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Systems of Signals Generating and Processing in the Field of on Board Communications Conference

作者： Kudryashova, A. Y. Adzhemov, A. S. Vlasuyk, I. V. Moscow Tech Univ Commun & Informat Moscow Russia

ISBN: (纸本)9781728106069

In the modern world, image transmission, including transmission of television and video signals, is carried out using a preliminary and restorative correction according to the law, which was due to the use of imaging devices on cathode ray tubes. This law differs from the law of dependence of the visibility threshold of a visual stimulus on its magnitude, but continues to be used for compatibility reasons. Therefore, in the work, instead of linearizing the sensations of the quantization scale of a television signal, it is proposed to optimize the choice of code combinations for image transmission. This approach can be effective in television systems without compression of video information with losses, for example, for transmitting signals over short distances or in channels for transmitting signals of the image of Earth remote sensing systems

关键词： Weber-Fechner law gamma correction transfer characteristic efficient coding risk matrix probability matrix

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Exploring Action-Centric Representations Through the Lens of Rate-Distortion Theory 4th

Exploring Action-Centric Representations Through the Lens of...

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4th International Workshop on Active Inference

作者： Varona, Miguel De Llanza Buckley, Christopher Millidge, Beren Univ Sussex Sch Engn & Informat Brighton England VERSES Res Lab Los Angeles CA 90016 USA Univ Oxford MRC Brain Networks Dynam Unit Oxford England

ISBN: (纸本)9783031479571;9783031479588

Organisms have to keep track of the information in the environment that is relevant for adaptive behaviour. Transmitting information in an economical and efficient way becomes crucial for limited-resourced agents living in high-dimensional environments. The efficient coding hypothesis claims that organisms seek to maximize the information about the sensory input in an efficient manner. Under Bayesian inference, this means that the role of the brain is to efficiently allocate resources in order to make predictions about the hidden states that cause sensory data. However, neither of those frameworks accounts for how that information is exploited downstream, leaving aside the action-oriented role of the perceptual system. Rate-distortion theory, which defines optimal lossy compression under constraints, has gained attention as a formal framework to explore goal-oriented efficient coding. In this work, we explore action-centric representations in the context of rate-distortion theory. We also provide a mathematical definition of abstractions and we argue that, as a summary of the relevant details, they can be used to fix the content of action-centric representations. We model action-centric representations using VAEs and we find that such representations i) are efficient lossy compressions of the data;ii) capture the task-dependent invariances necessary to achieve successful behaviour;and iii) are not in service of reconstructing the data. Thus, we conclude that full reconstruction of the data is rarely needed to achieve optimal behaviour, consistent with a teleological approach to perception.

关键词： Rate-distortion theory Action-centric representations efficient coding Bayesian Inference

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Colour Representation in Lateral Geniculate Nucleus and Natural Colour Distributions

Colour Representation in Lateral Geniculate Nucleus and Natu...

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2nd International Computational Color Imaging Workshop

作者： Goda, Naokazu Koida, Kowa Komatsu, Hidehiko Natl Inst Physiol Sci Okazaki Aichi 4448585 Japan

ISBN: (纸本)9783642032646

We investigated the representation of a wide range of colours in the lateral geniculate nucleus (LGN) of macaque monkeys. We took an approach to reconstruct a colour space from responses of a population of neurons. We found that, in the derived colour space ('LGN colour space'), red and blue regions were compressed whereas purple region was expanded, compared with those in a linear cone-opponent colour space. We found that the expanding/compressing pattern in the LGN colour space was related to the colour histogram derived from a natural image database. Quantitative analysis showed that the response functions of the population of the neurons were nearly optimal according to the principle of 'minimizing errors in estimation of stimulus colour in the presence of response noise'. Our findings support the idea that the colour representation at the early neural processing stage is adapted for efficient coding of colour information in the natural environment.

关键词： opponency efficient coding colour histogram

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Optimal Information Transmission by Overlapping Retinal Cell Mosaics 52

Optimal Information Transmission by Overlapping Retinal Cell...

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52nd Annual Conference on Information Sciences and Systems (CISS)

作者： Zhang, Yilun Kastner, David B. Baccus, Stephen A. Sharpee, Tatyana O. Salk Inst Biol Studies Computat Neurobiol Lab 10010 N Torrey Pines Rd La Jolla CA 92037 USA Univ Calif San Diego Dept Phys La Jolla CA 92093 USA Univ Calif San Francisco Dept Psychiat San Francisco CA USA Stanford Univ Dept Neurobiol Palo Alto CA 94304 USA

ISBN: (纸本)9781538605790

The retina provides an excellent system for understanding the trade-offs that influence distributed information processing across multiple neuron types. We focus here on the problem faced by the visual system of allocating a limited number neurons to encode different visual features at different spatial locations. The retina needs to solve three competing goals: 1) encode different visual features, 2) maximize spatial resolution for each feature, and 3) maximize accuracy with which each feature is encoded at each location. There is no current understanding of how these goals are optimized together. While information theory provides a platform for theoretically solving these problems, evaluating information provided by the responses of large neuronal arrays is in general challenging. Here we present a solution to this problem in the case where multi-dimensional stimuli can be decomposed into approximately independent components that are subsequently coupled by neural responses. Using this approach we quantify information transmission by multiple overlapping retinal ganglion cell mosaics. In the retina, translation invariance of input signals makes it possible to use Fourier basis as a set of independent components. The results reveal a transition where one high-density mosaic becomes less informative than two or more overlapping lower-density mosaics. The results explain differences in the fractions of multiple cell types, predict the existence of new retinal ganglion cell subtypes, relative distribution of neurons among cell types and differences in their nonlinear and dynamical response properties.

关键词： Mutual Information efficient coding Retina Ganglion Cell Photoreceptor Noise Functional Neuronal Types

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A homeostatic gain control mechanism to improve event-driven object recognition 18

A homeostatic gain control mechanism to improve event-driven...

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18th International Conference on Content-Based Multimedia Indexing (IEEE CBMI)

作者： Grimaldi, Antoine Boutin, Victor Perrinet, Laurent Ieng, Sio-Hoi Benosman, Ryad Aix Marseille Univ Inst Neurosci Timone UMR 7289 CNRS Marseille France Sorbonne Univ INSERM CNRS Inst Vis Paris France

ISBN: (纸本)9781665442206

We propose a neuromimetic architecture able to perform pattern recognition. To achieve this, we extended the existing event-based algorithm from [1] which introduced novel spatio-temporal features: time surfaces. Built from asynchronous events acquired by a neuromorphic camera, these time surfaces allow to code the local dynamics of a visual scene and create an efficient hierarchical event-based pattern recognition architecture. Inspired by biological findings and the efficient coding hypothesis, our main contribution is to integrate homeostatic regulation into the Hebbian learning rule. Indeed, in order to be optimally informative, average neural activity within a layer should be equally balanced across neurons. We used that principle to regularize neurons within the same layer by setting a gain depending on their past activity and such that they emit spikes with balanced firing rates. The efficiency of this technique was first demonstrated through a robust improvement in spatio-temporal patterns which were learnt during the training phase. In order to compare with state-of-the-art methods, we replicated past results on the same dataset as [1] and extended results in this study to the widely used N-MNIST dataset [2]. We expect to extend this fully event-driven approach to more naturalistic tasks, notably for ultra-fast object categorization.

关键词： event-based vision homeostasis pattern recognition efficient coding neuromorphic hardware

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The Role of Contrast Sensitivity in the Development of Binocular Vision: A Computational Study 5

The Role of Contrast Sensitivity in the Development of Binoc...

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5th IEEE Joint International Conference on Development and Learning and on Epigenetic Robotics (IEEE ICDL-EpiRob)

作者： Priamikov, Alexander Narayan, Vikram Shi, Bertram E. Triesch, Jochen Frankfurt Inst Adv Studies Frankfurt Germany Hong Kong Univ Sci & Technol Dept Elect & Comp Engn Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9781467393201

The development of accurate binocular vision relies on the acquisition of disparity tuning and the calibration of vergence eye movements. Both processes are fundamentally limited by visual acuity, which increases only gradually during the first year of life. Next to limiting performance, however, early limitations of visual acuity may also aid rapid learning analogous to Newport's "less-is-more" hypothesis. Here we use computational modeling to assess the potential impact of early acuity limitations on the development of binocular vision. Our starting point is a previous model of the development of binocular vision, formulated in the Active efficient coding framework. We extend this model to incorporate the development of visual acuity between birth and 8 months. We find that the model does in fact learn faster if visual acuity starts out poor and increases with time, supporting the less-is-more hypothesis. Furthermore, we find that the speed of acuity improvement needs to be "just right", i.e., neither too rapid nor too slow for fastest learning. Overall, our model suggests that early limitations of visual acuity may aid infants in acquiring binocular vision skills and it provides a good starting point for computational modeling of developmental disorders of binocular vision.

关键词： binocular vision contrast sensitivity function disparity tuning vision development vergence eye movements active efficient coding efficient coding

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Ising-like model for neural representation of natural images 12

Ising-like model for neural representation of natural images

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12th IEEE International Conference on Signal Processing (ICSP)

作者： Lu Xiankai Zhu Wenya Zhao Ziyi Xu Qimin Shanghai Jiao Tong Univ Dept Automat Shanghai 200030 Peoples R China Shanghai Jiao Tong Univ Sch Aeronaut & Astronaut Shanghai 200030 Peoples R China

ISBN: (纸本)9781479921867

efficient coding hypothesis was proposed as a model of sensory coding in the brain. One noteworthy assumption in efficient coding hypothesis is that the neuronal activities are independent. However, many neuroscience experiments evidences show that neuron interactions and correlations are ubiquitous in the retina and cortical vortex, independent hypothesis may be inappropriate in efficient coding. In this paper, Ising model is employed to describe pairwise correlation of the neural activities. A novel biological spike neuron network model based on efficient coding is proposed. When adapted to the statistics of natural images, our model can reproduce receptive fields resemble Sparse coding or Independent Components Analysis(ICA). The results validate the proposed modeling approach in this paper.

关键词： Ising model neuron correlation spiking neuron network efficient coding natural image

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Modeling Imprecision in Perception, Valuation, and Choice

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ANNUAL REVIEW OF ECONOMICS, VOL 12 2020年第1期12卷 579-601页

作者： Woodford, Michael Columbia Univ Dept Econ New York NY 10027 USA

Traditional decision theory assumes that people respond to the exact features of the options available to them, but observed behavior seemsmuch less precise. This review considers ways of introducing imprecision into models of economic decision making and stresses the usefulness of analogies with the way that imprecise perceptual judgments are modeled in psychophysics-the branch of experimental psychology concerned with the quantitative relationship between objective features of an observer's environment and elicited reports about their subjective appearance. It reviews key ideas from psychophysics, provides examples of the kinds of data that motivate them, and proposes lessons for economic modeling. Applications include stochastic choice, choice under risk, decoy effects in marketing, global game models of strategic interaction, and delayed adjustment of prices in response to monetary disturbances.

关键词： psychophysics efficient coding stochastic choice global games risk attitude context effect

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Log-Nets: Logarithmic Feature-Product Layers Yield More Compact Networks 29th

Log-Nets: Logarithmic Feature-Product Layers Yield More Comp...

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29th International Conference on Artificial Neural Networks (ICANN)

作者： Gruening, Philipp Martinetz, Thomas Barth, Erhardt Univ Lubeck Inst Neuro & Bioinformat Lubeck Germany

ISBN: (纸本)9783030616168;9783030616151

We introduce Logarithm-Networks (Log-Nets), a novel bio-inspired type of network architecture based on logarithms of feature maps followed by convolutions. Log-Nets are capable of surpassing the performance of traditional convolutional neural networks (CNNs) while using fewer parameters. Performance is evaluated on the Cifar-10 and ImageNet benchmarks.

关键词： Bio-inspired networks Deep Learning efficient coding Compact networks

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Comparing Activation Typicality and Sparsity in a Deep CNN to Predict Facial Beauty

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Computational Brain and Behavior 2024年 1-13页

作者： Tieo, Sonia Bardin, Melvin Bertin-Johannet, Roland Dibot, Nicolas Mendelson, Tamra C. Puech, William Renoult, Julien P. CEFE Univ Montpellier CNRS EPHE IRD Montpellier France Terakalis Montpellier France CERCO UMR5549 Centre de Recherche Cerveau Et Cognition Toulouse France Department of Biological Sciences University of Maryland Baltimore County Baltimore MD United States LIRMM Univ. Montpellier CNRS Montpellier France

Processing fluency, which describes the subjective sensation of ease with which information is processed by the sensory systems and the brain, has become one of the most popular explanations of aesthetic appreciation and beauty. Two metrics have recently been proposed to model fluency: the sparsity of neuronal activation, which describes the concentration of activity in a subset of neurons, and the statistical typicality of activations, which describes how well the encoding of a stimulus matches a reference representation of stimuli of the category to which it belongs. Using convolutional neural networks (CNNs) as a model for the human visual system, this study compares the ability of these metrics to explain variation in facial attractiveness. Our findings show that the sparsity of neuronal activations is a more robust predictor of facial attractiveness than statistical typicality. Refining the reference representation to a single ethnicity or gender does not increase the explanatory power of statistical typicality. However, statistical typicality and sparsity predict facial beauty based on different layers of the CNNs, suggesting that they describe different neural mechanisms underlying fluency. © Society for Mathematical Psychology 2024.

关键词： Attractiveness CNNs efficient coding Fluency Sparsity Statistical typicality

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