AIMC Topic: Models, Neurological

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Efficient learning with augmented spikes: A case study with image classification.

Neural networks : the official journal of the International Neural Network Society May 12, 2021
Efficient learning of spikes plays a valuable role in training spiking neural networks (SNNs) to have desired responses to input stimuli. However, current learning rules are limited to a binary form of spikes. The seemingly ubiquitous phenomenon of b...
Action Potentials Neurons Neural Networks, Computer Learning Models, Neurological
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Computational models link cellular mechanisms of neuromodulation to large-scale neural dynamics.

Nature neuroscience May 6, 2021
Decades of neurobiological research have disclosed the diverse manners in which the response properties of neurons are dynamically modulated to support adaptive cognitive functions. This neuromodulation is achieved through alterations in the biophysi...
Humans Neural Networks, Computer Models, Neurological Neurons Nerve Net Brain Animals Arousal
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Artificial Evolution Network: A Computational Perspective on the Expansibility of the Nervous System.

IEEE transactions on neural networks and learning systems May 3, 2021
Neurobiologists recently found the brain can use sudden emerged channels to process information. Based on this finding, we put forward a question whether we can build a computation model that is able to integrate a sudden emerged new type of perceptu...
Nervous System Physiological Phenomena Mental Processes Unsupervised Machine Learning Online Systems Algorithms Computer Simulation Rats Models, Neurological Animals Neural Networks, Computer Artificial Intelligence Humans
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Qualitative Analysis and Bifurcation in a Neuron System With Memristor Characteristics and Time Delay.

IEEE transactions on neural networks and learning systems May 3, 2021
This article focuses on the hybrid effects of memristor characteristics, time delay, and biochemical parameters on neural networks. First, we propose a novel neuron system with memristor and time delays in which the memristor is characterized by a sm...
Computer Simulation Models, Neurological Neural Networks, Computer Neurons Algorithms
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A minimal model of the interaction of social and individual learning.

Journal of theoretical biology Apr 30, 2021
Learning is thought to be achieved by the selective, activity dependent, adjustment of synaptic connections. Individual learning can also be very hard and/or slow. Social, supervised, learning from others might amplify individual, possibly mainly uns...
Models, Neurological Humans Neural Networks, Computer
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Volume of β-Bursts, But Not Their Rate, Predicts Successful Response Inhibition.

The Journal of neuroscience : the official journal of the Society for Neuroscience Apr 29, 2021
In humans, impaired response inhibition is characteristic of a wide range of psychiatric diseases and of normal aging. It is hypothesized that the right inferior frontal cortex (rIFC) plays a key role by inhibiting the motor cortex via the basal gang...
Beta Rhythm Machine Learning Models, Neurological Brain Humans Inhibition, Psychological Female Male
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Leveraging deep learning to control neural oscillators.

Biological cybernetics Apr 28, 2021
Modulation of the firing times of neural oscillators has long been an important control objective, with applications including Parkinson's disease, Tourette's syndrome, epilepsy, and learning. One common goal for such modulation is desynchronization,...
Humans Models, Neurological Neural Networks, Computer Deep Learning Parkinson Disease Neurons
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ELVISort: encoding latent variables for instant sorting, an artificial intelligence-based end-to-end solution.

Journal of neural engineering Apr 26, 2021
The growing number of recording sites of silicon-based probes means that an increasing amount of neural cell activities can be recorded simultaneously, facilitating the investigation of underlying complex neural dynamics. In order to overcome the cha...
Signal Processing, Computer-Assisted Models, Neurological Action Potentials Artificial Intelligence Algorithms
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Collective and synchronous dynamics of photonic spiking neurons.

Nature communications Apr 23, 2021
Nonlinear dynamics of spiking neural networks have recently attracted much interest as an approach to understand possible information processing in the brain and apply it to artificial intelligence. Since information can be processed by collective sp...
Animals Models, Neurological Action Potentials Neurons Algorithms Computer Simulation Humans Nonlinear Dynamics Neural Networks, Computer Photons
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Predictive Visual Motion Extrapolation Emerges Spontaneously and without Supervision at Each Layer of a Hierarchical Neural Network with Spike-Timing-Dependent Plasticity.

The Journal of neuroscience : the official journal of the Society for Neuroscience Apr 22, 2021
The fact that the transmission and processing of visual information in the brain takes time presents a problem for the accurate real-time localization of a moving object. One way this problem might be solved is extrapolation: using an object's past t...
Brain Humans Neuronal Plasticity Models, Neurological Neurons Neural Networks, Computer Motion Perception
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