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While resistors with memory, sometimes called memristive elements (such as ReRAM cells), are often studied under conditions of periodic driving, little attention has been paid to the Fourier features of their memory response (hysteresis).…

Applied Physics · Physics 2023-10-03 Y. V. Pershin , C. -C. Chien , M. Di Ventra

The cytoskeleton is an active composite of filamentous proteins that dictates diverse mechanical properties and processes in eukaryotic cells by generating forces and autonomously restructuring itself. Enzymatic motors that act on the…

Epigenetic cell memory, the inheritance of gene expression patterns across subsequent cell divisions, is a critical property of multi-cellular organisms. In recent work [10], a subset of the authors observed in a simulation study how the…

Probability · Mathematics 2024-05-17 Simone Bruno , Felipe A. Campos , Yi Fu , Domitilla Del Vecchio , Ruth J. Williams

Networks of filamentous proteins play a crucial role in cell mechanics. These cytoskeletal networks, together with various crosslinking and other associated proteins largely determine the (visco)elastic response of cells. In this letter we…

Disordered Systems and Neural Networks · Physics 2009-11-10 D. A. Head , A. J. Levine , F. C. MacKintosh

The task of the brain is to look for structure in the external input. We study a network of integrate-and-fire neurons with several types of recurrent connections that learns the structure of its time-varying feedforward input by attempting…

Neurons and Cognition · Quantitative Biology 2020-10-13 Lyudmila Kushnir , Sophie Denève

Network models are applied across many domains where data can be represented as a network. Two prominent paradigms for modeling networks are statistical models (probabilistic models for the observed network) and mechanistic models (models…

Methodology · Statistics 2019-06-20 Sixing Chen , Antonietta Mira , Jukka-Pekka Onnela

Deep neural networks have excelled on a wide range of problems, from vision to language and game playing. Neural networks very gradually incorporate information into weights as they process data, requiring very low learning rates. If the…

Atomically thin sheets, such as graphene, are widely used in nanotechnology. Recently they have also been used in applications including kirigami and self-folding origami, where it becomes important to understand how they respond to…

Statistical Mechanics · Physics 2022-09-21 Mohamed El Hedi Bahri , Siddhartha Sarkar , Andrej Košmrlj

Ferroelectric polarization switching, achieved by mechanical forces, enables the storage of stress information in ferroelectrics, and holds promise for human-interfacing applications. The prevailing mechanical approach is locally induced…

Understanding cellular response to mechanical forces is immensely important for a plethora of biological processes. Focal adhesions are multi-molecular protein assemblies that connect the cell to the extracellular matrix and play a pivotal…

Biological Physics · Physics 2019-10-25 Rumi De

The rheological properties of fibrin networks have been of long-standing interest. As such there is a wealth of studies of their shear and tensile responses, but their compressive behavior remains unexplored. Here, by characterization of…

Soft Condensed Matter · Physics 2015-08-27 O. V. Kim , Xiaojun Liang , Rustem I. Litvinov , John W. Weisel , Mark S. Alber , Prashant K. Purohit

We expose first a biological model of memory based on one hand of the mechanical oscillations of axons during action potential and on the other hand on the changes in the extra cellular matrix composition when a mechanical strain is applied…

Soft Condensed Matter · Physics 2008-09-24 N. Olivi-Tran , Sandra Kanani , Ian Robbins

Partial measurements of biochemical reaction networks are ubiquitous and limit our ability to reconstruct the topology of the reaction network and the strength of the interactions amongst both the observed and the unobserved molecular…

Biological Physics · Physics 2023-10-19 Moshir Harsh , Leonhard Götz Vulpius , Peter Sollich

Brain-inspired computing aims to mimic cognitive functions like associative memory, the ability to recall complete patterns from partial cues. Memristor technology offers promising hardware for such neuromorphic systems due to its potential…

Machine Learning · Computer Science 2025-05-20 Chengping He , Mingrui Jiang , Keyi Shan , Szu-Hao Yang , Zefan Li , Shengbo Wang , Giacomo Pedretti , Jim Ignowski , Can Li

Analytical and numerical calculations are presented for the mechanical response of fiber networks in a state of axisymmetric prestress, in the limit where geometric non-linearities such as fiber rotation are negligible. This allows us to…

Biological Physics · Physics 2014-02-27 D. A. Head , D. Mizuno

This manuscript presents a practical method for incorporating trained Neural Networks (NNs) into the Finite Element (FE) framework using a user material (UMAT) subroutine. The work exemplifies crystal plasticity, a complex inelastic…

Computational Physics · Physics 2024-10-14 Yuqing He , Yousef Heider , Bernd Markert

Networks of stiff fibers govern the elasticity of biological structures such as the extracellular matrix of collagen. These networks are known to stiffen nonlinearly under shear or extensional strain. Recently, it has been shown that such…

Soft Condensed Matter · Physics 2024-02-01 Sihan Chen , Tomer Markovich , Fred C. MacKintosh

Outer hair cells in the inner ear is important for the sensitivity, frequency selectivity, and dynamic range of the mammalian ear. Such a physiological role of outer hair cells is thought to be based an amplifying effect of those cells,…

Biological Physics · Physics 2020-02-04 Kuni H Iwasa

An In Silico model to relate the properties of proteins to the structure, sequence, function and evolutionary history of proteins is shown. The derived ideal sequences for amino acid residues in proteins can then be considered as attractors…

Condensed Matter · Physics 2007-05-23 S. Bumble

Stochastic network-dynamics are typically assumed to be memory-less. Involving prolonged dwells interrupted by instantaneous transitions between nodes such Markov networks stand as a coarse-graining paradigm for chemical reactions, gene…

Statistical Mechanics · Physics 2021-12-15 David Hartich , Aljaž Godec