Text-related functionality and dynamics of visual human pre-frontal activations revealed through neural network...

Area of Science:

• Neuroscience
• Cognitive Science
• Artificial Intelligence

Background:

• Human prefrontal cortex shows increased activation during image tasks, but its function is debated.
• Deep neural networks (DNNs) are used to model brain functions, including visual processing and memory.

Purpose of the Study:

• To investigate the functional role of prefrontal cortex activations during visual memorization.
• To compare the relational structure of prefrontal activations with visual and textual DNNs.

Main Methods:

• Analysis of intra-cranial recordings from patients performing a visual memorization task.
• Dynamic comparison of prefrontal activation structures with visual and textual DNNs.

Main Results:

• Prefrontal cortex activation structures during visual memorization were predicted by text-based DNNs, not visual DNNs.
• Visual component correlations rapidly declined, while text component correlations persisted, showing an image offset response.

Conclusions:

• The prefrontal cortex plays a dynamic, text-related role in visual memorization.
• Findings challenge purely visual models and highlight the influence of semantic (text-based) information in visual memory.