AIMC Topic: Neurons

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Deep learning-based real-time detection of neurons in brain slices for in vitro physiology.

Scientific reports
A common electrophysiology technique used in neuroscience is patch clamp: a method in which a glass pipette electrode facilitates single cell electrical recordings from neurons. Typically, patch clamp is done manually in which an electrophysiologist ...

Deep learning based neuronal soma detection and counting for Alzheimer's disease analysis.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Alzheimer's Disease (AD) is associated with neuronal damage and decrease. Micro-Optical Sectioning Tomography (MOST) provides an approach to acquire high-resolution images for neuron analysis in the whole-brain. Application ...

Machine learning-based classification of mitochondrial morphology in primary neurons and brain.

Scientific reports
The mitochondrial network continually undergoes events of fission and fusion. Under physiologic conditions, the network is in equilibrium and is characterized by the presence of both elongated and punctate mitochondria. However, this balanced, homeos...

Parallel Binary Image Cryptosystem Via Spiking Neural Networks Variants.

International journal of neural systems
Due to the inefficiency of multiple binary images encryption, a parallel binary image encryption framework based on the typical variants of spiking neural networks, spiking neural P (SNP) systems is proposed in this paper. More specifically, the two ...

Neuromorphic Binarized Polariton Networks.

Nano letters
The rapid development of artificial neural networks and applied artificial intelligence has led to many applications. However, current software implementation of neural networks is severely limited in terms of performance and energy efficiency. It is...

Unsupervised Anomaly Detection in Stream Data with Online Evolving Spiking Neural Networks.

Neural networks : the official journal of the International Neural Network Society
Unsupervised anomaly discovery in stream data is a research topic with many practical applications. However, in many cases, it is not easy to collect enough training data with labeled anomalies for supervised learning of an anomaly detector in order ...

Dynamics of a Large-Scale Spiking Neural Network with Quadratic Integrate-and-Fire Neurons.

Neural plasticity
Since the high dimension and complexity of the large-scale spiking neural network, it is difficult to research the network dynamics. In recent decades, the mean-field approximation has been a useful method to reduce the dimension of the network. In t...

Rapid 3D phenotypic analysis of neurons and organoids using data-driven cell segmentation-free machine learning.

PLoS computational biology
Phenotypic profiling of large three-dimensional microscopy data sets has not been widely adopted due to the challenges posed by cell segmentation and feature selection. The computational demands of automated processing further limit analysis of hard-...

Bioinspired multisensory neural network with crossmodal integration and recognition.

Nature communications
The integration and interaction of vision, touch, hearing, smell, and taste in the human multisensory neural network facilitate high-level cognitive functionalities, such as crossmodal integration, recognition, and imagination for accurate evaluation...

Machine learning identifies candidates for drug repurposing in Alzheimer's disease.

Nature communications
Clinical trials of novel therapeutics for Alzheimer's Disease (AD) have consumed a large amount of time and resources with largely negative results. Repurposing drugs already approved by the Food and Drug Administration (FDA) for another indication i...