Development of monotonic neuronal tuning in the monkey inferotemporal cortex through long-term learning of fine shape discrimination

Visual expertise in discriminating fine differences among a group of similar objects can be obtained through extensive long-term training. Here we investigated the neural bases of this superior capability. The inferotemporal cortex, located at the final stage along the ventral visual pathway, was a candidate site in monkeys because cells there respond to various complex features of objects. To identify the changes that underlie the development of visual expertise in fine discrimination, we created a set of parametrically designed object stimuli and compared the stimulus selectivity of inferotemporal cells between two different training histories. One group of recordings was conducted after the monkeys had been extensively trained for fine discrimination (fine-discrimination period) and the other after the monkeys had been exposed only for coarse discrimination (coarse-discrimination period). We found that the tuning of responses recorded in the fine-discrimination period was more monotonic in the stimulus parameter space. The stimuli located at the extreme in the parameter space evoked the maximum responses in a larger proportion of cells and the direction of response decrease in the parameter space was more consistent. Moreover, the stimulus arrangement reconstructed from the responses recorded during the fine-discrimination period was more similar to the original stimulus arrangement. These results suggest that visual expertise could be based on the development, in the inferotemporal cortex, of neuronal selectivity monotonically tuned over the parameter space of the object images

Development of monotonic neuronal tuning in the monkey inferotemporal cortex through long-term learning of fine shape discrimination

Visual expertise in discriminating fine differences among a group of similar objects can be obtained through extensive long-term training. Here we investigated the neural bases of this superior capability. The inferotemporal cortex, located at the final stage along the ventral visual pathway, was a candidate site in monkeys because cells there respond to various complex features of objects. To identify the changes that underlie the development of visual expertise in fine discrimination, we created a set of parametrically designed object stimuli and compared the stimulus selectivity of inferotemporal cells between two different training histories. One group of recordings was conducted after the monkeys had been extensively trained for fine discrimination (fine-discrimination period) and the other after the monkeys had been exposed only for coarse discrimination (coarse-discrimination period). We found that the tuning of responses recorded in the fine-discrimination period was more monotonic in the stimulus parameter space. The stimuli located at the extreme in the parameter space evoked the maximum responses in a larger proportion of cells and the direction of response decrease in the parameter space was more consistent. Moreover, the stimulus arrangement reconstructed from the responses recorded during the fine-discrimination period was more similar to the original stimulus arrangement. These results suggest that visual expertise could be based on the development, in the inferotemporal cortex, of neuronal selectivity monotonically tuned over the parameter space of the object images

Visual Recognition and Categorization on the Basis of Similarities to Multiple Class Prototypes

To recognize a previously seen object, the visual system must overcome the variability in the object's appearance caused by factors such as illumination and pose. Developments in computer vision suggest that it may be possible to counter the influence of these factors, by learning to interpolate between stored views of the target object, taken under representative combinations of viewing conditions. Daily life situations, however, typically require categorization, rather than recognition, of objects. Due to the open-ended character both of natural kinds and of artificial categories, categorization cannot rely on interpolation between stored examples. Nonetheless, knowledge of several representative members, or prototypes, of each of the categories of interest can still provide the necessary computational substrate for the categorization of new instances. The resulting representational scheme based on similarities to prototypes appears to be computationally viable, and is readily mapped onto the mechanisms of biological vision revealed by recent psychophysical and physiological studies

Renewing the respect for similarity

In psychology, the concept of similarity has traditionally evoked a mixture of respect, stemming from its ubiquity and intuitive appeal, and concern, due to its dependence on the framing of the problem at hand and on its context. We argue for a renewed focus on similarity as an explanatory concept, by surveying established results and new developments in the theory and methods of similarity-preserving associative lookup and dimensionality reduction—critical components of many cognitive functions, as well as of intelligent data management in computer vision. We focus in particular on the growing family of algorithms that support associative memory by performing hashing that respects local similarity, and on the uses of similarity in representing structured objects and scenes. Insofar as these similarity-based ideas and methods are useful in cognitive modeling and in AI applications, they should be included in the core conceptual toolkit of computational neuroscience. In support of this stance, the present paper (1) offers a discussion of conceptual, mathematical, computational, and empirical aspects of similarity, as applied to the problems of visual object and scene representation, recognition, and interpretation, (2) mentions some key computational problems arising in attempts to put similarity to use, along with their possible solutions, (3) briefly states a previously developed similarity-based framework for visual object representation, the Chorus of Prototypes, along with the empirical support it enjoys, (4) presents new mathematical insights into the effectiveness of this framework, derived from its relationship to locality-sensitive hashing (LSH) and to concomitant statistics, (5) introduces a new model, the Chorus of Relational Descriptors (ChoRD), that extends this framework to scene representation and interpretation, (6) describes its implementation and testing, and finally (7) suggests possible directions in which the present research program can be extended in the future

3D Object Recognition Based On Constrained 2D Views

The aim of the present work was to build a novel 3D object recognition system capable of classifying man-made and natural objects based on single 2D views. The approach to this problem has been one motivated by recent theories on biological vision and multiresolution analysis. The project's objectives were the implementation of a system that is able to deal with simple 3D scenes and constitutes an engineering solution to the problem of 3D object recognition, allowing the proposed recognition system to operate in a practically acceptable time frame. The developed system takes further the work on automatic classification of marine phytoplank- (ons, carried out at the Centre for Intelligent Systems, University of Plymouth. The thesis discusses the main theoretical issues that prompted the fundamental system design options. The principles and the implementation of the coarse data channels used in the system are described. A new multiresolution representation of 2D views is presented, which provides the classifier module of the system with coarse-coded descriptions of the scale-space distribution of potentially interesting features. A multiresolution analysis-based mechanism is proposed, which directs the system's attention towards potentially salient features. Unsupervised similarity-based feature grouping is introduced, which is used in coarse data channels to yield feature signatures that are not spatially coherent and provide the classifier module with salient descriptions of object views. A simple texture descriptor is described, which is based on properties of a special wavelet transform. The system has been tested on computer-generated and natural image data sets, in conditions where the inter-object similarity was monitored and quantitatively assessed by human subjects, or the analysed objects were very similar and their discrimination constituted a difficult task even for human experts. The validity of the above described approaches has been proven. The studies conducted with various statistical and artificial neural network-based classifiers have shown that the system is able to perform well in all of the above mentioned situations. These investigations also made possible to take further and generalise a number of important conclusions drawn during previous work carried out in the field of 2D shape (plankton) recognition, regarding the behaviour of multiple coarse data channels-based pattern recognition systems and various classifier architectures. The system possesses the ability of dealing with difficult field-collected images of objects and the techniques employed by its component modules make possible its extension to the domain of complex multiple-object 3D scene recognition. The system is expected to find immediate applicability in the field of marine biota classification

Mechanisms of Object Representation in Inferotemporal Cortex

The inferotemporal cortex in primates is thought to be the primary region that subserves object recognition. The studies presented here help to elucidate the role of IT in higher visual processing by addressing three specific outstanding issues. In the first study, we sought to determine whether IT neurons respond similarly to patterns that are perceptually confused. We considered a behavioral phenomenon whereby lateral mirror images are confused more frequently than vertical mirror images. By presenting mirror images to the monkey while simultaneously recording from IT neurons, we found that neurons differentiate less effectively between lateral mirror images than between vertical mirror images. This phenomenon may underlie the perceptual confusion documented in behavioral studies.In the second study, we sought to determine whether activity in IT reflects experience-based changes in perception. We tested this by first training monkeys to discriminate shape orientation. We then recorded from IT neurons while monkeys performed an orientation discrimination task with trained orientations, and passively viewed orientations of trained and untrained shapes. We found that training to discriminate between orientations of a shape significantly increases the ability of IT neurons to discriminate between those same orientations. This neuronal selectivity correlated with the monkeys' ability to discriminate orientation. These data suggest that training-induced changes in perception are supported by processes in IT.Some IT neurons respond to the onset of a visual stimulus by firing a series of bursts at a frequency of around 5 Hz. One explanation for this phenomenon is that stimuli in the visual scene compete, with alternating success, for processing resources in IT. In the third study, we tested this by examining the oscillatory activity of IT neurons in response to the presentation of multiple stimuli, a central "preferred" image and a peripheral "non-preferred" image. We observed that the onset of a central pattern in the presence of the peripheral stimulus elicited strong oscillations phase-locked to pattern-onset. Onset of the peripheral stimulus in the presence of the central pattern elicited a succession of inhibitory troughs phase-locked to stimulus-onset. These results are congruent with a model of mutual inhibition of competing neuronal populations

Pictorial Primates: A Search for Iconic Abilities in Great Apes

Pictures and other iconic media are used extensively in psychological experiments on nonhuman primate perception, categorisation, etc. They are also used in everyday interaction with primates, and as pure entertainment. But in what ways do primates understand iconic artefacts? What implications do these different ways have for the conclusions we can draw from those studies on perception and categorisation? What can pictures tell us about primate cognition, and what can primates tell us about pictures? The bulk of the thesis is a critical review of the primatological literature concerned with iconic artefacts. Drawing on work in developmental psychology, cross-cultural research, and semiotics, distinctions between different kinds of pictorial competence are made. The alternatives to viewing pictures as depictions, are to view them as the real world is viewed, in which case only realistic pictures evoke recognition, or to view them as a set of disjoint properties, in which case recognition of categorisable motifs fails. It is argued that approaching a picture as a depiction entails a set of expectations on the picture, which affects attention to e.g. part - whole relationships, "filling in," and integration into context. This in turn allows recognition also of non-realistic similarity. The question, then, is whether such expectations can be formed in other brains than an exclusively human one. The different forms of pictorial competence are discussed in relation to research on similarity judgements, abstraction, and categorisation, as well as applied to other iconic media than the picture, such as scale-models, mirrors, toy replicas, and video. Two lines of original empirical investigation are presented: A study of photographic recognition in picture-naïve gorillas, and recognition of line drawings in picture-experienced and language-competent bonobos. Only the latter study yielded evidence for recognition. The failures in the former study are discussed in terms of experimental shortcomings, and suggestions for future improvements are made