情绪识别研究中被“冷落”的线索:躯体表情加工的特点、神经基础及加工机制

躯体和面孔是个体情绪表达与识别的重要线索。与面部表情相比,躯体表情加工的显著特点是补偿情绪信息,感知运动与行为信息,及产生适应性行为。情绪躯体与面孔加工的神经基础可能相邻或部分重合,但也存在分离;EBA、FBA、SPL、IPL等是与躯体表情加工相关的特异性脑区。今后应系统研究面孔、躯体及语音情绪线索加工潜在的神经基础,探讨躯体情绪加工的跨文化差异,考察情绪障碍患者的躯体表情加工特点。     

人声加工的神经机制

人声是人类听觉环境中最熟知和重要的声音, 传递着大量社会相关信息。与视觉人脸加工类似, 大脑对人声也有着特异性加工。研究者使用电生理、脑成像等手段找到了对人声有特异性反应的脑区, 即颞叶人声加工区(TVA), 并发现非人类动物也有类似的特异性加工区域。人声加工主要涉及言语、情绪和身份信息的加工, 分别对应于三条既相互独立又相互作用的神经通路。研究者提出了双通路模型、多阶段模型和整合模型分别对人声的言语、情绪和身份加工进行解释。未来研究需要进一步讨论人声加工的特异性能否由特定声学特征的选择性加工来解释, 并深入探究特殊人群(如自闭症和精神分裂症患者)的人声加工的神经机制。     

Brain network interactions in auditory, visual and linguistic processing

In the paper, we discuss the importance of network interactions between brain regions in mediating performance of sensorimotor and cognitive tasks, including those associated with language processing. Functional neuroimaging, especially PET and fMRI, provide data that are obtained essentially simultaneously from much of the brain, and thus are ideal for enabling one to assess interregional functional interactions. Two ways to use these types of data to assess network interactions are presented. First, using PET, we demonstrate that anterior and posterior perisylvian language areas have stronger functional connectivity during spontaneous narrative production than during other less linguistically demanding production tasks. Second, we show how one can use large-scale neural network modeling to relate neural activity to the hemodynamically-based data generated by fMRI and PET. We review two versions of a model of object processing - one for visual and one for auditory objects. The regions comprising the models include primary and secondary sensory cortex, association cortex in the temporal lobe, and prefrontal cortex. Each model incorporates specific assumptions about how neurons in each of these areas function, and how neurons in the different areas are interconnected with each other. Each model is able to perform a delayed match-to-sample task for simple objects (simple shapes for the visual model; tonal contours for the auditory model). We find that the simulated electrical activities in each region are similar to those observed in nonhuman primates performing analogous tasks, and the absolute values of the simulated integrated synaptic activity in each brain region match human fMRI/PET data. Thus, this type of modeling provides a way to understand the neural bases for the sensorimotor and cognitive tasks of interest.     

Towards a neural basis of music perception

Music perception involves complex brain functions underlying acoustic analysis, auditory memory, auditory scene analysis, and processing of musical syntax and semantics. Moreover, music perception potentially affects emotion, influences the autonomic nervous system, the hormonal and immune systems, and activates (pre)motor representations. During the past few years, research activities on different aspects of music processing and their neural correlates have rapidly progressed. This article provides an overview of recent developments and a framework for the perceptual side of music processing. This framework lays out a model of the cognitive modules involved in music perception, and incorporates information about the time course of activity of some of these modules, as well as research findings about where in the brain these modules might be located.     

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.     

基于Think/No-think范式的动机性遗忘研究:行为与脑机制

想/不想范式(Think/No-think,TNT)是基于go/no-go范式提出来的用于研究动机性遗忘过程的实验范式,主要过程是指个体对于记忆的提取抑制可以导致随后该记忆的遗忘。近年来TNT范式的大量行为学研究都一致性地发现记忆提取抑制可以产生负性控制效应,验证了在实验室情境下对动机性遗忘进行研究的可行性。其中,负性控制效应指的是压抑条件的项目相对于基线条件的项目的回忆量有显著降低。关于动机性遗忘发生的神经机制的探讨已积累了大量的研究证据,总结脑电(EEG)和功能核磁共振(f MRI)两个模态的研究,我们提出了动机性遗忘发生的多模态功能网络模型。最后,在该模型的基础上,我们展望了TNT范式未来的研究方向,其中特别注意到同步EEG-f MRI技术的应用有望为我们揭示出记忆提取抑制导致的动机性遗忘发生的动态过程。     

基于神经网络的黑白图形视觉识别机制模拟

物理刺激引起视觉系统的生理反应．经过大脑的信息加工而形成视觉。现有多种模型从不同角度对视觉机制进行模拟。该文利用人工神经网络技术对黑白图形识别的视觉机制加以模拟,构建了一个两层BP(back-propagatbn)神经网络模型。应用所建网络对一幅目标和背景灰度分布曲线有重叠的图像进行了成功识别．对大脑视觉加工机制作了有益的探索。     

公平偏好的电生理测量：来自脑电、皮肤电和心电的证据

研究发现,人们普遍具有追求公平的偏好,即人们在追求个人收益时也会关注收益分配的公平性。随着电生理技术的发展,越来越多的研究者采用电生理技术对公平偏好进行深入探讨。本研究从脑电、皮肤电、心电等方面梳理公平偏好的电生理机制。脑电的研究发现,公平偏好相关的脑电主要涉及反馈相关负波和P300;皮肤电的研究发现,相比于公平分配,个体在不公平分配情况下其皮肤电的激活水平更高;心率的研究发现,相比于公平分配,个体遭遇不公平分配时其心率降低。研究公平偏好电生理机制有助于更深入地揭示公平偏好的产生根源与形成过程。未来可从公平偏好电生理的整合研究、公平偏好的脑成像与电生理的整合性探索,以及拓展公平偏好电生理的外部效度和研究范式等方面展开进一步探究。     

Towards a neural basis of auditory sentence processing

Functional dissociations within the neural basis of auditory sentence processing are difficult to specify because phonological, syntactic and semantic information are all involved when sentences are perceived. In this review I argue that sentence processing is supported by a temporo-frontal network. Within this network, temporal regions subserve aspects of identification and frontal regions the building of syntactic and semantic relations. Temporal analyses of brain activation within this network support syntax-first models because they reveal that building of syntactic structure precedes semantic processes and that these interact only during a later stage.     

Spatial and temporal limits in cognitive neuroimaging with fMRI

A large body of research in human perception and cognition has been concerned with the segregation of mental events into their presumed hierarchical processing stages, the temporal aspect of such processing being termed ‘mental chronometry’. Advances in single-event functional magnetic resonance imaging (fMRI) have allowed the extraction of relative timing information between the onset of activity in different neural substrates as well as the duration of cognitive processing during a task, offering new opportunities in the study of human perception and cognition. Single-event fMRI studies have also facilitated increased spatial resolution in fMRI, allowing studies of columnar organization in humans. Important processes such as object recognition, binocular vision and other processes are thought to be organized at the columnar level; thus, these advances in the spatial and temporal capabilities of fMRI allow a new generation of cognitive and basic neuroscience studies to be performed, investigating the temporal and spatial relationships between these cortical sub-units. Such experiments bear a closer resemblance to single-unit or evoked-potential studies than to classical static brain activation maps and might serve as a bridge between primate electrophysiology and human studies. These advances are initially demonstrated only in simple visual and motor system tasks and it is likely to be several years before the techniques we describe are robust enough for general use.     

成人依恋风格在信息加工中表现出差异性的神经机制

依恋风格的神经机制研究有助于更深层次理解依恋行为与类型：N1、N200、N400和P300等脑电成份的差异反映了不同依恋风格在编码、提取及注意资源分配上的不同; 额叶皮层、扣带回皮层、颞极、杏仁核、海马等脑区可以反映不同依恋风格在信息加工性质和注意资源分配上的差异。已有研究除安全依恋和非安全依恋策略的有效性在脑成像上的研究与依恋理论一致外, 其余研究还存在争议。未来的研究可深入探究更高质量的依恋测量工具, 依恋风格对内隐刺激加工影响的认知神经机制; 细化依恋风格在信息加工不同阶段的神经活动和脑成像研究; 以及关注依恋风格对信息加工影响差异的脑机制在临床治疗中的运用。     

汉语双字词在心理词典中的表征方式:来自fNIRS的证据

以汉语双字构成的真词与假词为实验材料,22名大学生为被试,采用功能性近红外脑成像技术(f NIRS)和事件相关设计,考察被试在完成词汇判断任务时的大脑激活模式,探索汉语双字词在心理词典中的表征方式。结果发现:(1)在完成真假词判断任务时,被试大脑左侧额叶和左侧颞叶均被激活;(2)与判断假词相比,被试在判断真词时显著地激活左额上回和左额中回。这一结果说明汉语双字词在心理词典中是混合表征的。     

时间认知神经科学研究进展

当前对时间认知的脑机制探讨有三个模型：特异化计时模型、分布网络模型和定域计时模型。在这些模型的框架下,时间认知的神经心理学研究集中探讨了小脑、基底神经节、前额叶在时间信息加工中的作用和大脑两半球在时间认知中的不对称性。小脑作为内部计时系统对时间控制具有重要作用,在周期性动作任务中,小脑对不连续动作计时具有特异性。基底神经节在时间加工任务中与小脑存在明显的作用分离,其具体机制还有待深入研究。前额叶的计时功能可能与注意和工作记忆对时间信息的获得、维持和组织有关。此外,还发现大脑右半球与时问信息的加工关系密切。     

Is There Room for ‘Development’ in Developmental Models of Information Processing Biases to Threat in Children and Adolescents?

Clinical and experimental theories assume that processing biases in attention and interpretation are a causal mechanism through which anxiety develops. Despite growing evidence that these processing biases are present in children and, therefore, develop long before adulthood, these theories ignore the potential role of child development. This review attempts to place information processing biases within a theoretical developmental framework. We consider whether child development has no impact on information processing biases to threat (integral bias model), or whether child development influences information processing biases and if so whether it does so by moderating the expression of an existing bias (moderation model) or by affecting the acquisition of a bias (acquisition model). We examine the extent to which these models fit with existing theory and research evidence and outline some methodological issues that need to be considered when drawing conclusions about the potential role of child development in the information processing of threat stimuli. Finally, we speculate about the developmental processes that might be important to consider in future research.     

Syntactic, prosodic, and semantic processes in the brain: evidence from event-related neuroimaging

The neural network supporting aspects of syntactic, prosodic, and semantic information processing is specified on the basis of two experiments using functional magnetic resonance imaging (fMRI). In these two studies, the presence/absence of lexical-semantic and syntactic information is systematically varied in spoken language stimuli. Inferior frontal and temporal brain areas in the left and the right hemisphere are identified to support different aspects of auditory language processing. Two additional experiments using event-related brain potentials investigate the possible interaction of syntactic and prosodic information, on the one hand, and syntactic and semantic information, on the other. While the first two information types were shown to interact early during processing, the latter two information types do not. Implications for models of auditory language comprehension are discussed.     

Modeling the emergence of informational content by adaptive networks for temporal factorisation and criterial causation

Propagated activation of neurons through their network is an important process in the brain. Another crucial part of neural processing concerns adaptation over time of characteristics of this network such as connection strengths or excitability thresholds. This adaptation can be slow, as in learning from a multiple experiences, or it can be fast, as in memory formation. These adaptive network characteristics can be considered informational criteria for activation of a neuron. This then is viewed as a form of emergent information formation. Activation of neurons is determined by such information via a process termed criterial causation. In the current paper, the relationship of criterial causation with the principle of temporal factorisation for the dynamics of the world in general is explored. Temporal factorisation describes how the world represents information about its past in its present state, which then in turn determines the world’s future. In the paper, it is shown how these processes are analysed in more detail and modeled by (adaptive) network models.     

The Importance of the Default Mode Network in Creativity—A Structural MRI Study

Anecdotal reports as well as behavioral studies have suggested that creative performance benefits from unconscious processes. So far, however, little is known about how creative ideas arise from the brain. In the current study, we aimed to investigate the neural correlates of creativity by means of structural MRI research. Given that unconscious and less controlled processes are important in creative thinking, structural brain research may find a positive correlation between well‐established creativity measures and cortical thickness in brain structures of the default mode network (i.e., the counterpart of the cognitive control network). Individuals performed the Alternative Uses task by which an individual's cognitive flexibility and the average uniqueness and average creativity of a participant's ideas were assessed. We computed optimized voxel‐based‐morphometry (VBM) to explore the correlation between inter‐individual differences in creativity and inter‐individual differences in gray matter volume. For all creativity measures, a positive correlation was found between creative performance and gray matter volume of the default mode network. These findings support the idea that the default mode network is important in creativity, and provide neurostructural support for the idea that unconscious forms of information processing are important in creativity. Theoretical and practical implications are discussed.     

神经网络模型对内隐学习的探索

近几年来,研究者们借助人工神经网络模型的方法对内隐学习研究中突出的争论性问题进行了新的探索。针对内隐学习的无意识问题,模拟研究发现确实存在一种无意识的内隐学习,然而这种无意识加工的发生与否要取决于规则的难易程度;针对内隐学习的抽象性问题,人工神经网络模型所主张的分布式概率表征能较好地加以解释。可见,神经网络模型的原理和模拟研究可能为真正地解决内隐学习的无意识性和抽象性等目前争论较多的领域提供一个全新的视角和研究方向。     

Bridging the gap between physiology and behavior: evidence from the sSoTS model of human visual attention

We present the case for a role of biologically plausible neural network modeling in bridging the gap between physiology and behavior. We argue that spiking-level networks can allow "vertical" translation between physiological properties of neural systems and emergent "whole-system" performance-enabling psychological results to be simulated from implemented networks and also inferences to be made from simulations concerning processing at a neural level. These models also emphasize particular factors (e.g., the dynamics of performance in relation to real-time neuronal processing) that are not highlighted in other approaches and that can be tested empirically. We illustrate our argument from neural-level models that select stimuli by biased competition. We show that a model with biased competition dynamics can simulate data ranging from physiological studies of single-cell activity (Study 1) to whole-system behavior in human visual search (Study 2), while also capturing effects at an intermediate level, including performance breakdown after neural lesion (Study 3) and data from brain imaging (Study 4). We also show that, at each level of analysis, novel predictions can be derived from the biologically plausible parameters adopted, which we proceed to test (Study 5). We argue that, at least for studying the dynamics of visual attention, the approach productively links single-cell to psychological data.     

Neural-network models of learning and memory: leading questions and an emerging framework

Real-time neural-network models provide a conceptual framework for formulating questions about the nature of cognition, an architectural framework for mapping cognitive functions to brain regions, a semantic framework for defining terms, and a computational framework for testing hypotheses. This article considers key questions about how a physical system might simultaneously support one-trial learning and lifetime memories, in the context of neural models that test possible solutions to the problems posed. Model properties point to partial answers, and model limitations lead to new questions. Placing individual system components in the context of a unified real-time network allows analysis to move from the level of neural processes, including learning laws and rules of synaptic transmission, to cognitive processes, including attention and consciousness.