In recent years, many new cortical areas have been identified in the macaque monkey. The number of identified connections between areas has increased even more dramatically. We report here on (1) a summary of the layout of cortical areas associated with vision and with other modalities, (2) a computerized database for storing and representing large amounts of information on connectivity patterns, and (3) the application of these data to the analysis of hierarchical organization of the cerebral cortex. Our analysis concentrates on the visual system, which includes 25 neocortical areas that are predominantly or exclusively visual in function, plus an additional 7 areas that we regard as visual-association areas on the basis of their extensive visual inputs. A total of 305 connections among these 32 visual and

blindness seems especially paradoxical: it implies that identifying "forest before trees." For later vision with processing has proceeded to the level of determining scrutiny, reverse hierarchy routines focus attention that one element is a conceptual or categorical repeti- to specific, active, low-level units, incorporating into tion of another---a repetition to which we are then blind. conscious perception detailed information available How can we know that two elements are similar if we there. Reverse Hierarchy Theory dissociates between are blind to the double occurrence? A similar paradox early explicit perception and implicit low-level vision, appears when we briefly view a scene containing many explaining a variety of phenomena. Feature search elements. We can more easily report the average value "pop-out" is attributed to high areas, where large re- of a parameter (such as the mean size or orientation of ceptive fields underlie spread attention detecting cat- elements) than ju

We propose a perceptually based system for pattern retrieval and matching. There is a need for such an "intelligent" retrieval system in applications such as digital museums and libraries, design, architecture, and digital stock photography. The central idea of the work is that similarity judgment has to be modeled along perceptual dimensions. Hence, we detect basic visual categories that people use in judgment of similarity, and design a computational model that accepts patterns as input, and depending on the query, produces a set of choices that follow human behavior in pattern matching. There are two major research aspects to our work. The first one addresses the issue of how humans perceive and measure similarity within the domain of color patterns. To understand and describe this mechanism we performed a subjective experiment. The experiment yielded five perceptual criteria used in comparison between color patterns (vocabulary), as well as a set of rules governing the use of these criteria in similarity judgment (grammar). The second research aspect is the actual implementation of the perceptual criteria and rules in an image retrieval system. Following the processing typical for human vision, we design a system to: 1) extract perceptual features from the vocabulary and 2) perform the comparison between the patterns according to the grammar rules. The modeling of human perception of color patterns is new---starting with a new color codebook design, compact color representation, and texture description through multiple scale edge distribution along different directions. Moreover, we propose new color and texture distance functions that correlate with human performance. The performance of the system is illustrated with numerous examples from image databases from diff...

To investigate the relations between structure and function in both artificial and natural neural networks, we present a series of simulations and analyses with modular neural networks. We suggest a number of design principles in the form of explicit ways in which neural modules can cooperate in recognition tasks. These results may supplement recent accounts of the relation between structure and function in the brain. The networks used consist out of several modules, standard subnetworks that serve as higher-order units with a distinct structure and function. The simulations rely on a particular network module called CALM (Murre, Phaf, and Wolters, 1989, 1992). This module, developed mainly for unsupervised categorization and learning, is able to adjust its local learning dynamics. The way in which modules are interconnected is an important determinant of the learning and categorization behaviour of the network as a whole. Based on arguments derived from neuroscience, psychology, compu...

Using noninvasive functional magnetic resonance imaging (fMRI) techniques, we analyzed the responses in human area MT with regard to visual motion, color, and luminance contrast sensitivity, and retinotopy. As in previous PET studies, we found that area MT responded selectively to moving (compared to stationary) stimuli. The location of human MT in the present fMRl results is consistent with that of MT in earlier PET and anatomical studies. In addition we found that area MT has a much higher contrast sensitivity than that in several other areas, includ-ing primary visual cortex (Vl). Functional MRI half-ampli-tudes in Vl and MT occurred at approximately 15 % and 1% luminance contrast, respectively. High sensitivity to con-trast and motion in MT have been closely associated with magnocellular stream specialization in nonhuman pri-mates. Human psychophysics indicates that visual motion ap-pears to diminish when moving color-varying stimuli are equated in luminance. Electrophysiological results from macaque MT suggest that the human percept could be due to decreases in firing of area MT cells at equiluminance. We show here that fMRl activity in human MT does in fact decrease at and near individually measured equilumi-nance. Tests with visuotopically restricted stimuli in each hem-ifield produced spatial variations in fMRl activity consistent with retinotopy in human homologs of macaque areas Vl, V2, V3, and VP. Such activity in area MT appeared much less retinotopic, as in macaque. However, it was possible to measure the interhemispheric spread of fMRl activity in human MT (half amplitude activation across the vertical meridian =-15’).

This article develops the FACADE theory of 3-dimensional (3-D) vision and figure-ground separation to explain data concerning how 2-dimensional pictures give rise to 3-D percepts of occluding and occluded objects. The model describes how geometrical and contrastive properties of a picture can either cooperate or compete when fonning the boundaries and surface representations that subserve conscious percepts. Spatially long-range cooperation and spatially short-range competition work together to separate the boundaries of occluding figures from their occluded neighbors. This boundary ownership process is sensitive to image T junctions at which occluded figures contact occluding figures. These boundaries control the filling-in of color within multiple depth-sensitive surface representations. Feedback between surface and boundary representations strengthens consistent boundaries while inhibiting inconsistent ones. Both the boundary and the surface representations of occluded objects may be amodally completed, while the surface representations of unoccluded objects become visible through modal completion. Functional roles for conscious modal and amodal representations in object recognition, spatial attention, and reaching behaviors are discussed. Model interactions are interpreted in tenns of visual, temporal, and parietal cortices. The human urge to represent the three-dimensional (3-D)

performing a specific visual task (for an exposition of this issue, see Ungerleider and Haxby, 1994; DeYoe et al., 1994; Goodale et al., 1994). Single neuron recordings in the macaque provide evidence both for segregation of visual cues into different †Diagnostic Imaging Department channels (Livingstone and Hubel, 1988; DeYoe et al., The Chaim Sheba Medical Center 1994) and for convergence of several primary cues even Tel Hashomer 52621 at the level of single cortical neurons (Sary et al., 1993). Israel Similarly, studies of anatomical connections indicate ‡School of Cognitive and Computing Sciences the existence of parallel specialized cortical streams University of Sussex, Falmer (Young, 1992) but also show substantial interstream Brighton BN1 9QH communication both between areas (reviewed by Felle-

A neural model of motion perception simulates psychophysical data concerning first-order and second-order motion stimuli, including the reversal of perceived motion direction with distance from the stimulus (\Gamma display), and data about directional judgments as a function of relative spatial phase or spatial and temporal frequency. Many other second-order motion percepts that have been ascribed to a second non-Fourier processing stream can also be explained in the model by interactions between ON and OFF cells within a single, neurobiologically interpreted magnocellular processing stream. Yet other percepts may be traced to interactions between form and motion processing streams, rather than to processing within multiple motion processing streams. The model hereby explains why monkeys with lesions of of the parvocellular layers, but not the magnocellular layers, of the lateral geniculate nucleus (LGN) are capable of detecting the correct direction of second-order motion, why most ce...

Neural responses in sensory systems are typically triggered by a multitude of stimulus features. Using information theory, we study the encoding accuracy of a population of stochastically spiking neurons characterized by different tuning widths for the different features. The optimal encoding strategy for representing one feature most accurately consists of (i) narrow tuning in the dimension to be encoded to increase the single-neuron Fisher information, and (ii) broad tuning in all other dimensions to increase the number of active neurons. Extremely narrow tuning without sufficient receptive field overlap will severely worsen the coding. This implies the existence of an optimal tuning width for the feature to be encoded. Empirically, only a subset of all stimulus features will normally be accessible. In this case, relative encoding errors can be calculated which yield a criterion for the function of a neural population based on the measured tuning curves. 1 Introduction The question...

this article that the choice of a variability model has a major, nontrivial impact on the encoding properties of the neural population. The immense variability of individual response parameters, such as tuning widths or correlation coef#cients, has also been neglected in most previous work. Although these parameter variations are always found in empirical data, they were considered functionally insignificant, and hence theoretical studies have almost always assumed uniform parameters throughout the population. We will show here that this uniform case is unfavorable in the sense that the introduction of parameter variability improves the encoding performance