视觉学习与成人大脑的可塑性

我们对视觉特征和客体的分辨与识别能力会随着训练提高,这种现象被称为视知觉学习。对其神经机制的研究使我们更好地理解成人大脑可塑性。回顾了该研究领域的两大核心问题:(1)视知觉学习发生的皮层位置:学习发生在早期信息加工的视皮层,或是涉及决策等认知功能的高级额顶叶区域,抑或是视觉区域到高级认知区域的连接;(2)视知觉学习发生的形式:包括表征增强、表征锐化、易化等多种机制。最后,讨论了神经干预手段在知觉学习领域的应用,并展望该领域未来的研究方向。     

面孔社会性线索的加工机制

本文旨在综述面孔社会性线索加工的神经机制。通过系统回顾面孔社会性线索相关的研究,分别从面孔情绪、面孔吸引力、眼睛注视方向和面孔朝向以及唇读四个角度阐述其加工的神经机制。首先简要阐述了人类大脑对面孔刺激的一般加工机制,包括下颞叶梭状回面孔区、颞上沟后部面孔区和枕下回的枕叶面孔区等脑区在加工面孔刺激中的功能。接下来探讨了大脑对情绪面孔的加工。情绪面孔加工主要包括对面孔的知觉编码和情绪编码。研究显示,除了视觉皮层的面孔加工区之外,杏仁核在情绪编码中具有重要作用。神经系统对面孔表情的反应受到情绪类型、情绪面孔的动态性以及情绪面孔阈下呈现等因素的影响。在面孔吸引力加工方面,研究表明高吸引力面孔会激活奖赏相关的神经环路,但是吸引力对神经活动的具体影响目前仍存在争议。对面孔吸引力的神经反应可能受实验任务类型、观察者性取向和性别、观察者心理因素、面孔其他社会线索等因素的调节。眼睛注视方向和面孔朝向线索则和视觉注意有关,其神经加工系统除了包括面孔加工区外,还包括和注意相关的顶内沟等区域。关于唇读的研究则表明唇读在言语知觉中具有重要作用,可以激活听觉皮层和言语相关皮层。最后,一方面总结了以上各方面实验证据对面孔信息加工理论的支持和改善作用,另一方面进一步探讨了特殊人群中这些加工存在的缺陷,并指出了该领域未来的研究方向。     

综述: 初级视皮层的亮度信息加工

亮度(luminance)是最基本的视觉信息.与其他视觉特征相比,由于视神经元对亮度刺激的反应较弱,并且许多神经元对均匀亮度无反应,对亮度信息编码的神经机制知之甚少.初级视皮层部分神经元对亮度的反应要慢于对比度反应,被认为是由边界对比度诱导的亮度知觉(brightness)的神经基础.我们的研究表明,初级视皮层许多神经元的亮度反应要快于对比度反应,并且这些神经元偏好低的空间频率、高的时间频率和高的运动速度,提示皮层下具有低空间频率和高运动速度通路的信息输入对产生初级视皮层神经元的亮度反应有贡献.已经知道初级视皮层神经元对空间频率反应的时间过程是从低空间频率到高空间频率,我们发现的早期亮度反应是对极低空间频率的反应,与这一时间过程是一致的,是这一从粗到细的视觉信息加工过程的第一步,揭示了处理最早的粗的视觉信息的神经基础.另外,初级视皮层含有偏好亮度下降和高运动速度的神经元,这群神经元的活动有助于在光照差的环境中检测高速运动的低亮度物体.     

初级视皮层的亮度信息加工

亮度(luminance)是最基本的视觉信息.与其他视觉特征相比,由于视神经元对亮度刺激的反应较弱,并且许多神经元对均匀亮度无反应,对亮度信息编码的神经机制知之甚少.初级视皮层部分神经元对亮度的反应要慢于对比度反应,被认为是由边界对比度诱导的亮度知觉(brightness)的神经基础.我们的研究表明,初级视皮层许多神经元的亮度反应要快于对比度反应,并且这些神经元偏好低的空间频率、高的时间频率和高的运动速度,提示皮层下具有低空间频率和高运动速度通路的信息输入对产生初级视皮层神经元的亮度反应有贡献.已经知道初级视皮层神经元对空间频率反应的时间过程是从低空间频率到高空间频率,我们发现的早期亮度反应是对极低空间频率的反应,与这一时间过程是一致的,是这一从粗到细的视觉信息加工过程的第一步,揭示了处理最早的粗的视觉信息的神经基础.另外,初级视皮层含有偏好亮度下降和高运动速度的神经元,这群神经元的活动有助于在光照差的环境中检测高速运动的低亮度物体.     

视知觉学习的神经机制

感知分辨能力经过训练而提高的现象称为知觉学习。由于缺乏有力的生理学证据,已往主要基于行为和脑成像的研究存在分歧,焦点在于知觉学习发生的脑区和编码形式。近年来,结合心理物理和清醒猴电生理的系列研究表明,视觉检测训练可以优化大脑初级视皮层神经元的编码,该过程依赖于自上而下的信号调控。这些发现提示,知觉学习改变了前馈输入和反馈信号之间的相互作用。这种多脑区间的协同编码机制为理解学习与脑的可塑性提供了新的视角。     

视觉编码的快速学习

活动依赖的神经可塑性在视觉皮层信息处理过程中起着很重要的作用。该文将讲述几个关于视觉刺激引起皮层反应发生快速变化的研究工作。在体膜片钳的实验结果表明,将视觉刺激与能够诱发孽个视皮层神经元发放动作电位的电刺激相偶联可以改变神经元的感受野特性。单电极和多电极胞外记录的实验结果显示,反复地给予自然图形电影刺激,不仅能增加视皮层神经元反应的可靠性,而且能造成之后的自发活动中存在“记忆的痕迹”。最后,用电压敏感染料成像的方法对群体细胞活动进行考察,结果提示视觉活动之后的皮层回放可能是由皮层波介导的。     

自然感觉刺激对脑发育的影响

大脑的正常认知功能依赖于其复杂而精细的神经网络。来自环境的刺激,特别是自然的感觉刺激,对大脑皮层的多个脑区中神经元的生长、突触的形成,以及神经网络的建立至关重要。感觉输入不仅可以影响其对应感觉皮层的功能,而且可以通过跨模态机制影响其他感觉皮层的功能。然而,前人关于跨模态可塑性机制的研究主要集中在成年个体上,基本没有涉及发育早期的机制。为了研究自然感觉刺激对大脑皮层的调节,中科院神经所于翔研究组建立了对新生小鼠进行感觉刺激或剥夺的行为范式,包括通过胡须拔除对小鼠进行特异的触觉剥夺、黑暗环境饲养对小鼠进行特异的视觉剥夺,和丰富环境饲养对小鼠进行多模态的自然感觉刺激。研究发现,从出生起对小鼠进行触觉或视觉剥夺,不仅影响了对应大脑皮层的发育,而且还减缓了其他感觉皮层的发育,而通过丰富环境饲养增加感觉刺激可以促进多个感觉皮层的发育。该研究揭示了一种新型的发育早期感觉经验依赖的感觉皮层跨模态可塑性机制,并发现了催产素这种由下丘脑分泌的神经肽是介导该跨模态可塑性的关键分子。催产素由于其与情绪和社交行为的相关性,已成为孤独症治疗的热点分子之一。该研究提示催产素在发育更早期就对感觉皮层的神经环路形成有重要的促进作用。鉴于孤独症患儿经常伴随有感觉输入的异常,该发现对进一步解析孤独症的致病机制有重要的借鉴意义。     

视觉轮廓整合的神经机制

视觉轮廓整合是指视觉系统将视野中的离散元素组合为整体轮廓线的加工过程,是连接初级感觉加工和高级视觉物体知觉间的关键桥梁。对视觉轮廓整合神经机制的研究不仅能促进我们对人类知觉整合的理解,也有助于启发计算科学领域图形整合和分隔算法的改进。然而,轮廓整合的神经机制尚无最终定论。当前的争议主要集中在轮廓整合是基于初级视皮层固有水平连接的产物,还是基于脑区内水平连接及脑区间反馈连接共同作用的产物。本文在回顾这两种理论框架及其研究证据的基础上,对未来的研究问题和方向进行了展望。     

整体知觉依赖于双侧视皮层的协同工作: TMS研究

以往研究表明, 右侧和左侧大脑半球分别主要负责复合图形的整体和局部知觉. 本研究使用经颅磁刺激(TMS)研究对复合刺激的整体知觉是否需要双侧皮层的协同工作. 在实验一中, 被试辨别复合字母的整体或者局部属性, 在施加单脉冲TMS或者伪TMS的同时记录反应时. 尽管观测到了整体优势效应(即对整体目标的反应快于局部目标, 整体对于局部有更强的干扰), 但是TMS减弱了整体对局部加工的干扰并且增强局部对整体加工的干扰. 实验二排除了实验一中观测到的效应是知觉学习后果的可能性. 实验三利用复合图形刺激, 观测到了与实验一相似的TMS效应, 而且发现TMS延长对整体的反应时(RTs)并减少对局部的反应时. 最后, 实验一和实验三中观测到的TMS效应在左半球或者右半球没有显著差异. 这些结果支持了协同假设, 该假设认为复合刺激的整体知觉依赖于双侧视皮层的协同工作     

老年猫视皮层细胞对刺激反应的对比敏感度下降伴随皮层内抑制作用减弱(英文)

对人类和动物的心理学研究证实,老年个体的视觉对比敏感度相对青年个体显著下降。为揭示其可能的神经机制,采用在体细胞外单细胞记录技术研究青、老年猫(Felis catus)初级视皮层(primary visual cortex,V1)细胞对不同视觉刺激对比度的调谐反应。结果显示,老年猫V1细胞对视觉刺激反应的平均对比敏感度比青年猫显著下降,这与灵长类报道的研究结果相一致,表明衰老影响视皮层细胞对视觉刺激反应的对比敏感度是灵长类和非灵长类哺乳动物中普遍存在的现象,并可能是介导老年性视觉对比敏感度下降的神经基础。另外,与青年猫相比,老年猫初级视皮层细胞对视觉刺激的反应性显著增强,信噪比下降,感受野显著增大,表明衰老导致的初级视皮层细胞对视觉刺激反应的对比敏感度下降伴随着皮层内抑制性作用减弱。     

Learning to link visual contours

In complex visual scenes, linking related contour elements is important for object recognition. This process, thought to be stimulus driven and hard wired, has substrates in primary visual cortex (V1). Here, however, we find contour integration in V1 to depend strongly on perceptual learning and top-down influences that are specific to contour detection. In naive monkeys, the information about contours embedded in complex backgrounds is absent in V1 neuronal responses and is independent of the locus of spatial attention. Training animals to find embedded contours induces strong contour-related responses specific to the trained retinotopic region. These responses are most robust when animals perform the contour detection task but disappear under anesthesia. Our findings suggest that top-down influences dynamically adapt neural circuits according to specific perceptual tasks. This may serve as a general neuronal mechanism of perceptual learning and reflect top-down mediated changes in cortical states.     

Stimulus timing-dependent plasticity in high-level vision

Humans are able to efficiently learn and remember complex visual patterns after only a few seconds of exposure [1]. At a cellular level, such learning is thought to involve changes in synaptic efficacy, which have been linked to the precise timing of action potentials relative to synaptic inputs [2-4]. Previous experiments have tapped into the timing of neural spiking events by using repeated asynchronous presentation of visual stimuli to induce changes in both the tuning properties of visual neurons and the perception of simple stimulus attributes [5, 6]. Here we used a similar approach to investigate potential mechanisms underlying the perceptual learning of face identity, a high-level stimulus property based on the spatial configuration of local features. Periods of stimulus pairing induced a systematic bias in face-identity perception in a manner consistent with the predictions of spike timing-dependent plasticity. The perceptual shifts induced for face identity were tolerant to a 2-fold change in stimulus size, suggesting that they reflected neuronal changes in nonretinotopic areas, and were more than twice as strong as the perceptual shifts induced for low-level visual features. These results support the idea that spike timing-dependent plasticity can rapidly adjust the neural encoding of high-level stimulus attributes [7-11].     

Perceptual Grouping Enhances Visual Plasticity

Visual perceptual learning, a manifestation of neural plasticity, refers to improvements in performance on a visual task achieved by training. Attention is known to play an important role in perceptual learning, given that the observer''s discriminative ability improves only for those stimulus feature that are attended. However, the distribution of attention can be severely constrained by perceptual grouping, a process whereby the visual system organizes the initial retinal input into candidate objects. Taken together, these two pieces of evidence suggest the interesting possibility that perceptual grouping might also affect perceptual learning, either directly or via attentional mechanisms. To address this issue, we conducted two experiments. During the training phase, participants attended to the contrast of the task-relevant stimulus (oriented grating), while two similar task-irrelevant stimuli were presented in the adjacent positions. One of the two flanking stimuli was perceptually grouped with the attended stimulus as a consequence of its similar orientation (Experiment 1) or because it was part of the same perceptual object (Experiment 2). A test phase followed the training phase at each location. Compared to the task-irrelevant no-grouping stimulus, orientation discrimination improved at the attended location. Critically, a perceptual learning effect equivalent to the one observed for the attended location also emerged for the task-irrelevant grouping stimulus, indicating that perceptual grouping induced a transfer of learning to the stimulus (or feature) being perceptually grouped with the task-relevant one. Our findings indicate that no voluntary effort to direct attention to the grouping stimulus or feature is necessary to enhance visual plasticity.     

Interaction between Attention and Bottom-Up Saliency Mediates the Representation of Foreground and Background in an Auditory Scene

The mechanism by which a complex auditory scene is parsed into coherent objects depends on poorly understood interactions between task-driven and stimulus-driven attentional processes. We illuminate these interactions in a simultaneous behavioral–neurophysiological study in which we manipulate participants' attention to different features of an auditory scene (with a regular target embedded in an irregular background). Our experimental results reveal that attention to the target, rather than to the background, correlates with a sustained (steady-state) increase in the measured neural target representation over the entire stimulus sequence, beyond auditory attention's well-known transient effects on onset responses. This enhancement, in both power and phase coherence, occurs exclusively at the frequency of the target rhythm, and is only revealed when contrasting two attentional states that direct participants' focus to different features of the acoustic stimulus. The enhancement originates in auditory cortex and covaries with both behavioral task and the bottom-up saliency of the target. Furthermore, the target's perceptual detectability improves over time, correlating strongly, within participants, with the target representation's neural buildup. These results have substantial implications for models of foreground/background organization, supporting a role of neuronal temporal synchrony in mediating auditory object formation.     

From perceptual to language-mediated categorization

From at least two months onwards, infants can form perceptual categories. During the first year of life, object knowledge develops from the ability to represent individual object features to representing correlations between attributes and to integrate information from different sources. At the end of the first year, these representations are shaped by labels, opening the way to conceptual knowledge. Here, we review the development of object knowledge and object categorization over the first year of life. We then present an artificial neural network model that models the transition from early perceptual categorization to categories mediated by labels. The model informs a current debate on the role of labels in object categorization by suggesting that although labels do not act as object features they nevertheless affect perceived similarity of perceptually distinct objects sharing the same label. The model presents the first step of an integrated account from early perceptual categorization to language-based concept learning.     

Neural plasticity in high-level visual cortex underlying object perceptual learning

With intensive training, human can achieve impressive behavioral improvement on various perceptual tasks. This phenomenon, termed perceptual learning, has long been considered as a hallmark of the plasticity of sensory neural system. Not surprisingly, high-level vision, such as object perception, can also be improved by perceptual learning. Here we review recent psychophysical, electrophysiological, and neuroimaging studies investigating the effects of training on object selective cortex, such as monkey inferior temporal cortex and human lateral occipital area. Evidences show that learning leads to an increase in object selectivity at the single neuron level and/or the neuronal population level. These findings indicate that high-level visual cortex in humans is highly plastic and visual experience can strongly shape neural functions of these areas. At the end of the review, we discuss several important future directions in this area.     

Abnormal FMRI adaptation to unfamiliar faces in a case of developmental prosopamnesia

In rare cases, damage to the temporal lobe causes a selective impairment in the ability to learn new faces, a condition known as prosopamnesia [1]. Here we present the case of an individual with prosopamnesia in the absence of any acquired structural lesion. "C" shows intact processing of simple and complex nonface objects, but her ability to learn new faces is severely impaired. We used a neural marker of perceptual learning known as repetition suppression to examine functioning within C's fusiform face area (FFA), a region of cortex involved in face perception [2]. For comparison, we examined repetition suppression in the scene-selective parahippocampal place area (PPA) [3]. As expected, normal controls showed significant region-specific attenuation of neural activity across repetitions of each stimulus class. C also showed normal attenuation within the PPA to familiar and unfamiliar scenes, and within the FFA to familiar faces. Critically, however, she failed to show any adaptive change within the FFA for repeated unfamiliar faces, despite a face-specific blood-oxygen-dependent response (BOLD) response in her FFA during viewing of face stimuli. Our findings suggest that in developmental prosopamnesia, the FFA cannot maintain stable representations of new faces for subsequent recall or recognition.     

How Lateral Connections and Spiking Dynamics May Separate Multiple Objects Moving Together

Over successive stages, the ventral visual system of the primate brain develops neurons that respond selectively to particular objects or faces with translation, size and view invariance. The powerful neural representations found in Inferotemporal cortex form a remarkably rapid and robust basis for object recognition which belies the difficulties faced by the system when learning in natural visual environments. A central issue in understanding the process of biological object recognition is how these neurons learn to form separate representations of objects from complex visual scenes composed of multiple objects. We show how a one-layer competitive network comprised of ‘spiking’ neurons is able to learn separate transformation-invariant representations (exemplified by one-dimensional translations) of visual objects that are always seen together moving in lock-step, but separated in space. This is achieved by combining ‘Mexican hat’ functional lateral connectivity with cell firing-rate adaptation to temporally segment input representations of competing stimuli through anti-phase oscillations (perceptual cycles). These spiking dynamics are quickly and reliably generated, enabling selective modification of the feed-forward connections to neurons in the next layer through Spike-Time-Dependent Plasticity (STDP), resulting in separate translation-invariant representations of each stimulus. Variations in key properties of the model are investigated with respect to the network’s ability to develop appropriate input representations and subsequently output representations through STDP. Contrary to earlier rate-coded models of this learning process, this work shows how spiking neural networks may learn about more than one stimulus together without suffering from the ‘superposition catastrophe’. We take these results to suggest that spiking dynamics are key to understanding biological visual object recognition.     

The Visual Priming of Motion-Defined 3D Objects

The perception of a stimulus can be influenced by previous perceptual experience, a phenomenon known as perceptual priming. However, there has been limited investigation on perceptual priming of shape perception of three-dimensional object structures defined by moving dots. Here we examined the perceptual priming of a 3D object shape defined purely by motion-in-depth cues (i.e., Shape-From-Motion, SFM) using a classic prime-target paradigm. The results from the first two experiments revealed a significant increase in accuracy when a “cloudy” SFM stimulus (whose object structure was difficult to recognize due to the presence of strong noise) was preceded by an unambiguous SFM that clearly defined the same transparent 3D shape. In contrast, results from Experiment 3 revealed no change in accuracy when a “cloudy” SFM stimulus was preceded by a static shape or a semantic word that defined the same object shape. Instead, there was a significant decrease in accuracy when preceded by a static shape or a semantic word that defined a different object shape. These results suggested that the perception of a noisy SFM stimulus can be facilitated by a preceding unambiguous SFM stimulus—but not a static image or a semantic stimulus—that defined the same shape. The potential neural and computational mechanisms underlying the difference in priming are discussed.