The neural basis of haptic object processing.

We review the organization of the neural networks that underlie haptic object processing and compare that organization with the visual system. Haptic object processing is separated into at least two neural pathways, one for geometric properties or shape, and one for material properties, including texture. Like vision, haptic processing pathways are organized into a hierarchy of processing stages, with different stages represented by different brain areas. In addition, the haptic pathway for shape processing may be further subdivided into different streams for action and perception. These streams may be analogous to the action and perception streams of the visual system and represent two points of neural convergence for vision and haptics.     

A neural basis for expert object recognition

Although most adults are considered to be experts in the identification of faces, fewer people specialize in the recognition of other objects, such as birds and dogs. In this research, the neurophysiological processes associated with expert bird and dog recognition were investigated using event-related potentials. An enhanced early negative component (N170, 164 ms) was found when bird and dog experts categorized objects in their domain of expertise relative to when they categorized objects outside their domain of expertise. This finding indicates that objects from well-learned categories are neurologically differentiated from objects from lesser-known categories at a relatively early stage of visual processing.     

The visual basis of category effects in object identification: evidence from the visual hemifield paradigm

The basis for the category specific living things advantage in object recognition (i.e., faster and more accurate identification of living compared to nonliving things) was investigated in two experiments. It was hypothesised that the global shape of living things on average provides more information about their basic level identity than the global shape of nonliving things. In two experiments subjects performed name-picture or picture-name verification tasks, in which blurred or clear images of living and nonliving things were presented in either the right or the left visual hemifield. With blurred images, recognition performance was worst for nonliving things presented to the right visual field/left hemisphere, indicating that the lack of visual detail in the stimulus combined with a left hemisphere bias toward processing high frequency visual elements proved detrimental for processing nonliving stimuli in this condition. In addition, an overall living things advantage was observed in both experiments. This advantage was considerably larger with blurred images than with clear. These results are compatible with the global shape hypothesis and converge with evidence using other paradigms.     

视觉表象个体差异及其神经基础

视觉表象涉及人类一种重要信息表征方式, 与工作记忆和注意相比, 视觉表象研究更为关注其所产生的主观内容, 而这一主观内容的产生存在明显的个体差异。本文从个体差异的角度, 系统介绍了视觉表象个体差异的表现与内在的神经基础及其可能的应用, 并展望了未来的研究方向。本研究将有助于对视觉表象个体差异的认识, 促进视觉表象功能与实质问题研究的进一步开展。     

Perceived object trajectories during occlusion constrain visual statistical learning

Visual statistical learning of shape sequences was examined in the context of occluded object trajectories. In a learning phase, participants viewed a sequence of moving shapes whose trajectories and speed profiles elicited either a bouncing or a streaming percept: the sequences consisted of a shape moving toward and then passing behind an occluder, after which two different shapes emerged from behind the occluder. At issue was whether statistical learning linked both object transitions equally, or whether the percept of either bouncing or streaming constrained the association between pre- and postocclusion objects. In familiarity judgments following the learning, participants reliably selected the shape pair that conformed to the bouncing or streaming bias that was present during the learning phase. A follow-up experiment demonstrated that differential eye movements could not account for this finding. These results suggest that sequential statistical learning is constrained by the spatiotemporal perceptual biases that bind two shapes moving through occlusion, and that this constraint thus reduces the computational complexity of visual statistical learning.     

Selective learning of spatial configuration and object identity in visual search

To conduct an efficient visual search, visual attention must be guided to a target appropriately. Previous studies have suggested that attention can be quickly guided to a target when the spatial configurations of search objects or the object identities have been repeated. This phenomenon is termed contextual cuing. In this study, we investigated the effect of learning spatial configurations, object identities, and a combination of both configurations and identities on visual search. The results indicated that participants could learn the contexts of spatial configurations, but not of object identities, even when both configurations and identities were completely correlated (Experiment 1). On the other hand, when only object identities were repeated, an effect of identity learning could be observed (Experiment 2). Furthermore, an additive effect of configuration learning and identity learning was observed when, in some trials, each context was the relevant cue for predicting the target (Experiment 3). Participants could learn only the context that was associated with target location (Experiment 4). These findings indicate that when multiple contexts are redundant, contextual learning occurs selectively, depending on the predictability of the target location.     

Internal attention to features in visual short-term memory guides object learning

Attending to objects in the world affects how we perceive and remember them. What are the consequences of attending to an object in mind? In particular, how does reporting the features of a recently seen object guide visual learning? In three experiments, observers were presented with abstract shapes in a particular color, orientation, and location. After viewing each object, observers were cued to report one feature from visual short-term memory (VSTM). In a subsequent test, observers were cued to report features of the same objects from visual long-term memory (VLTM). We tested whether reporting a feature from VSTM: (1) enhances VLTM for just that feature (practice-benefit hypothesis), (2) enhances VLTM for all features (object-based hypothesis), or (3) simultaneously enhances VLTM for that feature and suppresses VLTM for unreported features (feature-competition hypothesis). The results provided support for the feature-competition hypothesis, whereby the representation of an object in VLTM was biased towards features reported from VSTM and away from unreported features (Experiment 1). This bias could not be explained by the amount of sensory exposure or response learning (Experiment 2) and was amplified by the reporting of multiple features (Experiment 3). Taken together, these results suggest that selective internal attention induces competitive dynamics among features during visual learning, flexibly tuning object representations to align with prior mnemonic goals.     

The temporal dynamics of visual object priming

Priming reflects an important means of learning that is mediated by implicit memory. Importantly, priming occurs for previously viewed objects (item-specific priming) and their category relatives (category-wide priming). Two distinct neural mechanisms are known to mediate priming, including the sharpening of a neural object representation and the retrieval of stimulus–response mappings. Here, we investigated whether the relationship between these neural mechanisms could help explain why item-specific priming generates faster responses than category-wide priming. Participants studied pictures of everyday objects, and then performed a difficult picture identification task while we recorded event-related potentials (ERP). The identification task gradually revealed random line segments of previously viewed items (Studied), category exemplars of previously viewed items (Exemplar), and items that were not previously viewed (Unstudied). Studied items were identified sooner than Unstudied items, showing evidence of item-specific priming, and importantly Exemplar items were also identified sooner than Unstudied items, showing evidence of category-wide priming. Early activity showed sustained neural suppression of parietal activity for both types of priming. However, these neural suppression effects may have stemmed from distinct processes because while category-wide neural suppression was correlated with priming behavior, item-specific neural suppression was not. Late activity, examined with response-locked ERPs, showed additional processes related to item-specific priming including neural suppression in occipital areas and parietal activity that was correlated with behavior. Together, we conclude that item-specific and category-wide priming are mediated by separate, parallel neural mechanisms in the context of the current paradigm. Temporal differences in behavior are determined by the timecourses of these distinct processes.     

多目标追踪的神经机制

多目标追踪任务是研究动态场景中视觉注意加工机制常用的范式。自1998年开始对多目标追踪神经机制的影像学研究以来, 研究者采用ERP和fMRI等技术对多目标注意追踪所涉及的神经电生理活动和脑功能区激活方面开展了大量研究。ERP研究发现, 追踪过程持续的ERP脑电成分如N2pc、CDA的波幅与注意追踪负荷有关, 并且出现在目标与非目标上的探测刺激诱发的脑电成分如N1、P1波幅的差异可反映注意资源的分配, 具体为目标在追踪过程中得到了激活, 而非目标受到了抑制。fMRI研究比较一致地发现了顶叶(包括前顶内沟、后顶内沟、顶上小叶)、背外侧额叶皮层等在注意追踪中的强烈激活。其中顶内沟主要与注意负荷有关, 顶内沟的活动水平直接决定了观察者注意追踪的行为表现。而顶上小叶可能更多的负责注意转移。背外侧额叶皮层可能负责追踪时的感觉运动预测过程。     

The influence of location and visual features on visual object memory

In five experiments, we examined the influence of contextual objects’ location and visual features on visual memory. Participants’ visual memory was tested with a change detection task in which they had to judge whether the orientation (Experiments 1A, 1B, and 2) or color (Experiments 3A and 3B) of a target object was the same. Furthermore, contextual objects’ locations and visual features were manipulated in the test image. The results showed that change detection performance was better when contextual objects’ locations remained the same from study to test, demonstrating that the original spatial configuration is important for subsequent visual memory retrieval. The results further showed that changes to contextual objects’ orientation, but not color, reduced orientation change detection performance; and changes to contextual objects’ color, but not orientation, impaired color change detection performance. Therefore, contextual objects’ visual features are capable of affecting visual memory. However, selective attention plays an influential role in modulating such effects.     

The neural basis of event-time introspection

We explored the neural mechanisms allowing humans to report the subjective onset times of conscious events. Magnetoencephalographic recordings of neural oscillations were obtained while human subjects introspected the timing of sensory, intentional, and motor events during a forced choice task. Brain activity was reconstructed with high spatio-temporal resolution. Event-time introspection was associated with specific neural activity at the time of subjective event onset which was spatially distinct from activity induced by the event itself. Different brain regions were selectively recruited for introspection of different event types, e.g., the bilateral angular gyrus for introspection of intention. Our results suggest that event-time introspection engages specific neural networks to assess the contents of consciousness. Subjective event times should therefore be interpreted as the result of complex interactions between introspection and experience networks, rather than as direct reproduction of the individual’s conscious state or as a mere post hoc interpretation.     

Mechanisms and neural basis of object and pattern recognition: a study with chess experts

Comparing experts with novices offers unique insights into the functioning of cognition, based on the maximization of individual differences. Here we used this expertise approach to disentangle the mechanisms and neural basis behind two processes that contribute to everyday expertise: object and pattern recognition. We compared chess experts and novices performing chess-related and -unrelated (visual) search tasks. As expected, the superiority of experts was limited to the chess-specific task, as there were no differences in a control task that used the same chess stimuli but did not require chess-specific recognition. The analysis of eye movements showed that experts immediately and exclusively focused on the relevant aspects in the chess task, whereas novices also examined irrelevant aspects. With random chess positions, when pattern knowledge could not be used to guide perception, experts nevertheless maintained an advantage. Experts' superior domain-specific parafoveal vision, a consequence of their knowledge about individual domain-specific symbols, enabled improved object recognition. Functional magnetic resonance imaging corroborated this differentiation between object and pattern recognition and showed that chess-specific object recognition was accompanied by bilateral activation of the occipitotemporal junction, whereas chess-specific pattern recognition was related to bilateral activations in the middle part of the collateral sulci. Using the expertise approach together with carefully chosen controls and multiple dependent measures, we identified object and pattern recognition as two essential cognitive processes in expert visual cognition, which may also help to explain the mechanisms of everyday perception.     

The neural correlates of visual self-recognition

This paper presents a review of studies that were aimed at determining which brain regions are recruited during visual self-recognition, with a particular focus on self-face recognition. A complex bilateral network, involving frontal, parietal and occipital areas, appears to be associated with self-face recognition, with a particularly high implication of the right hemisphere. Results indicate that it remains difficult to determine which specific cognitive operation is reflected by each recruited brain area, in part due to the variability of used control stimuli and experimental tasks. A synthesis of the interpretations provided by previous studies is presented. The relevance of using self-recognition as an indicator of self-awareness is discussed. We argue that a major aim of future research in the field should be to identify more clearly the cognitive operations induced by the perception of the self-face, and search for dissociations between neural correlates and cognitive components.     

The cortical basis of visual scene processing

Several lines of evidence suggest that the human brain contains special-purpose machinery for processing information about visual scenes. In particular, a region in medial occipitotemporal cortex—the “parahippocampal place area”, or PPA—represents the geometric structure of scenes as defined primarily by their background elements. Neuroimaging studies have demonstrated that the PPA responds preferentially to scenes but not to the objects within them, while neuropsychological studies have shown that damage to this region leads to an impaired ability to learn new scenes. More recent evidence suggests that the PPA encodes novel scenes in a viewpoint-specific manner and that these codes are more reliable in good navigators than bad navigators. The PPA may be part of a larger network of regions involved in processing navigationally relevant spatial information. The role of this region in place recognition and gist comprehension is also discussed.     

The automaticity of visual statistical learning

The visual environment contains massive amounts of information involving the relations between objects in space and time, and recent studies of visual statistical learning (VSL) have suggested that this information can be automatically extracted by the visual system. The experiments reported in this article explore the automaticity of VSL in several ways, using both explicit familiarity and implicit response-time measures. The results demonstrate that (a) the input to VSL is gated by selective attention, (b) VSL is nevertheless an implicit process because it operates during a cover task and without awareness of the underlying statistical patterns, and (c) VSL constructs abstracted representations that are then invariant to changes in extraneous surface features. These results fuel the conclusion that VSL both is and is not automatic: It requires attention to select the relevant population of stimuli, but the resulting learning then occurs without intent or awareness.