Toward a formal theory for computing machines made out of whatever physics offers

H Jaeger, B Noheda, WG Van Der Wiel - Nature communications, 2023 - nature.com
Approaching limitations of digital computing technologies have spurred research in
neuromorphic and other unconventional approaches to computing. Here we argue that if we …

A review of learning in biologically plausible spiking neural networks

A Taherkhani, A Belatreche, Y Li, G Cosma… - Neural Networks, 2020 - Elsevier
Artificial neural networks have been used as a powerful processing tool in various areas
such as pattern recognition, control, robotics, and bioinformatics. Their wide applicability has …

On the nature and use of models in network neuroscience

DS Bassett, P Zurn, JI Gold - Nature Reviews Neuroscience, 2018 - nature.com
Network theory provides an intuitively appealing framework for studying relationships
among interconnected brain mechanisms and their relevance to behaviour. As the space of …

Training deep neural density estimators to identify mechanistic models of neural dynamics

PJ Gonçalves, JM Lueckmann, M Deistler… - elife, 2020 - elifesciences.org
Mechanistic modeling in neuroscience aims to explain observed phenomena in terms of
underlying causes. However, determining which model parameters agree with complex and …

Predictive coding and stochastic resonance as fundamental principles of auditory phantom perception

A Schilling, W Sedley, R Gerum, C Metzner, K Tziridis… - Brain, 2023 - academic.oup.com
Mechanistic insight is achieved only when experiments are employed to test formal or
computational models. Furthermore, in analogy to lesion studies, phantom perception may …

All-in-one metal-oxide heterojunction artificial synapses for visual sensory and neuromorphic computing systems

Q Liu, L Yin, C Zhao, Z Wu, J Wang, X Yu, Z Wang… - Nano Energy, 2022 - Elsevier
An all-in-one artificial synapse integrating central nervous and sensory nervous functions
utilizing low-dimensional metal-oxide heterojunction is demonstrated in this work. With an …

Test-retest reliabilities of resting-state FMRI measurements in human brain functional connectomics: a systems neuroscience perspective

XN Zuo, XX **_learning_and_understanding_of_spatio-temporal_brain_data/links/5fc2dc21299bf104cf8f92da/NeuCube-A-spiking-neural-network-architecture-for-map**-learning-and-understanding-of-spatio-temporal-brain-data.pdf" data-clk="hl=ro&sa=T&oi=gga&ct=gga&cd=7&d=2440250691497359706&ei=Gq_HZ4WYNIC96rQPkZbxiA0" data-clk-atid="WvmZLROD3SEJ" target="_blank">[PDF] researchgate.net

NeuCube: A spiking neural network architecture for map**, learning and understanding of spatio-temporal brain data

NK Kasabov - Neural networks, 2014 - Elsevier
The brain functions as a spatio-temporal information processing machine. Spatio-and
spectro-temporal brain data (STBD) are the most commonly collected data for measuring …

[CARTE][B] Hardwiring happiness: The new brain science of contentment, calm, and confidence

R Hanson - 2013 - books.google.com
With New York Times bestselling author, Dr. Hanson's four steps, you can counterbalance
your brain's negativity bias and learn to hardwire happiness in only a few minutes each day …

A ferrite synaptic transistor with topotactic transformation

C Ge, C Liu, Q Zhou, Q Zhang, J Du, J Li… - Advanced …, 2019 - Wiley Online Library
Hardware implementation of artificial synaptic devices that emulate the functions of
biological synapses is inspired by the biological neuromorphic system and has drawn …