Chiara Bagattini, Italy
IRCCS Fatebenefratelli Cognitive Neuroscience SectionAuthor Of 1 Presentation
COMBINING FUNCTIONAL IMAGING AND NEUROSTIMULATION TO DESIGN NETWORK-BASED TMS TREATMENTS FOR ALZHEIMER’S DISEASE
Abstract
Aims
In recent years, repetitive transcranial magnetic stimulation (rTMS) has received increasing attention as a potential treatment for Alzheimer’s disease (AD). Combining neurostimulation techniques with neuroimaging allows designing personalized protocols that take into account the functional organization of the brain. AD is associated with alterations of specific large-scale networks, such as the Default Mode (DMN) and Fronto-Parietal (FPN) networks, which might represent targets for rTMS interventions. Here, we propose a novel tailored approach in which functional MRI (fMRI) is used to identify individual network targets for rTMS stimulation.
Methods
Single-subject resting-state fMRI independent component analysis was used to extract individual coordinates of two hubs: the inferior parietal cortex node of the DMN and the dorsolateral prefrontal cortex (DLPFC) node of the FPN in 8 mild AD patients (age [IQR]: 75 [69-80] years; MMSE: 22 [18-25]). The localization of these targets was compared to that of group-level targets defined according to traditional anatomical approaches, assuming different levels of spatial extent of rTMS-induced activation (12mm vs. 20mm).
Results
Both DMN and FPN fMRI-derived hub coordinates showed a large variability between subjects (distance in mm [IQR]: DMN=19 [15-26]; FPN=21 [14-26]) and were significantly distant from traditionally-defined targets when assuming a rTMS focality of 12mm (p<0.05) but not of 20mm (p>0.08).
Conclusions
Our results show the feasibility of tailored network-based fMRI-guided rTMS targeting. This approach may enhance the spatial selectivity of rTMS compared to traditional anatomical approaches. Clinical trials testing the efficacy and the advantage of this approach in AD are needed.