382 research outputs found
Near-optimal combination of disparity across a log-polar scaled visual field
The human visual system is foveated: we can see fine spatial details in central vision, whereas resolution is poor in our peripheral visual field, and this loss of resolution follows an approximately logarithmic decrease. Additionally, our brain organizes visual input in polar coordinates. Therefore, the image projection occurring between retina and primary visual cortex can be mathematically described by the log-polar transform. Here, we test and model how this space-variant visual processing affects how we process binocular disparity, a key component of human depth perception. We observe that the fovea preferentially processes disparities at fine spatial scales, whereas the visual periphery is tuned for coarse spatial scales, in line with the naturally occurring distributions of depths and disparities in the real-world. We further show that the visual system integrates disparity information across the visual field, in a near-optimal fashion. We develop a foveated, log-polar model that mimics the processing of depth information in primary visual cortex and that can process disparity directly in the cortical domain representation. This model takes real images as input and recreates the observed topography of human disparity sensitivity. Our findings support the notion that our foveated, binocular visual system has been moulded by the statistics of our visual environment
Modelling Short-Latency Disparity-Vergence Eye Movements Under Dichoptic Unbalanced Stimulation
Vergence eye movements align the optical axes of our two eyes onto an object of interest, thus facilitating the binocular summation of the images projected onto the left and the right retinae into a single percept. Both the computational substrate and the functional behaviour of binocular vergence eye movements have been the topic of in depth investigation. Here, we attempt to bring together what is known about computation and function of vergence mechanism. To this aim, we evaluated of a biologically inspired model of horizontal and vertical vergence control, based on a network of V1 simple and complex cells. The model performances were compared to that of human observers, with dichoptic stimuli characterized by a varying amounts of interocular correlation, interocular contrast, and vertical disparity.
The model provides a qualitative explanation of psychophysiological data. Nevertheless, human vergence response to interocular contrast differs from model’s behavior, suggesting that the proposed disparity-vergence model may be improved to account for human behavior. More than this, this observation also highlights how dichoptic unbalanced stimulation can be used to investigate the significant but neglected role of sensory processing in motor planning of eye movements in depth
Multifractal analysis of perceptron learning with errors
Random input patterns induce a partition of the coupling space of a
perceptron into cells labeled by their output sequences. Learning some data
with a maximal error rate leads to clusters of neighboring cells. By analyzing
the internal structure of these clusters with the formalism of multifractals,
we can handle different storage and generalization tasks for lazy students and
absent-minded teachers within one unified approach. The results also allow some
conclusions on the spatial distribution of cells.Comment: 11 pages, RevTex, 3 eps figures, version to be published in Phys.
Rev. E 01Jan9
Progress report and first operation of the GANIL injector
http://accelconf.web.cern.ch/AccelConf/c81/papers/abp-07.pdfInternational audienc
Chaos in neural networks with a nonmonotonic transfer function
Time evolution of diluted neural networks with a nonmonotonic transfer
function is analitically described by flow equations for macroscopic variables.
The macroscopic dynamics shows a rich variety of behaviours: fixed-point,
periodicity and chaos. We examine in detail the structure of the strange
attractor and in particular we study the main features of the stable and
unstable manifolds, the hyperbolicity of the attractor and the existence of
homoclinic intersections. We also discuss the problem of the robustness of the
chaos and we prove that in the present model chaotic behaviour is fragile
(chaotic regions are densely intercalated with periodicity windows), according
to a recently discussed conjecture. Finally we perform an analysis of the
microscopic behaviour and in particular we examine the occurrence of damage
spreading by studying the time evolution of two almost identical initial
configurations. We show that for any choice of the parameters the two initial
states remain microscopically distinct.Comment: 12 pages, 11 figures. Accepted for publication in Physical Review E.
Originally submitted to the neuro-sys archive which was never publicly
announced (was 9905001
Changing current practice in urology: Improving guideline development and implementation through stakeholder engagement
Effective stakeholder integration for guideline development should improve outcomes and adherence to clinical practice guidelines
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