How distributed is visual category information in human occipito-temporal cortex? An fMRI study

We used fMRI to study the distribution of object category information in the ventral visual pathway. Extending the findings of, we find that categories of stimuli can be distinguished by the pattern of activation they elicit across this entire pathway, even when the stimuli within a category differ in viewpoint, exemplar, or image format. However, regions within the ventral visual pathway are neither interchangeable nor equipotential. Although the FFA and PPA permit excellent discrimination between preferred versus nonpreferred stimuli (e.g., faces-bottles and houses-bottles, respectively), we find that neither region alone permits accurate discrimination between pairs of nonpreferred stimuli (e.g., bottles-shoes). These findings indicate that the ventral visual pathway is not homogeneous, but contains some regions (including FFA and PPA) that are primarily involved in the analysis of a single class of stimulus.     

Distributed neural systems for the generation of visual images

Visual perception of houses, faces, and chairs evoke differential responses in ventral temporal cortex. Using fMRI, we compared activations evoked by perception and imagery of these object categories. We found content-related activation during imagery in extrastriate cortex, but this activity was restricted to small subsets of the regions that showed category-related activation during perception. Within ventral temporal cortex, activation during imagery evoked stronger responses on the left whereas perception evoked stronger responses on the right. Additionally, visual imagery evoked activity in parietal and frontal cortex, but this activity was not content related. These results suggest that content-related activation during imagery in visual extrastriate cortex may be implemented by "top-down" mechanisms in parietal and frontal cortex that mediate the retrieval of face and object representations from long-term memory and their maintenance through visual imagery.     

Category selectivity in the ventral visual pathway confers robustness to clutter and diverted attention

Are objects coded by a small number of neurons or cortical regions that respond preferentially to the object in question, or by more distributed patterns of responses, including neurons or regions that respond only weakly? Distributed codes can represent a larger number of alternative items than sparse codes but produce ambiguities when multiple items are represented simultaneously (the "superposition" problem). Recent studies found category information in the distributed pattern of response across the ventral visual pathway, including in regions that do not "prefer" the object in question. However, these studies measured neural responses to isolated objects, a situation atypical of real-world vision, where multiple objects are usually present simultaneously ("clutter"). We report that information in the spatial pattern of fMRI response about standard object categories is severely disrupted by clutter and eliminated when attention is diverted. However, information about preferred categories in category-specific regions is undiminished by clutter and partly preserved under diverted attention. These findings indicate that in natural conditions, the pattern of fMRI response provides robust category information only for objects coded in selective cortical regions and highlight the vulnerability of distributed representations to clutter and the advantages of sparse cortical codes in mitigating clutter costs.     

Crowding: a cortical constraint on object recognition

The external world is mapped retinotopically onto the primary visual cortex (V1). We show here that objects in the world, unless they are very dissimilar, can be recognized only if they are sufficiently separated in visual cortex: specifically, in V1, at least 6mm apart in the radial direction (increasing eccentricity) or 1mm apart in the circumferential direction (equal eccentricity). Objects closer together than this critical spacing are perceived as an unidentifiable jumble. This is called 'crowding'. It severely limits visual processing, including speed of reading and searching. The conclusion about visual cortex rests on three findings. First, psychophysically, the necessary 'critical' spacing, in the visual field, is proportional to (roughly half) the eccentricity of the objects. Second, the critical spacing is independent of the size and kind of object. Third, anatomically, the representation of the visual field on the cortical surface is such that the position in V1 (and several other areas) is the logarithm of eccentricity in the visual field. Furthermore, we show that much of this can be accounted for by supposing that each 'combining field', defined by the critical spacing measurements, is implemented by a fixed number of cortical neurons.     

Generalization of learning by synchronous waves: from perceptual organization to invariant organization

From a few presentations of an object, perceptual systems are able to extract invariant properties such that novel presentations are immediately recognized. This may be enabled by inferring the set of all representations equivalent under certain transformations. We implemented this principle in a neurodynamic model that stores activity patterns representing transformed versions of the same object in a distributed fashion within maps, such that translation across the map corresponds to the relevant transformation. When a pattern on the map is activated, this causes activity to spread out as a wave across the map, activating all the transformed versions represented. Computational studies illustrate the efficacy of the proposed mechanism. The model rapidly learns and successfully recognizes rotated and scaled versions of a visual representation from a few prior presentations. For topographical maps such as primary visual cortex, the mechanism simultaneously represents identity and variation of visual percepts whose features change through time.     

A Representational Similarity Analysis of the Dynamics of Object Processing Using Single-Trial EEG Classification

The recognition of object categories is effortlessly accomplished in everyday life, yet its neural underpinnings remain not fully understood. In this electroencephalography (EEG) study, we used single-trial classification to perform a Representational Similarity Analysis (RSA) of categorical representation of objects in human visual cortex. Brain responses were recorded while participants viewed a set of 72 photographs of objects with a planned category structure. The Representational Dissimilarity Matrix (RDM) used for RSA was derived from confusions of a linear classifier operating on single EEG trials. In contrast to past studies, which used pairwise correlation or classification to derive the RDM, we used confusion matrices from multi-class classifications, which provided novel self-similarity measures that were used to derive the overall size of the representational space. We additionally performed classifications on subsets of the brain response in order to identify spatial and temporal EEG components that best discriminated object categories and exemplars. Results from category-level classifications revealed that brain responses to images of human faces formed the most distinct category, while responses to images from the two inanimate categories formed a single category cluster. Exemplar-level classifications produced a broadly similar category structure, as well as sub-clusters corresponding to natural language categories. Spatiotemporal components of the brain response that differentiated exemplars within a category were found to differ from those implicated in differentiating between categories. Our results show that a classification approach can be successfully applied to single-trial scalp-recorded EEG to recover fine-grained object category structure, as well as to identify interpretable spatiotemporal components underlying object processing. Finally, object category can be decoded from purely temporal information recorded at single electrodes.     

Argument Structure and Morphological Factors in Noun and Verb Processing: An fMRI Study

In a functional MRI (fMRI) study, we have investigated the grammatical categories of object noun, event noun and verb in order to assess the cortical regions of activation supporting their processing. Twelve Italian healthy participants performed a lexical decision task. They had to decide whether a string was an Italian word or not. Words could be objects like medaglia (medal), or events like the noun pianto (cry); or the verb dormire (to sleep). Noun and verb comparison shows differences in regions of activation in the left Inferior Frontal cortex and in the extent of the same areas. We have found specific areas of activation for object noun, and similarities in the pattern of activation for event noun and verb. The activations induced by pseudowords highly resembled the areas activated by the corresponding word category. The implications of the results are discussed in light of the recent debate on the role of grammatical category in the brain.     

用脑光学成像精确测定猫初级视皮层视野拓扑投射关系

利用基于脑内源信号的光学成像和二维互相关分析的方法,对猫初级视皮层17区的视野拓扑离心度(即视网膜-皮层拓扑关系)进行了精确测量。当采用在同一屏幕内处于上下视野的、方位互相垂直的两个相邻光栅刺激时,皮层中一部分区域的绝大部分细胞因同时兴奋而导致方位功能图模糊不清。将这种方位功能图和用单一方位(水平或垂直)全屏光栅刺激所得到的功能图进行比较,通过计算每一像素的互相关系数,从而获得皮层的精确视野拓扑离心度。同时用电生理的方法测量了同一视皮层内的单细胞的感受野位置,证明这种方法得到的视野离心度和光学记录方法得到的相同。因此,本研究为大面积地确定视皮层细胞感受野在视野中的位置提供了一种快速和较准确的方法。     

Using FMRI brain activation to identify cognitive states associated with perception of tools and dwellings

Previous studies have succeeded in identifying the cognitive state corresponding to the perception of a set of depicted categories, such as tools, by analyzing the accompanying pattern of brain activity, measured with fMRI. The current research focused on identifying the cognitive state associated with a 4s viewing of an individual line drawing (1 of 10 familiar objects, 5 tools and 5 dwellings, such as a hammer or a castle). Here we demonstrate the ability to reliably (1) identify which of the 10 drawings a participant was viewing, based on that participant's characteristic whole-brain neural activation patterns, excluding visual areas; (2) identify the category of the object with even higher accuracy, based on that participant's activation; and (3) identify, for the first time, both individual objects and the category of the object the participant was viewing, based only on other participants' activation patterns. The voxels important for category identification were located similarly across participants, and distributed throughout the cortex, focused in ventral temporal perceptual areas but also including more frontal association areas (and somewhat left-lateralized). These findings indicate the presence of stable, distributed, communal, and identifiable neural states corresponding to object concepts.     

Shaping of object representations in the human medial temporal lobe based on temporal regularities

Regularities are gradually represented in cortex after extensive experience [1], and yet they can influence behavior after minimal exposure [2, 3]. What kind of representations support such rapid statistical learning? The medial temporal lobe (MTL) can represent information from even a single experience [4], making it a good candidate system for assisting in initial learning about regularities. We combined anatomical segmentation of the MTL, high-resolution fMRI, and multivariate pattern analysis to identify representations of objects in cortical and hippocampal areas of human MTL, assessing how these representations were shaped by exposure to regularities. Subjects viewed a continuous visual stream containing hidden temporal relationships-pairs of objects that reliably appeared nearby in time. We compared the pattern of blood oxygen level-dependent activity evoked by each object before and after this exposure, and found that perirhinal cortex, parahippocampal cortex, subiculum, CA1, and CA2/CA3/dentate gyrus (CA2/3/DG) encoded regularities by increasing the representational similarity of their constituent objects. Most regions exhibited bidirectional associative shaping, whereas CA2/3/DG represented regularities in a forward-looking predictive manner. These findings suggest that object representations in MTL come to mirror the temporal structure of the environment, supporting rapid and incidental statistical learning.     

The chronoarchitecture of the cerebral cortex

We review here a new approach to mapping the human cerebral cortex into distinct subdivisions. Unlike cytoarchitecture or traditional functional imaging, it does not rely on specific anatomical markers or functional hypotheses. Instead, we propose that the unique activity time course (ATC) of each cortical subdivision, elicited during natural conditions, acts as a temporal fingerprint that can be used to segregate cortical subdivisions, map their spatial extent, and reveal their functional and potentially anatomical connectivity. We argue that since the modular organisation of the brain and its connectivity evolved and developed in natural conditions, these are optimal for revealing its organisation. We review the concepts, methodology and first results of this approach, relying on data obtained with functional magnetic resonance imaging (fMRI) when volunteers viewed traditional stimuli or a James Bond movie. Independent component analysis (ICA) was used to identify voxels belonging to distinct functional subdivisions, based on their differential spatio-temporal fingerprints. Many more regions could be segregated during natural viewing, demonstrating that the complexity of natural stimuli leads to more differential responses in more functional modules. We demonstrate that, in a single experiment, a multitude of distinct regions can be identified across the whole brain, even within the visual cortex, including areas V1, V4 and V5. This differentiation is based entirely on the differential ATCs of different areas during natural viewing. Distinct areas can therefore be identified without any a priori hypothesis about their function or spatial location. The areas we identified corresponded anatomically across subjects, and their ATCs showed highly area-specific inter-subject correlations. Furthermore, natural conditions led to a significant de-correlation of interregional ATCs compared to rest, indicating an increase in regional specificity during natural conditions. In contrast, the correlation between ATCs of distant regions of known substantial anatomical connections increased and reflected their known anatomical connectivity pattern. We demonstrate this using the example of the language network involving Broca's and Wernicke's area and homologous areas in the two hemispheres. In conclusion, this new approach to brain mapping may not only serve to identify novel functional subdivisions, but to reveal their connectivity as well.     

Fragment-based learning of visual object categories

When we perceive a visual object, we implicitly or explicitly associate it with a category we know. It is known that the visual system can use local, informative image fragments of a given object, rather than the whole object, to classify it into a familiar category. How we acquire informative fragments has remained unclear. Here, we show that human observers acquire informative fragments during the initial learning of categories. We created new, but naturalistic, classes of visual objects by using a novel "virtual phylogenesis" (VP) algorithm that simulates key aspects of how biological categories evolve. Subjects were trained to distinguish two of these classes by using whole exemplar objects, not fragments. We hypothesized that if the visual system learns informative object fragments during category learning, then subjects must be able to perform the newly learned categorization by using only the fragments as opposed to whole objects. We found that subjects were able to successfully perform the classification task by using each of the informative fragments by itself, but not by using any of the comparable, but uninformative, fragments. Our results not only reveal that novel categories can be learned by discovering informative fragments but also introduce and illustrate the use of VP as a versatile tool for category-learning research.     

Occipital Alpha Activity during Stimulus Processing Gates the Information Flow to Object-Selective Cortex

Given the limited processing capabilities of the sensory system, it is essential that attended information is gated to downstream areas, whereas unattended information is blocked. While it has been proposed that alpha band (8–13 Hz) activity serves to route information to downstream regions by inhibiting neuronal processing in task-irrelevant regions, this hypothesis remains untested. Here we investigate how neuronal oscillations detected by electroencephalography in visual areas during working memory encoding serve to gate information reflected in the simultaneously recorded blood-oxygenation-level-dependent (BOLD) signals recorded by functional magnetic resonance imaging in downstream ventral regions. We used a paradigm in which 16 participants were presented with faces and landscapes in the right and left hemifields; one hemifield was attended and the other unattended. We observed that decreased alpha power contralateral to the attended object predicted the BOLD signal representing the attended object in ventral object-selective regions. Furthermore, increased alpha power ipsilateral to the attended object predicted a decrease in the BOLD signal representing the unattended object. We also found that the BOLD signal in the dorsal attention network inversely correlated with visual alpha power. This is the first demonstration, to our knowledge, that oscillations in the alpha band are implicated in the gating of information from the visual cortex to the ventral stream, as reflected in the representationally specific BOLD signal. This link of sensory alpha to downstream activity provides a neurophysiological substrate for the mechanism of selective attention during stimulus processing, which not only boosts the attended information but also suppresses distraction. Although previous studies have shown a relation between the BOLD signal from the dorsal attention network and the alpha band at rest, we demonstrate such a relation during a visuospatial task, indicating that the dorsal attention network exercises top-down control of visual alpha activity.     

Neural activities in v1 create a bottom-up saliency map

The bottom-up contribution to the allocation of exogenous attention is a saliency map, whose neural substrate is hard to identify because of possible contamination by top-down signals. We obviated this possibility using stimuli that observers could not perceive, but that nevertheless, through orientation contrast between foreground and background regions, attracted attention to improve a localized visual discrimination. When orientation contrast increased, so did the degree of attraction, and two physiological measures: the amplitude of the earliest (C1) component of the ERP, which is associated with primary visual cortex, and fMRI BOLD signals in areas V1-V4 (but not the intraparietal sulcus). Significantly, across observers, the degree of attraction correlated with the C1 amplitude and just the V1 BOLD signal. These findings strongly support the proposal that a bottom-up saliency map is created in V1, challenging the dominant view that the saliency map is generated in the parietal cortex.     

Dynamic shape integration in extrastriate cortex

BACKGROUND: In anorthoscopic viewing conditions, observers can perceive a moving object through a narrow slit even when only portions of its contour are visible at any time. We used fMRI to examine the contribution of early and later visual cortical areas to dynamic shape integration. Observers' success at integrating the shape of the slit-viewed object was manipulated by varying the degree to which the stimulus was dynamically distorted. Line drawings of common objects were either moderately distorted, strongly distorted, or shown undistorted. Phenomenologically, increasing the stimulus distortion made both object shape and motion more difficult to perceive.RESULTS: We found that bilateral cortical activity in portions of the ventral occipital cortex, corresponding to known object areas within the lateral occipital complex (LOC), was inversely correlated with the degree of stimulus distortion. We found that activity in left MT+, the human cortical area specialized for motion, showed a similar pattern as the ventral occipital region. The LOC also showed greater activity to a fully visible moving object than to the undistorted slit-viewed object. Area MT+, however, showed more equivalent activity to both the slit-viewed and fully visible moving objects.CONCLUSIONS: In early retinotopic cortex, the distorted and undistorted stimuli elicited the same amount of activity. Higher visual areas, however, were correlated with the percept of the coherent object, and this correlation suggests that the shape integration is mediated by later visual cortical areas. Motion information from the dorsal stream may project to the LOC to produce the shape percept.     

宽周边视视网膜皮层映射的核磁共振研究

目的:人类视觉皮层的组织方式是视网膜皮层映射组织,先前研究已经证实视觉皮层在中心视采用这种组织方式,本文主要研究宽周边视的视觉皮层组织方式.方法:本文采用一种可以在核磁共振室中使用的光纤设备,设计了30度、40度、50度、60度的类圆环block刺激,使用1.5T的功能性核磁共振仪器,T1高分辨率图像分辨率为1*1*5.5mm,T2加权图像分辨率为4*4*5.5mm,TR反应时间为60,矩阵大小为64*64.核磁共振数据分析使用了SPM2和Brain voyager软件.结果:通过对试验者的数据处理分析,周边视的刺激的反应区域在枕叶上,主要分布在枕叶的前部,刺激反应区域随着偏心率的增大而沿着距状沟从距状沟的后部向前部移动.结论:周边视的视网膜皮层映射组织特性和中心视的特性非常相似.     

Emerging Object Representations in the Visual System Predict Reaction Times for Categorization

Recognizing an object takes just a fraction of a second, less than the blink of an eye. Applying multivariate pattern analysis, or “brain decoding”, methods to magnetoencephalography (MEG) data has allowed researchers to characterize, in high temporal resolution, the emerging representation of object categories that underlie our capacity for rapid recognition. Shortly after stimulus onset, object exemplars cluster by category in a high-dimensional activation space in the brain. In this emerging activation space, the decodability of exemplar category varies over time, reflecting the brain’s transformation of visual inputs into coherent category representations. How do these emerging representations relate to categorization behavior? Recently it has been proposed that the distance of an exemplar representation from a categorical boundary in an activation space is critical for perceptual decision-making, and that reaction times should therefore correlate with distance from the boundary. The predictions of this distance hypothesis have been born out in human inferior temporal cortex (IT), an area of the brain crucial for the representation of object categories. When viewed in the context of a time varying neural signal, the optimal time to “read out” category information is when category representations in the brain are most decodable. Here, we show that the distance from a decision boundary through activation space, as measured using MEG decoding methods, correlates with reaction times for visual categorization during the period of peak decodability. Our results suggest that the brain begins to read out information about exemplar category at the optimal time for use in choice behaviour, and support the hypothesis that the structure of the representation for objects in the visual system is partially constitutive of the decision process in recognition.     

Olfaction spontaneously highlights visual saliency map

Attention is intrinsic to our perceptual representations of sensory inputs. Best characterized in the visual domain, it is typically depicted as a spotlight moving over a saliency map that topographically encodes strengths of visual features and feedback modulations over the visual scene. By introducing smells to two well-established attentional paradigms, the dot-probe and the visual-search paradigms, we find that a smell reflexively directs attention to the congruent visual image and facilitates visual search of that image without the mediation of visual imagery. Furthermore, such effect is independent of, and can override, top-down bias. We thus propose that smell quality acts as an object feature whose presence enhances the perceptual saliency of that object, thereby guiding the spotlight of visual attention. Our discoveries provide robust empirical evidence for a multimodal saliency map that weighs not only visual but also olfactory inputs.     

Fragment-based learning of visual object categories in non-human primates

When we perceive a visual object, we implicitly or explicitly associate it with an object category we know. Recent research has shown that the visual system can use local, informative image fragments of a given object, rather than the whole object, to classify it into a familiar category. We have previously reported, using human psychophysical studies, that when subjects learn new object categories using whole objects, they incidentally learn informative fragments, even when not required to do so. However, the neuronal mechanisms by which we acquire and use informative fragments, as well as category knowledge itself, have remained unclear. Here we describe the methods by which we adapted the relevant human psychophysical methods to awake, behaving monkeys and replicated key previous psychophysical results. This establishes awake, behaving monkeys as a useful system for future neurophysiological studies not only of informative fragments in particular, but also of object categorization and category learning in general.