对存在显著差异脑区的ReHo值与认知评估量表及临床生理指标进行相关分析。结果与正常对照比较,MCI组右侧岛叶、左侧小脑半球、旁扣带回、颞下回、左右梭状回ReHo值升高;而左侧颞上回、右侧背外侧额上回ReHo值降低。所有被试蒙特利尔认知评估量表(montreal cognitive assessment scale,MoCA)评分与右侧脑岛区(r=-0.487,P=0.002)ReHo值呈负相关,与左侧颞上回(r=0.610,P<0.001)及右侧背外侧额上回(r=0.475,P=0.002)呈正相关。所有被试简易智能状态检查量表(mini mental status examination,MMSE)评分与左侧小脑上回(r=-0.407,P=0.010)呈负相关,与左侧颞上回(r=0.466,P=0.003)呈正相关。MCI组右侧岛叶ReHo值与血浆果糖胺浓度呈负相关(r=-0.630,P=0.007),左侧小脑半球ReHo值与血清肌酐浓度呈负相关(r=-0.579,P=0.015)。结论轻度认知障碍患者rs-fMRI的ReHo值有明显改变,并与认知功能改变及临床生理指标存在一定的相关性。     

Ethanol modulates cortical activity: direct evidence with combined TMS and EEG

The motor cortex of 10 healthy subjects was stimulated by transcranial magnetic stimulation (TMS) before and after ethanol challenge (0.8 g/kg resulting in blood concentration of 0.77 +/- 0.14 ml/liter). The electrical brain activity resulting from the brief electromagnetic pulse was recorded with high-resolution electroencephalography (EEG) and located using inversion algorithms. Focal magnetic pulses to the left motor cortex were delivered with a figure-of-eight coil at the random interstimulus interval of 1.5-2.5 s. The stimulation intensity was adjusted to the motor threshold of abductor digiti minimi. Two conditions before and after ethanol ingestion (30 min) were applied: (1) real TMS, with the coil pressed against the scalp; and (2) control condition, with the coil separated from the scalp by a 2-cm-thick piece of plastic. A separate EMG control recording of one subject during TMS was made with two bipolar platinum needle electrodes inserted to the left temporal muscle. In each condition, 120 pulses were delivered. The EEG was recorded from 60 scalp electrodes. A peak in the EEG signals was observed at 43 ms after the TMS pulse in the real-TMS condition but not in the control condition or in the control scalp EMG. Potential maps before and after ethanol ingestion were significantly different from each other (P = 0.01), but no differences were found in the control condition. Ethanol changed the TMS-evoked potentials over right frontal and left parietal areas, the underlying effect appearing to be largest in the right prefrontal area. Our findings suggest that ethanol may have changed the functional connectivity between prefrontal and motor cortices. This new noninvasive method provides direct evidence about the modulation of cortical connectivity after ethanol challenge.     

基于多通道自适应自回归模型脑-机接口系统特征的提取

背景：由于脑电图信号的非平稳特性,脑-机接口系统至今仍然没有走出实验室,制约脑-机接口实用的主要原因之一是由于被试生理或心理状态的干扰下,脑电特征信号动态变化,难以得到稳定可靠的分类特征。目的：观察动态提取基于左手、右手和脚3种运动想象时的脑电信号分类特征,提高在线脑-机接口系统分类准确率和反应速度。方法：共有3位自愿受试者参加了实验,按照屏幕上的提示分别想象左手、右手和脚3种运动,对采集到的脑电图信号,首先通过带通及拉普拉斯滤波,去除眼电等干扰;其次提取改进的多变量自适应自回归模型模型参数作为分类特征;最后与传统的自适应自回归模型和自回归模型方法进行了比较。结果与结论：结果表明改进的多通道自适应自回归模型算法能够比较稳定的提取出对应左手、右手和脚的分类特征,有利于进一步改进在线脑-机接口数据分析算法的自适应能力,促进脑-机接口系统的实际应用。