视觉注意与神经振荡

人脑每时每刻都要接收大量视觉信息，由于人脑加工信息的能力有限，所以在较大视野内将注意分配给相关信息，同时抑制引起注意分散的不相关信息，对执行目标导向的行为至关重要。这种对视觉信息的选择性和主动性加工以适应当前目标的过程被称作视觉注意（visual attention），且视觉注意可分为自上而下的注意与自下而上的注意两种不同功能。由于来自大脑电信号的神经振荡活动在认知加工中发挥重要作用，已有研究综述了视觉注意与神经振荡（neural oscillation）的密切关系，但并未涉及不同的注意功能与神经振荡的关系。本文系统性调查了不同注意功能与神经振荡的关系，发现额-顶区域的theta频带振荡活动反映了自上而下的认知控制，而后部脑区的theta振荡与自下而上的注意相关。顶-枕区域alpha振荡的偏侧化有助于注意分配，而alpha频带的大规模同步促成了注意对视皮层自上而下的影响。Beta振荡介导了自上而下的信息与自下而上的信息之间的互动，作为信息载体促进了视觉信息处理。Gamma振荡则可能与自上而下和自下而上的注意间整合相关。本文就视觉注意功能与神经振荡关系的研究现状展开综述，旨在揭示不同的神经振荡活动在特定的视觉注意功能中的作用。     

Effects of cholinergic enhancement on visual stimulation, spatial attention, and spatial working memory

We compared behavioral and neural effects of cholinergic enhancement between spatial attention, spatial working memory (WM), and visual control tasks, using fMRI and the anticholinesterase physostigmine. Physostigmine speeded responses nonselectively but increased accuracy selectively for attention. Physostigmine also decreased activations to visual stimulation across all tasks within primary visual cortex, increased extrastriate occipital cortex activation selectively during maintained attention and WM encoding, and decreased parietal activation selectively during maintained attention. Finally, lateralization of occipital activation as a function of the visual hemifield toward which attention or memory was directed was decreased under physostigmine. In the case of attention, this effect correlated strongly with a decrease in a behavioral measure of selective spatial processing. Our results suggest that, while cholinergic enhancement facilitates visual attention by increasing activity in extrastriate cortex generally, it accomplishes this in a manner that reduces expectation-driven selective biasing of extrastriate cortex.     

Sensory gain control (amplification) as a mechanism of selective attention: electrophysiological and neuroimaging evidence.

Both physiological and behavioral studies have suggested that stimulus-driven neural activity in the sensory pathways can be modulated in amplitude during selective attention. Recordings of event-related brain potentials indicate that such sensory gain control or amplification processes play an important role in visual-spatial attention. Combined event-related brain potential and neuroimaging experiments provide strong evidence that attentional gain control operates at an early stage of visual processing in extrastriate cortical areas. These data support early selection theories of attention and provide a basis for distinguishing between separate mechanisms of attentional suppression (of unattended inputs) and attentional facilitation (of attended inputs).     

The neurobiology of selective attention.

Research in the field of selective visual attention has recently seen substantial progress in several areas. Neuroimaging and electrical recording results have indicated that selective attention amplifies neural activity in prestriate areas concerned with basic visual processing. Imaging and cellular studies are delineating the networks of anatomical areas that serve as the source of attentional modulation and have suggested that these networks are anatomically distinct from the sites of the resulting amplifications. Cognitive studies of visual search have explored the role of these amplified computations in the integration of visual features into objects. Attentional effects in normal subjects, and their disruption following brain injury, have revealed the mental representations upon which attention operates.     

Modality-specific control of strategic spatial attention in parietal cortex

The neural basis of selective spatial attention presents a significant challenge to cognitive neuroscience. Recent neuroimaging studies have suggested that regions of the parietal and temporal cortex constitute a "supramodal" network that mediates goal-directed attention in multiple sensory modalities. Here we used transcranial magnetic stimulation (TMS) to determine which cortical subregions control strategic attention in vision and touch. Healthy observers undertook an orienting task in which a central arrow cue predicted the location of a subsequent visual or somatosensory target. To determine the attentional role of cortical subregions at different stages of processing, TMS was delivered to the right hemisphere during cue or target events. Results indicated a critical role of the inferior parietal cortex in strategic orienting to visual events, but not to somatosensory events. These findings are inconsistent with the existence of a supramodal attentional network and instead provide direct evidence for modality-specific attentional processing in parietal cortex.     

An emergent mechanism of selective visual attention in Drosophila

Due to the limited computational capacity of visual systems and the limited capacity to perform several mental operations at once, animals only select a small proportion of the stimuli available at any one time. It remains to be clarified how this process is related to the spatio-temporal dynamics of cell assemblies in the brain. By employing the flight simulator, selective visual attention behavior is studied in Drosophila. It has been found that for the visual objects presented, the tethered fruitflies display various attention patterns. Specifically, the learning memory mutants dunce and amnesiac possess attention patterns totally different from that of the wild-type fly. To explain these results from the viewpoint of dynamic cell assemblies, a neural network has been developed in which a possible link between the activity of cell assemblies, encoding of sensory information, and selective attention in Drosophila is proposed. Received: 3 November 1998 / Accepted in revised form: 1 July 1999     

A neural network model of attention-modulated neurodynamics

Visual attention appears to modulate cortical neurodynamics and synchronization through various cholinergic mechanisms. In order to study these mechanisms, we have developed a neural network model of visual cortex area V4, based on psychophysical, anatomical and physiological data. With this model, we want to link selective visual information processing to neural circuits within V4, bottom-up sensory input pathways, top-down attention input pathways, and to cholinergic modulation from the prefrontal lobe. We investigate cellular and network mechanisms underlying some recent analytical results from visual attention experimental data. Our model can reproduce the experimental findings that attention to a stimulus causes increased gamma-frequency synchronization in the superficial layers. Computer simulations and STA power analysis also demonstrate different effects of the different cholinergic attention modulation action mechanisms.     

Visuomotor origins of covert spatial attention

Covert spatial attention produces biases in perceptual performance and neural processing of behaviorally relevant stimuli in the absence of overt orienting movements. The neural mechanism that gives rise to these effects is poorly understood. This paper surveys past evidence of a relationship between oculomotor control and visual spatial attention and more recent evidence of a causal link between the control of saccadic eye movements by frontal cortex and covert visual selection. Both suggest that the mechanism of covert spatial attention emerges as a consequence of the reciprocal interactions between neural circuits primarily involved in specifying the visual properties of potential targets and those involved in specifying the movements needed to fixate them.     

Cholinergic enhancement of visual attention and neural oscillations in the human brain

Cognitive processes such as visual perception and selective attention induce specific patterns of brain oscillations. The neurochemical bases of these spectral changes in neural activity are largely unknown, but neuromodulators are thought to regulate processing. The cholinergic system is linked to attentional function in vivo, whereas separate in vitro studies show that cholinergic agonists induce high-frequency oscillations in slice preparations. This has led to theoretical proposals that cholinergic enhancement of visual attention might operate via gamma oscillations in visual cortex, although low-frequency alpha/beta modulation may also play a key role. Here we used MEG to record cortical oscillations in the context of administration of a cholinergic agonist (physostigmine) during a spatial visual attention task in humans. This cholinergic agonist enhanced spatial attention effects on low-frequency alpha/beta oscillations in visual cortex, an effect correlating with a drug-induced speeding of performance. By contrast, the cholinergic agonist did not alter high-frequency gamma oscillations in visual cortex. Thus, our findings show that cholinergic neuromodulation enhances attentional selection via an impact on oscillatory synchrony in visual cortex, for low rather than high frequencies. We discuss this dissociation between high- and low-frequency oscillations in relation to proposals that lower-frequency oscillations are generated by feedback pathways within visual cortex.     

Neural network model of selective visual attention using Hodgkin–Huxley equation

We propose a mathematical model of selective visual attention using a two-layered neural network with neurons described by the Hodgkin–Huxley equation in order to investigate part of the assumption proposed by Desimone and Duncan. The neural network consists of a layer of hippocampal formation and of visual cortex. A frequency of firing and a firing time for each neuron and also a correlation of the firing times between neurons are calculated numerically to clarify an attention state, a nonattention state, and an attention shift. We find that synchronous phenomena occur not only for the frequency but also for the firing time between the neurons in the hippocampal formation and those in a part of the visual cortex in our model. It also turns out that the attention shift is performed quickly in our model.Acknowledgements We are grateful to T. Omori for his valuable discussions and comments. K. K. was partially supported by Research Fellowships of the Japan Society for the Promotion of Science for Young Scientists. This work was partially supported by Grant-In-Aid for Scientific Research No. 13680383 from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan.     

The scope and limits of top-down attention in unconscious visual processing

Attentional selection plays a critical role in conscious perception. When attention is diverted, even salient stimuli fail to reach visual awareness. Attention can be voluntarily directed to a spatial location or a visual feature for facilitating the processing of information relevant to current goals. In everyday situations, attention and awareness are tightly coupled. This has led some to suggest that attention and awareness might be based on a common neural foundation, whereas others argue that they are mediated by distinct mechanisms. A body of evidence shows that visual stimuli can be processed at multiple stages of the visual-processing streams without evoking visual awareness. To illuminate the relationship between visual attention and conscious perception, we investigated whether top-down attention can target and modulate the neural representations of unconsciously processed visual stimuli. Our experiments show that spatial attention can target only consciously perceived stimuli, whereas feature-based attention can modulate the processing of invisible stimuli. The attentional modulation of unconscious signals implies that attention and awareness can be dissociated, challenging a simplistic view of the boundary between conscious and unconscious visual processing.     

The dark side of visual attention

The limited capacity of neural processing restricts the number of objects and locations that can be attended to. Selected events are readily enhanced: the bright side of attention. However, such focal processing comes at a cost, namely, functional blindness for unattended events: the dark side of visual attention. Recent work has advanced our understanding of the neural mechanisms that facilitate visual processing, as well as the neural correlates of unattended, unconscious visual events. Also, new results have revealed how attentional deployment is optimized by non-visual factors such as behavioral set, past experience, and emotional salience.     

Neuro-robotics study on integrative learning of proactive visual attention and motor behaviors

The current paper proposes a novel model for integrative learning of proactive visual attention and sensory-motor control as inspired by the premotor theory of visual attention. The model is characterized by coupling a slow dynamics network with a fast dynamics network and by inheriting our prior proposed multiple timescales recurrent neural networks model (MTRNN) that may correspond to the fronto-parietal networks in the cortical brains. The neuro-robotics experiments in a task of manipulating multiple objects utilizing the proposed model demonstrated that some degrees of generalization in terms of position and object size variation can be achieved by organizing seamless integration of the proactive object-related visual attention and the related sensory-motor control into a set of action primitives in the distributed neural activities appearing in the fast dynamics network. It was also shown that such action primitives can be combined in compositional ways in acquiring novel actions in the slow dynamics network. The experimental results presented substantiate the premotor theory of visual attention.     

Spatiotopic coding of BOLD signal in human visual cortex depends on spatial attention

The neural substrate of the phenomenological experience of a stable visual world remains obscure. One possible mechanism would be to construct spatiotopic neural maps where the response is selective to the position of the stimulus in external space, rather than to retinal eccentricities, but evidence for these maps has been inconsistent. Here we show, with fMRI, that when human subjects perform concomitantly a demanding attentive task on stimuli displayed at the fovea, BOLD responses evoked by moving stimuli irrelevant to the task were mostly tuned in retinotopic coordinates. However, under more unconstrained conditions, where subjects could attend easily to the motion stimuli, BOLD responses were tuned not in retinal but in external coordinates (spatiotopic selectivity) in many visual areas, including MT, MST, LO and V6, agreeing with our previous fMRI study. These results indicate that spatial attention may play an important role in mediating spatiotopic selectivity.     

Effects of Multimodal Load on Spatial Monitoring as Revealed by ERPs

While the role of selective attention in filtering out irrelevant information has been extensively studied, its characteristics and neural underpinnings when multiple environmental stimuli have to be processed in parallel are much less known. Building upon a dual-task paradigm that induced spatial awareness deficits for contralesional hemispace in right hemisphere-damaged patients, we investigated the electrophysiological correlates of multimodal load during spatial monitoring in healthy participants. The position of appearance of briefly presented, lateralized targets had to be reported either in isolation (single task) or together with a concurrent task, visual or auditory, which recruited additional attentional resources (dual-task). This top-down manipulation of attentional load, without any change of the sensory stimulation, modulated the amplitude of the first positive ERP response (P1) and shifted its neural generators, with a suppression of the signal in the early visual areas during both visual and auditory dual tasks. Furthermore, later N2 contralateral components elicited by left targets were particularly influenced by the concurrent visual task and were related to increased activation of the supramarginal gyrus. These results suggest that the right hemisphere is particularly affected by load manipulations, and confirm its crucial role in subtending automatic orienting of spatial attention and in monitoring both hemispaces.     

Visual saliency and spike timing in the ventral visual pathway.

Visual saliency is a fundamental yet hard to define property of objects or locations in the visual world. In a context where objects and their representations compete to dominate our perception, saliency can be thought of as the "juice" that makes objects win the race. It is often assumed that saliency is extracted and represented in an explicit saliency map, which serves to determine the location of spatial attention at any given time. It is then by drawing attention to a salient object that it can be recognized or categorized. I argue against this classical view that visual "bottom-up" saliency automatically recruits the attentional system prior to object recognition. A number of visual processing tasks are clearly performed too fast for such a costly strategy to be employed. Rather, visual attention could simply act by biasing a saliency-based object recognition system. Under natural conditions of stimulation, saliency can be represented implicitly throughout the ventral visual pathway, independent of any explicit saliency map. At any given level, the most activated cells of the neural population simply represent the most salient locations. The notion of saliency itself grows increasingly complex throughout the system, mostly based on luminance contrast until information reaches visual cortex, gradually incorporating information about features such as orientation or color in primary visual cortex and early extrastriate areas, and finally the identity and behavioral relevance of objects in temporal cortex and beyond. Under these conditions the object that dominates perception, i.e. the object yielding the strongest (or the first) selective neural response, is by definition the one whose features are most "salient"--without the need for any external saliency map. In addition, I suggest that such an implicit representation of saliency can be best encoded in the relative times of the first spikes fired in a given neuronal population. In accordance with our subjective experience that saliency and attention do not modify the appearance of objects, the feed-forward propagation of this first spike wave could serve to trigger saliency-based object recognition outside the realm of awareness, while conscious perceptions could be mediated by the remaining discharges of longer neuronal spike trains.     

Attention Increases the Temporal Precision of Conscious Perception: Verifying the Neural-ST2 Model

What role does attention play in ensuring the temporal precision of visual perception? Behavioural studies have investigated feature selection and binding in time using fleeting sequences of stimuli in the Rapid Serial Visual Presentation (RSVP) paradigm, and found that temporal accuracy is reduced when attentional control is diminished. To reduce the efficacy of attentional deployment, these studies have employed the Attentional Blink (AB) phenomenon. In this article, we use electroencephalography (EEG) to directly investigate the temporal dynamics of conscious perception. Specifically, employing a combination of experimental analysis and neural network modelling, we test the hypothesis that the availability of attention reduces temporal jitter in the latency between a target''s visual onset and its consolidation into working memory. We perform time-frequency analysis on data from an AB study to compare the EEG trials underlying the P3 ERPs (Event-related Potential) evoked by targets seen outside vs. inside the AB time window. We find visual differences in phase-sorted ERPimages and statistical differences in the variance of the P3 phase distributions. These results argue for increased variation in the latency of conscious perception during the AB. This experimental analysis is complemented by a theoretical exploration of temporal attention and target processing. Using activation traces from the Neural-ST² model, we generate virtual ERPs and virtual ERPimages. These are compared to their human counterparts to propose an explanation of how target consolidation in the context of the AB influences the temporal variability of selective attention. The AB provides us with a suitable phenomenon with which to investigate the interplay between attention and perception. The combination of experimental and theoretical elucidation in this article contributes to converging evidence for the notion that the AB reflects a reduction in the temporal acuity of selective attention and the timeliness of perception.     

A neural network model for selective attention in visual pattern recognition

A neural network model of the mechanism of selective attention in visual pattern recognition is proposed and simulated on a digital computer.When a complex figure consisting of two patterns or more is presented to the model, it is segmented into individual patterns, and each pattern is recognized separately. Even if one of the patterns to which the model is paying selective attention is affected by noise or defects, the model can recall the complete pattern from which the noise has been eliminated and the defects corrected. It is not necessary for perfect recall that the stimulus pattern should be identical in shape to the training pattern. Even though the pattern is distorted in shape or changed in size, it can be correctly recognized and the missing portions restored.The model consists of a hierarchical neural network which has efferent as well as afferent connections between cells. The afferent and the efferent signals interact with each other in the network: the efferent signals, that is, the signals for selective attention, have a facilitating effect on the afferent ones, and, at the same time, the afferent signals gate efferent signal flow. When some feature in the stimulus is not extracted in the afferent paths, the threshold for detection of that feature is automatically lowered by decreasing the efficiency of inhibition, and the model tries to extract even vague traces of the undetected feature.     

多方式认知功能成像研究进展

对大脑结构和功能的深入研究要求认知功能成像技术同时具有高时间分辨率和高空间分辨率.多方式认知功能成像通过不同成像技术fMRI/PET和EEG/MEG的结合,能够同时在空间定位和时间过程上研究大脑认知活动的动态过程.多方式认知功能成像已经被成功地应用于选择性注意、视觉通路、随意运动和语义加工等的研究,并揭示了相关大脑活动的空间和时间特征.今后的研究将进一步提高多方式认知功能成像的时空分辨率和准确性,以更深入地探索认知功能的神经机制.     

A Neurodynamical Model of Visual Attention: Feedback Enhancement of Spatial Resolution in a Hierarchical System

Human beings have the capacity to recognize objects in natural visual scenes with high efficiency despite the complexity of such scenes, which usually contain multiple objects. One possible mechanism for dealing with this problem is selective attention. Psychophysical evidence strongly suggests that selective attention can enhance the spatial resolution in the input region corresponding to the focus of attention. In this work we adopt a computational neuroscience perspective to analyze the attentional enhancement of spatial resolution in the area containing the objects of interest. We extend and apply the computational model of Deco and Schürmann (2000), which consists of several modules with feedforward and feedback interconnections describing the mutual links between different areas of the visual cortex. Each module analyses the visual input with different spatial resolution and can be thought of as a hierarchical predictor at a given level of resolution. Moreover, each hierarchical predictor has a submodule that consists of a group of neurons performing a biologically based 2D Gabor wavelet transformation at a given resolution level. The attention control decides in which local regions the spatial resolution should be enhanced in a serial fashion. In this sense, the scene is first analyzed at a coarse resolution level, and the focus of attention enhances iteratively the resolution at the location of an object until the object is identified. We propose and simulate new psychophysical experiments where the effect of the attentional enhancement of spatial resolution can be demonstrated by predicting different reaction time profiles in visual search experiments where the target and distractors are defined at different levels of resolution.