AIMC Topic: Neurons

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Prediction-error neurons in circuits with multiple neuron types: Formation, refinement, and functional implications.

Proceedings of the National Academy of Sciences of the United States of America
SignificanceAn influential idea in neuroscience is that neural circuits do not only passively process sensory information but rather actively compare them with predictions thereof. A core element of this comparison is prediction-error neurons, the ac...

Intrinsic bursts facilitate learning of Lévy flight movements in recurrent neural network models.

Scientific reports
Isolated spikes and bursts of spikes are thought to provide the two major modes of information coding by neurons. Bursts are known to be crucial for fundamental processes between neuron pairs, such as neuronal communications and synaptic plasticity. ...

Rotating neurons for all-analog implementation of cyclic reservoir computing.

Nature communications
Hardware implementation in resource-efficient reservoir computing is of great interest for neuromorphic engineering. Recently, various devices have been explored to implement hardware-based reservoirs. However, most studies were mainly focused on the...

Ultrafast neuromorphic photonic image processing with a VCSEL neuron.

Scientific reports
The ever-increasing demand for artificial intelligence (AI) systems is underlining a significant requirement for new, AI-optimised hardware. Neuromorphic (brain-like) processors are one highly-promising solution, with photonic-enabled realizations re...

Neural Network-Based Decoding Input Stimulus Data Based on Recurrent Neural Network Neural Activity Pattern.

Doklady biological sciences : proceedings of the Academy of Sciences of the USSR, Biological sciences sections
The paper reports the assessment of the possibility to recover information obtained using an artificial neural network via inspecting neural activity patterns. A simple recurrent neural network forms dynamic excitation patterns for storing data on in...

Neuronal Apoptosis in Patients with Liver Cirrhosis and Neuronal Epileptiform Discharge Model Based upon Multi-Modal Fusion Deep Learning.

Journal of healthcare engineering
Neurons refer to nerve cells. Each neuron is connected with thousands of other neurons to form a corresponding functional area and carry out complex communication with other functional areas. Its importance to the human body is self-evident. There ar...

Image Inpainting With Local and Global Refinement.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Image inpainting has made remarkable progress with recent advances in deep learning. Popular networks mainly follow an encoder-decoder architecture (sometimes with skip connections) and possess sufficiently large receptive field, i.e., larger than th...

Emergence of Direction-Selective Retinal Cell Types in Task-Optimized Deep Learning Models.

Journal of computational biology : a journal of computational molecular cell biology
Convolutional neural networks (CNNs), a class of deep learning models, have experienced recent success in modeling sensory cortices and retinal circuits through optimizing performance on machine learning tasks, otherwise known as task optimization. P...

Toward Efficient Processing and Learning With Spikes: New Approaches for Multispike Learning.

IEEE transactions on cybernetics
Spikes are the currency in central nervous systems for information transmission and processing. They are also believed to play an essential role in low-power consumption of the biological systems, whose efficiency attracts increasing attentions to th...

A behavioral paradigm for cortical control of a robotic actuator by freely moving rats in a one-dimensional two-target reaching task.

Journal of neuroscience methods
BACKGROUND: Controlling the trajectory of a neuroprosthesis to reach distant targets is a commonly used brain-machine interface (BMI) task in primates and has not been available for rodents yet.