In our daily lives, we encounter new objects from various categories through different sensory modalities, such as vision and touch. Yet, how learning new categories reshapes brain connectivity networks to adapt to these objects remains poorly understood. To address this question, our research team developed an innovative paradigm that combines 3D digital embryos (artificial objects) with virtual reality and 3D-printed replicas of the same objects, simulating real-life interactions in an experimental setup.

Using dual regression analysis on resting-state fMRI data, we identified the frontoparietal network (FPN) as a shared hub modulated across both visual and tactile sensory modalities. These findings provide strong evidence for the flexible hub theory of the FPN, which suggests this network enables humans to adaptively perform a wide range of tasks by dynamically reorganizing itself.

Our study reveals that learning new categories induces sensory-modality-dependent reorganization within the brain's resting-state networks. These insights enhance our understanding of neural adaptability and may inform strategies to optimize learning through sensory experiences.

Tabrik, S., Dinse, H. R., Tegenthoff, M. & Behroozi, M. (2024). Resting‐State Network Plasticity Following Category Learning Depends on Sensory Modality. Human Brain Mapping, 45(18).