Models of object recognition.

Progress in the understanding of visual recognition in the past year has been signified by the demonstration of computational feasibility of and psychophysical support for two-dimensional view-interpolation methods.     

Modelling face recognition.

Much early work in the psychology of face processing was hampered by a failure to think carefully about task demands. Recently our understanding of the processes involved in the recognition of familiar faces has been both encapsulated in, and guided by, functional models of the processes involved in processing and recognizing faces. The specification and predictive power of such theory has been increased with the development of an implemented model, based upon an 'interactive activation and competition' architecture. However, a major deficiency in most accounts of face processing is their failure to spell out the perceptual primitives that form the basis of our representations for faces. Possible representational schemes are discussed, and the potential role of three-dimensional representations of the face is emphasized.     

Neural mechanisms of object recognition

Single-unit recordings from behaving monkeys and human functional magnetic resonance imaging studies have continued to provide a host of experimental data on the properties and mechanisms of object recognition in cortex. Recent advances in object recognition, spanning issues regarding invariance, selectivity, representation and levels of recognition have allowed us to propose a putative model of object recognition in cortex.     

Neuropsychological studies of object recognition

It is well established that disorders of visual perception are associated with lesions in the right hemisphere. Performances on tasks as disparate as the identification of objects from unusual views of objects drawn so as to overlap, of fragmented letters, of familiar faces, and of anomalous features in drawings, have been shown to be impaired in patients with focal right posterior lesions. A series of investigations are reviewed, directed towards analysing the basis of these deficits. Explanations in terms of primary visual impairment can be rejected, as can an account in terms of faulty figure-ground organization. It is argued that a wide variety of such perceptual deficits--all of which are concerned with meaningful visual stimuli--can be encompassed by the notion of faulty perceptual categorization at an early post-sensory stage of object recognition. Moreover, there is evidence suggesting that some of these various perceptual deficits can be mutually dissociated. The concept of perceptual categorization is discussed in the wider context of tentative model of object recognition.     

Disruptive camouflage impairs object recognition

Whether hiding from predators, or avoiding battlefield casualties, camouflage is widely employed to prevent detection. Disruptive coloration is a seemingly well-known camouflage mechanism proposed to function by breaking up an object''s salient features (for example their characteristic outline), rendering objects more difficult to recognize. However, while a wide range of animals are thought to evade detection using disruptive patterns, there is no direct experimental evidence that disruptive coloration impairs recognition. Using humans searching for computer-generated moth targets, we demonstrate that the number of edge-intersecting patches on a target reduces the likelihood of it being detected, even at the expense of reduced background matching. Crucially, eye-tracking data show that targets with more edge-intersecting patches were looked at for longer periods prior to attack, and passed-over more frequently during search tasks. We therefore show directly that edge patches enhance survivorship by impairing recognition, confirming that disruptive coloration is a distinct camouflage strategy, not simply an artefact of background matching.     

Low-level correlations between object properties and viewpoint can cause viewpoint-dependent object recognition

Viewpoint-dependent recognition performance of 3-D objects has often been taken as an indication of a viewpoint-dependent object representation. This viewpoint dependence is most often found using metrically manipulated objects. We aim to investigate whether instead these results can be explained by viewpoint and object property (e.g. curvature) information not being processed independently at a lower level, prior to object recognition itself. Multidimensional signal detection theory offers a useful framework, allowing us to model this as a low-level correlation between the internal noise distributions of viewpoint and object property dimensions. In Experiment 1, we measured these correlations using both Yes/No and adjustment tasks. We found a good correspondence across tasks, but large individual differences. In Experiment 2, we compared these results to the viewpoint dependence of object recognition through a Yes/No categorization task. We found that viewpoint-independent object recognition could not be fully reached using our stimuli, and that the pattern of viewpoint dependence was strongly correlated with the low-level correlations we measured earlier. In part, however, the viewpoint was abstracted despite these correlations. We conclude that low-level correlations do exist prior to object recognition, and can offer an explanation for some viewpoint effects on the discrimination of metrically manipulated 3-D objects.     

Cortical mechanisms of sensory learning and object recognition

Learning about the world through our senses constrains our ability to recognise our surroundings. Experience shapes perception. What is the neural basis for object recognition and how are learning-induced changes in recognition manifested in neural populations? We consider first the location of neurons that appear to be critical for object recognition, before describing what is known about their function. Two complementary processes of object recognition are considered: discrimination among diagnostic object features and generalization across non-diagnostic features. Neural plasticity appears to underlie the development of discrimination and generalization for a given set of features, though tracking these changes directly over the course of learning has remained an elusive task.     

Field of attention for instantaneous object recognition

Background

Instantaneous object discrimination and categorization are fundamental cognitive capacities performed with the guidance of visual attention. Visual attention enables selection of a salient object within a limited area of the visual field; we referred to as “field of attention” (FA). Though there is some evidence concerning the spatial extent of object recognition, the following questions still remain unknown: (a) how large is the FA for rapid object categorization, (b) how accuracy of attention is distributed over the FA, and (c) how fast complex objects can be categorized when presented against backgrounds formed by natural scenes.

Methodology/Principal Findings

To answer these questions, we used a visual perceptual task in which subjects were asked to focus their attention on a point while being required to categorize briefly flashed (20 ms) photographs of natural scenes by indicating whether or not these contained an animal. By measuring the accuracy of categorization at different eccentricities from the fixation point, we were able to determine the spatial extent and the distribution of accuracy over the FA, as well as the speed of categorizing objects using stimulus onset asynchrony (SOA). Our results revealed that subjects are able to rapidly categorize complex natural images within about 0.1 s without eye movement, and showed that the FA for instantaneous image categorization covers a visual field extending 20°×24°, and accuracy was highest (>90%) at the center of FA and declined with increasing eccentricity.

Conclusions/Significance

In conclusion, human beings are able to categorize complex natural images at a glance over a large extent of the visual field without eye movement.     

Learning and neural plasticity in visual object recognition

The capability of the adult primate visual system for rapid and accurate recognition of targets in cluttered, natural scenes far surpasses the abilities of state-of-the-art artificial vision systems. Understanding this capability remains a fundamental challenge in visual neuroscience. Recent experimental evidence suggests that adaptive coding strategies facilitated by underlying neural plasticity enable the adult brain to learn from visual experience and shape its ability to integrate and recognize coherent visual objects.     

Visual exploration and object recognition by lattice deformation

Mechanisms of explicit object recognition are often difficult to investigate and require stimuli with controlled features whose expression can be manipulated in a precise quantitative fashion. Here, we developed a novel method (called "Dots"), for generating visual stimuli, which is based on the progressive deformation of a regular lattice of dots, driven by local contour information from images of objects. By applying progressively larger deformation to the lattice, the latter conveys progressively more information about the target object. Stimuli generated with the presented method enable a precise control of object-related information content while preserving low-level image statistics, globally, and affecting them only little, locally. We show that such stimuli are useful for investigating object recognition under a naturalistic setting--free visual exploration--enabling a clear dissociation between object detection and explicit recognition. Using the introduced stimuli, we show that top-down modulation induced by previous exposure to target objects can greatly influence perceptual decisions, lowering perceptual thresholds not only for object recognition but also for object detection (visual hysteresis). Visual hysteresis is target-specific, its expression and magnitude depending on the identity of individual objects. Relying on the particular features of dot stimuli and on eye-tracking measurements, we further demonstrate that top-down processes guide visual exploration, controlling how visual information is integrated by successive fixations. Prior knowledge about objects can guide saccades/fixations to sample locations that are supposed to be highly informative, even when the actual information is missing from those locations in the stimulus. The duration of individual fixations is modulated by the novelty and difficulty of the stimulus, likely reflecting cognitive demand.     

A Neurocomputational Model of the Mismatch Negativity

The mismatch negativity (MMN) is an event related potential evoked by violations of regularity. Here, we present a model of the underlying neuronal dynamics based upon the idea that auditory cortex continuously updates a generative model to predict its sensory inputs. The MMN is then modelled as the superposition of the electric fields evoked by neuronal activity reporting prediction errors. The process by which auditory cortex generates predictions and resolves prediction errors was simulated using generalised (Bayesian) filtering – a biologically plausible scheme for probabilistic inference on the hidden states of hierarchical dynamical models. The resulting scheme generates realistic MMN waveforms, explains the qualitative effects of deviant probability and magnitude on the MMN – in terms of latency and amplitude – and makes quantitative predictions about the interactions between deviant probability and magnitude. This work advances a formal understanding of the MMN and – more generally – illustrates the potential for developing computationally informed dynamic causal models of empirical electromagnetic responses.     

Structural bases for substrate recognition and repair system of base-excision DNA repair proteins.

The model structure of Escherichia coli AlkA (3-methyladenine-DNA glycosylase II) protein complexed with the double helical DNA is elucidated from X-ray structures of related DNA glycosylase enzymes and mutagenic studies. The free enzyme structure has no difficulty in building the platform to afford the bended and wedge DNA with the flipped out nucleotide. The helix-hairpin-helix motif and the insertion residue L125 in free structure can be located without severe contacts. The alkylated base is surrounded with a variety of aromatic rings, such as W218, W272, Y273 and F18. The aromatic indole ring of tryptophan is a good candidate for forming the stacking with the positively charged base moiety pi-cation interaction). Some hydrophobic residues, such as V128 and L240, also attend to substrate recognition.     

The effect of face inversion on activity in human neural systems for face and object perception

The differential effect of stimulus inversion on face and object recognition suggests that inverted faces are processed by mechanisms for the perception of other objects rather than by face perception mechanisms. We investigated the face inversion using functional magnetic resonance imaging (fMRI). The principal effect of face inversion on was an increased response in ventral extrastriate regions that respond preferentially to another class of objects (houses). In contrast, house inversion did not produce a similar change in face-selective regions. Moreover, stimulus inversion had equivalent, minimal effects for faces in in face-selective regions and for houses in house-selective regions. The results suggest that the failure of face perception systems with inverted faces leads to the recruitment of processing resources in object perception systems, but this failure is not reflected by altered activity in face perception systems.     

Mechanisms of visual object recognition studied in monkeys

Cells in area TE of the inferotemporal cortex of the monkey brain selectively respond to various moderately complex object-features, and those responding to similar features cluster in a columnar region elongated vertical to the cortical surface. Although cells within a column respond to similar features, their selectivity is not identical. The data of optical imaging in TE have suggested that the borders between neighboring columns are not discrete but columns representing related features overlap one another. We have also found, by training adult monkeys for discrimination of a specific set of shapes, that such a long-term training increases the proportion of TE cells responding to the shapes used in the training even in the adult. The data suggested that TE plays important roles in discrimination of complex shapes and in visual expert learning of discriminating a certain class of objects in the adult.     

The significance of hair for face recognition

Hair is a feature of the head that frequently changes in different situations. For this reason much research in the area of face perception has employed stimuli without hair. To investigate the effect of the presence of hair we used faces with and without hair in a recognition task. Participants took part in trials in which the state of the hair either remained consistent (Same) or switched between learning and test (Switch). It was found that in the Same trials performance did not differ for stimuli presented with and without hair. This implies that there is sufficient information in the internal features of the face for optimal performance in this task. It was also found that performance in the Switch trials was substantially lower than in the Same trials. This drop in accuracy when the stimuli were switched suggests that faces are represented in a holistic manner and that manipulation of the hair causes disruption to this, with implications for the interpretation of some previous studies.