AIMC Topic: Neurons

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NeuroCellCentreDB: Exploring a Novel Dataset for Neuron-like Cell Centre Detection with Deep Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The manipulation and stimulation of cell growth is invaluable for neuroscience research such as brain-machine interfaces or applications of neural tissue engineering. For the implementation of such research avenues, in particular the analysis of cell...

Comparing the Graphical Features of Simple Artificial Neural Networks and Cortical Development.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Brain development is characterized by changes in connections and information processing complexity. These changes inspire the training process of artificial neural network (ANN), which requires adjusting the neuron weights and biases to enhance effic...

Symbiosis of an artificial neural network and models of biological neurons: Training and testing.

Chaos (Woodbury, N.Y.)
In this paper, we show the possibility of creating and identifying the features of an artificial neural network (ANN), which consists of mathematical models of biological neurons. The FitzHugh-Nagumo (FHN) system is used as a paradigmatic model demon...

AI Techniques to Identify Nerve Cell Alterations in Digital Images.

Studies in health technology and informatics
Artificial intelligence (AI), utilising computing power, has managed to influence the health sector with many applications based on algorithms, tools, and automated processes. In this work, neuronbiological images acquired by an electronic microscope...

Sensitivity to Control Signals in Triphasic Rhythmic Neural Systems: A Comparative Mechanistic Analysis via Infinitesimal Local Timing Response Curves.

Neural computation
Similar activity patterns may arise from model neural networks with distinct coupling properties and individual unit dynamics. These similar patterns may, however, respond differently to parameter variations and specifically to tuning of inputs that ...

Modern Artificial Neural Networks: Is Evolution Cleverer?

Neural computation
Machine learning tools, particularly artificial neural networks (ANN), have become ubiquitous in many scientific disciplines, and machine learning-based techniques flourish not only because of the expanding computational power and the increasing avai...

Adopting improved Adam optimizer to train dendritic neuron model for water quality prediction.

Mathematical biosciences and engineering : MBE
As one of continuous concern all over the world, the problem of water quality may cause diseases and poisoning and even endanger people's lives. Therefore, the prediction of water quality is of great significance to the efficient management of water ...

Stochastic photonic spiking neuron for Bayesian inference with unsupervised learning.

Optics letters
Stochasticity is an inherent feature of biological neural activities. We propose a noise-injection scheme to implement a GHz-rate stochastic photonic spiking neuron (S-PSN). The firing-probability encoding is experimentally demonstrated and exploited...

NeuroAI: If grid cells are the answer, is path integration the question?

Current biology : CB
Spatially modulated neurons known as grid cells are thought to play an important role in spatial cognition. A new study has found that units with grid-cell-like properties can emerge within artificial neural networks trained to path integrate, and de...