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How far is neuroepithelial cell proliferation in the developing central nervous system a deterministic process? Or, to put it in a more precise way, how accurately can it be described by a deterministic mathematical model? To provide tracks…

Analysis of PDEs · Mathematics 2010-05-04 Jean Clairambault , Vladimir Flores , Benoit Perthame , Melina Rapacioli , Edmundo Rofman , Rafael Verdes

Synaptic connections in neuronal circuits are modulated by pre- and post-synaptic spiking activity. Heuristic models of this process of synaptic plasticity can provide excellent fits to results from in-vitro experiments in which pre- and…

Neurons and Cognition · Quantitative Biology 2022-07-14 Federico Devalle , Alex Roxin

Vital to primary visual processing, retinal circuitry shows many similar structures across a very broad array of species, both vertebrate and non-vertebrate, especially functional components such as lateral inhibition. This surprisingly…

Neural and Evolutionary Computing · Computer Science 2021-02-23 Ziyi Gong , Paul Munro

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

Orientation selectivity is a remarkable feature of the neurons located in the primary visual cortex. Provided that the visual neurons acquire orientation selectivity through activity-dependent Hebbian learning, the development process could…

Neurons and Cognition · Quantitative Biology 2016-01-20 Myoung Won Cho

The brain may be thought of as a many-body architecture with a spatio-temporal dynamics described by neuronal structures. The oscillatory nature of brain activity allows these structures (nodes) to be described as a set of coupled…

Neurons and Cognition · Quantitative Biology 2021-02-03 J. Mendoza-Ruiz , C. E. Alonso-Malaver , M. Valderrama , O. A. Rosso , J. H. Martínez

Continual learning is a key feature of biological neural systems, but artificial neural networks often suffer from catastrophic forgetting. Instead of backpropagation, biologically plausible learning algorithms may enable stable continual…

Neural and Evolutionary Computing · Computer Science 2025-08-19 Denis Larionov , Nikolay Bazenkov , Mikhail Kiselev

Recent studies have shown how spiking networks can learn complex functionality through error-correcting plasticity, but the resulting structures and dynamics remain poorly studied. To elucidate how these models may link to observed dynamics…

Neurons and Cognition · Quantitative Biology 2025-08-19 Jonas Oberste-Frielinghaus , Anno C. Kurth , Julian Göltz , Laura Kriener , Junji Ito , Mihai A. Petrovici , Sonja Grün

Oscillatory activities are widely observed in specific frequency bands of recorded field potentials in different brain regions, and play critical roles in processing neural information. Understanding the structure of these oscillatory…

Neurons and Cognition · Quantitative Biology 2015-07-23 Pengsheng Zheng

In early years of life, the cranium rapidly changes in size and shape to accommodate brain growth, primarily driven by mechanical stress from brain expansion. Developmental disorders such as premature fusion of sutures in craniosynostosis,…

Tissues and Organs · Quantitative Biology 2025-10-30 Mahtab Vafaeefar , Conall Quinn , Ted J. Vaughan

The spiking activity of principal cells in mammalian hippocampus encodes an internalized neuronal representation of the ambient space---a cognitive map. Once learned, such a map enables the animal to navigate a given environment for a long…

Neurons and Cognition · Quantitative Biology 2017-10-10 Andrey Babichev , Dmitriy Morozov , Yuri Dabaghian

Many processes in eukaryotic cells, including cell motility, rely on the growth of branched actin networks from surfaces. Despite its central role the mechano-chemical coupling mechanisms which guide the growth process are poorly…

Soft Condensed Matter · Physics 2015-06-23 Karin John , Denis Caillerie , Chaouqi Misbah

A sufficiently large information flux in recurrent neural networks, quantified by the mutual information between successive network states, is considered a prerequisite for rich information processing capabilities. This raises the question…

Neurons and Cognition · Quantitative Biology 2026-05-15 Claus Metzner , Ali Ghebleh , Karin Prebeck , Achim Schilling , Andreas Maier , Thomas Kinfe , Patrick Krauss

We formulate the search for phenomenological models of synaptic plasticity as an optimization problem. We employ Cartesian genetic programming to evolve biologically plausible human-interpretable plasticity rules that allow a given network…

Neural and Evolutionary Computing · Computer Science 2021-02-09 Henrik D. Mettler , Maximilian Schmidt , Walter Senn , Mihai A. Petrovici , Jakob Jordan

Understanding the relation between cortical neuronal network structure and neuronal activity is a fundamental unresolved question in neuroscience, with implications to our understanding of the mechanism by which neuronal networks evolve…

Motivated by recent experiments on growing fibroblasts, we examine the development of nematic order in a colony of elongated cells proliferating on a nematic elastomer substrate. After sparse seeding, the cells divide and grow into locally…

Soft Condensed Matter · Physics 2026-01-06 Toshi Parmar , Fridtjof Brauns , Yimin Luo , M. Cristina Marchetti

The analysis of complex networks has revealed patterns of organization in a variety of natural and artificial systems, including neuronal networks of the brain at multiple scales. In this paper, we describe a novel analysis of the…

Neurons and Cognition · Quantitative Biology 2015-06-26 Luciano da F. Costa , Olaf Sporns

Learning and memory relies on synapses changing their strengths in response to neural activity. However there is a substantial gap between the timescales of neural electrical dynamics (1-100 ms) and organism behaviour during learning…

Neurons and Cognition · Quantitative Biology 2023-08-08 Cian O'Donnell

Loss of plasticity refers to the progressive inability of a model to adapt to new tasks and poses a fundamental challenge for continual learning. While this phenomenon has been extensively studied in homogeneous neural architectures, such…

Machine Learning · Computer Science 2026-03-10 Caihao Sun , Mingqi Yuan , Shiyuan Wang , Jiayu Chen

In order to keep trace of information and grow up, the infant brain has to resolve the problem about where old information is located and how to index new ones. We propose that the immature prefrontal cortex (PFC) use its primary…

Neural and Evolutionary Computing · Computer Science 2022-01-03 Alexandre Pitti , Mathias Quoy , Catherine Lavandier , Sofiane Boucenna , Wassim Swaileh , Claudio Weidmann
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