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Brain decoding involves the determination of a subject's cognitive state or an associated stimulus from functional neuroimaging data measuring brain activity. In this setting the cognitive state is typically characterized by an element of a…

Machine Learning · Statistics 2015-04-14 Nicole Croteau , Farouk S. Nathoo , Jiguo Cao , Ryan Budney

The brain is a complex system comprising a myriad of interacting elements, posing significant challenges in understanding its structure, function, and dynamics. Network science has emerged as a powerful tool for studying such intricate…

The relationship between physiological systems and modern electromechanical technologies is fast becoming intimate with high degrees of complex interaction. It can be argued that muscular function, limb movements, and touch perception serve…

Human-Computer Interaction · Computer Science 2012-03-15 Bradly Alicea

In many adult tissues, stem cells and differentiated cells are not homogeneously distributed : stem cells are arranged in periodic "niches", and differentiated cells are constantly produced and migrate out of these niches. In this article,…

Biological Physics · Physics 2016-03-23 Edouard Hannezo , Alice Coucke , Jean-François Joanny

Degeneration and adaptation are two competing sides of the same coin called resilience in the progressive processes of brain aging or diseases. Degeneration accumulates during brain aging and other cerebral activities, causing structural…

As the world's first primary morbidity factor, depression has a considerable impact on both an individual as well as a societal level. despite their discovery several decades ago, classical antidepressants have been shown to provide limited…

Quantitative Methods · Quantitative Biology 2020-07-17 Camile Bahi

Neurofeedback is a form of brain training in which subjects are fed back information about some measure of their brain activity which they are instructed to modify in a way thought to be functionally advantageous. Over the last twenty…

Neurons and Cognition · Quantitative Biology 2018-05-15 David Papo

The brain has the phenomenal ability to reorganize itself by forming new connections among neurons and by pruning others. The so-called neural or brain plasticity facilitates the modification of brain structure and function over different…

Developing a macroscopic theory of elasto-plasticity in amorphous solids calls for (i) identifying the relevant macro state-variables and (ii) discriminating the different time-scales which characterize these variables. In current theories…

Statistical Mechanics · Physics 2009-11-25 Laurent Boue , Peter Harrowell , Smarajit Karmakar , Edan Lerner , Itamar Procaccia , Ido Regev , Jacques Zylberg

Psycholinguistics and neurolinguistics are two complementary disciplines that study language from different perspectives. Psycholinguistics focuses on the cognitive processes involved in language production and comprehension, while…

Neurons and Cognition · Quantitative Biology 2025-09-24 Charlotte Jacquemot , Marine Lunven

Plasticity refers to a network's ability to adapt to changing data distributions, which is crucial for the successful training of deep reinforcement learning agents. Loss of plasticity causes performance plateaus and contributes to scaling…

Artificial Intelligence · Computer Science 2026-04-21 Timo Klein , Christoph Luther , Manus McAuliffe , Lukas Miklautz , Claudia Plant , Sebastian Tschiatschek

Self-organized criticality has been proposed to be a universal mechanism for the emergence of scale-free dynamics in many complex systems, and possibly in the brain. While such scale-free patterns were identified experimentally in many…

Neurons and Cognition · Quantitative Biology 2021-05-11 Roxana Zeraati , Viola Priesemann , Anna Levina

Inner porous regions play a critical role in the load bearing capability of large bones.We show that an extension of disordered elastic networks [Chung et. al., Phys. Rev. B, {\bf 54}, 15094 (1996)] exhibits analogs of several known…

Deep continual learning requires models to adapt to new tasks without retraining from scratch. However, neural networks can lose their ability to adapt to new tasks after training on previous ones, a phenomenon known as loss of plasticity.…

Machine Learning · Computer Science 2026-05-12 Jiuqi Wang , Jayanth Srinivasa , Claire Chen , Shuze Daniel Liu , Ali Payani , Shangtong Zhang

Elastic effects in a model of disordered nematic elastomers are numerically investigated in two dimensions. Networks crosslinked in the isotropic phase exhibit unusual soft mechanical response against stretching. It arises from gradual…

Soft Condensed Matter · Physics 2009-10-31 Nariya Uchida

This paper addresses the question of the brain's critical dynamics after an injury such as a stroke. It is hypothesized that the healthy brain operates near a phase transition (critical point), which provides optimal conditions for…

Neurons and Cognition · Quantitative Biology 2023-08-01 Jakub Janarek , Zbigniew Drogosz , Jacek Grela , Jeremi K. Ochab , Paweł Oświęcimka

We report the first results of simulating the coupling of neuronal, astrocyte, and cerebrovascular activity. It is suggested that the dynamics of the system is different from systems that only include neurons. In the neuron-vascular…

Neural and Evolutionary Computing · Computer Science 2007-05-23 Xi Shen , Philippe De Wilde

Learning and decision making in the brain are key processes critical to survival, and yet are processes implemented by non-ideal biological building blocks which can impose significant error. We explore quantitatively how the brain might…

Neurons and Cognition · Quantitative Biology 2011-04-19 Jake Bouvrie , Jean-Jacques Slotine

Understanding of short-term synaptic depression (STSD) and other forms of synaptic plasticity is a topical problem in neuroscience. Here we study the role of STSD in the formation of complex patterns of brain rhythms. We use a cortical…

Disordered Systems and Neural Networks · Physics 2015-06-12 K. -E. Lee , A. V. Goltsev , M. A. Lopes , J. F. F. Mendes

Decoding neurons to extract information from transmission and employ them into other use is the goal of neuroscientists' study. Due to that the field of neuroscience is utilizing the traditional methods presently, we hence combine the…

Machine Learning · Computer Science 2020-06-30 Donghan Liu , Benjamin C. M. Fung , Tak Pan Wong