AIMC Topic: Neurons

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Deep CovDenseSNN: A hierarchical event-driven dynamic framework with spiking neurons in noisy environment.

Neural networks : the official journal of the International Neural Network Society Sep 28, 2019
Neurons in the brain use an event signal, termed spike, encode temporal information for neural computation. Spiking neural networks (SNNs) take this advantage to serve as biological relevant models. However, the effective encoding of sensory informat...
Signal-To-Noise Ratio Brain Visual Perception Models, Neurological Neurons Humans Neural Networks, Computer
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Responses of midbrain auditory neurons to two different environmental sounds-A new approach on cross-sound modeling.

Bio Systems Sep 28, 2019
When modeling auditory responses to environmental sounds, results are satisfactory if both training and testing are restricted to datasets of one type of sound. To predict 'cross-sound' responses (i.e., to predict the response to one type of sound e....
Rats Rats, Sprague-Dawley Models, Biological Animals Systems Biology Evoked Potentials, Auditory, Brain Stem Inferior Colliculi Neurons Acoustic Stimulation Neural Networks, Computer
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A biologically plausible supervised learning method for spiking neural networks using the symmetric STDP rule.

Neural networks : the official journal of the International Neural Network Society Sep 27, 2019
Spiking neural networks (SNNs) possess energy-efficient potential due to event-based computation. However, supervised training of SNNs remains a challenge as spike activities are non-differentiable. Previous SNNs training methods can be generally cat...
Neurons Pattern Recognition, Automated Action Potentials Supervised Machine Learning Neural Networks, Computer Neuronal Plasticity Humans
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Design Space Exploration of Hardware Spiking Neurons for Embedded Artificial Intelligence.

Neural networks : the official journal of the International Neural Network Society Sep 26, 2019
Machine learning is yielding unprecedented interest in research and industry, due to recent success in many applied contexts such as image classification and object recognition. However, the deployment of these systems requires huge computing capabil...
Neurons Computer Systems Action Potentials Humans Machine Learning Neural Networks, Computer Computers Artificial Intelligence Brain
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Gated spiking neural network using Iterative Free-Energy Optimization and rank-order coding for structure learning in memory sequences (INFERNO GATE).

Neural networks : the official journal of the International Neural Network Society Sep 25, 2019
We present a framework based on iterative free-energy optimization with spiking neural networks for modeling the fronto-striatal system (PFC-BG) for the generation and recall of audio memory sequences. In line with neuroimaging studies carried out in...
Memory, Short-Term Neurons Reinforcement, Psychology Mental Recall Learning Prefrontal Cortex Action Potentials Humans Neural Networks, Computer
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Decoding and encoding (de)mixed population responses.

Current opinion in neurobiology Sep 25, 2019
A central tenet of neuroscience is that the brain works through large populations of interacting neurons. With recent advances in recording techniques, the inner working of these populations has come into full view. Analyzing the resulting large-scal...
Neural Networks, Computer Brain Animals Models, Neurological Neurons
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Event-driven implementation of deep spiking convolutional neural networks for supervised classification using the SpiNNaker neuromorphic platform.

Neural networks : the official journal of the International Neural Network Society Sep 24, 2019
Neural networks have enabled great advances in recent times due mainly to improved parallel computing capabilities in accordance to Moore's Law, which allowed reducing the time needed for the parameter learning of complex, multi-layered neural archit...
Algorithms Brain Supervised Machine Learning Neurons Action Potentials Humans Neural Networks, Computer Biomimetics Recognition, Psychology
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Using intersection information to map stimulus information transfer within neural networks.

Bio Systems Sep 21, 2019
Analytical tools that estimate the directed information flow between simultaneously recorded neural populations, such as directed information or Granger causality, typically focus on measuring how much information is exchanged between such population...
Algorithms Synaptic Transmission Animals Information Theory Action Potentials Neurons Nerve Net Models, Neurological Electric Stimulation Neural Networks, Computer
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Rethinking the performance comparison between SNNS and ANNS.

Neural networks : the official journal of the International Neural Network Society Sep 19, 2019
Artificial neural networks (ANNs), a popular path towards artificial intelligence, have experienced remarkable success via mature models, various benchmarks, open-source datasets, and powerful computing platforms. Spiking neural networks (SNNs), a ca...
Brain Action Potentials Algorithms Pattern Recognition, Automated Memory Neurons Humans Neural Networks, Computer Artificial Intelligence
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Mutual Inhibition with Few Inhibitory Cells via Nonlinear Inhibitory Synaptic Interaction.

Neural computation Sep 16, 2019
In computational neural network models, neurons are usually allowed to excite some and inhibit other neurons, depending on the weight of their synaptic connections. The traditional way to transform such networks into networks that obey Dale's law (i....
Humans Neurons Synapses Synaptic Transmission Animals Models, Neurological Neural Networks, Computer
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