AIMC Topic: Models, Neurological

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A patient-specific EMG-driven neuromuscular model for the potential use of human-inspired gait rehabilitation robots.

Computers in biology and medicine Jan 11, 2016
A patient-specific electromyography (EMG)-driven neuromuscular model (PENm) is developed for the potential use of human-inspired gait rehabilitation robots. The PENm is modified based on the current EMG-driven models by decreasing the calculation tim...
Humans Precision Medicine Female Robotics Electromyography Gait Rehabilitation Male Adolescent Models, Neurological
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FPGA-Based Stochastic Echo State Networks for Time-Series Forecasting.

Computational intelligence and neuroscience Dec 31, 2015
Hardware implementation of artificial neural networks (ANNs) allows exploiting the inherent parallelism of these systems. Nevertheless, they require a large amount of resources in terms of area and power dissipation. Recently, Reservoir Computing (RC...
Forecasting Computer Systems Time Factors Models, Neurological Neurons Nonlinear Dynamics Humans Neural Networks, Computer Algorithms Electronic Data Processing Stochastic Processes
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Using Self-Organizing Neural Network Map Combined with Ward's Clustering Algorithm for Visualization of Students' Cognitive Structural Models about Aliveness Concept.

Computational intelligence and neuroscience Dec 27, 2015
We propose an approach to clustering and visualization of students' cognitive structural models. We use the self-organizing map (SOM) combined with Ward's clustering to conduct cluster analysis. In the study carried out on 100 subjects, a conceptual ...
Concept Formation Self-Control Students Cognition Cluster Analysis Models, Neurological Neurons Comprehension Neural Networks, Computer Artificial Intelligence Humans Algorithms
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Multiclass Posterior Probability Twin SVM for Motor Imagery EEG Classification.

Computational intelligence and neuroscience Dec 22, 2015
Motor imagery electroencephalography is widely used in the brain-computer interface systems. Due to inherent characteristics of electroencephalography signals, accurate and real-time multiclass classification is always challenging. In order to solve ...
Electroencephalography Support Vector Machine Movement Humans Probability Models, Neurological Imagination Brain-Computer Interfaces Algorithms Models, Statistical Databases, Factual
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Effect of edge pruning on structural controllability and observability of complex networks.

Scientific reports Dec 17, 2015
Controllability and observability of complex systems are vital concepts in many fields of science. The network structure of the system plays a crucial role in determining its controllability and observability. Because most naturally occurring complex...
Animals Models, Neurological Neurons Nerve Net Neural Networks, Computer Algorithms Computer Simulation Humans
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Correlational Neural Networks.

Neural computation Dec 14, 2015
Common representation learning (CRL), wherein different descriptions (or views) of the data are embedded in a common subspace, has been receiving a lot of attention recently. Two popular paradigms here are canonical correlation analysis (CCA)-based a...
Statistics as Topic Learning Models, Neurological Pattern Recognition, Automated Humans Neural Networks, Computer
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Memory Stacking in Hierarchical Networks.

Neural computation Dec 14, 2015
Robust representations of sounds with a complex spectrotemporal structure are thought to emerge in hierarchically organized auditory cortex, but the computational advantage of this hierarchy remains unknown. Here, we used computational models to stud...
Humans Neural Networks, Computer Action Potentials Neurons Synapses Brain Computer Simulation Models, Neurological Memory Association Learning
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Mirrored STDP Implements Autoencoder Learning in a Network of Spiking Neurons.

PLoS computational biology Dec 3, 2015
The autoencoder algorithm is a simple but powerful unsupervised method for training neural networks. Autoencoder networks can learn sparse distributed codes similar to those seen in cortical sensory areas such as visual area V1, but they can also be ...
Biomimetics Learning Information Storage and Retrieval Neural Networks, Computer Neuronal Plasticity Nerve Net Action Potentials Machine Learning Humans Models, Neurological Signal Processing, Computer-Assisted Computer Simulation Neurons
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On the Universality and Non-Universality of Spiking Neural P Systems With Rules on Synapses.

IEEE transactions on nanobioscience Nov 25, 2015
Spiking neural P systems with rules on synapses are a new variant of spiking neural P systems. In the systems, the neuron contains only spikes, while the spiking/forgetting rules are moved on the synapses. It was obtained that such system with 30 neu...
Synapses Computers, Molecular Humans Neural Networks, Computer Models, Neurological Action Potentials
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Reduction of Trial-to-Trial Perceptual Variability by Intracortical Tonic Inhibition.

Neural computation Nov 24, 2015
Variability is a prominent characteristic of cognitive brain function. For instance, different trials of presentation of the same stimulus yield higher variability in its perception: subjects sometimes fail in perceiving the same stimulus. Perceptual...
Nerve Net Neural Inhibition Membrane Potentials Humans Neurons Cerebral Cortex gamma-Aminobutyric Acid Neural Networks, Computer Models, Neurological Dose-Response Relationship, Drug
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