Targeting the pathological network: feasibility of network-based optimization of transcranial magnetic stimulation coil placement for treatment of psychiatric disorders

Abstract

It has been recognized that the efficacy of TMS-based modulation may depend on the network profile of the stimulated regions throughout the brain. However, what profile of this stimulation network optimally benefits treatment outcomes is yet to be addressed. The answer to the question is crucial for informing network-based optimization of stimulation parameters, such as coil placement, in TMS treatments. In this study, we aimed to investigate the feasibility of taking a disease-specific network as the target of stimulation network for guiding individualized coil placement in TMS treatments. We present here a novel network-based model for TMS targeting of the pathological network. First, combining E-field modeling and resting-state functional connectivity, stimulation networks were modeled from locations and orientations of the TMS coil. Second, the spatial anti-correlation between the stimulation network and the pathological network of a given disease was hypothesized to predict the treatment outcome. The proposed model was validated to predict treatment efficacy from the position and orientation of TMS coils in two depression cohorts and one auditory verbal hallucinations cohort. We further demonstrate the utility of the proposed model in guiding individualized TMS treatment for psychiatric disorders. In this proof-of-concept study, we demonstrated the feasibility of the novel network-based targeting strategy that uses the whole-brain, system-level abnormity of a specific psychiatric disease as a target. Results based on empirical data suggest that the strategy may potentially be utilized to identify individualized coil parameters for maximal therapeutic effects.

Personalized connectivity-based network targeting model of TMS for treatment of psychiatric disorders: computational feasibility and reproducibility

“…In this study, we aim to assess these technical variances and propose two strategies to mitigate them: extending the duration of rsfMRI scans to enhance the signal-to-noise ratio of individual rsfMRI data and employing alternative searching methods to identify optimal targets. (Cao et al, 2023). (C) For the entire search space, the NTA map is generated by considering all parameter combinations, with the optimal target site indicated by a black circle.…”

“…We created an electric field for an individual coil placement using SimNIBS 3.2 and assigned default isotropic tissue conductivities (Wagner et al, 2004). We selected the Magstim 70 mm figure-of-8 coil for electric field simulations (Thielscher and Kammer, 2004), following which we created individual E-field weights using the previous pipeline (Cao et al, 2023). The practical scans for clinical uses range from 6 to 8 minutes (Liu et al, 2017;Park et al, 2020;Kong et al, 2022), so we used half of right-to-left functional images of individuals (about 7 minutes) for the construction of individual rsFC.…”

“…The practical scans for clinical uses range from 6 to 8 minutes (Liu et al, 2017;Park et al, 2020;Kong et al, 2022), so we used half of right-to-left functional images of individuals (about 7 minutes) for the construction of individual rsFC. To determine individual rsFC, we masked the spatially normalized functional images of individuals in NMI space with a customized gray-matter mask consisting of 50740 voxels (Cao et al, 2023). We constructed a voxel-to-voxel correlation matrix (50740×50740) for each individual using Pearson's correlation.…”

“…On observation that the treatment efficacy is associated with the extend how the pathological network of given disorder is engaged in the stimulation network, our previous work (Cao et al, 2023) proposed the network targeting model (NTM) for guiding TMS coil placement for individual patients. Considering the reliability of the targeting result, the stimulation network of NTM was originally based on group-level FC.…”

Targeting the pathological network: Feasibility of network-based optimization of transcranial magnetic stimulation coil placement for treatment of psychiatric disorders

“…Jean–Luc Martinot, INSERM U A10, is acknowledged for setting up the sponsorship and contributing to data acquisition in this patient cohort. The manuscript have appeared online as a preprint ( Cao et al, 2022 ).…”