A PET Study of the Brain Mechanisms Underlying Perception of Phrases with Syntagmatic Splitting

Positron emission tomography (PET) was used to localize the brain regions involved in the processing of pauses and intonation changes, which underlie the syntactically correct perception of auditory verbal stimuli. Subjects were asked to listen to a phrase and to choose a correct answer from two variants presented on a monitor screen. Differences in cerebral blood circulation were mapped for perception of phrases containing or lacking a pause determining the meaning. Conscious analysis of the phrase structure was associated with activation of the right lower prefrontal area and the right posterior medial area of the cerebellum. The possible role of these brain structures in analyzing factors of syntagmatic splitting is discussed.     

Combining Brain Imaging with Microarray: Isolating Molecules Underlying the Physiologic Disorders of the Brain

Many diseases of the nervous system cause dysfunction by impairing neuronal physiology more than by altering brain anatomy--including age-related cognitive decline, most psychiatric disorders, and even the earliest stages of Alzheimer's disease. The absence of clear anatomical markers makes it difficult to identify targeted cells, which in turn impedes attempts to isolate the pathogenic molecules that cause physiologic disruption. Here we show how brain imaging and microarray can be used as complimentary techniques that together can characterize the cellular and molecular aspects of this class of diseases.     

Cooperative Integration and Representation Underlying Bilateral Network of Fly Motion-Sensitive Neurons

How is binocular motion information integrated in the bilateral network of wide-field motion-sensitive neurons, called lobula plate tangential cells (LPTCs), in the visual system of flies? It is possible to construct an accurate model of this network because a complete picture of synaptic interactions has been experimentally identified. We investigated the cooperative behavior of the network of horizontal LPTCs underlying the integration of binocular motion information and the information representation in the bilateral LPTC network through numerical simulations on the network model. First, we qualitatively reproduced rotational motion-sensitive response of the H2 cell previously reported in vivo experiments and ascertained that it could be accounted for by the cooperative behavior of the bilateral network mainly via interhemispheric electrical coupling. We demonstrated that the response properties of single H1 and Hu cells, unlike H2 cells, are not influenced by motion stimuli in the contralateral visual hemi-field, but that the correlations between these cell activities are enhanced by the rotational motion stimulus. We next examined the whole population activity by performing principal component analysis (PCA) on the population activities of simulated LPTCs. We showed that the two orthogonal patterns of correlated population activities given by the first two principal components represent the rotational and translational motions, respectively, and similar to the H2 cell, rotational motion produces a stronger response in the network than does translational motion. Furthermore, we found that these population-coding properties are strongly influenced by the interhemispheric electrical coupling. Finally, to test the generality of our conclusions, we used a more simplified model and verified that the numerical results are not specific to the network model we constructed.     

A New Statistical Goodness-of-Fit Test Based on Graphical Representation

A statistical goodness-of-fit test, based on representing the sample observations by linked vectors, is developed. The direction and the length of the linked vectors are defined as functions of the expected values of the order statistics and sample order statistics, respectively. The underlying method can be used to test distributional assumptions for any location-scale family. A test statistic Q_n is introduced and some of its properties are studied. It is shown that the proposed test can be generalized to test if two or more independent samples come from the same distribution. The test procedure provides a graphical method of identifying the true distribution when the null hypothesis is rejected.     

Task-Related Changes in Functional Properties of the Human Brain Network Underlying Attentional Control

Previous studies have demonstrated task-related changes in brain activation and inter-regional connectivity but the temporal dynamics of functional properties of the brain during task execution is still unclear. In the present study, we investigated task-related changes in functional properties of the human brain network by applying graph-theoretical analysis to magnetoencephalography (MEG). Subjects performed a cue-target attention task in which a visual cue informed them of the direction of focus for incoming auditory or tactile target stimuli, but not the sensory modality. We analyzed the MEG signal in the cue-target interval to examine network properties during attentional control. Cluster-based non-parametric permutation tests with the Monte-Carlo method showed that in the cue-target interval, beta activity was desynchronized in the sensori-motor region including premotor and posterior parietal regions in the hemisphere contralateral to the attended side. Graph-theoretical analysis revealed that, in beta frequency, global hubs were found around the sensori-motor and prefrontal regions, and functional segregation over the entire network was decreased during attentional control compared to the baseline. Thus, network measures revealed task-related temporal changes in functional properties of the human brain network, leading to the understanding of how the brain dynamically responds to task execution as a network.     

一种基于信息理论的距离系数

给出了一种基于信息理论的距离系数,这一新的信息系数是通过对信息论中的离散增量系数改进而得,并证明其满足距离系数的三个性质．将其应用于一组同源辅助蛋白的聚类分析,表明是可行的．与离散增量系数及经典的欧氏距离系数的聚类结果进行比较,应用相干系数对聚类结果进行评价,结果表明由新信息距离系数所确定的聚类结构与聚类数据问的拟合程度最好.     

Spatial Representation of Feeding and Oviposition Odors in the Brain of a Hawkmoth

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High-Field fMRI Reveals Brain Activation Patterns Underlying Saccade Execution in the Human Superior Colliculus

Background

The superior colliculus (SC) has been shown to play a crucial role in the initiation and coordination of eye- and head-movements. The knowledge about the function of this structure is mainly based on single-unit recordings in animals with relatively few neuroimaging studies investigating eye-movement related brain activity in humans.

Methodology/Principal Findings

The present study employed high-field (7 Tesla) functional magnetic resonance imaging (fMRI) to investigate SC responses during endogenously cued saccades in humans. In response to centrally presented instructional cues, subjects either performed saccades away from (centrifugal) or towards (centripetal) the center of straight gaze or maintained fixation at the center position. Compared to central fixation, the execution of saccades elicited hemodynamic activity within a network of cortical and subcortical areas that included the SC, lateral geniculate nucleus (LGN), occipital cortex, striatum, and the pulvinar.

Conclusions/Significance

Activity in the SC was enhanced contralateral to the direction of the saccade (i.e., greater activity in the right as compared to left SC during leftward saccades and vice versa) during both centrifugal and centripetal saccades, thereby demonstrating that the contralateral predominance for saccade execution that has been shown to exist in animals is also present in the human SC. In addition, centrifugal saccades elicited greater activity in the SC than did centripetal saccades, while also being accompanied by an enhanced deactivation within the prefrontal default-mode network. This pattern of brain activity might reflect the reduced processing effort required to move the eyes toward as compared to away from the center of straight gaze, a position that might serve as a spatial baseline in which the retinotopic and craniotopic reference frames are aligned.     

On the Number of Neurons and Time Scale of Integration Underlying the Formation of Percepts in the Brain

All of our perceptual experiences arise from the activity of neural populations. Here we study the formation of such percepts under the assumption that they emerge from a linear readout, i.e., a weighted sum of the neurons’ firing rates. We show that this assumption constrains the trial-to-trial covariance structure of neural activities and animal behavior. The predicted covariance structure depends on the readout parameters, and in particular on the temporal integration window w and typical number of neurons K used in the formation of the percept. Using these predictions, we show how to infer the readout parameters from joint measurements of a subject’s behavior and neural activities. We consider three such scenarios: (1) recordings from the complete neural population, (2) recordings of neuronal sub-ensembles whose size exceeds K, and (3) recordings of neuronal sub-ensembles that are smaller than K. Using theoretical arguments and artificially generated data, we show that the first two scenarios allow us to recover the typical spatial and temporal scales of the readout. In the third scenario, we show that the readout parameters can only be recovered by making additional assumptions about the structure of the full population activity. Our work provides the first thorough interpretation of (feed-forward) percept formation from a population of sensory neurons. We discuss applications to experimental recordings in classic sensory decision-making tasks, which will hopefully provide new insights into the nature of perceptual integration.     

Systems-Based Analyses of Brain Regions Functionally Impacted in Parkinson's Disease Reveals Underlying Causal Mechanisms

Detailed analysis of disease-affected tissue provides insight into molecular mechanisms contributing to pathogenesis. Substantia nigra, striatum, and cortex are functionally connected with increasing degrees of alpha-synuclein pathology in Parkinson''s disease. We undertook functional and causal pathway analysis of gene expression and proteomic alterations in these three regions, and the data revealed pathways that correlated with disease progression. In addition, microarray and RNAseq experiments revealed previously unidentified causal changes related to oligodendrocyte function and synaptic vesicle release, and these and other changes were reflected across all brain regions. Importantly, subsets of these changes were replicated in Parkinson''s disease blood; suggesting peripheral tissue may provide important avenues for understanding and measuring disease status and progression. Proteomic assessment revealed alterations in mitochondria and vesicular transport proteins that preceded gene expression changes indicating defects in translation and/or protein turnover. Our combined approach of proteomics, RNAseq and microarray analyses provides a comprehensive view of the molecular changes that accompany functional loss and alpha-synuclein pathology in Parkinson''s disease, and may be instrumental to understand, diagnose and follow Parkinson''s disease progression.     

基于3-D图形表示的DNA序列的相似性分析

基于DNA序列的3D图形表示,通过L／L矩阵的规范化最大特征值组成的3维向量来刻画了DNA序列,并基于这种方法,用β-globin基因的第一个外显子分析了11个物种的相似性问题。     

基于扩散张量成像的脑组织各向异性电导率计算模型的研究综述

脑组织电导率不仅对脑电源分析起着至关重要的作用,而且也是及时发现脑组织发生功能性病变的重要依据之一.扩散张量成像是一种无损伤功能性成像新技术,具有很高的空间分辨率.基于扩散张量成像的脑组织电导率计算是近年来的一项重要研究课题.本文综述了已有脑组织各向异性电导率的计算模型,主要包括张量特征值线性模型、电场力-粘力平衡模型...