AIMC Topic: Models, Neurological

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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 Apr 16, 2018
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...
Photic Stimulation Adaptation, Physiological Grasshoppers Motion Perception Neurons Vision, Ocular Models, Neurological Action Potentials Neural Networks, Computer Animals
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Effect of dilution in asymmetric recurrent neural networks.

Neural networks : the official journal of the International Neural Network Society Apr 16, 2018
We study with numerical simulation the possible limit behaviors of synchronous discrete-time deterministic recurrent neural networks composed of N binary neurons as a function of a network's level of dilution and asymmetry. The network dilution measu...
Hippocampus Neocortex Humans Neural Networks, Computer Learning Models, Neurological Machine Learning
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A unified hierarchical oscillatory network model of head direction cells, spatially periodic cells, and place cells.

The European journal of neuroscience Apr 16, 2018
Spatial cells in the hippocampal complex play a pivotal role in the navigation of an animal. Exact neural principles behind these spatial cell responses have not been completely unraveled yet. Here we present two models for spatial cells, namely the ...
Models, Neurological Unsupervised Machine Learning Hippocampus Neural Networks, Computer Animals Spatial Navigation Grid Cells Place Cells Locomotion Nerve Net
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Inferring Clinical Correlations from EEG Reports with Deep Neural Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium Apr 16, 2018
Successful diagnosis and management of neurological dysfunction relies on proper communication between the neurologist and the primary physician (or other specialists). Because this communication is documented within medical records, the ability to a...
Models, Neurological Male Nervous System Diseases Humans Natural Language Processing Deep Learning Female Neurology Electroencephalography
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A Theory of Sequence Indexing and Working Memory in Recurrent Neural Networks.

Neural computation Apr 13, 2018
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...
Neural Networks, Computer Algorithms Computer Simulation Humans Neurons Models, Neurological Memory, Short-Term
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Bio-inspired spiking neural network for nonlinear systems control.

Neural networks : the official journal of the International Neural Network Society Apr 12, 2018
Spiking neural networks (SNN) are the third generation of artificial neural networks. SNN are the closest approximation to biological neural networks. SNNs make use of temporal spike trains to command inputs and outputs, allowing a faster and more co...
Neural Networks, Computer Machine Learning Models, Neurological Nonlinear Dynamics
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Runtime Programmable and Memory Bandwidth Optimized FPGA-Based Coprocessor for Deep Convolutional Neural Network.

IEEE transactions on neural networks and learning systems Apr 9, 2018
The deep convolutional neural network (DCNN) is a class of machine learning algorithms based on feed-forward artificial neural network and is widely used for image processing applications. Implementation of DCNN in real-world problems needs high comp...
Humans Software Memory Neural Networks, Computer Algorithms Models, Neurological Machine Learning Computer Simulation Signal Processing, Computer-Assisted
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Robust Regression Estimation Based on Low-Dimensional Recurrent Neural Networks.

IEEE transactions on neural networks and learning systems Apr 9, 2018
The robust Huber's M-estimator is widely used in signal and image processing, classification, and regression. From an optimization point of view, Huber's M-estimation problem is often formulated as a large-sized quadratic programming (QP) problem in ...
Regression Analysis Signal Processing, Computer-Assisted Algorithms Models, Neurological Humans Neural Networks, Computer
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Scale-freeness or partial synchronization in neural mass phase oscillator networks: Pick one of two?

NeuroImage Apr 4, 2018
Modeling and interpreting (partial) synchronous neural activity can be a challenge. We illustrate this by deriving the phase dynamics of two seminal neural mass models: the Wilson-Cowan firing rate model and the voltage-based Freeman model. We establ...
Brain Animals Models, Neurological Nerve Net Humans Models, Theoretical Neural Networks, Computer
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The role of phase shifts of sensory inputs in walking revealed by means of phase reduction.

Journal of computational neuroscience Mar 27, 2018
Detailed neural network models of animal locomotion are important means to understand the underlying mechanisms that control the coordinated movement of individual limbs. Daun-Gruhn and Tóth, Journal of Computational Neuroscience 31(2), 43-60 (2011) ...
Animals Central Pattern Generators Models, Neurological Psychomotor Performance Humans Neural Networks, Computer Locomotion Neural Pathways
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