Effect of aiTBS on Intrinsic Spectral Dynamics and Task Performance

The Effect of Within-network aiTBS on Cortical Excitability, Intrinsic Oscillatory Bands, and Behavioral Task Performance

Aim 1: Measure local shifts in cortical spectral dynamics following aiTBS. Aim 2: Measure network-specific shifts in task performance following aiTBS. Exploratory aim: Evaluate changes to resting state spectral dynamics in absence of stimulation after aiTBS.

Study Design. The study design comprises a two-group (DLPFC, TPJ) two-condition (active, sham) parallel design. Order of condition will be counterbalanced across subjects.

Aim 1 Outcome: Spectral Dynamics. All participants will undergo TEP measurements before and after aiTBS therapy (peri-therapeutic) at the left DLPFC and left TPJ to evaluate changes cortical excitability. We will average the results of repeated single pulse stimulation at an intensity of 120% RMT. Participants will also undergo scalp EEG recording during aiTBS sessions and while at rest. Peri-therapeutic oscillatory bands will be determined by averaging responses to across multiple baseline recording sessions using the MATLAB toolbox FieldTrip for detection of signal within the 4-8Hz spectral band. We hypothesize that theta power increases in participants after completing three days of aiTBS when compared against their respective baselines. Intra-therapeutic changes to theta oscillatory signal will also be collected as an additional primary outcome. Averages of theta oscillatory power within each day of aiTBS will be recorded and compared against baseline.

Aim 2 Outcome: Task Performance. Participants will complete both a working memory and affective interference task. The primary outcome measure will be task performance as measured by response time for each subject. Values collected after aiTBS will be compared against their pre-stimulation counterparts using a paired t-test for a given task. The change in these metrics will then be compared across the two tasks using an unpaired t-test. Change in performance metrics for each task will similarly be compared against changes in metrics of the participant group receiving stimulation to the alternate site. We hypothesize performance on network-congruent tasks increase after aiTBS.

Data Analyses. The primary responses will be continuously distributed, and we will compare the active to sham conditions using linear mixed effects models. For the response of Aim 1, we will possibly transform the responses to reduce levels of skewness. When conducting TEP measurements, the order in which participants receive stimulation will be randomly assigned such that 50% of participants receive stimulation to the DLPFC first and 50% receive stimulation to the TPJ first. For the behavioral responses of Aim 2 we will use Fisher's z-transform to symmetrize the distribution and stabilize the variance. The models will include two-level categorical factors for treatment and period; as the period and treatment factors are categorical, these models accommodate arbitrary treatment effects, and, for example, do not assume a linear trend across the treatments. We will include random intercepts for participant and will check whether additional covariance structure is required to account for within-participant correlations. We will also examine treatment by period interaction effects. If these effects are significant, we will report estimated effects and associated standard errors and p-values separately by period; if the interaction effects are non-significant, then we will report estimates of effect pooled over periods.

Inclusion Criteria:

• Able to give their consent
• Right-handed or ambidextrous

Exclusion Criteria:

• Non-english speaking
• Current or past non-anxiety-related psychiatric comorbidity.
• 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
• Increased risk of seizure for any reason
• Pregnancy, or positive pregnancy test
• Any medical (e.g., stroke, breathing problems, motion disorders) or neurological (e.g., a significant brain injury or brain infection history that increases seizure risk) condition that increases risk for fMRI or TMS (Protocol will follow recommendations from Rossi et al. 2021 doi:10.1016/j.clinph.2020.10.003)
• Any metal in their body which would make having an MRI scan unsafe
• Any sort of medical implants
• Hearing loss
• Claustrophobia
• orthostatic hypotension