Numerous theories of neural processing, often motivated by experimental observations, have explored the computational properties of neural codes based on the precise or relative occurrence of spikes in a spike train. Spiking neuron models and theories however, as well as their experimental counterparts, have generally been limited to the simulation or observation of isolated neurons, isolated spike trains, or reduced neural populations. Such theories would therefore seem inappropriate to capture the properties of a neural code relying on temporal spike patterns distributed across large neuronal populations. Here we report a range of computer simulations and theoretical considerations that were designed to explore the possibilities of such a code and its relevance for visual processing. In a single, unified framework where the relation between stimulus saliency and spike asynchrony plays the central role, we describe how the ventral stream of the visual system could process natural input scenes and extract meaningful information, both rapidly and reliably. The first wave of spikes generated in the retina in response to a visual stimulation carries information explicitly in its spatio-temporal structure. This spike wave, propagating through a hierarchy of visual areas, is regenerated at each processing stage, where its temporal structure can be modified by (i) the selectivity of the cortical neurons, (ii) lateral interactions and (iii) top-down attentional influences from higher order cortical areas. The concept of temporal asynchrony within a wave of single spikes allows a unique theoretical framework to address the fundamental and complementary notions of neural information coding and representation, visual saliency and attention. 1.

Why do stabilized images fade? How can X cells in the retina respond linearly to a broad range of spatiotemporal stimulation functions in spite of possible nonlinear preprocessing? Why have models of spatial vision that utilize static images and assume linearity of preprocessing led to reasonable results in spite of the two questions above? This chapter introduces the push-pull shunting network, a model of spatiotemporal visual processing that resolves these and other controversial findings. Development of the model is based on an analysis of the spatial and temporal response characteristics of networks of neurons that obey membrane equations. The resulting architecture is structurally similar to the mammalian retina, requiring a mechanism for temporal adaptation analogous to photoreceptors, followed by cells of opposite polarity analogous to on and off bipolar cells, and finally a layer of ganglion cells that summate bipolar cell inputs. The model predicts that X and Y cells consist ...

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Abstract: We consider adaptive control problem in presence of nonlinear parametrization of uncertainties in the model. It is shown that despite traditional approaches require for domination in the control loop during adaptation, it is not often necessary to use such energy inefficient compensators it in wide range of applications. In particular, we show that recently introduced adaptive control algorithms in finite form which are applicable to monotonic parameterized systems can be extended to general smooth non-monotonic parametrization. These schemes do not require any damping or domination in control inputs.

Attention and conscious perception in the hypothesis

Visual response properties of retinal ganglion cells (GCs), the retinal output neurons, are shaped by numerous processes and interactions within the retina. In particular, amacrine cells are known to form microcircuits that affect GC responses in specific ways. So far, relatively little is known about the influence of retinal processing on GC responses under naturalistic viewing conditions, in particular in the presence of fixational eye movements. Here we used a detailed model of the mammalian retina to investigate possible effects of fixational eye movements on retinal GC activity. Populations of linear, sustained (parvocellular, PC) and nonlinear, transient (magnocellular, MC) GCs were simulated during fixation of a star-shaped stimulus, and two distinct effects were found: (1) a fading of complete wedges of the star and (2) an apparent splitting of stimulus lines. Both effects only occur in MC-cells, and an analysis shows that fading is caused by an expression of the aperture problem in retinal GCs, and the splitting effect by spatiotemporal nonlinearities in the MC-cell receptive field. These effects strongly resemble perceived instabilities during fixation of the same stimulus, and we propose that these illusions may have a retinal origin. We further suggest that in this case two parallel retinal streams send conflicting, rather than complementary, information to the higher visual system, which here leads to a dominant influence of the MC pathway. Similar situations may be common during natural vision, since retinal processing involves numerous nonlinearities.