New Visualization Technique Reveals Geometric Patterns in Brain Activity

Researchers at University of Tsukuba have applied a visualization technique to depict the brain's activity related to visual perception as geometric patterns. They visualized different shapes as the ever-changing neuronal activity in the temporal and frontal lobes of the brain during object recognition and recalling memories. This achievement promises further extraction of brain activity observed in various aspects of daily life.

Our daily lives involve many processes, such as getting up, checking the time, leaving the house, arriving at the office, and starting work. Behind the scenes, brain neurons are active and process complicated tasks. In July 2023, this research team developed and published the principal component analysis in regression subspace (PCArs) to easily visualize brain neuronal activity in various situations. PCArs can determine the most critical events and whether multiple activities exist in the observed brain neuronal activity data.

In this study, researchers applied PCArs to neuronal activity in a wide range of brain regions, from the temporal to frontal lobes, and connected subcortical structures of monkeys. They analyzed four behavioral situations, including activities for remembering the location of objects by looking at the presented figures and activities where the presented figure is a cue for food. The results showed that the temporal regions involved in object recognition had a higher percentage of geometric figures close to circles. In contrast, the hippocampus and frontal lobe, which are considered to be memory regions, had an increased occurrence of curved and straight geometric patterns.

Classifying neuronal activity based on geometric figures revealed that the activity of neuronal populations in the processes of perception, memory, and judgment of visual information changes from moment to moment and is classified into different geometric figures.

Applying PCArs to the neuronal activity of the entire brain can achieve real-time imaging of its ever-changing activity. This achievement is expected to lead to the discovery of a new information processing mechanism in the brain.