Neuroscience databases: tools for exploring brain structure-function relationships.

Faster than ever, neuroscience is generating vast amounts of data that await cross-referencing, comparison, integration and interpretation in the endeavour to unravel the mechanisms of the brain. The complex, diverse and distributed nature of these data requires the development of advanced neuroinformatics methodologies for databases and associated tools that are now beginning to emerge. This paper presents an overview of current issues in the representation, integration and analysis of neuroscience data from molecular to brain systems levels, including issues of implementation, standardization, management, quality control, copyright, confidentiality and acceptance. Particular emphasis is given to integrative neuroinformatics approaches for exploring structure-function relationships in the brain.     

神经信息学的原理与展望

神经信息学是研究神经系统信息的载体形式,神经信息的产生、传输、加工、编码、存储与提取机理,以及建立神经数据库系统的科学。它是脑科学,信息科学和计算机科学相互交叉的边缘学科。神经信息学可分为分子神经信息学和系统神经信息学两个层次。神经信息编码可分为神经元脉冲序列的数字编码和突触联结权重编码两种编码方式。对21世纪神经信息学可能取得的新进展进行分析和预测,并论证开展人类神经组计划（HuNP）和建立神经数据库系统的必要性与可行性。对人类神经计划与人类脑计划的异同步,进行比较和讨论。     

人类脑计划与神经信息学

了解脑及其功能是21世纪科学的重大挑战之一。神经信息学是神经科学与信息科学相结合的交叉学科。目前的“人类脑计划”旨在加强脑功能的基础研究,并开发用于分析、整合、合成、建模、模拟与提供各种数据的工具。中国应参与人类脑计划,为发展神经信息学作出贡献。     

From the science of learning (and development) to learning engineering

ABSTRACT

In this issue, Cantor and colleagues synthesize a broad representation of the literature on the science of learning, and how learning changes over the course of development. Their perspective highlights three important factors about the emerging field of science of learning and development: (1) that it draws insights from increasingly diverse fields of research inquiry, from neuroscience and social science to computer science and adversity science; (2) that it provides a means to understand principles that generalize across learners, and yet also allow individual differences in learning to emerge and inform; and (3) that it recognizes that learning occurs in context, and is thus a shared responsibility between the learner, the instructor, and the environment. Here I discuss how this complex systems dynamical perspective can be integrated with the emerging framework of ‘learning engineering’ to provide a blueprint for significant innovations in education.     

Bundles of choice: Variety and the creation and manipulation of Kenyan Khat's value

This article examines the enormous variety evident in the ‘social life’ of Kenyan khat (miraa) and the role of this variety in the creation and manipulation of value. The article, after a discussion of the literature on value and its relevance to miraa, describes variables used in distinguishing the many different types of miraa, describes how consumers associate themselves with certain varieties and suggests why some varieties are more valued – culturally and economically – than others. The article then looks at the international trade in miraa, and how value is manipulated as exporters – well positioned to exploit different ‘fields of value’ – blend different varieties together to ensure a decent financial reward. It concludes by emphasising that understanding miraa requires an appreciation of its complex particularity.     

Quantum physics in neuroscience and psychology: a neurophysical model of mind-brain interaction

Neuropsychological research on the neural basis of behaviour generally posits that brain mechanisms will ultimately suffice to explain all psychologically described phenomena. This assumption stems from the idea that the brain is made up entirely of material particles and fields, and that all causal mechanisms relevant to neuroscience can therefore be formulated solely in terms of properties of these elements. Thus, terms having intrinsic mentalistic and/or experiential content (e.g. 'feeling', 'knowing' and 'effort') are not included as primary causal factors. This theoretical restriction is motivated primarily by ideas about the natural world that have been known to be fundamentally incorrect for more than three-quarters of a century. Contemporary basic physical theory differs profoundly from classic physics on the important matter of how the consciousness of human agents enters into the structure of empirical phenomena. The new principles contradict the older idea that local mechanical processes alone can account for the structure of all observed empirical data. Contemporary physical theory brings directly and irreducibly into the overall causal structure certain psychologically described choices made by human agents about how they will act. This key development in basic physical theory is applicable to neuroscience, and it provides neuroscientists and psychologists with an alternative conceptual framework for describing neural processes. Indeed, owing to certain structural features of ion channels critical to synaptic function, contemporary physical theory must in principle be used when analysing human brain dynamics. The new framework, unlike its classic-physics-based predecessor, is erected directly upon, and is compatible with, the prevailing principles of physics. It is able to represent more adequately than classic concepts the neuroplastic mechanisms relevant to the growing number of empirical studies of the capacity of directed attention and mental effort to systematically alter brain function.     

''The surface management system'' (SuMS) database: a surface-based database to aid cortical surface reconstruction, visualization and analysis.

Surface reconstructions of the cerebral cortex are increasingly widely used in the analysis and visualization of cortical structure, function and connectivity. From a neuroinformatics perspective, dealing with surface-related data poses a number of challenges. These include the multiplicity of configurations in which surfaces are routinely viewed (e.g. inflated maps, spheres and flat maps), plus the diversity of experimental data that can be represented on any given surface. To address these challenges, we have developed a surface management system (SuMS) that allows automated storage and retrieval of complex surface-related datasets. SuMS provides a systematic framework for the classification, storage and retrieval of many types of surface-related data and associated volume data. Within this classification framework, it serves as a version-control system capable of handling large numbers of surface and volume datasets. With built-in database management system support, SuMS provides rapid search and retrieval capabilities across all the datasets, while also incorporating multiple security levels to regulate access. SuMS is implemented in Java and can be accessed via a Web interface (WebSuMS) or using downloaded client software. Thus, SuMS is well positioned to act as a multiplatform, multi-user 'surface request broker' for the neuroscience community.     

What can we teach Lymnaea and what can Lymnaea teach us?

This review describes the advantages of adopting a molluscan complementary model, the freshwater snail Lymnaea stagnalis, to study the neural basis of learning and memory in appetitive and avoidance classical conditioning; as well as operant conditioning of its aerial respiratory and escape behaviour. We firstly explored ‘what we can teach Lymnaea’ by discussing a variety of sensitive, solid, easily reproducible and simple behavioural tests that have been used to uncover the memory abilities of this model system. Answering this question will allow us to open new frontiers in neuroscience and behavioural research to enhance our understanding of how the nervous system mediates learning and memory. In fact, from a translational perspective, Lymnaea and its nervous system can help to understand the neural transformation pathways from behavioural output to sensory coding in more complex systems like the mammalian brain. Moving on to the second question: ‘what can Lymnaea teach us?’, it is now known that Lymnaea shares important associative learning characteristics with vertebrates, including stimulus generalization, generalization of extinction and discriminative learning, opening the possibility to use snails as animal models for neuroscience translational research.     

Opinion: the neural basis of human moral cognition

Moral cognitive neuroscience is an emerging field of research that focuses on the neural basis of uniquely human forms of social cognition and behaviour. Recent functional imaging and clinical evidence indicates that a remarkably consistent network of brain regions is involved in moral cognition. These findings are fostering new interpretations of social behavioural impairments in patients with brain dysfunction, and require new approaches to enable us to understand the complex links between individuals and society. Here, we propose a cognitive neuroscience view of how cultural and context-dependent knowledge, semantic social knowledge and motivational states can be integrated to explain complex aspects of human moral cognition.     

功能磁共振和脑电神经成像技术与大脑刺激相结合的研究进展

随着对神经机制问题阐述水平的迅速提高,所应用的神经成像技术、方法及各种工具的复杂程度也在不断提高．一方面是神经成像技术本身的不断发展,另一方面则是大脑直接刺激与神经成像技术同步记录方法的发展．经颅磁刺激-功能磁共振成像同步技术(TMS-fMRI)和经颅磁刺激-脑电技术(TMS-EEG)能为研究大脑网络的功能和有效连通性提供技术手段,该技术在多种认知领域的发展和应用,为神经科学、认知心理学、神经信息学等学科的研究者对人脑的研究开启了多条通道,更加有利于深入地理解人类大脑的工作机制．     

The BRAIN Initiative: developing technology to catalyse neuroscience discovery

The evolution of the field of neuroscience has been propelled by the advent of novel technological capabilities, and the pace at which these capabilities are being developed has accelerated dramatically in the past decade. Capitalizing on this momentum, the United States launched the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative to develop and apply new tools and technologies for revolutionizing our understanding of the brain. In this article, we review the scientific vision for this initiative set forth by the National Institutes of Health and discuss its implications for the future of neuroscience research. Particular emphasis is given to its potential impact on the mapping and study of neural circuits, and how this knowledge will transform our understanding of the complexity of the human brain and its diverse array of behaviours, perceptions, thoughts and emotions.     

Encoding brain network response to free viewing of videos

A challenging goal for cognitive neuroscience researchers is to determine how mental representations are mapped onto the patterns of neural activity. To address this problem, functional magnetic resonance imaging (fMRI) researchers have developed a large number of encoding and decoding methods. However, previous studies typically used rather limited stimuli representation, like semantic labels and Wavelet Gabor filters, and largely focused on voxel-based brain patterns. Here, we present a new fMRI encoding model to predict the human brain’s responses to free viewing of video clips which aims to deal with this limitation. In this model, we represent the stimuli using a variety of representative visual features in the computer vision community, which can describe the global color distribution, local shape and spatial information and motion information contained in videos, and apply the functional connectivity to model the brain’s activity pattern evoked by these video clips. Our experimental results demonstrate that brain network responses during free viewing of videos can be robustly and accurately predicted across subjects by using visual features. Our study suggests the feasibility of exploring cognitive neuroscience studies by computational image/video analysis and provides a novel concept of using the brain encoding as a test-bed for evaluating visual feature extraction.     

脑内微透析采样技术及其在神经科学中的应用

作为一种新的在体化学采样技术,脑内微透析引起了神经科学家的关注。它与迅速发展起来的高灵敏度的微量分析技术相结合,实现了对体内细胞外环境中化学物质变化的动态监测,从而在神经科学领域获得应用。本系统地介绍了这一新技术的原理和方法,并扼要地介绍了一这一技术在神经科学中的应用及其取得的新进展,并结合本实验室的工作经验,对该技术存在的一些问题进行了讨论。     

社会神经科学研究进展

社会神经科学是研究人类的社会行为及其神经机制的综合性学科.从1992年学科成立至今,社会神经科学研究取得了丰硕的成果.本文系统介绍了该领域4个主要研究方向:社会知觉、社会认知、社会调节和社会互动的研究成果,并在此基础上总结了各研究方向的核心问题,即社会知觉加工的模块化问题、人类社会认知的独特性问题和社会调节加工的跨文化一致性问题.已有研究表明,社会知觉加工至少在计算算法层面是特异化的;心智化系统是人类独有的加工模块;人类社会调节不具备跨文化的一致性;大脑间耦合可能是社会互动共有的神经机制.最后,展望了社会神经科学未来的发展方向.     

Simple high-performance liquid chromatographic method for the concurrent determination of the amine metabolites vanillylmandelic acid, 3-methoxy-4-hydroxyphenylglycol, 5-hydroxyindoleacetic acid, dihydroxyphenylacetic acid and homovanillic acid in urine using electrochemical detection

A simple method for the concurrent analysis of the noradrenaline metabolites vanillylmandelic acid and 3-methoxy-4-hydroxyphenylglycol, the dopamine metabolites dihydroxyphenylacetic acid and homovanillic acid, and the serotonin metabolite 5-hydroxyindoleacetic acid in human urine is described. Following organic extraction of the metabolites from acidified urine, they are separated by single-step gradient elution high-performance liquid chromatography on a reversed-phase column. Detection and quantification are achieved with an electrochemical detector using a carbon-paste electrode; samples can be injected at 40-min intervals. Optimisation of analytical parameters is described, and examples of the application of the method in the fields of clinical chemistry and clinical neuroscience are given. This provides a convenient method for the concurrent study of the metabolism of three major biogenic amines, and is readily adaptable for studies on cerebrospinal fluid and brain tissue.     

Epistemic artefacts: on the uses of complexity in anthropology

Distinctions between the ‘simple’ and the ‘complex’ have enjoyed a long and varied career in anthropology. Simplicity was once part of a collective fantasy about what life was like elsewhere, tingeing studies of tribal life with human longing for simpler ways of being. With the reflexive turn and the rise of cultural critique, simplicity has been all but excommunicated in favour of widespread diagnoses of complexity. In this article, I tease out some transformations in the uses of complexity in anthropology, and weave in some critical responses to these uses, spanning many decades, from within the discipline. I pay special attention to recent critiques by anthropologists who are beginning to grow weary of complexity as both an end‐in‐itself for scholarship and an empirical diagnosis. For these critics, complexity is deeply entwined with anthropological methods and knowledge practices. Drawing on these critical views, I suggest that complexity may be an epistemological artefact, rather than something that can be diagnosed ‘out there’, and offer a way of reframing complexity as a ‘dominant problematic’ in anthropology and beyond.     

How do high-level specifications of the brain relate to variational approaches?

High-level specification of how the brain represents and categorizes the causes of its sensory input allows to link "what is to be done" (perceptual task) with "how to do it" (neural network calculation). In this article, we describe how the variational framework, which encountered a large success in modeling computer vision tasks, has some interesting relationships, at a mesoscopic scale, with computational neuroscience. We focus on cortical map computations such that "what is to be done" can be represented as a variational approach, i.e., an optimization problem defined over a continuous functional space. In particular, generalizing some existing results, we show how a general variational approach can be solved by an analog neural network with a given architecture and conversely. Numerical experiments are provided as an illustration of this general framework, which is a promising framework for modeling macro-behaviors in computational neuroscience.