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Neuronal Plasticity

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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 ...

Multi-layer network utilizing rewarded spike time dependent plasticity to learn a foraging task.

PLoS computational biology
Neural networks with a single plastic layer employing reward modulated spike time dependent plasticity (STDP) are capable of learning simple foraging tasks. Here we demonstrate advanced pattern discrimination and continuous learning in a network of s...

The Combined Effects of Adaptive Control and Virtual Reality on Robot-Assisted Fine Hand Motion Rehabilitation in Chronic Stroke Patients: A Case Study.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Robot-assisted therapy is regarded as an effective and reliable method for the delivery of highly repetitive training that is needed to trigger neuroplasticity following a stroke. However, the lack of fully adaptive assist-as-needed control of the ro...

Parsing learning in networks using brain-machine interfaces.

Current opinion in neurobiology
Brain-machine interfaces (BMIs) define new ways to interact with our environment and hold great promise for clinical therapies. Motor BMIs, for instance, re-route neural activity to control movements of a new effector and could restore movement to pe...

Hidden Markov modeling of frequency-following responses to Mandarin lexical tones.

Journal of neuroscience methods
BACKGROUND: The frequency-following response (FFR) is a scalp-recorded electrophysiological potential reflecting phase-locked activity from neural ensembles in the auditory system. The FFR is often used to assess the robustness of subcortical pitch p...

Robot-Applied Resistance Augments the Effects of Body Weight-Supported Treadmill Training on Stepping and Synaptic Plasticity in a Rodent Model of Spinal Cord Injury.

Neurorehabilitation and neural repair
BACKGROUND: The application of resistive forces has been used during body weight-supported treadmill training (BWSTT) to improve walking function after spinal cord injury (SCI). Whether this form of training actually augments the effects of BWSTT is ...

Memristive neural network for on-line learning and tracking with brain-inspired spike timing dependent plasticity.

Scientific reports
Brain-inspired computation can revolutionize information technology by introducing machines capable of recognizing patterns (images, speech, video) and interacting with the external world in a cognitive, humanlike way. Achieving this goal requires fi...

Familiarity Detection is an Intrinsic Property of Cortical Microcircuits with Bidirectional Synaptic Plasticity.

eNeuro
Humans instantly recognize a previously seen face as "familiar." To deepen our understanding of familiarity-novelty detection, we simulated biologically plausible neural network models of generic cortical microcircuits consisting of spiking neurons w...

Biologically plausible learning in neural networks with modulatory feedback.

Neural networks : the official journal of the International Neural Network Society
Although Hebbian learning has long been a key component in understanding neural plasticity, it has not yet been successful in modeling modulatory feedback connections, which make up a significant portion of connections in the brain. We develop a new ...