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Eukaryotic cells are large enough to detect signals and then orient to them by differentiating the signal strength across the length and breadth of the cell. Amoebae, fibroblasts, neutrophils and growth cones all behave in this way. Little…

Cell Behavior · Quantitative Biology 2008-05-19 Liang Li , Simon F. Norrelykke , Edward C. Cox

The potential of memristive devices is often seeing in implementing neuromorphic architectures for achieving brain-like computation. However, the designing procedures do not allow for extended manipulation of the material, unlike CMOS…

Emerging Technologies · Computer Science 2016-04-25 Shari Lim Wei , Eleni Vasilaki , Ali Khiat , Iulia Salaoru , Radu Berdan , Themistoklis Prodromakis

Memristors are novel non volatile devices that manage to combine storing and processing capabilities in the same physical place.Their nanoscale dimensions and low power consumption enable the further design of various nanoelectronic…

Cellular automata have been useful artificial models for exploring how relatively simple rules combined with spatial memory can give rise to complex emergent patterns. Moreover, studying the dynamics of how rules emerge under artificial…

Cellular Automata and Lattice Gases · Physics 2014-07-11 Theodore P. Pavlic , Alyssa M. Adams , Paul C. W. Davies , Sara Imari Walker

P. polycephalum may be considered as a spatially represented parallel unconventional computing substrate, but how can this `computer' be programmed? In this paper we examine and catalogue individual low-level mechanisms which may be used to…

Emerging Technologies · Computer Science 2016-10-23 Jeff Jones

Memristors can mimic the functions of biological synapse, where it can simultaneously store the synaptic weight and modulate the transmitted signal. Here, we report Nb/Nb2O5/Pt based memristors with bipolar resistive switching, exhibiting…

Applied Physics · Physics 2019-10-02 Sweety Deswal , Ashok Kumar , Ajeet Kumar

The giant single-celled slime mould Physarum polycephalum exhibits complex morphological adaptation and amoeboid movement as it forages for food and may be seen as a minimal example of complex robotic behaviour. Swarm computation has…

Multiagent Systems · Computer Science 2012-12-04 Jeff Jones , Andrew Adamatzky

Multistability-induced hysteresis has been widely studied in mechanical systems, but such behavior has proven more difficult to reproduce experimentally in flow networks. Natural flow networks like animal and plant vasculature can exhibit…

Soft Condensed Matter · Physics 2025-12-03 Lauren E. Altman , Nadia Aguilar , Douglas J. Durian , Miguel Ruiz-Garcia , Eleni Katifori

Synthetic biology aims at designing modular genetic circuits that can be assembled according to the desired function. When embedded in a cell, a circuit module becomes a small subnetwork within a larger environmental network, and its…

Molecular Networks · Quantitative Biology 2019-01-14 Johannes Falk , Leo Bronstein , Maleen Hanst , Barbara Drossel , Heinz Koeppl

During the last years, a well studied biological substrate, namely Physarum polycephalum, has been proven efficient on finding appropriate and efficient solutions in hard to solve complex mathematical problems. The plasmodium of P.…

Slime mould Physarum polycephalum is large single cell with intriguingly smart behaviour. The slime mould shows outstanding abilities to adapt its protoplasmic network to varying environmental conditions. The slime mould can solve tasks of…

Emerging Technologies · Computer Science 2013-04-09 Andrew Adamatzky , Rachel Armstrong , Jeff Jones , Yukio-Pegio Gunji

Since its inception the memristive fuse has been a good example of how small numbers of memristors can be combined to obtain useful behaviours unachievable by individual devices. In this work, we link the memristive fuse concept with that…

Emerging Technologies · Computer Science 2016-09-09 Alexander Serb , Ali Khiat , Themistoklis Prodromakis

Human brain processes sensory information in real-time with extraordinary efficiency compared to the possibilities of current artificial computing systems. It operates as a complex nonlinear system, composed of interacting dynamic units -…

Emerging Technologies · Computer Science 2025-04-21 Manuel Escudero , Sabina Spiga , Stefano Brivio

The insect olfactory system, which includes the antennal lobe (AL), mushroom body (MB), and ancillary structures, is a relatively simple neural system capable of learning. Its structural features, which are widespread in biological neural…

Neurons and Cognition · Quantitative Biology 2018-02-09 Charles B. Delahunt , Jeffrey A. Riffell , J. Nathan Kutz

Biological and living systems process information across spatiotemporal scales, exhibiting the hallmark ability to constantly modulate their behavior to ever-changing and complex environments. In the presence of repeated stimuli, a…

Statistical Mechanics · Physics 2025-02-04 Giorgio Nicoletti , Matteo Bruzzone , Samir Suweis , Marco Dal Maschio , Daniel Maria Busiello

Time perception is essential for task switching, and in the mammalian brain appears alongside other processes. Memristors are electronic components used as synapses and as models for neurons. The d.c. response of memristors can be…

Robotics · Computer Science 2014-02-18 Ella Gale , Ben de Lacy Costello , Andrew Adamatzky

In systems of active programmable matter, individual modules require a constant supply of energy to participate in the system's collective behavior. These systems are often powered by an external energy source accessible by at least one…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-07-21 Joshua J. Daymude , Andréa W. Richa , Jamison W. Weber

We present a model for a random walk with memory, phenomenologically inspired in a biological system. The walker has the capacity to remember the time of the last visit to each site and the step taken from there. This memory affects the…

Adaptation and Self-Organizing Systems · Physics 2015-01-15 Laila D. Kazimierski , Guillermo Abramson , Marcelo N. Kuperman

A popular theory of perceptual processing holds that the brain learns both a generative model of the world and a paired recognition model using variational Bayesian inference. Most hypotheses of how the brain might learn these models assume…

Neurons and Cognition · Quantitative Biology 2021-06-01 Ari S. Benjamin , Konrad P. Kording

The plasmodium of slime mould Physarum polycephalum behaves as an amorphous reaction-diffusion computing substrate and is capable of apparently intelligent behaviour. But how does intelligence emerge in an acellular organism? Through a…

Emerging Technologies · Computer Science 2015-03-11 Richard Mayne , Andrew Adamatzky , Jeff Jones