Subjects. Twenty healthy English native speakers (7 males, mean age = 23 years ± 4, range from 20 to 36 years) participated in this study. Right-handedness was confirmed using the Edinburgh Handedness Inventory62. All subjects provided informed written consent. The study was approved by the local ethics committee.
Experimental design and procedure. All subjects had an fMRI and MRS at rest at the beginning of the study. They performed a semantic association task and a picture matching task as a control task during fMRI. We used the picture version of semantic association task employed by previous studies31, 63. The semantic association task required subjects to select which of two pictures was more related in meaning to a probe picture. Three pictures were presented on the screen, a probe picture on the top, the target, and unrelated picture at the bottom (Fig. 1B left). In the control task, subjects had to select which of two patterns was identical to a probe pattern (Fig. 1B right). The items for the pattern matching task were created by scrambling the pictures used in the semantic association task. An fMRI scanning had 9 blocks of each task (interleaved order, A-B-A-B). Fixation blocks for 4000ms were interleaved with task blocks. A task block had 4 trials of each task and a trial started with 500ms fixation followed by the stimuli for the duration of 4500ms.
After the MRI, all subjects had two TMS sessions on different days. In each session, subjects received TMS stimulation at the left ATL or control site (occipital pole). The order of stimulation was counterbalanced across subjects. A session consisted of a baseline block (No-TMS) and the after TMS block (post cTBS). The baseline was performed before or 50mins after the stimulation. The order of blocks was counterbalanced across subjects. In each session, subjects performed the same semantic association task and the control task. Tasks had 63 trials and a trial started with 500ms fixation then the stimuli were presented until response or 3000ms. E-prime software (Psychology Software Tools Inc., Pittsburgh, USA) was used to display stimuli and to record responses.
fMRI-guided transcranial magnetic stimulation. To guide a TMS target site, we used the individual fMRI results of the contrast of interest (semantic > control). The maximal peak activation in the ATL (MNI coordinates) was selected and converted to the untransformed individual naïve space coordinate. The target site was used to guide the frameless sterotaxy, a Brainsight TMS-fMRI co-registration system (Rogue Research, Montreal, Canada). TMS target sites were located within the left anterior/ventrolateral ATL. Table 1 and Fig. 1C summarise the maximal peak activation and the actual TMS target site on the normalized brain (the lateral view). Occipital pole (Oz) was used as a control site using international 10-20 system.
Table 1
fMRI-guided TMS sites for individuals
|
Maximal peak coordinates
|
|
TMS target coordinates
|
|
x
|
y
|
z
|
|
x
|
y
|
z
|
sub01
|
-32
|
-10
|
-34
|
|
-60
|
-10
|
-34
|
sub02
|
-38
|
-10
|
-28
|
|
-66
|
-10
|
-28
|
sub03
|
-48
|
-16
|
-29
|
|
-65
|
-16
|
-29
|
sub04
|
-33
|
-13
|
-38
|
|
-57
|
-13
|
-38
|
sub05
|
-57
|
-19
|
-26
|
|
-68
|
-19
|
-26
|
sub06
|
-45
|
5
|
-35
|
|
-58
|
5
|
-35
|
sub07
|
-48
|
5
|
-32
|
|
-58
|
5
|
-32
|
sub08
|
-33
|
-13
|
-29
|
|
-65
|
-13
|
-29
|
sub09
|
-45
|
11
|
-32
|
|
-56
|
11
|
-32
|
sub10
|
-36
|
8
|
-38
|
|
-54
|
8
|
-38
|
sub11
|
-39
|
-16
|
-26
|
|
-68
|
-16
|
-26
|
sub12
|
-33
|
-10
|
-32
|
|
-60
|
-10
|
-32
|
sub13
|
-33
|
2
|
-36
|
|
-58
|
2
|
-36
|
sub14
|
-33
|
-13
|
-29
|
|
-65
|
-13
|
-29
|
sub15
|
-54
|
-1
|
-20
|
|
-63
|
-1
|
-20
|
sub16
|
-48
|
17
|
-32
|
|
-54
|
17
|
-32
|
sub17
|
-48
|
8
|
-35
|
|
-57
|
8
|
-35
|
sub18
|
-33
|
-13
|
-35
|
|
-60
|
-13
|
-35
|
sub19
|
-33
|
-13
|
-35
|
|
-59
|
-13
|
-35
|
sub20
|
-48
|
-1
|
-35
|
|
-59
|
-1
|
-35
|
Theta-burst stimulation. cTBS was delivered over the left ATL using a Magstim Super Rapid stimulator with a figure-of-eight coil (70mm standard coil, MagStim Company, Whitland, UK) according to Huang et al64. cTBS was applied at 80% of the resting motor threshold (RMT). RMT was defined as a minimal intensity of stimulation inducing motor evoked potentials in the contralateral FDI muscle in at least 5 of 10 stimulation trials at the optimal scalp position. The average stimulation intensity was 47% ranging from 42–60%.
Definition of responders. The aim of this study was to investigate whether inter-individual differences in the behavioural performance response to cTBS were related to the different neural profiles of the stimulated region and the related-brain network before the stimulation. Therefore, responders and non-responders were classified according to their semantic performance changes after the ATL stimulation: subjects showing a decrease in task performance at the post cTBS compared to the baseline were defined as responders; whereas subjects showing no changes or an increase in their task performance after the cTBS were defined as non-responders. This criterion ensured that responders had a task-specific TMS effect (inhibitory) as expected by the stimulation protocol.
fMRI data acquisition and analysis. fMRI images were acquired on a 3T Philips Achieva scanner using a 32-channel head coil with a SENSE factor 2.5 using a dual-echo sequence with the following parameters: 42 slices, 96 x 96 matrix, 240 x 240 x 126mm FOV, in-plane resolution 2.5 x 2.5, slice thickness 3mm, TR = 2.8s, TE = 12ms and 35ms, 258 volumes. The sequence was developed to maximise signal-to-noise (SNR) in the ATL by Halai et al65. A high-resolution T1-weighted structural image was acquired using a 3D MPRAGE pulse sequence with following parameters: 200 slices, in-planed resolution 0.94 x 0.94mm slice thickness 0.9mm, TR = 8.4ms, TE =3.9ms.
fMRI data were analysed using Statistical Parametric Map (SPM8, http://www.fil.ion.ucl.ac.uk/spm/). First, dual gradient echo images were realigned to the mean image of each time series and corrected for slice timing by shifting the signal measured in each slice relative to the acquisition of the middle slice. Then, the dual gradient echo images were averaged using in-house MATLAB code developed by Halai et al65. The mean EPI volumes were coregistered with the structural T1-weighted image. All images were spatially normalized to the MNI template using the DARTEL (diffeomorphic anatomical registration through an exponentiated lie algebra) toolbox66 and smoothed with an isotropic Gaussian kernel of 8mm full-with at half-maximum.
A general linear model (GLM) was used for statistical analyses. The three experimental conditions (semantic, control, and fixation) were modelled using boxcar stimulus functions convolved with a canonical hemodynamic response function. Six head motion parameters resulting from the realignment were entered as covariates to remove movement-related variance. The time series of each voxel were high-pass filtered at 1/128Hz. A contrast of interest (sematic > control) for each participant were calculated. Voxels were considered significant on the individual level if passing a threshold of p uncorrected < 0.001 (for the TMS target site). For the group-level analysis, the estimations of the contrast of interest were entered into one-sample t-tests. Clusters were considered significant when passing a threshold of p FWE−corrected < 0.05, with at least 100 contiguous voxels.
Marsbar67 was used for region of interest (ROI) analysis. Six ROIs based on the result of group level analysis were defined as a sphere with a radius of 5mm from the contrast of interest (semantic > control). The ROIs defined as the semantic network included the ATL (peak activation left: -36, -6, -36; right: 33, -6, -36), vlPFC (peak activation left: -48, 21, 24; right: 57, 24, 21), and pMTG (peak activation left: -57, -48, -3; right: 54, -69, 12).
Functional connectivity toolbox (CONN) (http://web.mit.edu/swg/software.htm) was used for computing temporal correlation between the defined ROIs. Pre-processed fMRI images were registered into the toolbox with the six ROIs. Connectivity analyses provided ROI-to-ROI functional connectivity estimations for the experimental conditions (semantic, control, and baseline). The head motion parameters were entered as regressors and all voxels were filtered (0.01 < ƒ < Inf) to decrease the effect of low-frequency drift. CompCor strategy implemented in the toolbox removed several sources of noise from white matter, cerebral fluid, and the others. Functional connectivity (Fisher’s Z-transformed Pearson correlation coefficient) among ROIs was averaged for network-level analyses.
MRS data acquisition and analysis. GABA-edited MEGA-PRESS spectra were acquired from an ATL voxel (35 × 25 × 15mm) and an occipital control voxel (30 × 30 × 30mm). The ATL voxel was positioned on the left anterior/lateral temporal lobe, excluding hippocampus (Fig. 1C). The occipital voxel was aligned with the occipital midline covering both hemispheres (Fig. 1C). The following parameters were used: repetition time = 2000ms, echo time = 68ms. Spectra were acquired in interleaved blocks of 4 scans with application of the MEGA inversion pulses at 1.95 ppm to edit the GABA signal and at 7.45 ppm as control; 79 repeats at the ATL and 74 repeats at the OCC. A total of 1024 sample points were collected at a spectral width of 2 kHz. Each MRS voxel took approximately 10mins to complete. Quantification was conducted using the Advanced Magnetic Resonance (AMARES) in the Java-based magnetic resonance user’s interface (jMRUI.1, EU project www.jmrui.eu) 68The water resonance was removed using the Hankel Lanczos Singular Valve Decomposition (HLSVD) algorithm69. To improve the display of the spectra, line broadening of 7 Hz was used. No time-domain filtering was performed on the data before analysis by AMARES. All metabolite resonances were measured and a ratio was calculated for NAA, GABA and Glx (a combined measure of glutamate and glutamine). No correlations of GABA and Glx levels between the ATL and OCC were found (ps > 0.47).
To examine partial volume effects on MRS VOIs, the T1-weighted anatomical images were segmented into gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF) using SPM8. Then voxel registration was performed using custom-made scripts developed in MATLAB by Dr. Nia Goulden, which can be accessed at http://biu.bangor.ac.uk/projects.php.en. The scripts generated a mask for voxel location by combining location information for the Philips SPAR file with orientation and location information contained within the T1 image. The calculation of partial volume within the voxels provided the percentage of each tissue type within the relevant voxels. Partial correlation analyses were performed with the percentage of each tissue (GM, WM) as covariates accounting for the partial volume effects in the voxels.