Complex-valued neural networks represent an evolving frontier where the intrinsic properties of complex numbers—magnitude and phase—are harnessed to develop richer and more robust representations of ...

The representation of individual memories in a recurrent neural network can be efficiently differentiated using chaotic recurrent dynamics.

For decades, dopamine has been celebrated in neuroscience as the quintessential "reward molecule"—a chemical herald of ...

This valuable study links psychological theories of chunking with a physiological implementation based on short-term synaptic plasticity and synaptic augmentation. The theoretical derivation for ...

Every day, our brain takes countless fleeting experiences — from walks on the beach to presentations at work — and transforms them into long-term memories. How exactly this works remains a mystery, ...

To study how a key chemical neuromodulator affects signaling in the brain's cortex, Garrett Neske, PhD, has received a three-year, $300,000 grant from the Whitehall Foundation, a nonprofit ...

Scientists have created a novel probabilistic model for 5-minutes ahead PV power forecasting. The method combines a convolutional neural network with bidirectional long short-term memory, attention ...