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Large-scale integration of emerging nanoscale non-volatile memory devices, e.g. resistive random-access memory (RRAM), can enable a new generation of neuromorphic computers that can solve a wide range of machine learning problems. Such…

Emerging Technologies · Computer Science 2016-12-20 Xinyu Wu , Vishal Saxena

We propose a neural information processing system which is obtained by re-purposing the function of a biological neural circuit model, to govern simulated and real-world control tasks. Inspired by the structure of the nervous system of the…

Machine Learning · Computer Science 2019-11-21 Ramin Hasani , Mathias Lechner , Alexander Amini , Daniela Rus , Radu Grosu

Human learning is a complex phenomenon requiring flexibility to adapt existing brain function and precision in selecting new neurophysiological activities to drive desired behavior. These two attributes -- flexibility and selection -- must…

Neurons and Cognition · Quantitative Biology 2013-06-28 Danielle S. Bassett , Nicholas F. Wymbs , Mason A. Porter , Peter J. Mucha , Jean M. Carlson , Scott T. Grafton

Animal behaviour depends on learning to associate sensory stimuli with the desired motor command. Understanding how the brain orchestrates the necessary synaptic modifications across different brain areas has remained a longstanding puzzle.…

Neurons and Cognition · Quantitative Biology 2018-01-03 João Sacramento , Rui Ponte Costa , Yoshua Bengio , Walter Senn

Artificial intelligence can outperform humans in specific tasks but consumes substantial energy. How the human brain can work at just 20 watts with complex cognitive intelligence? Here we decode the fundamental information strategy unit of…

Biological Physics · Physics 2025-08-06 Jinxuan Ma , Wanlin Guo

We present an account of neuroplasticity with respect to cell-internal processing pathways in relation to membrane and synaptic plasticity. We think traditional synapse-centric, weight-based models of memorization are not sufficient or…

Neurons and Cognition · Quantitative Biology 2026-04-27 Gabriele Scheler

Memory information in the brain is commonly believed to be stored in the synapse. However, a recent groundbreaking electrophysiology research has raised the possibility that memory information may actually be stored inside the neuron…

Neurons and Cognition · Quantitative Biology 2021-01-26 James Tee , Desmond P. Taylor

Cognitive processes in the brain, like learning, formation of memory, recovery of memorized images, classification of objects have two features: First, there is no supervisor in the brain who controls these processes. Second there is a hugh…

Neurons and Cognition · Quantitative Biology 2009-02-20 Helmut Kroger

Evolution and its intelligence element present thrill and challenges in its exploration. Yet, how species have memory, retrieve them and maintain continuity are the fundamental questions. Most of the phenomenon can only be hypothesised by…

Neurons and Cognition · Quantitative Biology 2024-07-09 Anil Kumar Sharma , Asha Sharma

Neurons are thought of as the building blocks of excitable brain tissue. However, at the single neuron level, the neuronal membrane, the dendritic arbor and the axonal projections can also be considered an extended active medium. Active…

Neurons and Cognition · Quantitative Biology 2013-11-28 Leonardo L. Gollo , Osame Kinouchi , Mauro Copelli

The brain as a neuronal system has very complex structure with large diversity of neuronal types. The most basic complexity is seen from the structure of neuronal morphology, which usually has a complex tree-like structure with dendritic…

Neurons and Cognition · Quantitative Biology 2019-05-08 Lingling An , Yuanhong Tang , Quan Wang , Qingqi Pei , Ran Wei , Huiyuan Duan , Jian K. Liu

Uniquely human abilities may arise from special-purpose brain circuitry, or from concerted general capacity increases due to our outsized brains. We forward a novel hypothesis of the relation between computational capacity and brain size,…

Neurons and Cognition · Quantitative Biology 2016-12-06 A Rodriguez , R Granger

Biological information processing manifests a huge variety in its complexity and capability among different organisms, which presumably stems from the evolutionary optimization under limited computational resources. Starting from the…

Biological Physics · Physics 2025-10-21 Takehiro Tottori , Tetsuya J. Kobayashi

In many normative theories of synaptic plasticity, weight updates implicitly depend on the chosen parametrization of the weights. This problem relates, for example, to neuronal morphology: synapses which are functionally equivalent in terms…

Neurons and Cognition · Quantitative Biology 2022-02-25 Elena Kreutzer , Walter M. Senn , Mihai A. Petrovici

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

We study a model of spiking neurons, with recurrent connections that result from learning a set of spatio-temporal patterns with a spike-timing dependent plasticity rule and a global inhibition. We investigate the ability of the network to…

Neurons and Cognition · Quantitative Biology 2020-04-22 S. Scarpetta , A. de Candia

Synaptic plasticity is the capacity of a preexisting connection between two neurons to change in strength as a function of neural activity. Because synaptic plasticity is the major candidate mechanism for learning and memory, the…

Neurons and Cognition · Quantitative Biology 2015-05-05 Maurizio De Pittà , Nicolas Brunel , Andrea Volterra

Sensory neurons give highly variable responses to stimulation, which can limit the amount of stimulus information available to downstream circuits. Much work has investigated the factors that affect the amount of information encoded in…

Neurons and Cognition · Quantitative Biology 2017-04-20 Joel Zylberberg , Alexandre Pouget , Peter E. Latham , Eric Shea-Brown

A hallmark of human intelligence is the ability to adapt to new situations, by applying learned rules to new content (systematicity) and thereby enabling an open-ended number of inferences and actions (generativity). Here, we propose that…

Neurons and Cognition · Quantitative Biology 2021-08-10 Randall C. O'Reilly , Charan Ranganath , Jacob L. Russin

Neuromorphic computing is a brainlike information processing paradigm that requires adaptive learning mechanisms. A spiking neuro-evolutionary system is used for this purpose; plastic resistive memories are implemented as synapses in…

Neural and Evolutionary Computing · Computer Science 2015-05-19 Gerard David Howard , Larry Bull , Ben de Lacy Costello , Andrew Adamatzky , Ella Gale