AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Neuronal Plasticity

Showing 141 to 150 of 235 articles

Clear Filters

A memristive plasticity model of voltage-based STDP suitable for recurrent bidirectional neural networks in the hippocampus.

Scientific reports
Memristive systems have gained considerable attention in the field of neuromorphic engineering, because they allow the emulation of synaptic functionality in solid state nano-physical systems. In this study, we show that memristive behavior provides ...

Attractor Dynamics in Networks with Learning Rules Inferred from In Vivo Data.

Neuron
The attractor neural network scenario is a popular scenario for memory storage in the association cortex, but there is still a large gap between models based on this scenario and experimental data. We study a recurrent network model in which both lea...

A Dynamic Connectome Supports the Emergence of Stable Computational Function of Neural Circuits through Reward-Based Learning.

eNeuro
Synaptic connections between neurons in the brain are dynamic because of continuously ongoing spine dynamics, axonal sprouting, and other processes. In fact, it was recently shown that the spontaneous synapse-autonomous component of spine dynamics is...

Unsupervised heart-rate estimation in wearables with Liquid states and a probabilistic readout.

Neural networks : the official journal of the International Neural Network Society
Heart-rate estimation is a fundamental feature of modern wearable devices. In this paper we propose a machine learning technique to estimate heart-rate from electrocardiogram (ECG) data collected using wearable devices. The novelty of our approach li...

A new approach to detect the coding rule of the cortical spiking model in the information transmission.

Neural networks : the official journal of the International Neural Network Society
Investigation of the role of the local field potential (LFP) fluctuations in encoding the received sensory information by the nervous system remains largely unknown. On the other hand, transmission of these translation rules in information transmissi...

STDP-based spiking deep convolutional neural networks for object recognition.

Neural networks : the official journal of the International Neural Network Society
Previous studies have shown that spike-timing-dependent plasticity (STDP) can be used in spiking neural networks (SNN) to extract visual features of low or intermediate complexity in an unsupervised manner. These studies, however, used relatively sha...

Cortical frequency-specific plasticity is independently induced by intracortical circuitry.

Neuroscience letters
Auditory learning induces frequency-specific plasticity in the auditory cortex. Both the auditory cortex and thalamus are involved in the cortical plasticity; however, the precise role of the intracortical circuity remains unclear until the contribut...

Memristive stochastic plasticity enables mimicking of neural synchrony: Memristive circuit emulates an optical illusion.

Science advances
The human brain is able to integrate a myriad of information in an enormous and massively parallel network of neurons that are divided into functionally specialized regions such as the visual cortex, auditory cortex, or dorsolateral prefrontal cortex...

Stochastic spike synchronization in a small-world neural network with spike-timing-dependent plasticity.

Neural networks : the official journal of the International Neural Network Society
We consider the Watts-Strogatz small-world network (SWN) consisting of subthreshold neurons which exhibit noise-induced spikings. This neuronal network has adaptive dynamic synaptic strengths governed by the spike-timing-dependent plasticity (STDP). ...

Flexible three-dimensional artificial synapse networks with correlated learning and trainable memory capability.

Nature communications
If a three-dimensional physical electronic system emulating synapse networks could be built, that would be a significant step toward neuromorphic computing. However, the fabrication complexity of complementary metal-oxide-semiconductor architectures ...