AIMC Topic: Neuronal Plasticity

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Ultralow Power Wearable Organic Ferroelectric Device for Optoelectronic Neuromorphic Computing.

Nano letters Jun 23, 2022
In order to imitate brain-inspired biological information processing systems, various neuromorphic computing devices have been proposed, most of which were prepared on rigid substrates and have energy consumption levels several orders of magnitude hi...
Synapses Wearable Electronic Devices Neuronal Plasticity Artificial Intelligence Brain
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Sequence learning, prediction, and replay in networks of spiking neurons.

PLoS computational biology Jun 21, 2022
Sequence learning, prediction and replay have been proposed to constitute the universal computations performed by the neocortex. The Hierarchical Temporal Memory (HTM) algorithm realizes these forms of computation. It learns sequences in an unsupervi...
Neural Networks, Computer Models, Neurological Neurons Synapses Learning Neuronal Plasticity
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Pruning recurrent neural networks replicates adolescent changes in working memory and reinforcement learning.

Proceedings of the National Academy of Sciences of the United States of America May 27, 2022
Adolescent development is characterized by an improvement in multiple cognitive processes. While performance on cognitive operations improves during this period, the ability to learn new skills quickly, for example, a new language, decreases. During ...
Reinforcement, Psychology Adolescent Development Memory, Short-Term Synapses Prefrontal Cortex Adolescent Neuronal Plasticity Models, Neurological Humans Neural Networks, Computer
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Multiwavelength Optoelectronic Synapse with 2D Materials for Mixed-Color Pattern Recognition.

ACS nano May 25, 2022
Neuromorphic visual systems emulating biological retina functionalities have enormous potential for in-sensor computing, with prospects of making artificial intelligence ubiquitous. Conventionally, visual information is captured by an image sensor, s...
Algorithms Neuronal Plasticity Neural Networks, Computer Artificial Intelligence Synapses
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Rectified Linear Postsynaptic Potential Function for Backpropagation in Deep Spiking Neural Networks.

IEEE transactions on neural networks and learning systems May 2, 2022
Spiking neural networks (SNNs) use spatiotemporal spike patterns to represent and transmit information, which are not only biologically realistic but also suitable for ultralow-power event-driven neuromorphic implementation. Just like other deep lear...
Neurons Synaptic Potentials Algorithms Neural Networks, Computer Neuronal Plasticity
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Stretchable Temperature-Responsive Multimodal Neuromorphic Electronic Skin with Spontaneous Synaptic Plasticity Recovery.

ACS nano Apr 22, 2022
Multimodal electronic skin devices capable of detecting multimodal signals provide the possibility for health monitoring. Sensing and memory for temperature and deformation by human skin are of great significance for the perception and monitoring of ...
Humans Temperature Transistors, Electronic Robotics Electronics Wearable Electronic Devices Neuronal Plasticity
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Introducing principles of synaptic integration in the optimization of deep neural networks.

Nature communications Apr 7, 2022
Plasticity circuits in the brain are known to be influenced by the distribution of the synaptic weights through the mechanisms of synaptic integration and local regulation of synaptic strength. However, the complex interplay of stimulation-dependent ...
Learning Neuronal Plasticity Neural Networks, Computer Algorithms Brain
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Intrinsic bursts facilitate learning of Lévy flight movements in recurrent neural network models.

Scientific reports Mar 23, 2022
Isolated spikes and bursts of spikes are thought to provide the two major modes of information coding by neurons. Bursts are known to be crucial for fundamental processes between neuron pairs, such as neuronal communications and synaptic plasticity. ...
Neurons Movement Models, Neurological Action Potentials Neural Networks, Computer Neuronal Plasticity Humans
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Organic electrochemical neurons and synapses with ion mediated spiking.

Nature communications Feb 22, 2022
Future brain-machine interfaces, prosthetics, and intelligent soft robotics will require integrating artificial neuromorphic devices with biological systems. Due to their poor biocompatibility, circuit complexity, low energy efficiency, and operating...
Robotics Brain-Computer Interfaces Synapses Neurons Neuronal Plasticity Silicon
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Plasmonic Optoelectronic Memristor Enabling Fully Light-Modulated Synaptic Plasticity for Neuromorphic Vision.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Dec 29, 2021
Exploration of optoelectronic memristors with the capability to combine sensing and processing functions is required to promote development of efficient neuromorphic vision. In this work, the authors develop a plasmonic optoelectronic memristor that ...
Optical Phenomena Metal Nanoparticles Surface Plasmon Resonance Neural Networks, Computer Titanium Optical Devices Neuronal Plasticity Silver Equipment Design
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