Unveiling the Multifaceted Networks of the Left DLPFC for Precision TMS Targeting.

Area of Science:

• Neuroscience
• Cognitive Neuroscience
• Brain Imaging

Background:

• Treatment-resistant depression (TRD) has high non-response rates with standard left dorsolateral prefrontal cortex (lDLPFC) transcranial magnetic stimulation (TMS).
• TMS efficacy is linked to functional connectivity, particularly anti-correlation with the subgenual cingulate cortex (SGC), but lDLPFC network interactions remain unclear.
• Understanding lDLPFC heterogeneity is crucial for optimizing TMS and addressing treatment variability.

Purpose of the Study:

• To delineate functional subdivisions within the lDLPFC using connectivity-based parcellation.
• To characterize the connectivity patterns and behavioral associations of these subdivisions.
• To develop a network-informed reference for individualized TMS interventions in TRD.

Main Methods:

• Connectivity-based parcellation of the lDLPFC region, including common TMS targets and adjacent areas.
• Analysis of functional connectivity with large-scale brain networks, including the default-mode network (DMN) and salience network.
• Correlation of lDLPFC subdivisions with behavioral functions, such as cognitive control, inhibition, and social cognition.

Main Results:

• A hierarchical organization of the lDLPFC was identified, with coarse antagonism between anterior-central and superior-posterior subregions, and a finer nine-cluster architecture.
• Anterior-central lDLPFC subregions showed strong anti-correlation with SGC and DMN, positive connectivity with salience and attention networks, and association with cognitive control.
• Superior-posterior and ventral subregions exhibited distinct connectivity profiles and behavioral associations, including links to somatomotor, visual, and language networks.

Conclusions:

• The lDLPFC exhibits significant hierarchical and heterogeneous functional organization.
• Anterior-central lDLPFC subregions are identified as optimal targets for TMS in TRD due to their connectivity and behavioral profiles.
• These findings provide a network-informed foundation for developing personalized, symptom-specific TMS interventions, potentially improving treatment outcomes.