Neural mechanisms of tactile motion integration in somatosensory cortex

How are local motion signals integrated to form a global motion percept? We investigate the neural mechanisms of tactile motion integration by presenting tactile gratings and plaids to the fingertips of monkeys, using the tactile analogue of a visual monitor and recording the responses evoked in somatosensory cortical neurons. The perceived directions of the gratings and plaids are measured in parallel psychophysical experiments. We identify a population of somatosensory neurons that exhibit integration properties comparable to those induced by analogous visual stimuli in area MT and find that these neural responses account for the perceived direction of the stimuli across all stimulus conditions tested. The preferred direction of the neurons and the perceived direction of the stimuli can be predicted from the weighted average of the directions of the individual stimulus features, highlighting that the somatosensory system implements a vector average mechanism to compute tactile motion direction that bears striking similarities to its visual counterpart.     

The role of independent component analysis in the signal processing of ECG recordings.

Independent component analysis (ICA) is an emerging technique for multidimensional signal processing. In recent years, these techniques have been proposed for solving a large number of biomedical applications. This work reviews current knowledge on ICA in electrocardiographic (ECG) analysis. The benefits that ICA can bring to clinical practice are illustrated with four relevant clinical applications: foetal ECG extraction from maternal ECG recordings, analysis of atrial fibrillation, ECG denoising and removal of pacemaker artefacts.     

Interaction of perceptual grouping and crossmodal temporal capture in tactile apparent-motion

Previous studies have shown that in tasks requiring participants to report the direction of apparent motion, task-irrelevant mono-beeps can "capture" visual motion perception when the beeps occur temporally close to the visual stimuli. However, the contributions of the relative timing of multimodal events and the event structure, modulating uni- and/or crossmodal perceptual grouping, remain unclear. To examine this question and extend the investigation to the tactile modality, the current experiments presented tactile two-tap apparent-motion streams, with an SOA of 400 ms between successive, left-/right-hand middle-finger taps, accompanied by task-irrelevant, non-spatial auditory stimuli. The streams were shown for 90 seconds, and participants' task was to continuously report the perceived (left- or rightward) direction of tactile motion. In Experiment 1, each tactile stimulus was paired with an auditory beep, though odd-numbered taps were paired with an asynchronous beep, with audiotactile SOAs ranging from -75 ms to 75 ms. Perceived direction of tactile motion varied systematically with audiotactile SOA, indicative of a temporal-capture effect. In Experiment 2, two audiotactile SOAs--one short (75 ms), one long (325 ms)--were compared. The long-SOA condition preserved the crossmodal event structure (so the temporal-capture dynamics should have been similar to that in Experiment 1), but both beeps now occurred temporally close to the taps on one side (even-numbered taps). The two SOAs were found to produce opposite modulations of apparent motion, indicative of an influence of crossmodal grouping. In Experiment 3, only odd-numbered, but not even-numbered, taps were paired with auditory beeps. This abolished the temporal-capture effect and, instead, a dominant percept of apparent motion from the audiotactile side to the tactile-only side was observed independently of the SOA variation. These findings suggest that asymmetric crossmodal grouping leads to an attentional modulation of apparent motion, which inhibits crossmodal temporal-capture effects.     

Comparison between principal component analysis and independent component analysis in electroencephalograms modelling

Principal Component Analysis (PCA) is a classical technique in statistical data analysis, feature extraction and data reduction, aiming at explaining observed signals as a linear combination of orthogonal principal components. Independent Component Analysis (ICA) is a technique of array processing and data analysis, aiming at recovering unobserved signals or 'sources' from observed mixtures, exploiting only the assumption of mutual independence between the signals. The separation of the sources by ICA has great potential in applications such as the separation of sound signals (like voices mixed in simultaneous multiple records, for example), in telecommunication or in the treatment of medical signals. However, ICA is not yet often used by statisticians. In this paper, we shall present ICA in a statistical framework and compare this method with PCA for electroencephalograms (EEG) analysis.We shall see that ICA provides a more useful data representation than PCA, for instance, for the representation of a particular characteristic of the EEG named event-related potential (ERP).     

Coding of tactile stimulus amplitude by neuronal ensembles in the somatosensory cortex of the rat brain

Dependence of the neuronal excitatory responses in a barrel column of the primary somatosensory cortex on the amplitude of bending of a central vibrissa within the receptive field was studied in rats. The neurons localized at a layer IV level were shown to represent a region of the hierarchically organized thalamic input to a barrel column, which possesses the highest sensitivity to the variation of the stimulus amplitude. Concept is substantiated here whereby coding of the stimulus amplitude is based on the afferent impulsation-induced modulation of a structurally preformed gradient of synaptical efficiency in the specific input to a column.Neirofiziologiya/Neurophysiology, No. 2, Vol. 27, pp. 83–92, March–April, 1995.     

Time-frequency component analysis of somatosensory evoked potentials in rats

Background  

Somatosensory evoked potential (SEP) signal usually contains a set of detailed temporal components measured and identified in a time domain, giving meaningful information on physiological mechanisms of the nervous system. The purpose of this study is to measure and identify detailed time-frequency components in normal SEP using time-frequency analysis (TFA) methods and to obtain their distribution pattern in the time-frequency domain.     

Influence of body position on cortical pain-related somatosensory processing: an ERP study

Background

Despite the consistent information available on the physiological changes induced by head down bed rest, a condition which simulates space microgravity, our knowledge on the possible perceptual-cortical alterations is still poor. The present study investigated the effects of 2-h head-down bed rest on subjective and cortical responses elicited by electrical, pain-related somatosensory stimulation.

Methodology/Principal Findings

Twenty male subjects were randomly assigned to two groups, head-down bed rest (BR) or sitting control condition. Starting from individual electrical thresholds, Somatosensory Evoked Potentials were elicited by electrical stimuli administered randomly to the left wrist and divided into four conditions: control painless condition, electrical pain threshold, 30% above pain threshold, 30% below pain threshold. Subjective pain ratings collected during the EEG session showed significantly reduced pain perception in BR compared to Control group. Statistical analysis on four electrode clusters and sLORETA source analysis revealed, in sitting controls, a P1 component (40–50 ms) in the right somatosensory cortex, whereas it was bilateral and differently located in BR group. Controls'' N1 (80–90 ms) had widespread right hemisphere activation, involving also anterior cingulate, whereas BR group showed primary somatosensory cortex activation. The P2 (190–220 ms) was larger in left-central locations of Controls compared with BR group.

Conclusions/Significance

Head-down bed rest was associated to an overall decrease of pain sensitivity and an altered pain network also outside the primary somatosensory cortex. Results have implications not only for astronauts'' health and spaceflight risks, but also for the clinical aspects of pain detection in bedridden patients at risk of fatal undetected complications.     

Ubiquitous crossmodal Stochastic Resonance in humans: auditory noise facilitates tactile, visual and proprioceptive sensations

Background

Stochastic resonance is a nonlinear phenomenon whereby the addition of noise can improve the detection of weak stimuli. An optimal amount of added noise results in the maximum enhancement, whereas further increases in noise intensity only degrade detection or information content. The phenomenon does not occur in linear systems, where the addition of noise to either the system or the stimulus only degrades the signal quality. Stochastic Resonance (SR) has been extensively studied in different physical systems. It has been extended to human sensory systems where it can be classified as unimodal, central, behavioral and recently crossmodal. However what has not been explored is the extension of this crossmodal SR in humans. For instance, if under the same auditory noise conditions the crossmodal SR persists among different sensory systems.

Methodology/Principal Findings

Using physiological and psychophysical techniques we demonstrate that the same auditory noise can enhance the sensitivity of tactile, visual and propioceptive system responses to weak signals. Specifically, we show that the effective auditory noise significantly increased tactile sensations of the finger, decreased luminance and contrast visual thresholds and significantly changed EMG recordings of the leg muscles during posture maintenance.

Conclusions/Significance

We conclude that crossmodal SR is a ubiquitous phenomenon in humans that can be interpreted within an energy and frequency model of multisensory neurons spontaneous activity. Initially the energy and frequency content of the multisensory neurons'' activity (supplied by the weak signals) is not enough to be detected but when the auditory noise enters the brain, it generates a general activation among multisensory neurons of different regions, modifying their original activity. The result is an integrated activation that promotes sensitivity transitions and the signals are then perceived. A physiologically plausible model for crossmodal stochastic resonance is presented.     

Prefrontal cortex: procedural sequence learning and awareness

Activation of the prefrontal cortex has been linked to awareness during sequence-learning tasks. A recent study, however, finds activation of the prefrontal cortex during such tasks regardless of awareness. So what is the neurophysiological basis of awareness, and what is the role of the prefrontal cortex in sequence learning?     

Hemodynamic component in cerebral compensatory processes following unilateral exclusion of the somatosensory cortex]

In experiments on anesthetised and awake cats the dynamics of the cerebral blood flow was studied by the thermoelectric method in one hemisphere in experimental lesion of the somatosensory zone of the opposite one. Temporary exclusion of the cortical area by cold produced evident hemodynamic changes, i. e. a two-phase vasoreaction and an initial blood flow decrease followed by a prolonged increase of blood supply, in the other hemisphere. Analogous vasoreactions were seen on unilateral extirpation of the cortical layer of the somatosensory zone, as well. Such vasoreactions indicate enhanced activity of the cortical structures in the intact hemisphere and may be considered as a compensatory reaction to the local lesion of certain cortical areas.     

Application of independent component analysis to microarrays

We apply linear and nonlinear independent component analysis (ICA) to project microarray data into statistically independent components that correspond to putative biological processes, and to cluster genes according to over- or under-expression in each component. We test the statistical significance of enrichment of gene annotations within clusters. ICA outperforms other leading methods, such as principal component analysis, k-means clustering and the Plaid model, in constructing functionally coherent clusters on microarray datasets from Saccharomyces cerevisiae, Caenorhabditis elegans and human.     

基于空间ICA和时间相关方法的人脑视觉皮层V5区的功能连通性研究

利用功能磁共振成像技术,将空间ICA和时间相关方法相结合来研究不同活动状态下人脑视觉皮层V5区的功能连通性。首先利用空间ICA处理组块视觉运动刺激的数据,定位V5区;然后分别计算静息和连续视觉运动刺激两种稳态下V5区与其它脑区低频振荡的时间相关,检测出该区的功能连通网络。实验结果表明,静息时V5区的功能连通网络更广泛,且与已知的解剖连通一致;当被试接受连续视觉运动刺激时,与V5区连通的脑区网络局限在视觉皮层,此时的网络特定于处理视觉运动这一任务。     

Metabolite fingerprinting: detecting biological features by independent component analysis

MOTIVATION: Metabolite fingerprinting is a technology for providing information from spectra of total compositions of metabolites. Here, spectra acquisitions by microchip-based nanoflow-direct-infusion QTOF mass spectrometry, a simple and high throughput technique, is tested for its informative power. As a simple test case we are using Arabidopsis thaliana crosses. The question is how metabolite fingerprinting reflects the biological background. In many applications the classical principal component analysis (PCA) is used for detecting relevant information. Here a modern alternative is introduced-the independent component analysis (ICA). Due to its independence condition, ICA is more suitable for our questions than PCA. However, ICA has not been developed for a small number of high-dimensional samples, therefore a strategy is needed to overcome this limitation. RESULTS: To apply ICA successfully it is essential first to reduce the high dimension of the dataset, by using PCA. The number of principal components determines the quality of ICA significantly, therefore we propose a criterion for estimating the optimal dimension automatically. The kurtosis measure is used to order the extracted components to our interest. Applied to our A. thaliana data, ICA detects three relevant factors, two biological and one technical, and clearly outperforms the PCA.     

Prefrontal cortex and neural mechanisms of executive function

Executive function is a product of the coordinated operation of multiple neural systems and an essential prerequisite for a variety of cognitive functions. The prefrontal cortex is known to be a key structure for the performance of executive functions. To accomplish the coordinated operations of multiple neural systems, the prefrontal cortex must monitor the activities in other cortical and subcortical structures and control and supervise their operations by sending command signals, which is called top-down signaling. Although neurophysiological and neuroimaging studies have provided evidence that the prefrontal cortex sends top-down signals to the posterior cortices to control information processing, the neural correlate of these top-down signals is not yet known. Through use of the paired association task, it has been demonstrated that top-down signals are used to retrieve specific information stored in long-term memory. Therefore, we used a paired association task to examine the neural correlates of top-down signals in the prefrontal cortex. The preliminary results indicate that 32% of visual neurons exhibit pair-selectivity, which is similar to the characteristics of pair-coding activities in temporal neurons. The latency of visual responses in prefrontal neurons was longer than bottom-up signals but faster than top-down signals in inferior temporal neurons. These results suggest that pair-selective visual responses may be top-down signals that the prefrontal cortex provides to the temporal cortex, although further studies are needed to elucidate the neural correlates of top-down signals and their characteristics to understand the neural mechanism of executive control by the prefrontal cortex.     

Analyzing M-CSF dependent monocyte/macrophage differentiation: Expression modes and meta-modes derived from an independent component analysis

Background  

The analysis of high-throughput gene expression data sets derived from microarray experiments still is a field of extensive investigation. Although new approaches and algorithms are published continuously, mostly conventional methods like hierarchical clustering algorithms or variance analysis tools are used. Here we take a closer look at independent component analysis (ICA) which is already discussed widely as a new analysis approach. However, deep exploration of its applicability and relevance to concrete biological problems is still missing. In this study, we investigate the relevance of ICA in gaining new insights into well characterized regulatory mechanisms of M-CSF dependent macrophage differentiation.     

双任务事件中脑电信号的熵计算

采用复杂性分析中的样品熵算法,计算并分析了受试者在单任务事件以及双任务事件活动过程中的神经电生理数据.在利用样品熵算法对短时程（秒）脑电数据的复杂度和规则度进行计算之前,首先应用了代替数据分析法,以排除所分析的实验数据是由线性加随机部分构成.所有的实验数据分别在单任务和双任务等不同的生理条件下采集.其中单任务为一个听觉辨别任务;双任务有两种形式,分别为听觉任务和不同的震动任务的结合.计算结果显示,任何一种双任务过程中脑电信号的熵值都明显的低于单任务状态时脑电信号的熵值（P＜0.05～0.001）.研究表明对应于受试者仅仅进行单任务工作而言,当受试者处于双任务工作状态时大脑的神经信息传递可能会受到某种程度的削弱,神经信息流通的范围也可能更为孤立.结果进一步说明对于短时程（秒）脑电信号分析,样品熵算法是有效的非线性分析方法.     

Prefrontal cortex in humans and apes: a comparative study of area 10

Area 10 is one of the cortical areas of the frontal lobe involved in higher cognitive functions such as the undertaking of initiatives and the planning of future actions. It is known to form the frontal pole of the macaque and human brain, but its presence and organization in the great and lesser apes remain unclear. It is here documented that area 10 also forms the frontal pole of chimpanzee, bonobo, orangutan, and gibbon brains. Imaging techniques and stereological tools are used to characterize this area across species and provide preliminary estimates of its absolute and relative size. Area 10 has similar cytoarchitectonic features in the hominoid brain, but aspects of its organization vary slightly across species, including the relative width of its cortical layers and the space available for connections. The cortex forming the frontal pole of the gorilla appears highly specialized, while area 10 in the gibbon occupies only the orbital sector of the frontal pole. Area 10 in the human brain is larger relative to the rest of the brain than it is in the apes, and its supragranular layers have more space available for connections with other higher-order association areas. This suggests that the neural substrates supporting cognitive functions associated with this part of the cortex enlarged and became specialized during hominid evolution.     

基于时间聚类分析和独立成分分析的癫痫fMRI盲分析方法

提出了一种基于时间聚类分析和独立成分分析的癫痫fMRI数据盲分析方法,并将两种方法有效联合,提取发作间期的癫痫fMRI激活时空信息.该方法首先由时间聚类分析得到与激活相关的时间峰度特征曲线,以此特征作为时间参考信息;再由空间独立成分分析分解fMRI信号得到空间独立成分;最后将每个独立成分所对应的时间曲线与参考曲线做相关分析提取相应脑激活图.提出的方法无需任何关于癫痫fMRI的先验假设信息,有效解决了独立成分的排序问题,实现了对数据的盲分析.仿真试验结果阐明了这一方法的有效性及可靠性,对癫痫数据的试验结果显示空间定位准确性优于统计参数图方法.