从人脑到计算机─—鸿沟能否逾越

人类对人脑及其精神活动过程的彻底了解,意味着哲学上的根本性事件的发生。所谓彻底的了解,标志就是人类对这种精神活动的成功模拟和再现。作为神经科学的分支和广延的人工智能的兴起,使人类有理由希望：存在于人脑与计算机之间的鸿沟终将被人类逾越。     

冲突控制的神经机制

人类认知系统的一个重要特征是它能根据知觉选择、反应偏向以及实时更新的情境信息调节自身以适应特定的任务,使这种适应性得以实现的认知过程就是认知控制。该文简述了冲突控制的界定、实验范式、冲突的种类等方面,尤其详细介绍了冲突控制神经机制研究的最新进展,并对进一步的研究提出展望。     

Understanding Cognition Through Large-Scale Cortical Networks

An emerging body of evidence from a number of fields is beginning to reveal general neural principles underlying cognition. The characteristic adaptability of cognitive function is seen to derive from large-scale networks in the cerebral cortex that are able to repeatedly change the state of coordination among their constituent areas on a subsecond time scale. Experimental and theoretical studies suggest that large-scale network dynamics operate in a metastable regime in which the interdependence of cortical areas is balanced between integrating and segregating activities. Cortical areas, through their coordination dynamics, are thought to rapidly resolve a large number of mutually imposed constraints, leading to consistent local states and a globally coherent state of cognition.     

Connecting the Many Levels and Facets of Cognitive Aging

Basic cognitive mechanisms, such as the abilities to briefly maintain, focus, and process information, decline with age. Related fields of cognitive aging research have been advancing rapidly, but mostly independently, at the biological, information processing, and behavioral levels. To facilitate integration, this article reviews research on cognitive aging at the different levels, and describes a recent integrative theory postulating that aging-related deficiencies in neurotransmission cause increased noise in information processing and less distinctive cortical representation, which in turn lead to cognitive deficits. Aging-related attenuation of catecholaminergic modulation can be modeled by lowering a neural network parameter to reduce the signal-to-noise ratio of information processing. The performance of such models is consistent with benchmark phenomena observed in humans, ranging from age differences in learning rate, asymptotic performance, and interference susceptibility to intra- and interindividual variability and ability dedifferentiation. Although the details of the conjectured sequence of effects linking neuromodulation to cognitive aging deficits await further empirical validation, cross-level theorizing of the kind illustrated here could foster the coevolution of related fields through cross-level data synthesis and hypothesis testing.     

基于人工神经网络的一种效度凭证求取方法

针对基于统计学的效度凭证求取方法所存在的问题,提出了基于人工神经网络的效度凭证求取方法。蒙特卡罗模拟实验和对实际数据的分析表明,当测验分数和效标分数为单变量且非线性关系时,或者测验分数和效标分数为多变量时,运用神经网络方法可以比统计学方法更好地求取心理测验效度的基于和其他变量关系的凭证。     

客体相似性对不同认知方式个体视觉工作记忆表征的影响

采用整体检测的变化察觉范式,探讨客体的相似性对客体—空间型认知方式个体视觉工作记忆表征的影响。行为结果显示,在不相似客体的视觉工作记忆表征任务中,客体型者在长延时条件的成绩优于空间型者,而在相似客体的视觉工作记忆表征任务中,两者无差异;ERP结果显示,在不相似客体视觉工作记忆表征任务中,与客体型者相比,空间型者在大脑皮层诱发出更大的负SP。以上结果表明,客体型者比空间型者对不相似客体视觉工作记忆加工具有优势,其潜在机制可能在于,客体型者对不相似客体视觉工作记忆表征时的神经活动效能更高。     

舌尖现象的研究进展

舌尖现象(thetip of tongue phenomenon,简称TOT)具有非常重要的研究价值,通过了解TOT的产生机制可以为我们理解言语产生等问题提供一个视窗,本文总结和回顾了国外有关TOT研究各方面的进展情况,并指出了当前研究存在的一些问题,目的是给国内的同行提供一点借鉴。     

失用性失写的脑机制

失用性失写是指人们知道该如何书写, 但实际上却不会书写或错误书写的一种现象。失用性失写涉及的神经网络包括皮层与皮层连接、皮层与皮质下连接。其中前者包括额-顶叶相关脑区的连接、顶-枕叶相关脑区的连接以及额-顶-枕相关脑区的连接, 这些神经网络分别负责操作空间表征图像、回忆以及检索字母的形状等; 后者包括小脑与额-顶叶的连接、左丘脑-大脑皮质的连接以及纹状体-内囊-左额顶叶的连接等, 它们分别与图像输出程序、书写运动过程、操作指令的执行过程以及字素形成过程等有关。今后的研究应该集中在完善失用性失写的研究范式、深入探讨失用性失写的心理机制以及推动其康复工作的开展等方面。     

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.     

持续性植物状态若干问题的探讨

明确意识的含义及意识障碍的分类是分析持续性植物状态的前提。根据多年临床经验对持续性植物状态的定义、评分标准、诊断与鉴别诊断进行深入割析。植物状态的研究取得相当进展,但从诊断、评分到治疗手段仍面临诸多困惑,而神经干细胞移植和神经电刺激术是未来希望所在。