Metaplasticity tagged posts

Novel memristors to overcome AI’s ‘catastrophic forgetting’

Novel memristors to overcome AI's
Schematic illustration of the novel memristive device. Credit: Nature Communications (2025). DOI: 10.1038/s41467-025-57543-w

So-called “memristors” consume extremely little power and behave similarly to brain cells. Researchers from Jülich, led by Ilia Valov, have now introduced novel memristive components that offer significant advantages over previous versions: they are more robust, function across a wider voltage range, and can operate in both analog and digital modes. These properties could help address the problem of “catastrophic forgetting,” where artificial neural networks abruptly forget previously learned information.

The problem of catastrophic forgetting occurs when deep neural networks are trained for a new task...

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Brain-inspired Learning Algorithm realizes Metaplasticity in Artificial and Spiking Neural Networks

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...

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