A collaboration between SISSA's Physics and Neuroscience groups has taken a step forward in understanding how memories are ...

Researchers have developed a powerful new software toolbox that allows realistic brain models to be trained directly on data.

Figure 1: Delay-period activity recorded in the prefrontal cortex (PFC) in vivo. Activity may be maintained in a neural network through recurrent excitation. This idea underlies the Hopfield model 27 ...

A new project led by the UC Davis Center for Neuroscience will use brain imaging data to build a computer model of complex memory formation. Brain images by Charan Ranganath, Center for Neuroscience.

Recognition memory research encompasses a diverse range of models and decision processes that characterise how individuals differentiate between previously encountered stimuli and novel items. At the ...

The five senses. Credit: Modified by Nicolas Posunko/Skoltech from image generated by Deep Style (Abstract) model on Deep Dream Generator. Photo/Supplied. Skoltech scientists have devised a ...

Most electronics systems use memory components either for storing executable software or for storing data, and therefore the availability of accurate memory models is fundamental to most functional ...

Alzheimer's disease (AD), the leading cause of dementia, affects nearly 40 million individuals globally, resulting in a ...

The agentic AI revolution—or age of reasoning—demands memory architectures match persistent, contextual collaboration.

In the previous article, we left off with the basic storage model having its objects first existing as changed in the processor’s cache, then being aged into volatile DRAM memory, often with changes ...

A brief on how to ensure agentic AI systems remain understandable, accountable, and aligned with the people they serve.