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Neural dynamics is determined by the transmission of discrete synaptic pulses (synaptic shot-noise) among neurons. However, the neural responses are usually obtained within the diffusion approximation modeling synaptic inputs as continuous…

Disordered Systems and Neural Networks · Physics 2025-10-17 Denis S. Goldobin , Maria V. Ageeva , Matteo di Volo , Ferdinand Tixidre , Alessandro Torcini

Decades of research on the neural code underlying spatial navigation have revealed a diverse set of neural response properties. The Entorhinal Cortex (EC) of the mammalian brain contains a rich set of spatial correlates, including grid…

Neurons and Cognition · Quantitative Biology 2018-05-11 Christopher J. Cueva , Xue-Xin Wei

Deciphering the underpinnings of the dynamical processes leading to information transmission, processing, and storing in the brain is a crucial challenge in neuroscience. An inspiring but speculative theoretical idea is that such dynamics…

Statistical Mechanics · Physics 2023-07-21 Guillermo B. Morales , Serena Di Santo , Miguel A. Muñoz

The brain is made up of a vast set of heterogeneous regions that dynamically organize into pathways as a function of task demands. Examples of such pathways can be found in the interactions between cortical and subcortical networks during…

Neurons and Cognition · Quantitative Biology 2025-11-24 Jack Cook , Danyal Akarca , Rui Ponte Costa , Jascha Achterberg

As a result of a hundred million years of evolution, living animals have adapted extremely well to their ecological niche. Such adaptation implies species-specific interactions with their immediate environment by processing sensory cues and…

Disordered Systems and Neural Networks · Physics 2022-04-28 Tom Birkoben , Hermann Kohlstedt

A feature of the brains of intelligent animals is the ability to learn to respond to an ensemble of active neuronal inputs with a behaviorally appropriate ensemble of active neuronal outputs. Previously, a hypothesis was proposed on how…

Neurons and Cognition · Quantitative Biology 2025-02-04 Marat M. Rvachev

There is a concerted effort to build domain-general artificial intelligence in the form of universal neural network models with sufficient computational flexibility to solve a wide variety of cognitive tasks but without requiring…

Neural and Evolutionary Computing · Computer Science 2023-03-27 Jascha Achterberg , Danyal Akarca , Moataz Assem , Moritz Heimbach , Duncan E. Astle , John Duncan

Many agent-based mathematical models of cranial neural crest cell (CNCC) migration impose a binary phenotypic partition of cells into either leaders or followers. In such models, the movement of leader cells at the front of collectives is…

Cell Behavior · Quantitative Biology 2026-01-13 Samuel W. S. Johnson , Ruth E. Baker , Philip K. Maini

One fascinating aspect of the brain is its ability to process information in a fast and reliable manner. The functional architecture is thought to play a central role in this task, by encoding efficiently complex stimuli and facilitating…

Neurons and Cognition · Quantitative Biology 2016-02-17 Alberto Romagnoni , Jérôme Ribot , Daniel Bennequin , Jonathan D. Touboul

Animal brains evolved to optimize behavior in dynamically changing environments, selecting actions that maximize future rewards. A large body of experimental work indicates that such optimization changes the wiring of neural circuits,…

Neurons and Cognition · Quantitative Biology 2021-04-06 Mien Brabeeba Wang , Michael M. Halassa

The emergence of cognition requires a framework that bridges evolutionary principles with neurocomputational mechanisms. This paper introduces the novel "thoughtseed" framework, proposing that cognition arises from the dynamic interaction…

Neurons and Cognition · Quantitative Biology 2025-05-30 Prakash Chandra Kavi , Gorka Zamora-López , Daniel Ari Friedman

Although it has been notoriously difficult to pin down precisely what it is that makes life so distinctive and remarkable, there is general agreement that its informational aspect is one key property, perhaps the key property. The unique…

Adaptation and Self-Organizing Systems · Physics 2012-12-20 Sara Imari Walker , Paul C. W. Davies

Spike synchrony, which occurs in various cortical areas in response to specific perception, action and memory tasks, has sparked a long-standing debate on the nature of temporal organization in cortex. One prominent view is that this type…

Neurons and Cognition · Quantitative Biology 2017-12-18 Clemens Korndörfer , Ekkehard Ullner , Jordi García-Ojalvo , Gordon Pipa

Understanding how people allocate visual attention is central to Human-Computer Interaction (HCI), yet existing computational models of attention are often either descriptive, task-specific, or difficult to interpret. My dissertation…

Human-Computer Interaction · Computer Science 2026-03-03 Yunpeng Bai

This paper demonstrates that some non-classical models of human decision-making can be run successfully as circuits on quantum computers. Since the 1960s, many observed cognitive behaviors have been shown to violate rules based on classical…

Quantum Physics · Physics 2023-03-27 Dominic Widdows , Jyoti Rani , Emmanuel Pothos

This review highlights brain health as a dynamic process shaped by both genetic and environmental influences throughout development. Critical periods provide unique windows of heightened neural plasticity, during which genetic-environmental…

By retracing my scientific journey that began 20 years ago, I highlight in this thesis the need to consider the organization of the brain, which is certainly globally hierarchical, but also highly distributed and mixed in the neuronal…

Neurons and Cognition · Quantitative Biology 2025-01-03 David Thura

A stream of conscious experience is extremely contextual; it is impacted by sensory stimuli, drives and emotions, and the web of associations that link, directly or indirectly, the subject of experience to other elements of the individual's…

Neurons and Cognition · Quantitative Biology 2013-10-30 Diederik Aerts , Jan Broekaert , Liane Gabora

Causal discovery algorithms based on probabilistic graphical models have emerged in geoscience applications for the identification and visualization of dynamical processes. The key idea is to learn the structure of a graphical model from…

Machine Learning · Computer Science 2015-12-29 Imme Ebert-Uphoff , Yi Deng

Many important phenomena in scientific fields like climate, neuroscience, and epidemiology are naturally represented as spatiotemporal gridded data with complex interactions. Inferring causal relationships from these data is a challenging…

Machine Learning · Computer Science 2025-06-17 Kun Wang , Sumanth Varambally , Duncan Watson-Parris , Yi-An Ma , Rose Yu