AIMC Topic: Models, Neurological

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Dynamic Spatiotemporal Pattern Recognition With Recurrent Spiking Neural Network.

Neural computation Oct 12, 2021
Our real-time actions in everyday life reflect a range of spatiotemporal dynamic brain activity patterns, the consequence of neuronal computation with spikes in the brain. Most existing models with spiking neurons aim at solving static pattern recogn...
Humans Models, Neurological Action Potentials Neurons Neural Networks, Computer Algorithms
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Neuromorphic learning with Mott insulator NiO.

Proceedings of the National Academy of Sciences of the United States of America Sep 28, 2021
Habituation and sensitization (nonassociative learning) are among the most fundamental forms of learning and memory behavior present in organisms that enable adaptation and learning in dynamic environments. Emulating such features of intelligence fou...
Aplysia Neuronal Plasticity Models, Neurological Synapses Insulator Elements Nickel Algorithms Neural Networks, Computer Electrons Animals Artificial Intelligence
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Hidden coexisting firings in fractional-order hyperchaotic memristor-coupled HR neural network with two heterogeneous neurons and its applications.

Chaos (Woodbury, N.Y.) Aug 1, 2021
The firing patterns of each bursting neuron are different because of the heterogeneity, which may be derived from the different parameters or external drives of the same kind of neurons, or even neurons with different functions. In this paper, the di...
Neural Networks, Computer Cluster Analysis Models, Neurological Neurons
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Phase-locking intermittency induced by dynamical heterogeneity in networks of thermosensitive neurons.

Chaos (Woodbury, N.Y.) Aug 1, 2021
In this work, we study the phase synchronization of a neural network and explore how the heterogeneity in the neurons' dynamics can lead their phases to intermittently phase-lock and unlock. The neurons are connected through chemical excitatory conne...
Neural Networks, Computer Models, Neurological Neurons
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A neuro-symbolic method for understanding free-text medical evidence.

Journal of the American Medical Informatics Association : JAMIA Jul 30, 2021
OBJECTIVE: We introduce Medical evidence Dependency (MD)-informed attention, a novel neuro-symbolic model for understanding free-text clinical trial publications with generalizability and interpretability.
Information Storage and Retrieval Clinical Trials as Topic Computer Simulation Models, Neurological Natural Language Processing Data Mining Software COVID-19 Humans Artificial Intelligence
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Training Spiking Neural Networks in the Strong Coupling Regime.

Neural computation Apr 13, 2021
Recurrent neural networks trained to perform complex tasks can provide insight into the dynamic mechanism that underlies computations performed by cortical circuits. However, due to a large number of unconstrained synaptic connections, the recurrent ...
Neural Networks, Computer Models, Neurological Synapses Learning
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Transition to synchronization in heterogeneous inhibitory neural networks with structured synapses.

Chaos (Woodbury, N.Y.) Mar 1, 2021
Inhibitory neurons form an extensive network involved in the development of different rhythms in the cerebral cortex. A transition from an incoherent state, where all inhibitory neurons fire unrelated to each other, to a synchronized or locked state,...
Neural Networks, Computer Nerve Net Neurons Synapses Models, Neurological Action Potentials
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An ecologically motivated image dataset for deep learning yields better models of human vision.

Proceedings of the National Academy of Sciences of the United States of America Feb 23, 2021
Deep neural networks provide the current best models of visual information processing in the primate brain. Drawing on work from computer vision, the most commonly used networks are pretrained on data from the ImageNet Large Scale Visual Recognition ...
Models, Neurological Brain Mapping Neural Networks, Computer Humans Deep Learning Pattern Recognition, Visual Ecology Visual Cortex Visual Perception
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Visualizing a joint future of neuroscience and neuromorphic engineering.

Neuron Feb 17, 2021
Recent research resolves the challenging problem of building biophysically plausible spiking neural models that are also capable of complex information processing. This advance creates new opportunities in neuroscience and neuromorphic engineering, w...
Neurons Forecasting Biomedical Engineering Humans Neurosciences Models, Neurological Neural Networks, Computer
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Early phonetic learning without phonetic categories: Insights from large-scale simulations on realistic input.

Proceedings of the National Academy of Sciences of the United States of America Feb 9, 2021
Before they even speak, infants become attuned to the sounds of the language(s) they hear, processing native phonetic contrasts more easily than nonnative ones. For example, between 6 to 8 mo and 10 to 12 mo, infants learning American English get bet...
Speech Perception Phonetics Language Development Natural Language Processing Speech Recognition Software Humans Models, Neurological
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