AIMC Topic: Neuronal Plasticity

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Intrinsic Plasticity-Based Neuroadptive Control With Both Weights and Excitability Tuning.

IEEE transactions on neural networks and learning systems Jul 6, 2021
This brief presents an intrinsic plasticity (IP)-driven neural-network-based tracking control approach for a class of nonlinear uncertain systems. Inspired by the neural plasticity mechanism of individual neuron in nervous systems, a learning rule re...
Humans Neural Networks, Computer Feedback Neuronal Plasticity Nonlinear Dynamics Algorithms Computer Simulation Machine Learning
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Biological constraints on neural network models of cognitive function.

Nature reviews. Neuroscience Jun 28, 2021
Neural network models are potential tools for improving our understanding of complex brain functions. To address this goal, these models need to be neurobiologically realistic. However, although neural networks have advanced dramatically in recent ye...
Neuronal Plasticity Models, Neurological Neurons Brain Cognition Humans Neural Networks, Computer
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From synapse to network: models of information storage and retrieval in neural circuits.

Current opinion in neurobiology Jun 24, 2021
The mechanisms of information storage and retrieval in brain circuits are still the subject of debate. It is widely believed that information is stored at least in part through changes in synaptic connectivity in networks that encode this information...
Synapses Information Storage and Retrieval Nerve Net Neuronal Plasticity Models, Neurological Neural Networks, Computer
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Multimodal Tuning of Synaptic Plasticity Using Persistent Luminescent Memitters.

Advanced materials (Deerfield Beach, Fla.) Jun 19, 2021
Mimicking memory processes, including encoding, storing, and retrieving information, is critical for neuromorphic computing and artificial intelligence. Synaptic behavior simulations through electronic, magnetic, or photonic devices based on metal ox...
Oxides Luminescence Synapses Artificial Intelligence Neuronal Plasticity
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Computing Primitive of Fully VCSEL-Based All-Optical Spiking Neural Network for Supervised Learning and Pattern Classification.

IEEE transactions on neural networks and learning systems Jun 2, 2021
We propose computing primitive for an all-optical spiking neural network (SNN) based on vertical-cavity surface-emitting lasers (VCSELs) for supervised learning by using biologically plausible mechanisms. The spike-timing-dependent plasticity (STDP) ...
Pattern Recognition, Automated Synapses Lasers Neural Networks, Computer Algorithms Computer Systems Neuronal Plasticity Supervised Machine Learning
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Spine dynamics in the brain, mental disorders and artificial neural networks.

Nature reviews. Neuroscience May 28, 2021
In the brain, most synapses are formed on minute protrusions known as dendritic spines. Unlike their artificial intelligence counterparts, spines are not merely tuneable memory elements: they also embody algorithms that implement the brain's ability ...
Machine Learning Algorithms Receptors, Dopamine Brain Animals Dopamine Mental Disorders Dendritic Spines Humans Mental Processes Species Specificity Memory, Short-Term Neurotransmitter Agents Neural Networks, Computer Optogenetics Neuronal Plasticity Reward Artificial Intelligence Synapses Models, Neurological
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Burst-dependent synaptic plasticity can coordinate learning in hierarchical circuits.

Nature neuroscience May 13, 2021
Synaptic plasticity is believed to be a key physiological mechanism for learning. It is well established that it depends on pre- and postsynaptic activity. However, models that rely solely on pre- and postsynaptic activity for synaptic changes have, ...
Neuronal Plasticity Models, Neurological Pyramidal Cells Learning Animals Deep Learning Humans
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Predictive Visual Motion Extrapolation Emerges Spontaneously and without Supervision at Each Layer of a Hierarchical Neural Network with Spike-Timing-Dependent Plasticity.

The Journal of neuroscience : the official journal of the Society for Neuroscience Apr 22, 2021
The fact that the transmission and processing of visual information in the brain takes time presents a problem for the accurate real-time localization of a moving object. One way this problem might be solved is extrapolation: using an object's past t...
Motion Perception Humans Models, Neurological Brain Neuronal Plasticity Neurons Neural Networks, Computer
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On Robot Compliance: A Cerebellar Control Approach.

IEEE transactions on cybernetics Apr 15, 2021
The work presented here is a novel biological approach for the compliant control of a robotic arm in real time (RT). We integrate a spiking cerebellar network at the core of a feedback control loop performing torque-driven control. The spiking cerebe...
Humans Neuronal Plasticity Movement Robotics Upper Extremity Cerebellum Brain-Computer Interfaces Models, Neurological Action Potentials
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Spatial Memory in a Spiking Neural Network with Robot Embodiment.

Sensors (Basel, Switzerland) Apr 10, 2021
Cognitive maps and spatial memory are fundamental paradigms of brain functioning. Here, we present a spiking neural network (SNN) capable of generating an internal representation of the external environment and implementing spatial memory. The SNN in...
Spatial Memory Neuronal Plasticity Neural Networks, Computer Animals Models, Neurological Robotics
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