Using fMRI-guided TMS to Increase Central Executive Function in Older Adults (MCI_Sub)
Phase: NA
Conditions: Mild Cognitive Impairment
Sponsor: Duke University

 
 
 
 
 
 
 
 
 
 
 
 
 
 
Using fMRI-guided TMS to Increase Central 
Executive Function in Older Adults  
(MCI_Sub) 
 
 
 
NCT04176406 
 
 
 
 
This document includes the study protocol and the 
statistical plan approved on March 1st 2020. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Study Protocol: 
 
This experimental supplement is focused on applying TMS to a cortical network node in 30 patients diagnosed 
with MCI or found to be at risk for cognitive impairment (This cohort will be referred to as "MCI patients", but 
includes subjects with diagnosed MCI and subjects not currently diagnosed, but at risk for cognititve 
impairment as defined by criteria below). This blinded, sham-controlled trial will feature a mixed model 2 x 3 
x 2 x 2 cross-over design, with rTMS Type (active, sham), Difficulty Level defined by accuracy (easy, medium, 
hard levels), Stimulation Location (Network, Activity target), and Group (healthy OAs, MCI) as factors. As 
such, this design reflects the fact that all subjects receive both active and sham rTMS applied to up to two 
different scalp locations during a WM task at up to three levels of difficulty. Study procedures are listed 
in Table 3. Thirty healthy OAs (age range: 55-80 years) and thirty MCIs (age range: 55-80 years) will 
participate. In the first session, which will take about 2 hours, participants will be consented and screened for 
the study, submit a saliva sample for genetic testing, determine TMS motor threshold, and then learn and 
practice the WM task. The next visit will involve a structural MRI and fMRI recorded from both groups while 
they perform the WM task. Cortical locations within the FPN (Network target) and DLPFC (Activity target) will 
be used as targets for rTMS will be chosen from an analysis of subject-specific fMRI activations from 
the WM task completed in this MRI Session. This session, which will last up to 3 hours, will be followed by up 
to four sessions of rTMS + MRI, each lasting about 3 hours. These rTMS+MRI sessions will begin ~1 week 
after the MRI Session, to allow for time to process the imaging data. rTMS+MRI sessions (involving active or 
sham rTMS and Network or Activity targets) will use coil locations and rTMS device intensities based on realistic 
head modeling the MRI will collect structural and resting state information.  
  
Working Memory task. In order to test for cognitive performance differences in response to TMS, we will 
rely on a validated WM task that has shown (1) reliable univariate activity in response to parametric increases 
in set size or load, 2) multivariate connectivity increases in response to load, and (3) reliable deficits in MCIs 
using similar stimuli and paradigms. Each trial comprises a set of presented words. On “rehearse” 
trials, individualssubvocally 
rehearsed 
a 
list 
of 
words 
across 
a 
memory 
delay. 
On 
“reorder” 
trials, individuals mentally rearranged a list of words based on the weight of the objects that the words referred 
to. Individuals are then probed on the correct order or position of a random word from the array. After 
scanning, individuals administered a surprise LTM recognition test on words processed in both conditions.  
  
 Stimuli in this experiment consisted of 504 words selected from the Medical Research Council Psycholinguistic 
database (http://www.psych.rl.ac.uk/MRC_Psych_Db.html). The words are 2–13 letters in length and 
moderate frequency, highly concrete, and highly imageable. These words were used to construct three 
separate lists of 168 words matched for length, frequency, concreteness, and imageability. Two of the word 
lists were used for the WM tasks, whereas words from the third list were used as foils for the subsequent LTM 
recognition test. For the two WM word lists, unique word triplets were constructed in a psuedo-randomized 
manner. The authors inspected the triplets to ensure that there was no ambiguity in terms of the relative 
referent weight or pronunciation of the words. The two WM word lists were counterbalanced between subjects 
and WM condition.  
  
SALIVA SAMPLE: A saliva sample will be obtained from healthy volunteers and MCI patients in this cohort 
and will be used to perform APOE genetic testing, a risk marker for Alzheimer's Disease. Samples will be 
obtained by administration of a cheek swab and stored in a secure environment. Subject samples will be 
deidentified and labeled with the subject study number. Genetic testing will be performed at the Biofluids 
Shared Resource. 
  
Imaging acquisition and preprocessing. Three forms of structural images will be acquired: 1) full-brain 
high-resolution T1-weighted structural images (inversion recovery prepared 3D SPGR) with full coverage 
of the head and neck, (TR = 500ms; TE = 20ms; FoV = 24cm2; image matrix = 256x256; voxel size = 0.94 
x 0.94 x 1mm), and 2) echo-planar (EPI) sensitivity encoding (SENSE) DWI images with the same 
orientation (TR = 2000 ms; FoV = 24 cm2; image matrix = 1282; voxel size 0.94 x 0.94 x 1 mm; b-value = 
1000 s/mm2; 1 repetition; 36 diffusion-sensitizing directions). In addition, two forms of functional images will 
be collected: 1) for resting state EPI functional imaging data, which will be used to estimate RSFA, we will 
acquire 24 slices parallel to the AC-PC plane using a BOLD-sensitive gradient-echo sequence with EPI k-space 
sampling, at TR of 2s (TE: 35ms; FOV: 25.6cm; voxel size: 63mm), and 2) event-related EPI, which uses 
the same scan parameters and will measure the global reactivity to our Working Memory Task. 
 TMS methods. Coil targeting will be achieved using frameless stereotaxy (BrainSight: Rogue Research, 
Montreal). TMS is applied with a figure 8 coil based on 100% resting motor threshold (rMT)58, though TMS 
intensity will also be informed by E-field modeling (described below). TMS will be delivered consecutively over 

the individualized target region, based on the cortical site with the highest computed controllability (Network 
target) or parametric activity (Activity target), using a MagVenture stimulator. Neuronavigation (BrainSight, 
Rogue Research, Canada) and a robot (SmartMove, ANT, Netherlands) will be used to optimize the targeting. 
Brain atrophy could also reduce TMS effectiveness because it increases the distance between scalp and the 
cortex but this potential confound is addressed by adjusting TMS intensity using the E-field computation. In 
visits 3 to 6, participants will perform the Working Memory Task while active or electrical sham stimulation is 
delivered using an A/P Cool-B65 coil (MagVenture, Denmark). In a stimulation trial, twenty-five pulses of 5Hz 
rTMS will be delivered at 100% of the effective E-field. Sham rTMS will be administered with a sham coil 
equipped with shielding to block magnetic field output but retain the auditory and some of the tactile aspects 
of active stimulation. This method reproduces the somatosensory sensations as the magnetic field stimulates 
scalp muscles, and produces the same acoustic artifact than the active stimulation, without inducing current 
in the cortex59. 
DWI Structural Connectivity. Whole-brain tractography. As in our prior DWI tractography work, Dipy60 will 
be used to generate connectomes representing structural connections between all cortical regions in the 
Harvard-Oxford Atlas. For structural connection matrices, network edges are defined by the number of 
tractography streamlines between all nodes of the target network. 
Event-related fMRI analyses, functional connectivity and graph theory measures. The Frontoparietal 
network (FPN) is identified by standard atlas61, and will be validated with voxelwise independent component 
analysis (ICA). Task-related connectivity is measured using beta-series correlations20, which estimates a time-
series by examining region-by-region interactions that are modulated by task conditions. SMEs for activity 
and connectivity will be analyzed with a Group (healthy OAs vs. MCIs) x Targeting (Network-based vs. 
Traditional) x Stimulation (Active vs. Sham) ANOVA using SPM62. All matrices are evaluated for descriptive 
graph-theoretical properties (including degree and controllability) using the Brain Connectivity Toolbox. 
E-field Modeling. In order to determine the intensity of network-based targeting, we will use electric field 
(E-field) modeling. The BSEL lab has extensive experience with the creation of anatomically realistic E-field 
models of transcranial electric and magnetic stimulation in humans, which have been applied to healthy OA 
populations in ongoing NIH-funded projects by Co-I’s Cabeza and Appelbaum (U01-AG050618), using 
SimNIBS software63. A detailed model of the TMS coil is combined with a detailed head model. Isotropic tissue 
conductivities are assigned to the various tissue compartments. Critically, this method will also include 
anisotropic conductivity in the white matter based on the DWI data. We will carry out E-field simulations over 
a range of coil orientations and tilts to predict maximal activation of the FPN. The target node (i.e., the node 
with the highest controllability, identified above) will be used as the center of a 3×3 grid for positioning the 
coil in simulations of the E-field corresponding to these 9 coil positions and 6 orientations (54 combinations). 
The simulation E-field maps will be extracted and correlated, voxel-to-voxel, with the fMRI activation and the 
simulation that yields the highest correlation is selected as the target coil position and orientation. 
 
 
 
 
 
 
 
 
 
 

Statistical Plan:  
 
Power analysis. Our labs have considerable experience with combining neurostimulation and neuroimaging. 
Through the parent award we have enrolled 85 individuals in multiday memory protocols and results from 
these data reflect the size of potential future TMS effects. Power calculations were therefore conducted in R 
software (R Development Core Team, 2016) using the repeated-measures ANOVA module. With N=80 
subjects, in a mixed-effects design consisting of 4 repeated measurements per subject (2 groups x 2 TMS 
targeting [network-based, traditional targeting), Cohen’s d = 0.9 for each of the main effects, with interaction 
effects between 0.7-0.9, attaining an average power of 0.8 at an overall significance level of 5%. 
Analytical Rigor. In our analysis phase, we will ensure scientific rigor in the following ways. To address bias 
in ANOVAs due potential violation of the sphericity assumption in Studies 1 and 2, we will estimate sphericity 
and correct for this bias using a Greenhouse-Geisser correction. In order to ensure replicability in our findings, 
we will report analytical procedures according to the Committee on Best Practice in Data Analysis and Sharing 
(COBIDAS) report for fMRI data analysis. Finally, to ensure generalizability of our findings, we will perform a 
k-fold cross-validation on all fMRI data analyses. In k-fold cross-validation, the data is divided into k 
independent subsets. On each fold, one subset is held out as the test set, the others are used for training. 
Empirical studies suggest that choices of k in the range of 5 to 10, yield good results in practice. 
Consideration of sex as a biological variable. We will fulfill this recent NIH mandate by including both 
sexes in the research and by including gender as a covariate of interest in all analyses. Because this is an 
exploratory study, we have no a priori predictions on how gender might influence the TMS-imaging results. 
Although we may be underpowered to observe sex differences, the outcome of this Administrative Supplement 
can be used to estimate effect sizes to adequately power gender differences in future larger-scale studies.