AI Medical Compendium Topic

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Models, Neurological

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From spatial navigation via visual construction to episodic memory and imagination.

Biological cybernetics
This hybrid of review and personal essay argues that models of visual construction are essential to extend spatial navigation models to models that link episodic memory and imagination. The starting point is the TAM-WG model, combining the Taxon Affo...

Predicting motor outcome in preterm infants from very early brain diffusion MRI using a deep learning convolutional neural network (CNN) model.

NeuroImage
BACKGROUND AND AIMS: Preterm birth imposes a high risk for developing neuromotor delay. Earlier prediction of adverse outcome in preterm infants is crucial for referral to earlier intervention. This study aimed to predict abnormal motor outcome at 2 ...

A Novel Deep Neural Network for Robust Detection of Seizures Using EEG Signals.

Computational and mathematical methods in medicine
The detection of recorded epileptic seizure activity in electroencephalogram (EEG) segments is crucial for the classification of seizures. Manual recognition is a time-consuming and laborious process that places a heavy burden on neurologists, and he...

Automatic detection of cortical arousals in sleep and their contribution to daytime sleepiness.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: Significant interscorer variability is found in manual scoring of arousals in polysomnographic recordings (PSGs). We propose a fully automatic method, the Multimodal Arousal Detector (MAD), for detecting arousals.

Automata complete computation with Hodgkin-Huxley neural networks composed of synfire rings.

Neural networks : the official journal of the International Neural Network Society
Synfire rings are neural circuits capable of conveying synchronous, temporally precise and self-sustained activities in a robust manner. We propose a cell assembly based paradigm for abstract neural computation centered on the concept of synfire ring...

EO-MTRNN: evolutionary optimization of hyperparameters for a neuro-inspired computational model of spatiotemporal learning.

Biological cybernetics
For spatiotemporal learning with neural networks, hyperparameters are often set manually by a human expert. This is especially the case with multiple timescale networks that require a careful setting of the values of timescales in order to learn spat...

Simulating Small Neural Circuits with a Discrete Computational Model.

Biological cybernetics
Simulations of neural activity are commonly based on differential equations. We address the question what can be achieved with a simplified discrete model. The proposed model resembles artificial neural networks enriched with additional biologically ...

Nonlinear Spiking Neural P Systems.

International journal of neural systems
This paper proposes a new variant of spiking neural P systems (in short, SNP systems), nonlinear spiking neural P systems (in short, NSNP systems). In NSNP systems, the state of each neuron is denoted by a real number, and a real configuration vector...

Probabilistic inference of binary Markov random fields in spiking neural networks through mean-field approximation.

Neural networks : the official journal of the International Neural Network Society
Recent studies have suggested that the cognitive process of the human brain is realized as probabilistic inference and can be further modeled by probabilistic graphical models like Markov random fields. Nevertheless, it remains unclear how probabilis...

NeuroBayesSLAM: Neurobiologically inspired Bayesian integration of multisensory information for robot navigation.

Neural networks : the official journal of the International Neural Network Society
Spatial navigation depends on the combination of multiple sensory cues from idiothetic and allothetic sources. The computational mechanisms of mammalian brains in integrating different sensory modalities under uncertainty for navigation is enlighteni...