AI reveals how brain activity unfolds over time

Amazing stuff! Sounds promising!

"In brief

• Stanford researchers developed Brain-dynamic Convolutional-Network-based Embedding (BCNE) to analyze complex brain activity over time and space.
• This deep learning approach enables insights into memory, decision-making, and neurological conditions, offering potential applications in clinical settings.
• Further refinement is needed for real-time monitoring and integration with other imaging techniques.

...

applied deep learning to decipher such complex brain activity – in two and, in some cases, three dimensions and over long time scales to provide neuroscientific insights ...

In fact, in one experiment, the researchers recorded the brain activity of people watching movies to note how their brains transition from scene to scene and to evaluate changes in perception, emotion, and comprehension as the narrative unfolds.

In other experiments with lab monkeys and rats, BCNE captured detailed information about how physical movements are signaled from the brain to the muscles and provided other detailed information about the animals’ brain activity. ..."

From the abstract:

"Dynamic brain data are becoming increasingly accessible, providing a gateway to understanding the inner workings of the brain in living participants. However, the size and complexity of the data pose a challenge in extracting meaningful information across various data sources. Here we introduce a generalizable unsupervised deep manifold learning for exploration of neurocognitive and behavioral patterns. Unlike existing methods that extract patterns directly from the input data, the proposed brain-dynamic convolutional-network-based embedding (BCNE) captures brain-state trajectories by analyzing temporospatial correlations within the data and applying manifold learning.

The results demonstrate that BCNE effectively delineates scene transitions, underscores the involvement of different brain regions in memory and narrative processing, distinguishes dynamic learning processes and identifies differences between active and passive behaviors. BCNE provides an effective tool for exploring general neuroscience inquiries or individual-specific patterns."

AI reveals how brain activity unfolds over time | Stanford Report "Researchers have developed a deep learning model that transforms overwhelming brain data into clear trajectories, opening new possibilities for understanding thought, emotion, and neurological disease."

Revealing neurocognitive and behavioral patterns through unsupervised manifold learning of dynamic brain data (no public access)

Revealing Neurocognitive and Behavioral Patterns by Unsupervised Manifold Learning from Dynamic Brain Data (preprint, open access)