The fields of neuroscience and artificial intelligence (AI) have a long and intertwined history.
In more recent times, however, communication and collaboration between the two fields has …

During learning, the brain modifies synapses to improve behaviour. In the cortex, synapses
are embedded within multilayered networks, making it difficult to determine the effect of an …

Deep neural networks excel at learning the training data, but often provide incorrect and
confident predictions when evaluated on slightly different test examples. This includes …

Herein, it was aimed to optimize, model, and forecast the biosorption of Congo Red onto
biomass-derived biosorbent. Therefore, the waste-orange-peels were processed to fabricate …

Abstract Systems neuroscience seeks explanations for how the brain implements a wide
variety of perceptual, cognitive and motor tasks. Conversely, artificial intelligence attempts to …

Understanding spoken language requires transforming ambiguous acoustic streams into a
hierarchy of representations, from phonemes to meaning. It has been suggested that the …

This review article summarises recently proposed theories on how neural circuits in the
brain could approximate the error back-propagation algorithm used by artificial neural …

Neuroscience research is undergoing a minor revolution. Recent advances in machine
learning and artificial intelligence research have opened up new ways of thinking about …

Recent neurophysiological and neuroanatomical studies suggest a close interaction
between sensory and motor processes across the neocortex. Here, I propose that the …

Predictive coding offers a potentially unifying account of cortical function--postulating that the
core function of the brain is to minimize prediction errors with respect to a generative model …