AI Medical Compendium Topic

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Deep Learning for Robust Decomposition of High-Density Surface EMG Signals.

IEEE transactions on bio-medical engineering
Blind source separation (BSS) algorithms, such as gradient convolution kernel compensation (gCKC), can efficiently and accurately decompose high-density surface electromyography (HD-sEMG) signals into constituent motor unit (MU) action potential trai...

Empirically constrained network models for contrast-dependent modulation of gamma rhythm in V1.

NeuroImage
Gamma oscillations are thought to play a key role in neuronal network function and neuronal communication, yet the underlying generating mechanisms have not been fully elucidated to date. At least partly, this may be due to the fact that even in simp...

Statistical field theory of the transmission of nerve impulses.

Theoretical biology & medical modelling
BACKGROUND: Stochastic processes leading voltage-gated ion channel dynamics on the nerve cell membrane are a sufficient condition to describe membrane conductance through statistical mechanics of disordered and complex systems.

RippleNet: a Recurrent Neural Network for Sharp Wave Ripple (SPW-R) Detection.

Neuroinformatics
Hippocampal sharp wave ripples (SPW-R) have been identified as key bio-markers of important brain functions such as memory consolidation and decision making. Understanding their underlying mechanisms in healthy and pathological brain function and beh...

Constraints on Hebbian and STDP learned weights of a spiking neuron.

Neural networks : the official journal of the International Neural Network Society
We analyse mathematically the constraints on weights resulting from Hebbian and STDP learning rules applied to a spiking neuron with weight normalisation. In the case of pure Hebbian learning, we find that the normalised weights equal the promotion p...

Noise suppression ability and its mechanism analysis of scale-free spiking neural network under white Gaussian noise.

PloS one
With the continuous improvement of automation and informatization, the electromagnetic environment has become increasingly complex. Traditional protection methods for electronic systems are facing with serious challenges. Biological nervous system ha...

A simple Ca-imaging approach to neural network analyses in cultured neurons.

Journal of neuroscience methods
BACKGROUND: Ca-imaging is a powerful tool to measure neuronal dynamics and network activity. To monitor network-level changes in cultured neurons, neuronal activity is often evoked by electrical or optogenetic stimulation and assessed using multi-ele...

A generative spiking neural-network model of goal-directed behaviour and one-step planning.

PLoS computational biology
In mammals, goal-directed and planning processes support flexible behaviour used to face new situations that cannot be tackled through more efficient but rigid habitual behaviours. Within the Bayesian modelling approach of brain and behaviour, models...

A Novel Neural Model With Lateral Interaction for Learning Tasks.

Neural computation
We propose a novel neural model with lateral interaction for learning tasks. The model consists of two functional fields: an elementary field to extract features and a high-level field to store and recognize patterns. Each field is composed of some n...

Conductance-Based Adaptive Exponential Integrate-and-Fire Model.

Neural computation
The intrinsic electrophysiological properties of single neurons can be described by a broad spectrum of models, from realistic Hodgkin-Huxley-type models with numerous detailed mechanisms to the phenomenological models. The adaptive exponential integ...