AIMC Topic: Neuronal Plasticity

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Taming the chaos gently: a predictive alignment learning rule in recurrent neural networks.

Nature communications
Recurrent neural circuits often face inherent complexities in learning and generating their desired outputs, especially when they initially exhibit chaotic spontaneous activity. While the celebrated FORCE learning rule can train chaotic recurrent net...

The interplay between homeostatic synaptic scaling and homeostatic structural plasticity maintains the robust firing rate of neural networks.

eLife
Critical network states and neural plasticity enable adaptive behavior in dynamic environments, supporting efficient information processing and experience-dependent learning. Synaptic-weight-based Hebbian plasticity and homeostatic synaptic scaling a...

Stable recurrent dynamics in heterogeneous neuromorphic computing systems using excitatory and inhibitory plasticity.

Nature communications
Many neural computations emerge from self-sustained patterns of activity in recurrent neural circuits, which rely on balanced excitation and inhibition. Neuromorphic electronic circuits represent a promising approach for implementing the brain's comp...

Concept transfer of synaptic diversity from biological to artificial neural networks.

Nature communications
Recent developments in artificial neural networks have drawn inspiration from biological neural networks, leveraging the concept of the artificial neuron to model the learning abilities of biological nerve cells. However, while neuroscience has provi...

Parvalbumin neurons and cortical coding of dynamic stimuli: a network model.

Journal of neurophysiology
Cortical circuits feature both excitatory and inhibitory cells that underlie the encoding of dynamic sensory stimuli, e.g., speech, music, odors, and natural scenes. Although previous studies have shown that inhibition plays an important role in shap...

Effects of exoskeleton rehabilitation robot training on neuroplasticity and lower limb motor function in patients with stroke.

BMC neurology
BACKGROUND: Lower limb exoskeleton rehabilitation robot is a new technology to improve the lower limb motor function of stroke patients. Recovery of motor function after stroke is closely related to neuroplasticity in the motor cortex and associated ...

Supervised and unsupervised learning reveal heroin-induced impairments in astrocyte structural plasticity.

Science advances
Astrocytes regulate synaptic activity across large brain territories via their complex, interconnected morphology. Emerging evidence supports the involvement of astrocytes in shaping relapse to opioid use through morphological rearrangements in the n...

Enhanced Brain Functional Interaction Following BCI-Guided Supernumerary Robotic Finger Training Based on Sixth-Finger Motor Imagery.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Supernumerary robotic finger (SRF) has shown unique advantages in the field of motor augmentation and rehabilitation, while the development of brain computer interface (BCI) technology has provided the possibility for direct control of SRF. However, ...

Interictal network dysfunction and cognitive impairment in epilepsy.

Nature reviews. Neuroscience
Epilepsy is diagnosed when neural networks become capable of generating excessive or hypersynchronous activity patterns that result in observable seizures. In many cases, epilepsy is associated with cognitive comorbidities that persist between seizur...

Linking cellular-level phenomena to brain architecture: the case of spiking cerebellar controllers.

Neural networks : the official journal of the International Neural Network Society
Linking cellular-level phenomena to brain architecture and behavior is a holy grail for theoretical and computational neuroscience. Advances in neuroinformatics have recently allowed scientists to embed spiking neural networks of the cerebellum with ...