AI Medical Compendium Topic:
Models, Neurological

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EARSHOT: A Minimal Neural Network Model of Incremental Human Speech Recognition.

Cognitive science
Despite the lack of invariance problem (the many-to-many mapping between acoustics and percepts), human listeners experience phonetic constancy and typically perceive what a speaker intends. Most models of human speech recognition (HSR) have side-ste...

STDP Forms Associations between Memory Traces in Networks of Spiking Neurons.

Cerebral cortex (New York, N.Y. : 1991)
Memory traces and associations between them are fundamental for cognitive brain function. Neuron recordings suggest that distributed assemblies of neurons in the brain serve as memory traces for spatial information, real-world items, and concepts. Ho...

Dynamic behaviors of hyperbolic-type memristor-based Hopfield neural network considering synaptic crosstalk.

Chaos (Woodbury, N.Y.)
Crosstalk phenomena taking place between synapses can influence signal transmission and, in some cases, brain functions. It is thus important to discover the dynamic behaviors of the neural network infected by synaptic crosstalk. To achieve this, in ...

Deep learning for clustering of multivariate clinical patient trajectories with missing values.

GigaScience
BACKGROUND: Precision medicine requires a stratification of patients by disease presentation that is sufficiently informative to allow for selecting treatments on a per-patient basis. For many diseases, such as neurological disorders, this stratifica...

Characterization of SSMVEP-based EEG signals using multiplex limited penetrable horizontal visibility graph.

Chaos (Woodbury, N.Y.)
The steady state motion visual evoked potential (SSMVEP)-based brain computer interface (BCI), which incorporates the motion perception capabilities of the human visual system to alleviate the negative effects caused by strong visual stimulation from...

[Artificial Intelligence and Cerebellar Motor Learning].

Brain and nerve = Shinkei kenkyu no shinpo
Half a century ago, cerebellar learning models based on a simple perceptron were proposed independently by Marr and Albus. Soon, these models were combined with Ito's flocculus hypothesis that the cerebellar flocculus controls the vestibulo-ocular re...

Neural population control via deep image synthesis.

Science (New York, N.Y.)
Particular deep artificial neural networks (ANNs) are today's most accurate models of the primate brain's ventral visual stream. Using an ANN-driven image synthesis method, we found that luminous power patterns (i.e., images) can be applied to primat...

Optimizing Machine Learning Methods to Improve Predictive Models of Alzheimer's Disease.

Journal of Alzheimer's disease : JAD
BACKGROUND: Predicting clinical course of cognitive decline can boost clinical trials' power and improve our clinical decision-making. Machine learning (ML) algorithms are specifically designed for the purpose of prediction; however. identifying opti...