AIMC Topic: Synapses

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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 ...
Adolescent Development Synapses Reinforcement, Psychology Neuronal Plasticity Memory, Short-Term Models, Neurological Humans Adolescent Prefrontal Cortex 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...
Artificial Intelligence Neural Networks, Computer Neuronal Plasticity Algorithms Synapses
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Self-rectifying-based memristors for neuromorphic computing.

Science bulletin May 13, 2022
Synapses Neural Networks, Computer
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Neural sampling machine with stochastic synapse allows brain-like learning and inference.

Nature communications May 11, 2022
Many real-world mission-critical applications require continual online learning from noisy data and real-time decision making with a defined confidence level. Brain-inspired probabilistic models of neural network can explicitly handle the uncertainty...
Synapses Artificial Intelligence Neural Networks, Computer Bayes Theorem Brain
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Reconfigurable Artificial Synapses with Excitatory and Inhibitory Response Enabled by an Ambipolar Oxide Thin-Film Transistor.

ACS applied materials & interfaces May 6, 2022
A gate-tunable synaptic device controlling dynamically reconfigurable excitatory and inhibitory synaptic responses, which can emulate the fundamental synaptic responses for developing diverse functionalities of the biological nervous system, was deve...
Oxides Synapses Semiconductors Artificial Intelligence Reproducibility of Results
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Normalized unitary synaptic signaling of the hippocampus and entorhinal cortex predicted by deep learning of experimental recordings.

Communications biology May 5, 2022
Biologically realistic computer simulations of neuronal circuits require systematic data-driven modeling of neuron type-specific synaptic activity. However, limited experimental yield, heterogeneous recordings conditions, and ambiguous neuronal ident...
Neurons Synapses Deep Learning Entorhinal Cortex Hippocampus
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A Brain-Inspired Approach for Collision-Free Movement Planning in the Small Operational Space.

IEEE transactions on neural networks and learning systems May 2, 2022
In a small operational space, e.g., mesoscale or microscale, we need to control movements carefully because of fragile objects. This article proposes a novel structure based on spiking neural networks to imitate the joint function of multiple brain r...
Neural Networks, Computer Brain Synapses Movement Learning
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A Neuromorphic CMOS Circuit With Self-Repairing Capability.

IEEE transactions on neural networks and learning systems May 2, 2022
Neurophysiological observations confirm that the brain not only is able to detect the impaired synapses (in brain damage) but also it is relatively capable of repairing faulty synapses. It has been shown that retrograde signaling by astrocytes leads ...
Silicon Astrocytes Neural Networks, Computer Synapses Neurons
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Memristive Circuit Implementation of a Self-Repairing Network Based on Biological Astrocytes in Robot Application.

IEEE transactions on neural networks and learning systems May 2, 2022
A large number of studies have shown that astrocytes can be combined with the presynaptic terminals and postsynaptic spines of neurons to constitute a triple synapse via an endocannabinoid retrograde messenger to achieve a self-repair ability in the ...
Humans Neural Networks, Computer Astrocytes Synapses Robotics Reproducibility of Results
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Chalcogenide optomemristors for multi-factor neuromorphic computation.

Nature communications Apr 26, 2022
Neuromorphic hardware that emulates biological computations is a key driver of progress in AI. For example, memristive technologies, including chalcogenide-based in-memory computing concepts, have been employed to dramatically accelerate and increase...
Electronics Neural Networks, Computer Neurons Synapses Learning
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