发展性面孔失认的认知机制及其神经基础

发展性面孔失认症是指个体在童年期就开始表现出来的一种终生性面孔识别缺陷,其不能归因于智力衰退、情感障碍、物体识别困难以及后天性脑损伤.发展性面孔失认症涉及的认知机制包括面孔特异性机制、构型加工障碍、面孔探测、面孔记忆和面孔身份识别.此外,该面孔失认症的神经网络由核心神经网络和延伸的神经网络组成,前者与面孔选择反应和记忆表征有关,后者主要负责面孔知识表征、面孔长时记忆和面孔工作记忆.今后的研究应集中在完善延伸的神经网络、拓展其认知网络;进一步明确面孔探测与发展性面孔失认之间的关系;考察发展性面孔失认症的基因基础、加强其发展性研究以及推动康复工作的展开.     

Using computers in empirical and theoretical work in cognitive psychology

This article presents some of the issues I have faced in setting up my own laboratory system for research in cognitive psychology. First, for real-time subject testing systems, criteria for choosing hardware and software are presented along with a brief discussion of benchmarks. Stimulus generation and data analysis choices are also discussed. Second, choices of software for data analysis and data exploration are presented, including graphical presentation, statistics, and modeling tools. Third, some consideration is given to benchmarking workstations to be used in modeling (neural modeling in particular), and benchmarks of some of the fastest single processor systems available are presented. Fourth, two examples of the use of the various theoretical tools are given—one for testing compound cue models of priming, and the other for testing global memory models.     

短时记忆的一生发展研究

短时记忆的发展一直是认知发展领域的一个重要课题。近年来一生发展的思想给短时记忆的发展研究又注入了新的内容。文章介绍了关于从婴儿到老年各个时期中短时记忆发展状况及其机制的研究进展。对短时记忆在一生发展中是否存在真正的容量变化、个体差异原因与发展变化原因的关系、短时记忆的一生发展过程等基本问题进行了讨论。     

急性应激影响工作记忆的生理心理机制

急性应激是机体面对外界环境变化所产生的一系列生理和心理反应, 对认知加工, 尤其是核心的工作记忆能力产生深远影响, 然而以往的研究存在大量不一致的结果。从应激诱发方式、工作记忆加工子成分、个体差异等三个方面系统阐释应激影响工作记忆的生理心理机制, 并结合认知神经机制的框架, 可以更好地理解以往的结果。未来研究应综合考虑应激诱发、认知任务和响应个体等方面的差异对应激带来的影响, 并关注急性应激负面影响的干预与调控。     

Functional magnetic resonance imaging: basic principles of and application to developmental science

Functional magnetic resonance imaging (fMRI) has quickly become the preferred technique for imaging normal brain activity, especially in the typically developing child. This technique takes advantage of specific magnetic properties and physiological processes to generate images of brain activity. These images can be interpreted as a function of group or individual based differences to explore developmental patterns and/or cognitive abilities. In this paper we present an overview of the basic principles of fMRI and a discussion of what is currently known about the physiological bases of the resulting signal. We also report findings from developmental fMRI studies that examine the development of cognitive and neural systems underlying attention and memory. Behavioral performance and age‐related neural changes are examined independently in an attempt to disentangle developmental differences from individual variability in performance.     

注意的跨文化研究及意义

Nisbett提出东西方文化差异可能导致了注意的差异,但是并没有对这种现象的原因和机制提出直接的证据.最近几年来,文化对注意过程的影响有了新的研究和发现,证实了Nisbett最初的观点是正确的.文化与注意的行为研究包括在整体与局部加工、场依存与场独立、变化盲等方面的研究.对于注意文化差异的潜在原因和机制,研究者们主要从发展性研究、ERP和FMRI研究等方面进行探讨.未来研究需要进一步探索文化对其它注意指标的影响、文化与注意的脑机制以及文化与注意的应用研究等等.     

情景记忆成功年老化的神经机制

随着年龄的增长, 大部分老年人的情景记忆会出现衰退, 但也会有一部分老年人的情景记忆表现出成功的年老化, 即记忆成绩较好或随增龄的衰退程度较小。脑保持理论、神经去分化理论、认知储备理论以及神经补偿理论分别从不同角度解释了情景记忆成功年老化的神经机制。基于选择性优化与补偿模型对现有理论进行整合, 发现情景记忆成功年老化可能与个体的认知储备水平直接相关：高认知储备的老年人能够对情景记忆相关的脑区和脑网络进行优化且具备更强的神经补偿能力, 因而其脑功能(比如, 神经表征和神经加工通路的特异性)可能会保持地更好。未来研究需要更多地采用纵向设计来考察各理论之间的关系及其影响因素, 从而更好地解释记忆成功年老化的神经机制并为提升老年人的脑与认知健康提供支持。     

Contributions of dynamic systems theory to cognitive development

We examine the contributions of dynamic systems theory to the field of cognitive development, focusing on modeling using dynamic neural fields. After introducing central concepts of dynamic field theory (DFT), we probe empirical predictions and findings around two examples—the DFT of infant perseverative reaching that explains Piaget's A-not-B error and the DFT of spatial memory that explain changes in spatial cognition in early development. Review of the literature around these examples reveals that computational modeling is having an impact on empirical research in cognitive development; however, this impact does not extend to neural and clinical research. Moreover, there is a tendency for researchers to interpret models narrowly, anchoring them to specific tasks. We conclude on an optimistic note, encouraging both theoreticians and experimentalists to work toward a more theory-driven future.     

A review of brain-based neuro-cognitive models

We present a survey of recent brain-based neural network models of various aspects of cognition, covering learning and episodic memory, working memory, attention control, goal formation, language learning and use and consciousness. These models are assessed in the light of their explanation of experimental data, as well as the possible help they have provided in understanding global cognitive processing principles. The paper concludes with a discussion of how the models discussed might help to guide the creation of an artificial cognitive brain.     

Neural and cognitive plasticity: from maps to minds

Some species and individuals are able to learn cognitive skills more flexibly than others. Learning experiences and cortical function are known to contribute to such differences, but the specific factors that determine an organism's intellectual capacities remain unclear. Here, an integrative framework is presented suggesting that variability in cognitive plasticity reflects neural constraints on the precision and extent of an organism's stimulus representations. Specifically, it is hypothesized that cognitive plasticity depends on the number and diversity of cortical modules that an organism has available as well as the brain's capacity to flexibly reconfigure and customize networks of these modules. The author relates this framework to past proposals on the neural mechanisms of intelligence, including (a) the relationship between brain size and intellectual capacity; (b) the role of prefrontal cortex in cognitive control and the maintenance of stimulus representations; and (c) the impact of neural plasticity and efficiency on the acquisition and performance of cognitive skills. The proposed framework provides a unified account of variability in cognitive plasticity as a function of species, age, and individual, and it makes specific predictions about how manipulations of cortical structure and function will impact intellectual capacity.     

Spiking neural networks and hippocampal function: A web-accessible survey of simulations,modeling methods,and underlying theories

Computational modeling has contributed to hippocampal research in a wide variety of ways and through a large diversity of approaches, reflecting the many advanced cognitive roles of this brain region. The intensively studied neuron type circuitry of the hippocampus is a particularly conducive substrate for spiking neural models. Here we present an online knowledge base of spiking neural network simulations of hippocampal functions. First, we overview theories involving the hippocampal formation in subjects such as spatial representation, learning, and memory. Then we describe an original literature mining process to organize published reports in various key aspects, including: (i) subject area (e.g., navigation, pattern completion, epilepsy); (ii) level of modeling detail (Hodgkin-Huxley, integrate-and-fire, etc.); and (iii) theoretical framework (attractor dynamics, oscillatory interference, self-organizing maps, and others). Moreover, every peer-reviewed publication is also annotated to indicate the specific neuron types represented in the network simulation, establishing a direct link with the Hippocampome.org portal. The web interface of the knowledge base enables dynamic content browsing and advanced searches, and consistently presents evidence supporting every annotation. Moreover, users are given access to several types of statistical reports about the collection, a selection of which is summarized in this paper. This open access resource thus provides an interactive platform to survey spiking neural network models of hippocampal functions, compare available computational methods, and foster ideas for suitable new directions of research.     

Value systems for developmental cognitive robotics: A survey

This paper surveys value systems for developmental cognitive robotics. A value system permits a biological brain to increase the likelihood of neural responses to selected external phenomena. Many machine learning algorithms capture the essence of this learning process. However, computational value systems aim not only to support learning, but also autonomous attention focus to direct learning. This combination of unsupervised attention focus and learning aims to address the grand challenge of autonomous mental development for machines. This survey examines existing value systems for developmental cognitive robotics in this context. We examine the definitions of value used—including recent pioneering work in intrinsic motivation as value—as well as initialisation strategies for innate values, update strategies for acquired value and the data structures used for storing value. We examine the extent to which existing value systems support attention focus, learning and prediction in an unsupervised setting. The types of robots and applications in which these value systems are used are also examined, as well as the ways that these applications are evaluated. Finally, we study the strengths and limitations of current value systems for developmental cognitive robots and conclude with a set of research challenges for this field.     

Neurophysiology and neuroanatomy of reflexive and volitional saccades: evidence from studies of humans

This review provides a summary of the contributions made by human functional neuroimaging studies to the understanding of neural correlates of saccadic control. The generation of simple visually guided saccades (redirections of gaze to a visual stimulus or pro-saccades) and more complex volitional saccades require similar basic neural circuitry with additional neural regions supporting requisite higher level processes. The saccadic system has been studied extensively in non-human (e.g., single-unit recordings) and human (e.g., lesions and neuroimaging) primates. Considerable knowledge of this system’s functional neuroanatomy makes it useful for investigating models of cognitive control. The network involved in pro-saccade generation (by definition largely exogenously-driven) includes subcortical (striatum, thalamus, superior colliculus, and cerebellar vermis) and cortical (primary visual, extrastriate, and parietal cortices, and frontal and supplementary eye fields) structures. Activation in these regions is also observed during endogenously-driven voluntary saccades (e.g., anti-saccades, ocular motor delayed response or memory saccades, predictive tracking tasks and anticipatory saccades, and saccade sequencing), all of which require complex cognitive processes like inhibition and working memory. These additional requirements are supported by changes in neural activity in basic saccade circuitry and by recruitment of additional neural regions (such as prefrontal and anterior cingulate cortices). Activity in visual cortex is modulated as a function of task demands and may predict the type of saccade to be generated, perhaps via top-down control mechanisms. Neuroimaging studies suggest two foci of activation within FEF - medial and lateral - which may correspond to volitional and reflexive demands, respectively. Future research on saccade control could usefully (i) delineate important anatomical subdivisions that underlie functional differences, (ii) evaluate functional connectivity of anatomical regions supporting saccade generation using methods such as ICA and structural equation modeling, (iii) investigate how context affects behavior and brain activity, and (iv) use multi-modal neuroimaging to maximize spatial and temporal resolution.     

基于语义网络的创造性认知机制研究现状与展望

语义网络是主要的知识表征方式之一,对创造性研究具有重要意义。近年来不断发展的网络科学方法为相关研究提供了强大的方法论框架及量化工具,研究者得以分别从语义网络结构及语义相关认知操作的角度探讨语义网络与创造性的内在联系。已有证据表明语义网络中所储存的概念越丰富、概念间的连接通路越多元化或越灵活,则个体创造性水平越高;而个体创造性水平亦受制于个体对概念的检索、抑制、选择、整合及扩展等认知能力。在此方向上,未来研究工作应当更多地思考如何在一个相对整合的认知框架中深入探讨语义网络结构及相关认知过程对创造性的交互作用,并结合神经影像等技术手段,将语义网络之于创造性的认知机制嵌套于神经科学体系中进行解释。     

A nonlinear dynamic artificial neural network model of memory

Nonlinearity and dynamics in psychology are found in various domains such as neuroscience, cognitive science, human development, etc. However, the models that have been proposed are mostly of a computational nature and ignore dynamics. In those models that do include dynamic properties, only fixed points are used to store and retrieve information, leaving many principles of nonlinear dynamic systems (NDS) aside; for instance, chaos is often perceived as a nuisance. This paper considers a nonlinear dynamic artificial neural network (NDANN) that implements NDS principles while also complying with general neuroscience constraints. After a theoretical presentation, simulation results will show that the model can exhibit multi-valued, fixed-point, region-constrained attractors and aperiodic (including chaotic) behaviors. Because the capabilities of NDANN include the modeling of spatiotemporal chaotic activities, it may be an efficient tool to help bridge the gap between biological memory neural models and behavioral memory models.     

Neurophysiology and neuroanatomy of reflexive and volitional saccades: Evidence from studies of humans

This review provides a summary of the contributions made by human functional neuroimaging studies to the understanding of neural correlates of saccadic control. The generation of simple visually guided saccades (redirections of gaze to a visual stimulus or pro-saccades) and more complex volitional saccades require similar basic neural circuitry with additional neural regions supporting requisite higher level processes. The saccadic system has been studied extensively in non-human (e.g., single-unit recordings) and human (e.g., lesions and neuroimaging) primates. Considerable knowledge of this system’s functional neuroanatomy makes it useful for investigating models of cognitive control. The network involved in pro-saccade generation (by definition largely exogenously-driven) includes subcortical (striatum, thalamus, superior colliculus, and cerebellar vermis) and cortical (primary visual, extrastriate, and parietal cortices, and frontal and supplementary eye fields) structures. Activation in these regions is also observed during endogenously-driven voluntary saccades (e.g., anti-saccades, ocular motor delayed response or memory saccades, predictive tracking tasks and anticipatory saccades, and saccade sequencing), all of which require complex cognitive processes like inhibition and working memory. These additional requirements are supported by changes in neural activity in basic saccade circuitry and by recruitment of additional neural regions (such as prefrontal and anterior cingulate cortices). Activity in visual cortex is modulated as a function of task demands and may predict the type of saccade to be generated, perhaps via top-down control mechanisms. Neuroimaging studies suggest two foci of activation within FEF - medial and lateral - which may correspond to volitional and reflexive demands, respectively. Future research on saccade control could usefully (i) delineate important anatomical subdivisions that underlie functional differences, (ii) evaluate functional connectivity of anatomical regions supporting saccade generation using methods such as ICA and structural equation modeling, (iii) investigate how context affects behavior and brain activity, and (iv) use multi-modal neuroimaging to maximize spatial and temporal resolution.     

Cognition to genes via the brain in the study of conduct disorder

Although a single diagnostic label, conduct disorder, is currently applied to children exhibiting antisocial behaviour, multiple routes to the same behavioural phenomena exist. Morton and Frith's (1995) causal modelling has been fundamentally important in influencing models of cognitive/affective and associated neural differences between callous-unemotional (CU) and reactive/threat-based antisocial behaviour. Current behavioural genetic research is still catching up with the developmental cognitive neuroscience, and very few genetically informative studies differentiate between these two subtypes of antisocial behaviour. Our own work with preadolescent twins suggests that while the CU subtype is genetically vulnerable to antisocial behaviour, the non-CU subtype manifests a primarily environmental aetiology to their antisocial behaviour. Molecular genetic work to date has not differentiated between these two subtypes, and we highlight why it might be of interest to do so. Finally, we discuss how the novel approach of imaging genetics could be harnessed to study genes to cognition pathways for different subtypes of conduct disorder. Uta Frith's contributions to articulating research strategies for developmental disorders are important in conducting and interpreting this work.     

Understanding memory impairment with memory models and hierarchical Bayesian analysis

The study of human episodic memory is a topic that interests cognitive and mathematical psychologists as well as clinicians interested in the diagnosis and assessment of Alzheimer’s disease and related disorders (ADRD). In this paper, we use simple cognitive models for the recognition and recall tasks typically applied in clinical assessments of ADRD to study memory performance in ADRD patients. Our models make use of hierarchical Bayesian methods as a way to model individual differences in patient performance and to facilitate the modeling of performance changes that occur during multiple recall tasks. We show how the models are able to account for different aspects of patient performance, and also discuss some of the predictive capabilities of the model. We conclude with a discussion on the scope to improve on our results by discussing the link between memory theory in psychology and clinical practice.