AIMC Topic: Models, Neurological

Clear Filters Showing 491 to 500 of 1163 articles

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

Neural networks : the official journal of the International Neural Network Society Mar 4, 2020
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...
Brain Models, Neurological Robotics Animals Spatial Navigation Bayes Theorem Cues
View on PubMed DOI

Constructing large-scale cortical brain networks from scalp EEG with Bayesian nonnegative matrix factorization.

Neural networks : the official journal of the International Neural Network Society Mar 3, 2020
A large-scale network provides a high hierarchical level for understanding the adaptive adjustment of the human brain during cognition processes. Since high spatial resolution is required, most of the related works are based on functional magnetic re...
Models, Neurological Bayes Theorem Cerebral Cortex Neural Pathways Electroencephalography Humans Neural Networks, Computer
View on PubMed DOI

Modeling of the neural mechanism underlying the terrestrial turning of the salamander.

Biological cybernetics Feb 27, 2020
In order to explore the neural mechanism underlying salamander terrestrial turning, an improved biomechanical model is proposed by modifying the forelimb structure of the existing biomechanical model. Based on the proposed improved biomechanical mode...
Locomotion Forelimb Territoriality Caudata Animals Models, Neurological Walking Neural Networks, Computer Biomechanical Phenomena
View on PubMed DOI

Supervised learning in spiking neural networks: A review of algorithms and evaluations.

Neural networks : the official journal of the International Neural Network Society Feb 25, 2020
As a new brain-inspired computational model of the artificial neural network, a spiking neural network encodes and processes neural information through precisely timed spike trains. Spiking neural networks are composed of biologically plausible spiki...
Supervised Machine Learning Humans Brain Models, Neurological Neural Networks, Computer
View on PubMed DOI

Real-time sensory-motor integration of hippocampal place cell replay and prefrontal sequence learning in simulated and physical rat robots for novel path optimization.

Biological cybernetics Feb 24, 2020
An open problem in the cognitive dimensions of navigation concerns how previous exploratory experience is reorganized in order to allow the creation of novel efficient navigation trajectories. This behavior is revealed in the "traveling salesrat prob...
Animals Rats Models, Neurological Computer Simulation Learning Hippocampus Spatial Navigation Place Cells Robotics Reward Algorithms Ventral Striatum
View on PubMed DOI

Pre-Synaptic Pool Modification (PSPM): A supervised learning procedure for recurrent spiking neural networks.

PloS one Feb 24, 2020
Learning synaptic weights of spiking neural network (SNN) models that can reproduce target spike trains from provided neural firing data is a central problem in computational neuroscience and spike-based computing. The discovery of the optimal weight...
Connectome Models, Neurological Nerve Net Presynaptic Terminals Action Potentials Computer Simulation Supervised Machine Learning Animals
View on PubMed DOI

Towards deep learning for connectome mapping: A block decomposition framework.

NeuroImage Feb 15, 2020
We propose a new framework to map structural connectomes using deep learning and diffusion MRI. We show that our framework not only enables connectome mapping with a convolutional neural network (CNN), but can also be straightforwardly incorporated i...
Humans Brain Connectome Diffusion Magnetic Resonance Imaging Deep Learning Models, Neurological
View on PubMed DOI

Coding with transient trajectories in recurrent neural networks.

PLoS computational biology Feb 13, 2020
Following a stimulus, the neural response typically strongly varies in time and across neurons before settling to a steady-state. While classical population coding theory disregards the temporal dimension, recent works have argued that trajectories o...
Computational Biology Models, Neurological Normal Distribution Synapses Linear Models Neurons Neural Networks, Computer Humans Software Computer Simulation
View on PubMed DOI

Identifying the pulsed neuron networks' structures by a nonlinear Granger causality method.

BMC neuroscience Feb 12, 2020
BACKGROUND: It is a crucial task of brain science researches to explore functional connective maps of Biological Neural Networks (BNN). The maps help to deeply study the dominant relationship between the structures of the BNNs and their network funct...
Neural Networks, Computer Algorithms Brain Humans Nonlinear Dynamics Multivariate Analysis Neural Pathways Brain Mapping Neurons Models, Neurological
View on PubMed DOI

Small-worldness favours network inference in synthetic neural networks.

Scientific reports Feb 10, 2020
A main goal in the analysis of a complex system is to infer its underlying network structure from time-series observations of its behaviour. The inference process is often done by using bi-variate similarity measures, such as the cross-correlation (C...
Synaptic Potentials Neurons Nerve Net Caenorhabditis elegans Animals Models, Neurological Neural Networks, Computer
View on PubMed DOI
Popular Topics
Recent Journals