Catastrophic forgetting, an innate issue with backpropagation learning algorithms, is a challenging problem in artificial and spiking neural network (ANN and SNN) research.

The brain has somewhat solved this problem using multiscale plasticity. Under global regulation through specific pathways, neuromodulators are dispersed to target brain regions, where both synaptic and neuronal plasticity are modulated by neuromodulators locally. Specifically, neuromodulators modify the capacity and property of neuronal and synaptic plasticity. This modification is known as metaplasticity.

Researchers led by Prof...

A novel study from the University of South Australia has identified a range of metabolic biomarkers that could help predict the risk of cancer.

Deploying machine learning to examine data from 459,169 participants in the UK Biobank, the study identified 84 features that could signal increased cancer risk.

Several markers also signalled chronic kidney or liver disease, highlighting the significance of exploring the underlying pathogenic mechanisms of these diseases for their potential connections with cancer.

The study, “Hypothesis-free discovery of novel cancer predictors using machine learning,” was conducted by UniSA researchers: Dr Iqbal Madakkatel, Dr Amanda Lumsden, Dr Anwar Mulugeta, and Professor Elina Hyppönen, with University of Adelaide’s Professor Ian Olver.

“We...

A new atomic device sends high-fidelity quantum information over fiber optic networks. Researchers have a new way to connect quantum devices over long distances, a necessary step toward allowing the technology to play a role in future communications systems.

While today’s classical data signals can get amplified across a city or an ocean, quantum signals cannot. They must be repeated in intervals — that is, stopped, copied and passed on by specialized machines called quantum repeaters...