Large-scale cortical functional organization and speech perception across the lifespan

Aging is accompanied by substantial changes in brain function, including functional reorganization of large-scale brain networks. Such differences in network architecture have been reported both at rest and during cognitive task performance, but an open question is whether these age-related differences show task-dependent effects or represent only task-independent changes attributable to a common factor (i.e., underlying physiological decline). To address this question, we used graph theoretic analysis to construct weighted cortical functional networks from hemodynamic (functional MRI) responses in 12 younger and 12 older adults during a speech perception task performed in both quiet and noisy listening conditions. Functional networks were constructed for each subject and listening condition based on inter-regional correlations of the fMRI signal among 66 cortical regions, and network measures of global and local efficiency were computed. Across listening conditions, older adult networks showed significantly decreased global (but not local) efficiency relative to younger adults after normalizing measures to surrogate random networks. Although listening condition produced no main effects on whole-cortex network organization, a significant age group x listening condition interaction was observed. Additionally, an exploratory analysis of regional effects uncovered age-related declines in both global and local efficiency concentrated exclusively in auditory areas (bilateral superior and middle temporal cortex), further suggestive of specificity to the speech perception tasks. Global efficiency also correlated positively with mean cortical thickness across all subjects, establishing gross cortical atrophy as a task-independent contributor to age-related differences in functional organization. Together, our findings provide evidence of age-related disruptions in cortical functional network organization during speech perception tasks, and suggest that although task-independent effects such as cortical atrophy clearly underlie age-related changes in cortical functional organization, age-related differences also demonstrate sensitivity to task domains.     

Speech perception: a language-trained chimpanzee weighs in

A language-trained chimpanzee is able to interpret synthetic 'auditory caricatures' as speech. Important components of human speech perception thus rely upon general auditory mechanisms that predated the evolution of spoken language.     

RESOURCERER: a database for annotating and linking microarray resources within and across species

Microarray expression analysis is providing unprecedented data on gene expression in humans and mammalian model systems. Although such studies provide a tremendous resource for understanding human disease states, one of the significant challenges is cross-referencing the data derived from different species, across diverse expression analysis platforms, in order to properly derive inferences regarding gene expression and disease state. To address this problem, we have developed RESOURCERER, a microarray-resource annotation and cross-reference database built using the analysis of expressed sequence tags (ESTs) and gene sequences provided by the TIGR Gene Index (TGI) and TIGR Orthologous Gene Alignment (TOGA) databases [now called Eukaryotic Gene Orthologs (EGO)].     

Indexical Speech across Samoan Communities

By extending the work of linguistic anthropologists on indexicality to transnational communities, this article shows how a simple instruction to sit down can be a way of making physically distant worlds emotionally and ethically close. Comparison of the use and context of this expression among Samoan speakers in two communities, a Western Samoan village and a suburban neighborhood in southern California, illustrates the power of language to bridge the gap. Talking space is at the same time a socialization strategy to teach children proper ways of behaving in front of adults and an attempt to provide cultural and socioethical continuity despite the distance between the islands from which immigrant Samoans come and the new environment in which they live and raise their children.     

Biodiversity informatics: organizing and linking information across the spectrum of life

Biological knowledge can be inferred from three major levels of information: molecules, organisms and ecologies. Bioinformatics is an established field that has made significant advances in the development of systems and techniques to organize contemporary molecular data; biodiversity informatics is an emerging discipline that strives to develop methods to organize knowledge at the organismal level extending back to the earliest dates of recorded natural history. Furthermore, while bioinformatics studies generally focus on detailed examinations of key 'model' organisms, biodiversity informatics aims to develop over-arching hypotheses that span the entire tree of life. Biodiversity informatics is presented here as a discipline that unifies biological information from a range of contemporary and historical sources across the spectrum of life using organisms as the linking thread. The present review primarily focuses on the use of organism names as a universal metadata element to link and integrate biodiversity data across a range of data sources.     

爬行动物皮层的细胞构筑与纤维联系

大脑进化到爬行动物阶段,端脑开始占据大脑的绝大部分,成为处理信息的高级中枢.皮层是爬行动物端脑的一个主要组成部分,与哺乳动物的大脑皮层相似,它位于端脑的表面,覆盖整个脑室下结构,参与各种信息的处理,嗅觉、视觉、听觉、学习和记忆都跟它相关.本文就爬行动物皮层的分区、细胞构筑、纤维联系等最近的研究进展进行介绍.     

The fusiform face area: a cortical region specialized for the perception of faces

Faces are among the most important visual stimuli we perceive, informing us not only about a person's identity, but also about their mood, sex, age and direction of gaze. The ability to extract this information within a fraction of a second of viewing a face is important for normal social interactions and has probably played a critical role in the survival of our primate ancestors. Considerable evidence from behavioural, neuropsychological and neurophysiological investigations supports the hypothesis that humans have specialized cognitive and neural mechanisms dedicated to the perception of faces (the face-specificity hypothesis). Here, we review the literature on a region of the human brain that appears to play a key role in face perception, known as the fusiform face area (FFA). Section 1 outlines the theoretical background for much of this work. The face-specificity hypothesis falls squarely on one side of a longstanding debate in the fields of cognitive science and cognitive neuroscience concerning the extent to which the mind/brain is composed of: (i) special-purpose ('domain-specific') mechanisms, each dedicated to processing a specific kind of information (e.g. faces, according to the face-specificity hypothesis), versus (ii) general-purpose ('domain-general') mechanisms, each capable of operating on any kind of information. Face perception has long served both as one of the prime candidates of a domain-specific process and as a key target for attack by proponents of domain-general theories of brain and mind. Section 2 briefly reviews the prior literature on face perception from behaviour and neurophysiology. This work supports the face-specificity hypothesis and argues against its domain-general alternatives (the individuation hypothesis, the expertise hypothesis and others). Section 3 outlines the more recent evidence on this debate from brain imaging, focusing particularly on the FFA. We review the evidence that the FFA is selectively engaged in face perception, by addressing (and rebutting) five of the most widely discussed alternatives to this hypothesis. In section 4, we consider recent findings that are beginning to provide clues into the computations conducted in the FFA and the nature of the representations the FFA extracts from faces. We argue that the FFA is engaged both in detecting faces and in extracting the necessary perceptual information to recognize them, and that the properties of the FFA mirror previously identified behavioural signatures of face-specific processing (e.g. the face-inversion effect). Section 5 asks how the computations and representations in the FFA differ from those occurring in other nearby regions of cortex that respond strongly to faces and objects. The evidence indicates clear functional dissociations between these regions, demonstrating that the FFA shows not only functional specificity but also area specificity. We end by speculating in section 6 on some of the broader questions raised by current research on the FFA, including the developmental origins of this region and the question of whether faces are unique versus whether similarly specialized mechanisms also exist for other domains of high-level perception and cognition.     

Oscillations and synchrony in a cortical neural network

In this paper, the oscillations and synchronization status of two different network connectivity patterns based on Izhikevich model are studied. One of the connectivity patterns is a randomly connected neuronal network, the other one is a small-world neuronal network. This Izhikevich model is a simple model which can not only reproduce the rich behaviors of biological neurons but also has only two equations and one nonlinear term. Detailed investigations reveal that by varying some key parameters, such as the connection weights of neurons, the external current injection, the noise of intensity and the neuron number, this neuronal network will exhibit various collective behaviors in randomly coupled neuronal network. In addition, we show that by changing the number of nearest neighbor and connection probability in small-world topology can also affect the collective dynamics of neuronal activity. These results may be instructive in understanding the collective dynamics of mammalian cortex.     

Fast,cell-resolution,contiguous-wide two-photon imaging to reveal functional network architectures across multi-modal cortical areas

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Disruption of space perception due to cortical lesions

Space control has for a long time been considered a unitary function. The structure associated with this function was the right parietal lobe. Hemispheric specialization for space appeared to make it automatically a human-specific function. However, recent primate research shows different regions of the parietal lobes to be differently involved with space control. A review of the literature, together with own cases shows that there is ample evidence of a modular organization of space control in humans on the basis of specific deficits subsequent to circumscribed cerebral lesions. Lesions influence differentially retinotopic, spatiotopic, egocentric, and allocentric frames of references. They also influence differentially the attention to far or near space, or to global or local features of space. Moreover, preattentive processes can be studied in the neglected hemispace of humans and prove to be sensible to the meaning of visual stimuli. Space representation and attentional mechanisms that seem to operate on these representations are organized in our brain in a very modular fashion, similar to the modularity of visual submodalities. There is probably not a unified space representation in the parietal lobes, but distributed functional modules. Thus, the study of visual optic recognition, either by the brain or by machines, is inconceivable without considering space, attention and awareness.     

Bioenergetic food webs as a means of linking toxicological effects across scales of ecological organization

Although significant progress has been made in ourability to predict population-level consequences oftoxic effects on individuals, extending thispredictive ability to communities, functional guilds,and ecosystems will require more integration ofecological theory into environmental science. Bioenergetics and food webs have long been centralthemes in ecology and greatly expanded ourunderstanding of nature. Although numerousenergetic-based toxicological endpoints have beendeveloped, few have extended this framework beyond theindividual level. Most energetic endpoints includeindividual growth, and only occasionally is thisintegrated with population dynamics. However,population-level energetic analyses (e.g., secondaryproduction) integrate individual and populationprocesses, and provide two key parameters: consumptionand energy flow. Within a food web framework,estimates of consumption and energy flow throughpopulations facilitate linking population-levelcontaminant effects to ecosystem-level effects. Several examples are given to illustrate the utilityof this approach.     

Oscillatory synchronization in large-scale cortical networks predicts perception

Normal brain function requires the dynamic interaction of functionally specialized but widely distributed cortical regions. Long-range synchronization of oscillatory signals has been suggested to mediate these interactions within large-scale cortical networks, but direct evidence is sparse. Here we show that oscillatory synchronization is organized in such large-scale networks. We implemented an analysis approach that allows for imaging synchronized cortical networks and applied this technique to EEG recordings in humans. We identified two networks: beta-band synchronization (~20 Hz) in a fronto-parieto-occipital network and gamma-band synchronization (~80 Hz) in a centro-temporal network. Strong perceptual correlates support their functional relevance: the strength of synchronization within these networks predicted the subjects' perception of an ambiguous audiovisual stimulus as well as the integration of auditory and visual information. Our results provide evidence that oscillatory neuronal synchronization mediates neuronal communication within frequency-specific, large-scale cortical networks.     

Effects of cortical damage on binocular depth perception

Stereoscopic depth perception requires considerable neural computation, including the initial correspondence of the two retinal images, comparison across the local regions of the visual field and integration with other cues to depth. The most common cause for loss of stereoscopic vision is amblyopia, in which one eye has failed to form an adequate input to the visual cortex, usually due to strabismus (deviating eye) or anisometropia. However, the significant cortical processing required to produce the percept of depth means that, even when the retinal input is intact from both eyes, brain damage or dysfunction can interfere with stereoscopic vision. In this review, I examine the evidence for impairment of binocular vision and depth perception that can result from insults to the brain, including both discrete damage, temporal lobectomy and more systemic diseases such as posterior cortical atrophy.This article is part of the themed issue ‘Vision in our three-dimensional world’.     

Speech perception at the interface of neurobiology and linguistics

Speech perception consists of a set of computations that take continuously varying acoustic waveforms as input and generate discrete representations that make contact with the lexical representations stored in long-term memory as output. Because the perceptual objects that are recognized by the speech perception enter into subsequent linguistic computation, the format that is used for lexical representation and processing fundamentally constrains the speech perceptual processes. Consequently, theories of speech perception must, at some level, be tightly linked to theories of lexical representation. Minimally, speech perception must yield representations that smoothly and rapidly interface with stored lexical items. Adopting the perspective of Marr, we argue and provide neurobiological and psychophysical evidence for the following research programme. First, at the implementational level, speech perception is a multi-time resolution process, with perceptual analyses occurring concurrently on at least two time scales (approx. 20-80 ms, approx. 150-300 ms), commensurate with (sub)segmental and syllabic analyses, respectively. Second, at the algorithmic level, we suggest that perception proceeds on the basis of internal forward models, or uses an 'analysis-by-synthesis' approach. Third, at the computational level (in the sense of Marr), the theory of lexical representation that we adopt is principally informed by phonological research and assumes that words are represented in the mental lexicon in terms of sequences of discrete segments composed of distinctive features. One important goal of the research programme is to develop linking hypotheses between putative neurobiological primitives (e.g. temporal primitives) and those primitives derived from linguistic inquiry, to arrive ultimately at a biologically sensible and theoretically satisfying model of representation and computation in speech.     

Storing structured sparse memories in a multi-modular cortical network model

We investigate the properties of recently proposed “shotgun” sampling approach for the common inputs problem in the functional estimation of neuronal connectivity. We study the asymptotic correctness, the speed of convergence, and the data size requirements of such an approach. We show that the shotgun approach can be expected to allow the inference of complete connectivity matrix in large neuronal populations under some rather general conditions. However, we find that the posterior error of the shotgun connectivity estimator grows quickly with the size of unobserved neuronal populations, the square of average connectivity strength, and the square of observation sparseness. This implies that the shotgun connectivity estimation will require significantly larger amounts of neuronal activity data whenever the number of neurons in observed neuronal populations remains small. We present a numerical approach for solving the shotgun estimation problem in general settings and use it to demonstrate the shotgun connectivity inference in the examples of simulated synfire and weakly coupled cortical neuronal networks.     

An ecological framework linking scales across space and time based on self-thinning

Scaling up from measurements made at small spatial and short temporal scales is a central challenge in the ecological and related sciences, where predictions at larger scales and over long time periods are required. It involves two quite distinct aspects: a formulation of a theoretical framework for calculating space-time averages, and an acquisition of data to support that framework. In this paper, we address the theoretical part of the question, and although our primary motivation was an understanding of carbon accounting our formulation is more general. To that end, we adopt a dynamical systems approach, and incorporate a new dynamical formulation of self-thinning. We show how to calculate rates of change for total (and average) plant dry mass, volume, and carbon, in terms of the properties of the individual plants. The results emphasize how local scale statistics (such as, variation in the size of individuals) lead to nonlinear variation at larger scales. Further, we describe how regular and stochastic disturbance can be readily incorporated into this framework. It is shown that stochastic disturbance at patch-scales, results in (to first approximation) regular disturbance at ecosystem scales, and hence can be formulated as such. We conclude that a dynamical formulation of self-thinning can be used as a generic framework for scaling ecological processes in space and time.     

Object-oriented echo perception and cortical representation in echolocating bats

Echolocating bats can identify three-dimensional objects exclusively through the analysis of acoustic echoes of their ultrasonic emissions. However, objects of the same structure can differ in size, and the auditory system must achieve a size-invariant, normalized object representation for reliable object recognition. This study describes both the behavioral classification and the cortical neural representation of echoes of complex virtual objects that vary in object size. In a phantom-target playback experiment, it is shown that the bat Phyllostomus discolor spontaneously classifies most scaled versions of objects according to trained standards. This psychophysical performance is reflected in the electrophysiological responses of a population of cortical units that showed an object-size invariant response (14/109 units, 13%). These units respond preferentially to echoes from objects in which echo duration (encoding object depth) and echo amplitude (encoding object surface area) co-varies in a meaningful manner. These results indicate that at the level of the bat's auditory cortex, an object-oriented rather than a stimulus-parameter-oriented representation of echoes is achieved.