INTRODUCTION

tACS provides electric current stimulation over the scalp to modulate specific brain regions or functional connectivity (FC)¹. Concurrent fMRI and tACS can measure activations in the areas beneath the electrodes². Selection of the frequency and phase for the tACS stimulation influences capacity to modulate functional connectivity³. We aim to: (1) find the optimal frequency and phase for tACS stimulation that results in the highest frontoparietal FC; (2) examine in a working memory fMRI task whether the optimized tACS stimulation would improve frontoparietal connectivity and cognitive function compared to control parameters.

METHOD

Eleven healthy participants (Female=8; Age=20-53 years) underwent the closed-loop tACS-fMRI targeting frontoparietal synchronization (FPS). 3T MRI scanner (Discovery MR750; GE Healthcare Systems, Milwaukee, WI) with the 8-channel receive-only head coil was used for fMRI; tACS was provided with (Starstim R32; Neuroelectrics Barcelona SLU; Spain). fMRI parameters were: FOV/slice thickness = 240/2.9mm, matrix=96×96, 39 axial slices,TR/TE=2000/27ms. FPS targets: the right middle frontal gyrus and right inferior parietal cortex; nodes of the frontoparietal network, approximated by electrode positions F4 and P4 of the 10-20 EEG system. we modified of MRI Sponstim (model: NE026MRI, brand: Neuroelectrics) electrode that is placed inside next generation (NG) Pistim's shell (model:NE029; Neuroelectrics, the metal part (Ag/AgCl) removed). This modification creates an MR conditional electrode (circular pad r = 1cm with carbon rubber as electrode pad). Conductive gel/paste (model: Abralyt HiCl, brand:Easycap) was used to improve contact conductivity between the scalp and the carbon rubber pad. We use head caps with holes indicating electrode positioning places (model: Neoprene Headcap/ NE019, brand: Neuroelectrics). The coordinates of the region of interests (ROIs) were assigned by the highest electric field on frontal and parietal montage sites using SimNIBS simulation under F4 and P4 electrodes^4,5. ROIs: in frontal site (MNI F4 coordinates= [-45, 49, 27], 10mm radius) and in parietal site (MNI P4 coordinates= [-45, -75, 46], 10mm radius). The current of the center electrode at F4 and P4 were assigned constant 1mA current. Return-electrode for each site is four electrodes with the current on return-electrode 0.25mA. Return-electrode coordinates for the F4 site are: RF1=[37.99, 75.64, 22.32], RF2=[67.91, 48.88, 25.73], RF3=[52.23, 35.78, 60.45], and RF4=[ 22.31, 62.54, 57.04], and for P4 site are:(RP1=[22.12, -60.72, 59.04], RP2=[50.21, -35.60, 62.24], RP3=[69.58, -43.35, 30.70], and RP4=[48.22, -71.16, 16.55] in the position coordinates of the standard BioSemi head caps with circumference=550mm⁶. Figures 1a,1b show a montage of 10 high-definition electrodes for frontal and parietal sites. Participants underwent online FPS with tACS-fMRI, with study design shown on Figure 2. Protocol includes an anatomical scan, resting scans, a 2-back tasks and training scans with a 2-back tasks (Training 1, and 2 in optimization part), and testing the optimal or control parameters with a 2-back task (Testing), and 3rd resting scan. During the Training phase participants are divided into two groups (see Fig.2 captions). The training run is divided into 15 blocks (Figure 3a) where each block consists of 20 seconds tACS with parameters (frequency and phase) derived from the Simplex optimizer rules. This is followed by 10 seconds of rest. During each block, the Simplex optimizer searches the optimized parameter of the combination of frequency and phase from the parameters' field (range frequency:1-150Hz, and phase:0–359^o) based on the fMRI frontoparietal FC measurements. The initial Simplex parameter is placed around of the highest frontoparietal connectivity⁷, which is in the center of theta band (6Hz) and phase difference = 0^o to make it easier to find the highest frontoparietal FC. The edges of the initial Simplex parameter (equilateral triangle) are: (6Hz, 5^o), (10Hz, -3^o), and (2Hz, -3^o). The sliding-window fMRI connectivity response is calculated in real-time and analyzed by the optimizer to predict what frequency and phase cause the highest increase or lowest decrease in frontoparietal FC. The testing run is similar to the training, which is divided into 15 blocks (Figure 3b). However, during the testing run, we do not use the optimizer to calculate optimized parameters but only use the optimized parameters obtained from Training 1,2.

RESULTS

On the training 1,2 runs, the experimental and control groups' success to optimize the tACS parameters to get the highest or lowest frontoparietal connectivity (Figure 4). At the end of training 2, the experimental group vs. the control group has frontoparietal gap connectivity. On the testing-training1 average run (training1 as a baseline), the experimental group showed higher improvement of frontoparietal connectivity rather than control group (Figure 5a) [experimental group: mean=0.06, SD=0.09; control group: mean/SD=-0.1/0.06; t(9)=3.31, p=0.009]. Furthermore, within-group analysis of the percentage of 2-back task average (testing-training1), the experimental group improves accuracy to answer correctly rather than the control group [experimental group: mean/SD=6.02/3.96; control group: mean/SD=-2.41/7.95; t(9)=2.30, p=0.047] (Figure 5b).

DISCUSSION and CONCLUSION

The closed-loop tACS-fMRI is feasible and can potentially find the optimal tACS parameters for modulating frontoparietal connectivity. The preliminary results show the optimized tACS parameters can enhance frontoparietal connectivity more in the active stimulation as compared to control. Furthermore, the optimized tACS parameters also improve working memory accuracy in the active stimulation compared to the control condition. This study supports the feasibility of concurrent tACS-fMRI and potentials for its efficacy.

Acknowledgements

This work was supported by the Laureate Institute for Brain Research.