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Visual recognition takes a small fraction of a second and relies on the cascade of signals along the ventral visual stream. Given the rapid path through multiple processing steps between photoreceptors and higher visual areas, information…

Neurons and Cognition · Quantitative Biology 2014-04-28 Jedediah M. Singer , Joseph R. Madsen , William S. Anderson , Gabriel Kreiman

The latency of visual responses generally decreases as contrast increases. Recording in the lateral geniculate nucleus (LGN), we find that response latency increases with increasing contrast in ON cells for some visual stimuli. We propose…

Neurons and Cognition · Quantitative Biology 2012-10-01 Kate S. Gaudry , Pamela Reinagel

We consider the information transmission problem in neurons and its possible implications for learning in neural networks. Our approach is based on recent developments in statistical physics and complexity science. Combining sensory…

Neurons and Cognition · Quantitative Biology 2025-09-30 Siddharth Kackar

Models of neural responses to stimuli with complex spatiotemporal correlation structure often assume that neurons are only selective for a small number of linear projections of a potentially high-dimensional input. Here we explore recent…

Neurons and Cognition · Quantitative Biology 2013-06-19 Kanaka Rajan , Olivier Marre , Gašper Tkačik

Retinal implants aim to restore functional vision despite photoreceptor degeneration, yet are fundamentally constrained by low resolution electrode arrays and patient-specific perceptual distortions. Most deployed encoders rely on…

Image and Video Processing · Electrical Eng. & Systems 2026-02-12 Henning Konermann , Yuli Wu , Emil Mededovic , Volkmar Schulz , Peter Walter , Johannes Stegmaier

Neural populations encode information about their stimulus in a collective fashion, by joint activity patterns of spiking and silence. A full account of this mapping from stimulus to neural activity is given by the conditional probability…

Neurons and Cognition · Quantitative Biology 2013-06-14 Einat Granot-Atedgi , Gašper Tkačik , Ronen Segev , Elad Schneidman

Encoding information about continuous variables using noisy computational units is a challenge; nonetheless, asymptotic theory shows that combining multiple periodic scales for coding can be highly precise despite the corrupting influence…

Neurons and Cognition · Quantitative Biology 2013-08-22 Alexander Mathis , Andreas V. M. Herz , Martin B. Stemmler

Developments in reinforcement learning (RL) have allowed algorithms to achieve impressive performance in highly complex, but largely static problems. In contrast, biological learning seems to value efficiency of adaptation to a…

Artificial Intelligence · Computer Science 2022-05-20 Eric Chalmers , Artur Luczak

The optimal discrimination of coherent states of light with current technology is a key problem in classical and quantum communication, whose solution would enable the realization of efficient receivers for long-distance communications in…

Quantum Physics · Physics 2020-09-02 M. Bilkis , M. Rosati , R. Morral Yepes , J. Calsamiglia

It has been argued that humans rapidly adapt their lexical and syntactic expectations to match the statistics of the current linguistic context. We provide further support to this claim by showing that the addition of a simple adaptation…

Computation and Language · Computer Science 2018-10-29 Marten van Schijndel , Tal Linzen

The brain has no direct access to physical stimuli, but only to the spiking activity evoked in sensory organs. It is unclear how the brain can structure its representation of the world based on differences between those noisy, correlated…

Neurons and Cognition · Quantitative Biology 2018-04-16 Christophe Gardella , Olivier Marre , Thierry Mora

Agents acting in the natural world aim at selecting appropriate actions based on noisy and partial sensory observations. Many behaviors leading to decision mak- ing and action selection in a closed loop setting are naturally phrased within…

Machine Learning · Statistics 2014-06-30 Alex Susemihl , Ron Meir , Manfred Opper

A major goal of neuroscience is to understand brain computations during visual processing in naturalistic settings. A dominant approach is to use image-computable deep neural networks trained with different task objectives as a basis for…

Neurons and Cognition · Quantitative Biology 2026-02-06 Hossein Adeli , Sun Minni , Nikolaus Kriegeskorte

If modern computers are sometimes superior to humans in some specialized tasks such as playing chess or browsing a large database, they can't beat the efficiency of biological vision for such simple tasks as recognizing and following an…

Neurons and Cognition · Quantitative Biology 2009-11-13 Laurent Perrinet

The rate coding response of a single peripheral sensory neuron in the asymptotic, near-equilibrium limit can be derived using information theory, asymptotic Bayesian statistics and a theory of complex systems. Almost no biological knowledge…

Neurons and Cognition · Quantitative Biology 2020-12-14 Willy Wong

The inverse Ising model is used in computational neuroscience to infer probability distributions of the synchronous activity of large neuronal populations. This method allows for finding the Boltzmann distribution with single neuron biases…

Neurons and Cognition · Quantitative Biology 2022-07-27 Geoffroy Delamare , Ulisse Ferrari

The subcortical sensory pathways are the fundamental channels for mapping the outside world to our minds. Sensory pathways efficiently transmit information by adapting neural responses to the local statistics of the sensory input. The…

Neurons and Cognition · Quantitative Biology 2020-03-26 Alejandro Tabas , Glad Mihai , Stefan Kiebel , Robert Trampel , Katharina von Kriegstein

When an object moves smoothly across a field of view, the identify of the object is unchanged, but the activation pattern of the photoreceptors on the retina changes drastically. One of the major computational roles of our visual system is…

Neurons and Cognition · Quantitative Biology 2014-04-23 Minjoon Kouh

Human visual perception is a complex, dynamic and fluctuating process. In addition to the incoming visual stimulus, it is affected by many other factors including temporal context, both external and internal to the observer. In this study…

Neurons and Cognition · Quantitative Biology 2020-07-01 Urit Gordon , Shimon Marom , Naama Brenner

The sensory-triggered activity of a neuron is typically characterized in terms of a tuning curve, which describes the neuron's average response as a function of a parameter that characterizes a physical stimulus. What determines the shapes…

Neurons and Cognition · Quantitative Biology 2007-05-23 Emilio Salinas