Spatial attention was studied using a new visual ilhrsion of motion: a line, which was presented physically at once, was perceived to be drawn from one side when attention had been captured to that side of the line by a preceding visual cue stimulus. By comparing with a temporal order task, we showed that the line-motion illusion was produced by acceleration of visual information processing at the locus of attention. The results suggest that the facilitatory effect of attention is exerted at relatively early stages of visual information processing where visual signals are to be fed into the motion detecting mechanism. Visual attention Line-motion illusion Motion Perception Sustained/transient features Dichoptic presentation

The existence of recurrent collateral connections between pyramidal cells within a cortical area and, in addition, reciprocal connections between connected cortical areas, is well established. In this work we analyse the properties of a tri-modular architecture of this type in which two input modules have convergent connections to a third module (which in the brain might be the next module in cortical processing or a bi-modal area receiving connections from two different processing pathways). Memory retrieval is analysed in this system which has Hebb-like synaptic modifiability in the connections and attractor states. Local activity features are stored in the intra-modular connections while the associations between corresponding features in different modules present during training are stored in the inter-modular connections. The response of the network when tested with corresponding and contradictory stimuli to the two input pathways is studied in detail. The model is solved quantitatively using techniques of statistical physics. In one type of test, a sequence of stimuli is applied, with a delay between them. It is found that if the coupling between the modules is low a regime exists in which they retain the capability to retrieve any of their stored features independently of the features being retrieved by the other modules. Although independent in this sense, the modules still influence each other in this regime through persistent modulatory currents which are strong enough to initiate recall in the whole network when only a single module is stimulated, and to raise the mean firing rates of the neurons in the attractors if the features in the different modules are corresponding. Some of these mechanisms might be useful for the description of many phenomena observe...

A population of neurons in anterior inferotemporal cortex has sustained activity following the presentation of specific visual stimuli when monkeys perform a delayed match-to-sample (DMS) task. Typically, only stimuli that are repeatedly shown elicit robust delay activity. When the sample stimuli were shown in a fixed temporal order, the few images that evoked delay activity in the same neuron were often neighboring stimuli in the sequence. Therefore, this delay activity was suggested as the neural correlate of associative long-term memory of visual images. We report here that stimulus selective sustained activity is evident also following the presentation of the test stimulus in the same DMS task. We demonstrate, using a neural network model, that the persistence of stimulus selective activity across the inter-trial-interval can lead to similar menmonic representations (distribution of delay activity across the neural population) for neighboring visual stimuli. Thus, the neural machin...

Understanding how biological visual systems perform object recognition is one of the ultimate goals in computational neuroscience. Among the biological models of recognition the main distinctions are between feedforward and feedback and between object-centered and view-centered. From a computational viewpoint the different recognition tasks --- for instance categorization and identification --- are very similar, representing different trade-offs between specificity and invariance. Thus the different tasks do not strictly require different classes of models. The focus of the review is on feedforward, view-based models that are supported by psychophysical and physiological data.

. The binding problem is regarded as one of today's key questions about brain function. Several solutions have been proposed, yet the issue is still controversial. The goal of this article is twofold. Firstly, we propose a new experimental paradigm requiring feature binding, the "delayed binding response task". Secondly, we propose a binding mechanism employing fast reversible synaptic plasticity to express the binding between concepts. We discuss the experimental predictions of our model for the delayed binding response task. 1 Introduction What is the binding problem? If several objects have to be represented simultaneously in our brains, superposition of the activity patterns may lead to confusion. This effect is called the "superposition catastrophe" and the general problem behind it is called the "binding problem". Several solutions have been proposed, only two of which shall be mentioned here. For a recent review of theoretical ideas the reader may refer to [vdM95]. Combinatio...

The evidence from neurophysiological recordings from the primate visual system suggests that sensory patterns are processed using units arranged in a hierarchical multi-layered network. Responses of these units show progressively increasing receptive field size combined with selectivity for increasing stimulus complexity at successively higher levels. It is argued that the rate of the increase in receptive field size is less than the maximum possible given the initial spread of neuronal projections that occurs during development. We show here that a competitive learning mechanism using.a 'trace-Hebbian' learning rule [14] with a larger number of competing output units learns not only positional invariance for a given input feature but can also establish restricted receptive field sizes (i.e. less than the maximum size given the initial connections). Importantly the same stimulus selectivity was maintained throughout the receptive field. It is shown that this is accompanied by a relative increase in the spatial evenness of the representation of each detector type across position within the input array. The network properties were found to be robust and stable over a wide range of learning parameters. We suggest that such a competitive mechanism may help account for the reported properties of cells in the ventral stream of the primate visual system.

In this paper we review a series of works concerning models of spiking neurons interacting via spike-driven, plastic, Hebbian synapses, meant to implement stimulus driven, unsupervised formation of working memory (WM) states.

The unsupervised categorization of sensory stimuli is typically attributed to feedforward processing in a hierarchy of cortical areas. This purely sensory-driven view of cortical processing, however, ignores any internal modulation, e.g., by top-down attentional signals or neuromodulator release. To isolate the role of internal signaling on category formation, we consider an unbroken continuum of stimuli without intrinsic category boundaries. We show that a competitive network, shaped by recurrent inhibition and endowed with Hebbian and homeostatic synaptic plasticity, can enforce stimulus categorization. The degree of competition is internally controlled by the neuronal gain and the strength of inhibition. Strong competition leads to the formation of many attracting network states, each being evoked by a distinct subset of stimuli and representing a category. Weak competition allows more neurons to be co-active, resulting in fewer but larger categories. We conclude that the granularity of cortical category formation, i.e., the number and size of emerging categories, is not simply determined by the richness of the stimulus environment, but rather by some global internal signal modulating the network dynamics. The model also explains the salient non-additivity of visual object representation observed in the monkey inferotemporal (IT) cortex. Furthermore, it offers an explanation of a previously observed, demand-dependent modulation of IT activity on a stimulus categorization task and of categorization-related cognitive defi cits in schizophrenic patients.

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Visual processes do not amount to a simple filtering process performed by a series of hierarchical modules. They allow to select the items immediately useful for the current action from the information included in the external scene. To perform this selection, attentional top-down controls must combine with bottom-up information issued from the retina. In the prospect to understand how these informations are fused together, a computational model of the first steps of the visual process able to account for the pre-attentional and attentional mechanisms involved in visual search has been developed. This model, called Competitive Search, integrates the dynamical aspects of a local dynamical architecture. It accounts for 'pop-out' and attentional phenomena involved in the search for conjunctive targets without introducing ad hoc hypothetical mechanisms such as the attentional spotlight hypothesis. It suggests that such metaphors, issued from the conventional cognitive psychology, may in fa...