AIMC Topic: Models, Neurological

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Comparison of Regression Methods to Predict the First Spike Latency in Response to an External Stimulus in Intracellular Recordings for Cerebellar Cells.

Studies in health technology and informatics Aug 22, 2024
The significance of intracellular recording in neurophysiology is emphasized in this article, with considering the functions of neurons, particularly the role of first spike latency in response to external stimuli. The study employs advanced machine ...
Action Potentials Regression Analysis Neurons Animals Models, Neurological Machine Learning Cerebellum
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Self-organization toward 1/f noise in deep neural networks.

Chaos (Woodbury, N.Y.) Aug 1, 2024
In biological neural networks, it has been well recognized that a healthy brain exhibits 1/f noise patterns. However, in artificial neural networks that are increasingly matching or even out-performing human cognition, this phenomenon has yet to be e...
Neural Networks, Computer Humans Models, Neurological Neurons
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Learning Fixed Points of Recurrent Neural Networks by Reparameterizing the Network Model.

Neural computation Jul 19, 2024
In computational neuroscience, recurrent neural networks are widely used to model neural activity and learning. In many studies, fixed points of recurrent neural networks are used to model neural responses to static or slowly changing stimuli, such a...
Machine Learning Algorithms Brain Humans Neural Networks, Computer Learning Models, Neurological
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Internal world models in humans, animals, and AI.

Neuron Jul 17, 2024
How do brains-biological or artificial-respond and adapt to an ever-changing environment? In a recent meeting, experts from various fields of neuroscience and artificial intelligence met to discuss internal world models in brains and machines, arguin...
Brain Animals Neurosciences Models, Neurological Humans Artificial Intelligence
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Spike Neural Network of Motor Cortex Model for Arm Reaching Control.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Motor cortex modeling is crucial for understanding movement planning and execution. While interconnected recurrent neural networks have successfully described the dynamics of neural population activity, most existing methods utilize continuous signal...
Nerve Net Movement Motor Cortex Neurons Arm Humans Neural Networks, Computer Models, Neurological Action Potentials Animals
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Bioplausible Unsupervised Delay Learning for Extracting Spatiotemporal Features in Spiking Neural Networks.

Neural computation Jun 7, 2024
The plasticity of the conduction delay between neurons plays a fundamental role in learning temporal features that are essential for processing videos, speech, and many high-level functions. However, the exact underlying mechanisms in the brain for t...
Brain Neuronal Plasticity Models, Neurological Humans Neural Networks, Computer Neurons Action Potentials Unsupervised Machine Learning
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A Mean Field to Capture Asynchronous Irregular Dynamics of Conductance-Based Networks of Adaptive Quadratic Integrate-and-Fire Neuron Models.

Neural computation Jun 7, 2024
Mean-field models are a class of models used in computational neuroscience to study the behavior of large populations of neurons. These models are based on the idea of representing the activity of a large number of neurons as the average behavior of ...
Neurons Synapses Nerve Net Models, Neurological Action Potentials Humans Computer Simulation Animals Neural Networks, Computer
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Is Learning in Biological Neural Networks Based on Stochastic Gradient Descent? An Analysis Using Stochastic Processes.

Neural computation Jun 7, 2024
In recent years, there has been an intense debate about how learning in biological neural networks (BNNs) differs from learning in artificial neural networks. It is often argued that the updating of connections in the brain relies only on local infor...
Nerve Net Stochastic Processes Models, Neurological Supervised Machine Learning Neural Networks, Computer Deep Learning
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Convolutional neural network models applied to neuronal responses in macaque V1 reveal limited nonlinear processing.

Journal of vision Jun 3, 2024
Computational models of the primary visual cortex (V1) have suggested that V1 neurons behave like Gabor filters followed by simple nonlinearities. However, recent work employing convolutional neural network (CNN) models has suggested that V1 relies o...
Nonlinear Dynamics Models, Neurological Photic Stimulation Macaca Neurons Neural Networks, Computer Primary Visual Cortex Animals Visual Cortex
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Spiking Neural Membrane Systems with Adaptive Synaptic Time Delay.

International journal of neural systems Jun 1, 2024
Spiking neural membrane systems (or spiking neural P systems, SNP systems) are a new type of computation model which have attracted the attention of plentiful scholars for parallelism, time encoding, interpretability and extensibility. The original S...
Humans Adenosine Triphosphate Neural Networks, Computer Synapses Synaptic Transmission Astrocytes Time Factors Action Potentials Neurons Models, Neurological
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