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One aim shared by multiple settings, such as continual learning or transfer learning, is to leverage previously acquired knowledge to converge faster on the current task. Usually this is done through fine-tuning, where an implicit…

Machine Learning · Computer Science 2023-10-17 Tudor Berariu , Wojciech Czarnecki , Soham De , Jorg Bornschein , Samuel Smith , Razvan Pascanu , Claudia Clopath

After injury, if regeneration can be observed in hydra, planaria and some vertebrates, regeneration is rare in mammals and particularly in humans. In this paper, we investigate the mechanisms by which biological tissues recover after…

Tissues and Organs · Quantitative Biology 2019-03-05 Diane Peurichard , Marielle Ousset , Jenny Paupert , Benjamin Aymard , Anne Lorsignol , Louis Casteilla , Pierre Degond

This paper tries to give a gentle introduction to deep learning in medical image processing, proceeding from theoretical foundations to applications. We first discuss general reasons for the popularity of deep learning, including several…

Computer Vision and Pattern Recognition · Computer Science 2018-12-24 Andreas Maier , Christopher Syben , Tobias Lasser , Christian Riess

The possibility of simulating in detail in-vivo experiments could be highly beneficial to the neuroscientific community. It could easily allow for preliminary testing of different experimental conditions without having to be constrained by…

Neurons and Cognition · Quantitative Biology 2020-04-10 Lorenzo Vannucci , Maria Pasquini , Cristina Spalletti , Matteo Caleo , Silvestro Micera , Cecilia Laschi , Egidio Falotico

Neurological injuries and age-related decline can impair sensory processing and disrupt motor coordination, gait, and balance. As mechanisms of neuroplasticity have become better understood, vibration-based interventions have gained…

Emerging Technologies · Computer Science 2025-12-10 Ava Hays , Nolan Kosnic , Ryan Miller , Kunal Siddhawar

Neural network training is usually accomplished by solving a non-convex optimization problem using stochastic gradient descent. Although one optimizes over the networks parameters, the main loss function generally only depends on the…

Machine Learning · Computer Science 2023-02-10 Julius Berner , Dennis Elbrächter , Philipp Grohs

The action potential is widely considered a purely electrical phenomenon. However, one also finds mechanical and thermal changes that can be observed experimentally. In particular, nerve membranes become thicker and axons contract. The…

Neurons and Cognition · Quantitative Biology 2025-09-29 T. Heimburg

High resolution optical microscopy is essential in neuroscience but suffers from scattering in biological tissues. It therefore grants access to superficial layers only. Recently developed techniques use scattered photons for imaging by…

Demyelinating disorders of the central nervous system may have multiple causes, the most common are infections, autoimmune responses, genetic or vascular etiology. Demyelination lesions are characterized by areas were the myelin sheath of…

Image and Video Processing · Electrical Eng. & Systems 2025-08-20 Maria Popa , Gabriela Adriana Visa

Multiple sclerosis lesion activity segmentation is the task of detecting new and enlarging lesions that appeared between a baseline and a follow-up brain MRI scan. While deep learning methods for single-scan lesion segmentation are common,…

Computer Vision and Pattern Recognition · Computer Science 2020-06-02 Nils Gessert , Marcel Bengs , Julia Krüger , Roland Opfer , Ann-Christin Ostwaldt , Praveena Manogaran , Sven Schippling , Alexander Schlaefer

Novel imaging and neurostimulation techniques open doors for advancements in closed-loop control of activity in biological neural networks. This would allow for applications in the investigation of activity propagation, and for diagnosis…

Neurons and Cognition · Quantitative Biology 2024-09-30 Laurens Engwegen , Daan Brinks , Wendelin Böhmer

We present a class of 2D systems which shows a counterintuitive property that contradicts a semi classical intuition: A 2D quantum particle "prefers" tunneling through a barrier rather than traveling above it. Viewing the one particle 2D…

Quantum Physics · Physics 2011-02-14 Denys I. Bondar , Wing-Ki Liu , Misha Yu. Ivanov

Self-avoidance is a common mechanism to improve the efficiency of a random walker for covering a spatial domain. However, how this efficiency decreases when self-avoidance is impaired or limited by other processes has remained largely…

Statistical Mechanics · Physics 2019-12-11 Daniel Campos , Javier Cristín , Vicenç Méndez

Quantum tunneling from a thin wire or a thin film through a static potential barrier in a zero magnetic field is studied. The wire or the film should satisfy a condition of transverse quantization of levels and be inhomogeneous. Depending…

Quantum Physics · Physics 2008-06-11 B. Ivlev

Unlike the brain, artificial neural networks, including state-of-the-art deep neural networks for computer vision, are subject to "catastrophic forgetting": they rapidly forget the previous task when trained on a new one. Neuroscience…

Neural and Evolutionary Computing · Computer Science 2021-06-09 Axel Laborieux , Maxence Ernoult , Tifenn Hirtzlin , Damien Querlioz

Regeneration of the nervous system after injury remains an important therapeutic objective, especially in the central nervous system (CNS), in which regeneration is restricted by both neuronal limitations as well as adverse extracellular…

Neurons and Cognition · Quantitative Biology 2026-05-05 Maryam Kheyrollah , Reza Khanbabaie , Chris Ullrich , Mohammad Moulaeifard

In previous works, the author and collaborators establish a mathematical model for injury response in articular cartilage. In this paper we use mathematical software and computational techniques, applied to an existing model to explore in…

Quantitative Methods · Quantitative Biology 2013-07-26 Jason M Graham

From mass extinction to cell death, complex networked systems often exhibit abrupt dynamic transitions between desirable and undesirable states. Such transitions are often caused by topological perturbations, such as node or link removal,…

Adaptation and Self-Organizing Systems · Physics 2022-07-22 Hillel Sanhedrai , Jianxi Gao , Amir Bashan , Moshe Schwartz , Shlomo Havlin , Baruch Barzel

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

Introduced is a methodology for adapting the topology of dense neural networks, enabled by isotropic activation functions. Achieved through prescribed reparameterisation symmetries and singular-value decomposition of affine maps, this…

Neural and Evolutionary Computing · Computer Science 2026-05-08 George Bird
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