Transcranial magnetic stimulation (TMS) is increasingly being applied to effectively treat mental illness, however efforts to quantify the effects of TMS on the network architecture of the brain have largely been limited in scope and tied to specific neurologic and psychiatric disorders. The objective of the current work is to build and validate a whole-brain, domain-general model of brain connectivity changes following TMS, based on physical models of the current distribution at the cortex. PUBLIC HEALTH RELEVANCE: This work is relevant to public health because it will provide direct evidence that brain connectivity changes following neuromodulatory TMS vary as a function of the current density at the cortex, which can be used to predict psychiatric symptom change following neuromodulatory TMS.

Transcranial magnetic stimulation (TMS) is currently approved by the FDA for the treatment of depression, obsessive compulsive disorder, and smoking cessation. Despite evidence that TMS improves symptoms by modulating brain connectivity, the few published studies that have measured brain connectivity before and after neuromodulatory TMS have been population-, dose-, and pattern-specific, with connectivity effects that are limited in scope to a handful a priori regions of interest. Accordingly, there is a critical need for generalized, comprehensive model that explains how functional brain connectivity changes at the whole-brain level following neuromodulatory TMS. Therefore, the objectives of this grant are to 1) develop a model using whole-brain estimates of the TMS-induced electric (e)-field to predict changes in resting state functional connectivity following neuromodulatory TMS, and 2) validate this model in a large cohort of healthy volunteers receiving multiple doses of either intermittent or continuous theta burst stimulation (iTBS and cTBS, respectively). Our central hypothesis is that changes in functional connectivity will vary systematically with the current density at the cortex, operationally defined using e-field modelling. Investigators have pilot data suggesting that the variability in pre-post rsFC changes following TMS can be predicted using estimates of the current density at the cortex with a medium to large effect size. Our approach will be to measure rsFC in healthy volunteers before and after each of 3 doses (5 sessions/dose; 600 pulses/session) of iTBS or cTBS. Stimulation will be delivered to the left dlPFC, and targeting will be individualized based on fMRI data collected during the Sternberg working memory paradigm. Our primary outcome measure will be the percent of variability in pre-post rsFC accounted for by our model. Our rationale for this approach is that by collecting resting state data pre and post these doses of iTBS and cTBS, investigators will be able to quantify the effect of pattern (i.e. cTBS vs. iTBS) and dose (i.e. number of pulses) on functional connectivity changes. This work is innovative because it uses a novel application of e-field modelling to predict changes in rsFC data following TMS administration. PUBLIC HEALTH RELEVANCE: This work is relevant to public health because it will provide direct evidence that functional connectivity changes following neuromodulatory TMS vary as a function of the current density at the cortex. The empirical support for this model gained from this current work will set the stage for the use of this model for individualized targeting in subsequent clinical trials. Importantly, because of the domain-general nature of this approach its application is not limited to any specific disorder. Likewise, because our approach is not tied to any specific functional connectivity feature, it can be applied to regions outside those currently under investigation, which could facilitate target discovery in understudied disorders.

Inclusion Criteria

• Able to give their consent
• Right-handed

Exclusion Criteria

• Non-english speaking
• Any significant medical problems
• Current or past Axis I psychiatric disorder(s),
• Active or history of active suicidal ideation
• Alcohol/drug problems in the past year or lifetime alcohol or drug dependence
• Medications that act on the central nervous system
• History of seizure
• History of epilepsy or other neurological problems
• Increased risk of seizure for any reason
• Pregnancy
• Any medical condition that increases risk for fMRI or TMS
• Any metal in their body which would make having an MRI scan unsafe
• Any sort of medical implants
• Claustrophobia

Repositories receiving data and/or samples from this protocol may be open-access or restricted access. Samples and data will be stripped of identifiers and may be coded ("de-identified") or unlinked from an identifying code ("anonymized"). When coded data is shared, the key to the code will not be provided to collaborators, but will remain with the PI.

After study completion. No less than 5 years.

Data and samples may be shared with investigators and institutions with an FWA or operating under the Declaration of Helsinki (DoH) and reported to the IRB at the time of continuing review.