AI Medical Compendium Topic:
Neurons

Clear Filters Showing 881 to 890 of 1328 articles

Shaping the collision selectivity in a looming sensitive neuron model with parallel ON and OFF pathways and spike frequency adaptation.

Neural networks : the official journal of the International Neural Network Society
Shaping the collision selectivity in vision-based artificial collision-detecting systems is still an open challenge. This paper presents a novel neuron model of a locust looming detector, i.e. the lobula giant movement detector (LGMD1), in order to p...

A Theory of Sequence Indexing and Working Memory in Recurrent Neural Networks.

Neural computation
To accommodate structured approaches of neural computation, we propose a class of recurrent neural networks for indexing and storing sequences of symbols or analog data vectors. These networks with randomized input weights and orthogonal recurrent we...

Deep learning for healthcare applications based on physiological signals: A review.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: We have cast the net into the ocean of knowledge to retrieve the latest scientific research on deep learning methods for physiological signals. We found 53 research papers on this topic, published from 01.01.2008 to 31.12.20...

Computational Approach to Investigating Key GO Terms and KEGG Pathways Associated with CNV.

BioMed research international
Choroidal neovascularization (CNV) is a severe eye disease that leads to blindness, especially in the elderly population. Various endogenous and exogenous regulatory factors promote its pathogenesis. However, the detailed molecular biological mechani...

Spiking neural networks for handwritten digit recognition-Supervised learning and network optimization.

Neural networks : the official journal of the International Neural Network Society
We demonstrate supervised learning in Spiking Neural Networks (SNNs) for the problem of handwritten digit recognition using the spike triggered Normalized Approximate Descent (NormAD) algorithm. Our network that employs neurons operating at sparse bi...

Simplified and Yet Turing Universal Spiking Neural P Systems with Communication on Request.

International journal of neural systems
Spiking neural P systems are a class of third generation neural networks belonging to the framework of membrane computing. Spiking neural P systems with communication on request (SNQ P systems) are a type of spiking neural P system where the spikes a...

Modeling cognitive deficits following neurodegenerative diseases and traumatic brain injuries with deep convolutional neural networks.

Brain and cognition
The accurate diagnosis and assessment of neurodegenerative disease and traumatic brain injuries (TBI) remain open challenges. Both cause cognitive and functional deficits due to focal axonal swellings (FAS), but it is difficult to deliver a prognosis...

Ongoing brain rhythms shape I-wave properties in a computational model.

Brain stimulation
BACKGROUND: Responses to transcranial magnetic stimulation (TMS) are notoriously variable. Previous studies have observed a dependence of TMS-induced responses on ongoing brain activity, for instance sensorimotor rhythms. This suggests an opportunity...

Resonance with subthreshold oscillatory drive organizes activity and optimizes learning in neural networks.

Proceedings of the National Academy of Sciences of the United States of America
Network oscillations across and within brain areas are critical for learning and performance of memory tasks. While a large amount of work has focused on the generation of neural oscillations, their effect on neuronal populations' spiking activity an...

Design and validation of an ontology-driven animal-free testing strategy for developmental neurotoxicity testing.

Toxicology and applied pharmacology
Developmental neurotoxicity entails one of the most complex areas in toxicology. Animal studies provide only limited information as to human relevance. A multitude of alternative models have been developed over the years, providing insights into mech...