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Neural spikes in the brain form stochastic sequences, i.e., belong to the class of pulse noises. This stochasticity is a counterintuitive feature because extracting information - such as the commonly supposed neural information of mean…

Neural and Evolutionary Computing · Computer Science 2015-03-31 Laszlo B. Kish , Claes-Goran Granqvist , Sergey M. Bezrukov , Tamas Horvath

An increasing body of evidence suggests that the trial-to-trial variability of spiking activity in the brain is not mere noise, but rather the reflection of a sampling-based encoding scheme for probabilistic computing. Since the precise…

Recent advances in associative memory design through structured pattern sets and graph-based inference algorithms have allowed reliable learning and recall of an exponential number of patterns. Although these designs correct external errors…

Neural and Evolutionary Computing · Computer Science 2014-03-14 Amin Karbasi , Amir Hesam Salavati , Amin Shokrollahi , Lav R. Varshney

An assembly is a large population of neurons whose synchronous firing is hypothesized to represent a memory, concept, word, and other cognitive categories. Assemblies are believed to provide a bridge between high-level cognitive phenomena…

Neural and Evolutionary Computing · Computer Science 2022-07-05 Max Dabagia , Christos H. Papadimitriou , Santosh S. Vempala

Noise is an inherent part of neuronal dynamics, and thus of the brain. It can be observed in neuronal activity at different spatiotemporal scales, including in neuronal membrane potentials, local field potentials, electroencephalography,…

Neurons and Cognition · Quantitative Biology 2019-01-03 Daqing Guo , Matjaz Perc , Tiejun Liu , Dezhong Yao

Recent advances in associative memory design through strutured pattern sets and graph-based inference algorithms have allowed the reliable learning and retrieval of an exponential number of patterns. Both these and classical associative…

Neural and Evolutionary Computing · Computer Science 2013-06-04 Amin Karbasi , Amir Hesam Salavati , Amin Shokrollahi , Lav Varshney

Living systems implement and execute an extraordinary plethora of computational tasks. The inherent degree of large scale coordination emerges as a global property, from the intricate sea of microscopic interactions. The brain, with its…

Disordered Systems and Neural Networks · Physics 2018-01-03 Duccio Fanelli , Francesco Ginelli , Roberto Livi , Niccolò Zagli , Clement Zankoc

Neural-network models of high-level brain functions such as memory recall and reasoning often rely on the presence of stochasticity. The majority of these models assumes that each neuron in the functional network is equipped with its own…

Neurons and Cognition · Quantitative Biology 2022-05-17 Jakob Jordan , Mihai A. Petrovici , Oliver Breitwieser , Johannes Schemmel , Karlheinz Meier , Markus Diesmann , Tom Tetzlaff

Animals rely on different decision strategies when faced with ambiguous or uncertain cues. Depending on the context, decisions may be biased towards events that were most frequently experienced in the past, or be more explorative. A…

Neurons and Cognition · Quantitative Biology 2023-05-10 Younes Bouhadjar , Dirk J. Wouters , Markus Diesmann , Tom Tetzlaff

The brain is a noisy system subject to energy constraints. These facts are rarely taken into account when modelling artificial neural networks. In this paper, we are interested in demonstrating that those factors can actually lead to the…

Neural and Evolutionary Computing · Computer Science 2017-09-26 Eliott Coyac , Vincent Gripon , Charlotte Langlais , Claude Berrou

A steadily increasing body of evidence suggests that the brain performs probabilistic inference to interpret and respond to sensory input and that trial-to-trial variability in neural activity plays an important role. The neural sampling…

Neurons and Cognition · Quantitative Biology 2017-07-07 Ilja Bytschok , Dominik Dold , Johannes Schemmel , Karlheinz Meier , Mihai A. Petrovici

The highly irregular spiking activity of cortical neurons and behavioral variability suggest that the brain could operate in a fundamentally probabilistic way. Mimicking how the brain implements and learns probabilistic computation could be…

Neural and Evolutionary Computing · Computer Science 2024-04-23 Yang Qi , Zhichao Zhu , Yiming Wei , Lu Cao , Zhigang Wang , Jie Zhang , Wenlian Lu , Jianfeng Feng

Music is a universal feature of human culture, linked to embodied cognitive functions that drive learning, action, and the emergence of creativity and individuality. Evidence highlights the critical role of statistical learning an implicit…

Neurons and Cognition · Quantitative Biology 2025-11-21 Tatsuya Daikoku

The brain is believed to implement probabilistic reasoning and to represent information via population, or distributed, coding. Most previous population-based probabilistic (PPC) theories share several basic properties: 1) continuous-valued…

Neurons and Cognition · Quantitative Biology 2018-02-23 Gerard Rinkus

$\textbf{Formal version available at}$ https://cell.com/patterns/fulltext/S2666-3899(23)00200-3 Networks of spiking neurons underpin the extraordinary information-processing capabilities of the brain and have become pillar models in…

Neural and Evolutionary Computing · Computer Science 2023-09-18 Gehua Ma , Rui Yan , Huajin Tang

Understanding how the brain learns to compute functions reliably, efficiently and robustly with noisy spiking activity is a fundamental challenge in neuroscience. Most sensory and motor tasks can be described as dynamical systems and could…

Neurons and Cognition · Quantitative Biology 2017-05-24 Sophie Denève , Alireza Alemi , Ralph Bourdoukan

Even as machine learning exceeds human-level performance on many applications, the generality, robustness, and rapidity of the brain's learning capabilities remain unmatched. How cognition arises from neural activity is a central open…

Neural and Evolutionary Computing · Computer Science 2023-10-17 Max Dabagia , Christos H. Papadimitriou , Santosh S. Vempala

Neuronal responses are conspicuously variable. We focus on one particular aspect of that variability: the precision of action potential timing. We show that for common models of noisy spike generation, elementary considerations imply that…

Disordered Systems and Neural Networks · Physics 2009-10-31 Guillermo A. Cecchi , Mariano Sigman , Jose-Manuel Alonso , Luis Martinez , Dante R. Chialvo , Marcelo O. Magnasco

Perceptions and actions, thoughts and memories result from coordinated activity in hundreds or even thousands of neurons in the brain. It is an old dream of the physics community to provide a statistical mechanics description for these and…

Disordered Systems and Neural Networks · Physics 2024-09-04 Leenoy Meshulam , William Bialek

Varied sensory systems use noise in order to enhance detection of weak signals. It has been conjectured in the literature that this effect, known as stochastic resonance, may take place in central cognitive processes such as the memory…

Neurons and Cognition · Quantitative Biology 2007-05-23 Julien Mayor , Wulfram Gerstner
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