Neurologists use millisecond-level M/EEG tracking to prove the human brain and AI language models organize and predict language using parallel processing principles.

A team led by Professor Ed X. Wu and Dr. Alex T. L. Leong has achieved a major breakthrough in understanding how the brain processes information through large-scale network changes. Their findings, ...

The brain's ability to process information is known to be supported by intricate connections between different neuron populations. A key objective of neuroscience research has been to delineate the ...

The intersection of artificial intelligence and neuroscience has emerged as a frontier of great interest, particularly for understanding how large language models (LLMs) and the human brain process ...

Educational multimedia has become increasingly important in modern learning environments because of its cost-effectiveness and its ability to overcome the temporal and spatial constraints of ...

Researchers in Australia have developed a neuromorphic vision chip that can see, process, and ...

Scientists have discovered that the human brain understands spoken language in a way that closely resembles how advanced AI language models work. By tracking brain activity as people listened to a ...

Researchers have conducted groundbreaking research on memristor-based brain-computer interfaces (BCIs). This research presents an innovative approach for implementing energy-efficient adaptive ...

Challenging the classic view, two cognitive scientists argue in a new review that categorization is not a late, specialized stage of sensory processing. Instead, it is a core function operating at ...

New research from the Mark and Mary Stevens Neuroimaging and Informatics Institute (Stevens INI) at the Keck School of Medicine of USC has discovered subtle but widespread differences in the brain's ...