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RESEARCH ARTICLE
Comparing TMS perturbations to occipital and
parietal cortices in concurrent TMS-fMRI
studies—Methodological considerations
Joana Leitão
1,2,3
*, Axel Thielscher
1,4,5
, Johannes Tuennerhoff
1,6
, Uta Noppeney
1,2
1Max Planck Institute for biological Cybernetics, Tu¨bingen, Germany, 2Computational Neuroscience and
Cognitive Robotics Centre, University of Birmingham, Birmingham, United Kingdom, 3Laboratory for
Behavioral Neurology and Imaging of Cognition, Department of Neuroscience, University of Geneva, Geneva,
Switzerland, 4Department of Electrical Engineering, Technical University of Denmark, Lyngby, Denmark,
5DRCMR, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark, 6University Clinic of Neurology,
Tu¨bingen, Germany
*joana.leitao@tuebingen.mpg.de
Abstract
Neglect and hemianopia are two neuropsychological syndromes that are associated with
reduced awareness for visual signals in patients’ contralesional hemifield. They offer the
unique possibility to dissociate the contributions of retino-geniculate and retino-colliculo cir-
cuitries in visual perception. Yet, insights from patient fMRI studies are limited by heteroge-
neity in lesion location and extent, long-term functional reorganization and behavioural
compensation after stroke. Transcranial magnetic stimulation (TMS) has therefore been
proposed as a complementary method to investigate the effect of transient perturbations on
functional brain organization. This concurrent TMS-fMRI study applied TMS perturbation to
occipital and parietal cortices with the aim to ‘mimick’ neglect and hemianopia. Based on the
challenges and interpretational limitations of our own study we aim to provide tutorial guid-
ance on how future studies should compare TMS to primary sensory and association areas
that are governed by distinct computational principles, neural dynamics and functional
architecture.
Introduction
Neglect and hemianopia are two neuropsychological syndromes that are associated with
reduced awareness for visual signals in patients’ contralesional hemifield. While neglect results
primarily from right inferior parietal and temporal lesions impairing spatial and temporal
attention [1–5], hemianopia is caused by lesions to primary visual cortex leading to selective
visual perceptual deficits [6]. Contrasting these two syndromes therefore offers the unique pos-
sibility to dissociate retino-geniculate and retino-colliculo circuitries whereby ‘unaware’ visual
signals can impact human behaviour [7–9]. However, the insights gained from patient fMRI
studies are limited by the fact that lesions are often widespread and heterogeneous potentially
affecting underlying white matter tracts resulting in a large variability in behavioural deficits
PLOS ONE | https://doi.org/10.1371/journal.pone.0181438 August 2, 2017 1 / 20
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OPEN ACCESS
Citation: Leitão J, Thielscher A, Tuennerhoff J,
Noppeney U (2017) Comparing TMS perturbations
to occipital and parietal cortices in concurrent
TMS-fMRI studies—Methodological
considerations. PLoS ONE 12(8): e0181438.
https://doi.org/10.1371/journal.pone.0181438
Editor: Andrea Antal, University Medical Center
Goettingen, GERMANY
Received: February 20, 2017
Accepted: June 30, 2017
Published: August 2, 2017
Copyright: ©2017 Leitão et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: All relevant data are
within the paper and its supporting information
files.
Funding: This work was supported by the
European Research Council (ERC - multsens) and
the Max Planck Society.
Competing interests: The authors have declared
that no competing interests exist.
and performance. Further, patients’ symptoms and neural mechanisms may have changed as a
result of long-term functional reorganization and compensatory behavioural adaptation after
stroke or other permanent focal lesions.
Transcranial magnetic stimulation (TMS) allows one to circumvent these problems by tran-
siently perturbing ongoing activity to a particular task-relevant cortical region under the strict
experimental control of the applied TMS protocol. In addition, when combined with func-
tional magnetic resonance imaging (fMRI) it is possible to measure TMS effects not only
locally in the stimulated area but also in remote brain areas thereby providing insights into the
dynamic interactions between cortical areas [10–14].
We used concurrent TMS-fMRI as a complementary technically challenging transient per-
turbation approach to compare the functional contributions of parietal and occipital regions
to the network of regions involved in visual perception and attention. In a sustained spatial
attention paradigm participants had to detect low contrast visual targets that were presented in
their left lower visual quadrant on 50% of the trials. The contrast of the target was adjusted
individually for each participant to enable approximately 70% detection rate. In two separate
sessions, we applied 4 TMS pulses (10 Hz) starting 200 ms after trial begin (i.e. 100 ms after tar-
get onset on target present trials) to the right intraparietal sulcus or the right occipital cortex
(BA17/BA18) or during a third additional control Sham-TMS session. TMS pulses were
applied at intensity that did not significantly affect behavioural performance in any of the
three conditions. Critically, while permanent lesions to both primary visual and higher order
association areas in parietal cortices are known to result in deficits of perceptual awareness,
they are located at distinct cortical hierarchical levels. Hence, comparing the effects of TMS to
occipital and parietal cortices on visual processing (i.e. state-dependent TMS effect: interaction
between visual input and TMS) allows us to elucidate the underlying neural mechanisms. We
expected TMS to occipital cortices to substantially reduce visual evoked responses in lower
level visual areas with partially preserved activations in parietal cortices mediated via the intact
retino-colliculo circuitry. By contrast, TMS to parietal cortices would predominantly affect
visual processing in higher order visual areas.
Starting from the results and challenges of our study this communication will focus pre-
dominantly on the methodological and interpretational limitations when comparing TMS
effects in primary sensory and higher order association regions that are governed by distinct
functional principles. We aim to provide tutorial guidance for future concurrent TMS-fMRI
experiments intended to mimick and complement permanent lesion studies in neuropsycho-
logical patients.
Materials and methods
Participants
Ten right-handed participants (4 male; mean age: 31.5 years; standard deviation: 8.1; Edin-
burgh Handedness inventory score (mean ±SD) of 78±16.8) with no history of neurological
illness, normal or corrected-to-normal vision and reported normal hearing took part in the
study after giving written informed consent. Because of technical failure two participants did
not participate in the experiments with occipital TMS stimulation. The current comparison
between TMS to occipital and parietal cortices therefore focuses on 8 participants that took
part in both parts.
The study was approved by the Human Research Ethics Committee of the Medical Faculty
at the University of Tu¨bingen. The data from IPS stimulation have been included in a previous
report [15].
Methodological considerations on the comparison between occipital and parietal TMS
PLOS ONE | https://doi.org/10.1371/journal.pone.0181438 August 2, 2017 2 / 20
Experimental design and task
In a sustained spatial attention paradigm, participants detected visual targets that were pre-
sented in a placeholder in the left lower quadrant on 50% of the trials. Across sessions we
manipulated whether parietal, occipital or Sham-TMS was applied. Moreover, we also manip-
ulated the presence vs. absence of concurrent task-irrelevant auditory inputs across runs. In
short, the paradigm conformed to a 2x2x3 factorial design with factors: (i) task-relevant visual
input (V present, V absent) (ii) auditory context (A present, A absent) and (iii) TMS condition
(right occipital cortex (Occ), right anterior IPS, Sham) (Fig 1A). Hence, our design included
the following 4 trial types: (i) visual target present, without sound (V), (ii) visual target absent,
without sound (¬V)), (iii) visual target present with sound (AV) and (iv) visual target absent
with sound (A). Each trial type was presented with Occ-, IPS- and Sham-TMS resulting in 12
conditions in total. We limited the presentation of the visual target to the left hemifield because
right parietal and occipital TMS has previously been shown to elicit different effects for contra-
and ipsi-lateral visual stimuli (e.g. [16,17,18]). In all trial types, participants reported whether
Fig 1. Experimental design. (A) 2x2x3 factorial design manipulating (i) task-relevant visual input (V present, V absent), (ii) auditory context (A
present, A absent) and (iii) TMS condition (Occ, IPS, Sham). (B) Timeline example of stimuli presentation. Blocks of 12 trials started and ended with
a grey fixation cross and were interleaved with baseline periods, during which the fixation cross turned red. A trial began when the fixation cross
turned blue. In target present trials, the visual stimulus was presented 100 ms after trial begin. After a total period of 600 ms the fixation cross turned
back to grey and remained like this until the next trial. (C) Illustration of the concurrent TMS-fMRI protocol and stimuli presentation timing during
auditory present runs. Within a block the fixation cross was grey during volume acquisition and blue during the acquisition gaps. At 100 ms after trial
begin (i.e. 2790 ms after begin of volume acquisition), the task-relevant visual stimulus was either present (first depicted trial) or absent (second
depicted trial). Bursts of 4 TMS pulses were applied during acquisiton gaps at 10 Hz and started 100 ms after the target onset time (i.e. 2890 ms after
begin of volume acquisition). (D) Illustration of approximate coil positions during i) occipital and ii) parietal stimulation.
https://doi.org/10.1371/journal.pone.0181438.g001
Methodological considerations on the comparison between occipital and parietal TMS
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they had detected the visual target (see Visual and auditory stimuli) via a two choice key press.
They were instructed to use a strict decision criterion and report that they had detected a target
only when being confident and to report ‘unseen’ otherwise. Participants fixated a cross pre-
sented in the centre of the screen throughout the entire scanning session.
At the beginning of each trial, the fixation cross changed its colour from grey to blue (Fig
1B). After 100 ms the visual target was presented for a duration of 16 ms with 50% probability.
On each trial, we applied bursts of 4 TMS pulses (or Sham-TMS) 200 ms after trial onset (i.e.
100 ms after target onset in V and AV trials) (see Data acquisition and TMS procedures;Fig
1C). At 600 ms of trial onset, the fixation cross turned back to grey for a duration of 2690 ms
until a change in the colour of the fixation cross indicated the onset of the next trial. The inter-
stimulus interval amounted thus to 3290 ms, equalling one TR of the EPI acquisition (see Data
acquisition and TMS procedures).
In half of the runs, a sound (see Visual and auditory stimuli) was presented synchronously
with target onset, regardless of the presence/absence of the task-relevant visual input. Hence,
the sound did not predict the presence of the visual stimulus. Nevertheless, the presence of the
sounds may have reduced participants’ uncertainty about the temporal onset of the visual tar-
get. Auditory sounds were included because it has been shown that the presence of a synchro-
nously presented auditory sound can facilitate the detection of contra-laterally presented
visual signals in hemianopia and neglect patients [19]. Yet, the effect of auditory stimuli will
not be examined further in this report, which focuses on the methodological aspects of stimu-
lating lower sensory and higher-order association cortices.
Blocks of twelve trials were interleaved with fixation baseline periods of 13 seconds. Each
block contained an initial period of 2790 ms to signal the upcoming appearance of the first
trial of the block (see Fig 1C). Additionally, to avoid carry-over effects of the response to the
last trial into the baseline periods, an extra 3290 ms were introduced at the end of each block.
These time lengths were chosen based on the EPI acquisition (see Data acquisition and TMS
procedures;Fig 1C). Therefore, each block effectively consisted of 13 TRs of the EPI acquisi-
tion, resulting in a block length of about 43 seconds. The fixation periods were indicated by a
red fixation cross. The beginning and end of the activation blocks were indicated by a grey fix-
ation cross and the detection trials by a blue fixation cross. Hence, the colour of the fixation
cross indicated changes in the attentional settings: while blue and grey were associated with a
high attentional load, red indicated little attentional demands.
Each run encompassed seven activation blocks with 42 target present trials and 42 target
absent trials (i.e. 84 trials per run). The data of the main experiment were acquired in three ses-
sions on different days with each session including eight runs. Across days/sessions, we manip-
ulated whether Occ-, IPS- or Sham-TMS was applied. On each day, we manipulated the
auditory context across runs within an ABBAABBA design counterbalanced across partici-
pants (i.e. 4 ‘auditory context present (A)’ and 4 ‘auditory context absent (B)’ runs per day).
The visual target presence was randomized as trials within and across runs. Hence, we
obtained a total of 168 trials for each condition (e.g. number of trials for condition ‘visual tar-
get present, auditory context present, IPS-TMS: 42 target-present trials per run x 4 runs with
auditory context present x 1 TMS session for IPS). Each participant was trained in a minimum
of six runs prior to the actual fMRI experiment.
Visual and auditory stimuli
Visual stimuli. The task-relevant visual stimulus consisted of a small (9x9 pixels, visual
angle: 0.52˚) square presented for one frame (i.e. 16 ms) on a grey background. The visual
stimulus was presented in the centre of a blue placeholder (40x40 pixels, visual angle: 2.3˚) that
Methodological considerations on the comparison between occipital and parietal TMS
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was positioned 12˚ left and 5˚ down relative to the fixation cross. The placeholder was dis-
played throughout the entire run (i.e. including fixation periods).
The ‘overall grey level of the target square’ was adjusted with the help of dithering for each
participant in a Quest Procedure [20] inside the scanner aiming at a detection threshold of
70% and using the same parameters as in the main experiment. In other words, the ‘overall
grey level’ was adjusted by manipulating the density of white pixels within the square. This
detection threshold was selected to place increased demands on cognitive resources such as
spatial attention. Importantly, identical grey levels were used across Occ, IPS and Sham stimu-
lation and across auditory contexts.
Auditory stimuli. To ensure that auditory stimuli were easily segregated from the scanner
noise and TMS clicks we generated an auditory stimulus by adding sinusoidal tones with base
frequencies of 130.81 Hz, 164.81 Hz and 196 Hz and the following six terms of their respective
geometric progressions (i.e. adding the terms 2
n
f, where f represents each of the three base
frequencies and 1 n6). Hence, the auditory sound spanned a total of seven octaves and
ranged from 130.81 Hz to 12543.58 Hz. The duration of each auditory stimulus was 40 ms.
Next, we convolved this auditory signal with spatially specific head-related transfer func-
tions (HRTFs) to create a left localized stimulus. This will provide participants with audiovi-
sual spatial localization cues and thereby enhance audiovisual integration. The HRTFs were
pseudo-individualized by matching participants’ head width, height, depth and circumference
to the anthropometry of participants in the CIPIC database [21].
Stimulus presentation
Visual and auditory stimuli were presented using Psychophysics Toolbox version 3.0.10 [22,
23] running on MATLAB 7.9 (MathWorks Inc, MA, USA) and a Macintosh laptop running
OS-X 10.6.8 (Apple Inc, CA, USA). The visual stimulus was back-projected onto a frosted
Plexiglas screen using a LCD projector (JVC Ltd., Yokohama, Japan; resolution: 800x600 pix-
els, refresh rate: 60 Hz, viewing distance: 48 cm) visible to the participant through a mirror
mounted on the MR head coil. Auditory stimuli were presented via MR-compatible electrody-
namic headphones at a sampling frequency of 44100 Hz (MR Confon GmbH). Furthermore,
earplugs were used to attenuate both scanner and TMS noise.
Participants indicated their response (i.e. visual target seen or unseen) with their right hand
using an MR-compatible custom-built button device connected to the stimulus computer.
TMS sites
TMS was applied over the right anterior IPS and the right occipital cortex (Occ) as experimen-
tal sites and Sham TMS was included as a control condition.
For the parietal stimulation site, we selected the MNI coordinates (x = 42.3, y = -50.3,
z = 64.4) that had previously been associated with impairment of visuospatial processing by
Oliver et al [24].
For the occipital stimulation site, we determined the MNI coordinates in an initial pilot
hunting procedure outside the MRI scanner in seven additional participants. The hunting pro-
cedure used the same visual display and task as in the main experiment, established protocols
for visual suppression (i.e. single TMS pulse applied 100 ms after target onset; [25]) and a 3x3
grid of coil positions with an equidistant spacing of 1 cm, placed over the right hemisphere
guided by Thielscher et al. [26]. The positions showing larger decrements in detection perfor-
mance across participants were located in the middle row of the grid (hit rates (±SD) from left
to right were 41 ±26%, 43 ±26% and 42 ±16%, respectively). As the final location for occipital
TMS stimulation we selected the MNI coordinates that were associated with the maximal
Methodological considerations on the comparison between occipital and parietal TMS
PLOS ONE | https://doi.org/10.1371/journal.pone.0181438 August 2, 2017 5 / 20
decrement in detection performance across participants (MNI coordinates: x = 19.42, y =
-102.35, z = 13.4). Based on cytoarchitectonic probabilistic mapping [27] this position is
located in BA17/18.
With the bursts of 4 pulses and the stimulation intensity used in the TMS-fMRI experiment
(see Data acquisition and TMS procedures), this position did not induce peripheral nerve stim-
ulation that could cause discomfort to the participants. However, occipital stimulation inside
the scanner inevitably involves lying on the TMS coil, which is associated with additional
discomfort.
Individual stimulation coordinates for both experimental TMS sites were determined by
inverse transforming the MNI coordinates for parietal and occipital targets into native space
using the parameters obtained from spatial normalization. These coordinates were entered in
the neuronavigation system, which was used to mark the desired position on the participants’
skull. For occipital stimulation, the coil was oriented so that the electric field in the stimulation
hotspot was oriented from lateral to medial for the second half of the biphasic stimuli. For IPS
stimulation the coil was oriented so that the current flow was from anteromedial to posterolat-
eral in the second half of the stimulus (Fig 1D).
A posteriori coil reconstruction of the coil position was based on custom-written MATLAB
(MathWorks Inc, MA, USA) scripts. The centre of the TMS coil and its circumference were
marked with Vitamin E capsules and a water tube, respectively, to enable the automatic co-reg-
istration of the coil representation in the FLASH images with a pre-acquired reference image
of the coil. The coil representation included a line passing perpendicularly (to coil surface)
through the centre of the coil, which allowed determining the coordinates where it first
touched the cortical surface. In addition, the subject’s head in the FLASH images was co-regis-
tered to the high-resolution structural scan. Thereby, we were able to determine the coil posi-
tion inside the scanner with respect to an individual’s structural MRI. Across participants, the
target IPS coordinates were obtained with a mean deviance of 9 mm ±2.5 (mean, SD). The
across-participants mean coordinate in MNI space was (x = 34.7, y = -52.8, z = 63.5). The
across-participants mean of the target Occ coordinates in MNI space was (x = 18.8, y = -100.9,
z = 11.4) with a mean deviance of 5.1 mm ±1.7 (mean, SD). Due to the quadratic decay of the
TMS-induced magnetic field and the use of a fixed stimulation intensity across all participants
and stimulation sites (see Data acquisition and TMS procedures), it is important to make sure
that coil-cortex distances do not significantly differ between the two TMS conditions, as these
could confound the comparisons of the TMS-induced cortical effects between the two sites.
For each participant and each stimulation location, we calculated the Euclidean distance
between the centre of the coil and the reached cortical coordinates (i.e. the location where the
normal to the coil intersects with the brain surface). A paired t-test showed that the distances
between coil and this location defined on the brain surface did not differ significantly for the
two stimulation sites (t
(8)
= -1.764, p= 0.12). These results suggest that differences in TMS
effects for the different TMS sites cannot be explained by differences in the coil-brain surface
distances across participants.
In the sham condition, 2 cm thick plastic plates were fixed between the TMS coil and the
skull. Given the quadratic decay of the TMS-induced magnetic field, this Sham condition pre-
cluded the effects of direct brain stimulation. Indeed, when tested over the finger region of the
motor cortex, this Sham condition did not induce muscular twitches on pre-activated finger
muscles even at 100% of total output intensity. During the Sham condition the coil was placed
over the right hemisphere in a middle position between experimental locations, given the
space constraints inside the MR coil. Critically, the Sham-TMS condition tightly controlled for
the TMS side effects such as the TMS-noise and feelings of vibrations. Furthermore, compar-
ing IPS-TMS or Occ-TMS with Sham-TMS did not elicit significant activations in the auditory
Methodological considerations on the comparison between occipital and parietal TMS
PLOS ONE | https://doi.org/10.1371/journal.pone.0181438 August 2, 2017 6 / 20
cortex. Hence, we concluded that this particular application of Sham-TMS inside the scanner
is a better control than low intensity TMS that does not control effectively for auditory con-
founds (see Data acquisition and TMS procedures and [14]).
Data acquisition and TMS procedures
A 3T TIM Trio System (Siemens, Erlangen, Germany) was used to acquire both a T1-weighted
three-dimensional high-resolution structural image (MPRAGE, 176 sagittal slices, TR = 2300
ms, TE = 2.98 ms, TI = 1100 ms, flip angle = 9˚, FOV = 240 mm x 256 mm, image matrix = 240
x 256, voxel size = 1 mm x 1 mm x 1 mm, using a 12-channel head coil) and T2-weighted
axial echoplanar images (EPI) with blood oxygenation level dependent (BOLD) contrast
(GE-EPI, TR = 3290 ms, TE = 35 ms, flip angle = 90˚, FOV = 192 mm x 192 mm, image matrix
64 x 64, 40 axial slices acquired sequentially in ascending direction, slice thickness = 3 mm,
interslice gap = 0.3 mm, voxel size = 3 mm x 3 mm x 3.3 mm, using a 1-channel Tx/Rx head
coil). Each participant took part in a total of eight experimental runs per TMS condition. A
total of 124 volume images were acquired for each run.
After each EPI run, a fast structural image (fast low-angle shot [FLASH], 100 axial slices,
TR = 564 ms, TE = 2.46 ms, FOV = 256mm x 256 mm, image matrix = 256x256, voxel
size = 1x1x3 mm) was acquired to enable a posteriori reconstruction of the TMS coil position
inside the scanner, as described elsewhere [14].
The EPI sequence was adapted for concurrent TMS-fMRI experiments by introducing gaps
of 600 ms after every volume acquisition. Each gap was introduced to allow the delivery of four
TMS pulses without interference with image quality [28,29]. While this fixed relationship
between TMS and MR acquisition does not enable continuous sampling of the hemodynamic
response function, it is a common practice in concurrent TMS-fMRI study to minimize image
artefacts caused by the application of a TMS pulse. Bursts of four pulses at 10 Hz were applied
every trial, with the first pulse applied 2890 ms after begin of volume acquisition, i.e., 100 ms
after stimulus onset (Fig 1C). TMS pulses were applied after stimulus onset in order to mini-
mize crossmodal interaction effects between our stimuli and the TMS induced auditory and
somatosensory side effects [14,30].
Similar TMS protocols have been used over the parietal cortex in TMS studies outside the
scanner [24,31] and in concurrent TMS-fMRI studies [10–12,32–34] investigating the effects
of parietal TMS on visuospatial processing. However, occipital TMS studies have mainly been
performed using a single or double pulse TMS, in which an appropriate timing relative to stim-
ulus onset (effective time window: 80–110 ms) is crucial in the generation of suppression
effects [35,36]. To allow for comparison between parietal and occipital TMS conditions, we
also applied bursts of 4 TMS pulses in the occipital stimulation with the first pulse being
applied within the classical effective suppression time window and the remaining three pulses
in a wider window that may affect higher order visual processing (see [25]). Likewise, the TMS
intensities of each pulse were the same (see below) across parietal and occipital stimulation
conditions. Consequently, the intensity of the occipital stimulation was most likely in a range
where it perturbs activity locally under the coil and in remote brain areas as well as effective
connectivity between brain areas rather than actively impairing visual detection performance.
Indeed, previous studies have shown that visual evoked potentials can be influenced at TMS
intensities that do not yet affect participants’ visual discrimination performance (e.g. [37]).
Biphasic stimuli were delivered using a MagPro X100 stimulator (MagVenture, Denmark)
and a MR-compatible figure of eight TMS coil (MRi-B88), using the same coil-holding device
as described in Moisa et al [29]. To prevent the propagation of RF noise into the MR room, the
TMS stimulator was placed outside the MR room and was connect to the TMS coil via a high-
Methodological considerations on the comparison between occipital and parietal TMS
PLOS ONE | https://doi.org/10.1371/journal.pone.0181438 August 2, 2017 7 / 20
current filter (E-LMF-4071; ETS- Lindgren, St. Louis, MO, USA) attached to the copper
shielding of the MR room [29]. During occipital stimulation the coil was directly placed on a
cushion in the RF coil with the major axis oriented parallel to the scanner bore axis and the
cable pointing to the right relative to participants’ heads ([38] and Fig 1D).
During IPS and Occ stimulation, a fixed TMS intensity of 69% of total stimulator output
was used for all participants. This corresponded to 125% of the mean resting motor threshold,
as determined across twenty-four participants of prior studies using the same coil. To ensure
similar somatosensory side effects between experimental conditions and Sham-TMS the TMS
intensity was increased to 75% of total stimulator output during the Sham condition based on
the subjective report of two naïve participants that participated in a pilot test.
Extensive image quality tests of our setup are reported elsewhere ([29], [39]: Supplementary
Material). For completeness, we acquired EPI data with a phantom using the same experimen-
tal design. After realignment, data were entered in a first level analysis using the same model as
for the real participants. Computing all the relevant contrasts (height threshold: p<0.01
uncorrected) yielded only a spurious and randomly distributed pattern.
fMRI data analysis
The fMRI data were analysed using SPM8 (Wellcome Department of Imaging Neuroscience,
London; www.fil.ion.ucl.ac.uk/spm) [40]. Scans from each participant were realigned using
the first as a reference, unwarped, spatially normalized into MNI space, resampled to a spatial
resolution of 2 x 2 x 2 mm
3
, and spatially smoothed with a Gaussian kernel of 8 mm full-width
at half-maximum. The time series of all voxels were high-pass filtered to 1/128 Hz. The first 3
volumes were discarded to allow for T1-equilibration effects.
The fMRI experiment was modeled as a mixed block-event-related design. Individual trials
were modeled as events and entered into a design matrix after convolution with a canonical
hemodynamic function and its first temporal derivative. Each run included separate regressors
for visual present vs. visual absent trials as two types of events. In addition to modeling these
two trial types, our statistical model modeled block begin and end (i.e. the periods during
which the fixation cross was grey at the beginning and end of a block; see Experimental design
and task) as mini blocks of 2.69 s and 3.29 s duration, respectively. These additional regressors
were included to explicitly account for the increased attentional demands at the beginning and
end of the task blocks (note that models that did not include these additional regressors pro-
vided basically equivalent results for contrasts combining the remaining regressors). To allow
for a more efficient estimation we concatenated the four runs for each of the 3 (Occ, IPS,
Sham-TMS) x 2 (auditory present vs. absent) combinations and modeled the run-specific
means as separate regressors. Hence, the factors of auditory context and TMS were manipu-
lated across runs and sessions, respectively. Nuisance covariates included the realignment
parameters to account for residual motion artifacts.
For each participant, condition specific effects were estimated according to the general lin-
ear model by creating contrast images of each condition (i.e. limited to the canonical hemody-
namic response) relative to the arbitrary baseline. Hence, the baseline controls for non-specific
effects caused by the positioning of the coil (e.g. discomfort during the session with occipital
TMS). The statistical comparisons (see details listed below) were entered into independent sec-
ond-level one-sample t-tests to allow for random effects analyses and inferences at the popula-
tion level [41].
For full characterization of the data, we report activations at the cluster level at p<0.1 cor-
rected for multiple comparisons (family-wise error rate) within the entire brain based on non-
parametric permutation testing [42,43] using an auxiliary uncorrected voxel threshold of
Methodological considerations on the comparison between occipital and parietal TMS
PLOS ONE | https://doi.org/10.1371/journal.pone.0181438 August 2, 2017 8 / 20
p= 0.01. However, we only discuss activations that are significant at p<0.05 corrected for mul-
tiple comparisons in the entire brain. Moreover, based on our apriori hypothesis and questions
we report activations at the voxel level corrected for multiple comparisons within right IPS
and right lower level visual areas (i.e. V1 + V2) as our regions of interest (ROI) where Occ and
IPS-TMS were applied. The regions of interest were defined based on cytoarchitectonic proba-
bilistic mapping [27]. Right IPS combined right hIP1, hIP2 and hIP3, while low level right
visual regions included right hOC1 and hOC2.
Main effects of task-relevant visual input. Main effects of task-relevant visual input were
tested for by comparing visual target present (= AV + V) and visual target absent trials (= A +
¬V) pooled (i.e. summed) over TMS conditions (i.e. we performed the comparisons “target
present >target absent” and “target absent >target present” pooled over the remaining
factors).
Main effects of TMS. Since TMS effects in the absence of a neutral control condition may
result in interpretational ambiguities, comparisons between TMS conditions were imple-
mented in a paired-wise fashion by comparing each experimental condition (IPS or Occ) with
the control condition (Sham). While not the main focus of this study, comparisons between
each experimental condition with each other were also computed for completeness. Hence,
effects of IPS-TMS were identified by comparing IPS >Sham and Sham >IPS pooled (i.e.
summed) over conditions. Equivalent contrasts were calculated for Occ-TMS and for direct
comparisons between the two experimental conditions.
Please note that formally these ‘main effects of TMS’ test for an interaction (e.g. main effect
of Occ-TMS >Sham can be more precisely written as: (TMS stimulation—Baseline) under
Occ-TMS >(TMS stimulation—Baseline) under Sham-TMS). Hence, this interaction contrast
controls for non-specific TMS effects such as discomfort that may have been increased for
Occ-TMS.
State-dependent TMS effects: Interaction effects between visual input and TMS. Like-
wise, interaction effects between task-relevant visual input and TMS conditions were evaluated
through direct comparisons between TMS conditions. Consequently, interaction contrasts for
(target present >target absent)
IPS (or Occ)
>(target present >target absent)
Sham
and (target
absent >target present)
IPS (or Occ)
>(target absent >target present)
Sham
were estimated. Inter-
action effects between Occ- and IPS-TMS were directly evaluated in the same manner.
Evaluation of phosphene perception
It is well established that in addition to being able to disrupt visual perception, TMS over the
occipital cortex can elicit transient perceptions of light known as phosphenes. The ability to
perceive phosphenes is quite variable across participants [44–46] and strongly depends on the
amount of attention given to them [26,36]. On the other hand, the intensity needed to elicit
phosphenes is generally lower than the one necessary to induce effective suppression effects
[26,47,48]. As phosphenes are elicited contra-laterally to the stimulated hemisphere, they
could have potentially interfered with task performance [47–49]. To evaluate the effect of
phosphenes in our study, at the end of the Occ-TMS session we asked participants whether
they had perceived anything else apart from the standard visual display and requested them to
draw what they saw. Only three participants reported having seen something, of which only
two described image distortions near the placeholder. However, the reported distortions by
one of these two participants were not specific to the vicinity of the placeholder but extended
throughout the entire visual display comprising also the right visual field (i.e. ipsi-laterally to
TMS stimulation), which suggests that the reported distortions were not ‘authentic’ phos-
phenes. The remaining participant that reported visual distortions adjacent to the placeholder
Methodological considerations on the comparison between occipital and parietal TMS
PLOS ONE | https://doi.org/10.1371/journal.pone.0181438 August 2, 2017 9 / 20
also reported that these distortions were distinct from the task-relevant visual stimulus. Hence,
in total it is unlikely that phosphene perception influenced our results on the group level both
behaviourally and for the BOLD measurements.
Eye monitoring (outside the scanner)
To ensure that the observed activation pattern did not result from eye movements, twitches, or
startle effects, 8 additional participants (one left-handed; 2 male; mean age: 26.9 years; stan-
dard deviation: 5.3) took part in a supplementary TMS-psychophysics experiment outside the
scanner performed with equivalent parameters and comparable durations. One experimental
run was acquired per participant for each TMS condition. To account for the absence of the
high-current filter used in the concurrent TMS-MRI setup [29], the TMS intensity was
reduced to 63% of total output.
Horizontal and vertical eye movements were recorded using an iView XTM RED-III
remote eyetracker system (SensoMotoric Instruments Inc., Needham/Boston, MA, USA) (50
Hz sampling rate). The eyetracking system was calibrated using a 13-point calibration. Eye
position data were automatically corrected for blinks and converted to radial velocity.
For each trial condition the mean distance (degrees) from the fixation cross, the number of
saccades (defined by a radial eye velocity threshold >30˚/s for a minimum of 60 ms duration
and radial amplitude larger than 5˚), and the proportion of blinks were computed for the
entire trial duration separately for each individual condition and for baseline periods.
Across all participants, saccades were almost completely absent, precluding further statisti-
cal analyses for this index. For the two remaining indices we first evaluated whether they dif-
fered for activation trials and baseline periods. We therefore compared each index pooled (i.e.
averaged) over all activation conditions with baseline periods in a paired t-test. The mean dis-
tance from the fixation cross was significantly greater during baseline periods (1.38˚ ±0.44)
than task trials (0.92˚ ±0.25; paired t-test: t
(7)
= -3.038, p= 0.019). We also observed a non-sig-
nificant (t
(7)
= -1.349, p= 0.22) increase in eye blinks for fixation baseline periods (1.79 ±0.61)
relative to activation trials (1.39 ±0.54).
Second, to test for differences across individual task conditions, the two indices were inde-
pendently entered into 2 (task-relevant visual input: V present, V absent) x 2 (auditory context:
A present, A absent) x 3 (TMS: Occ, IPS, Sham) RM-ANOVAs. Importantly, neither of the
two RM-ANOVAs revealed any significant main effects or interactions, thereby confirming
that there was no significant difference in eye movements amongst our experimental
conditions.
Collectively, these results demonstrate that differences in eye movements across task condi-
tions are unlikely to account for activation differences across the eight task conditions. How-
ever, activation differences between task conditions and fixation baseline may result from eye
movements that participants made during the fixation conditions when they recovered from
the very demanding sustained attention task. Activations and deactivations relative to fixation
baseline may in part be accounted for by eye movement confounds. Hence, the parameter esti-
mate plots for the fMRI data should be interpreted only by comparing the eight task condi-
tions, while the activation or deactivation relative to fixation should not be further interpreted.
Results
Behavioural data
In a sustained spatial attention paradigm, participants reported whether they had detected a
visual target that was presented on 50% of the trials. For each participant, the behavioural indi-
ces were calculated for visual target present and visual target absent trials separately for each
Methodological considerations on the comparison between occipital and parietal TMS
PLOS ONE | https://doi.org/10.1371/journal.pone.0181438 August 2, 2017 10 / 20
auditory context and TMS condition. Across participants’ mean (±SD) of % correct responses
and reaction time data are summarized for each condition in Table 1.
For % correct responses, a 2 (visual input: present vs. absent) x 2 (auditory context: present
vs. absent) x 3 (IPS-TMS vs. Occ-IPS vs. Sham-TMS) RM-ANOVA revealed a significant main
effect of visual input (F
(1,7)
= 16.356; p= 0.005). This analysis did not reveal any other signifi-
cant main effects (TMS: F
(1,7)
= 1.418; p= 0.275; Auditory Context: F
(1,7)
= 0.000; p= 0.988)
nor interactions between the different factors (TMS and Auditory Context: F
(1,7)
= 2.233;
p= 0.144; TMS and Visual Input: F
(1,7)
= 1.239; p= 0.320; Auditory Context and Visual Input:
F
(1,7)
= 0.120; p= 0.739; Interaction between the three: F
(1,7)
= 1.598; p= 0.237). Participants
missed about 25–30% of the targets, but showed nearly no false alarms. This confirmed that
participants indeed placed a strict criterion for responding ‘target present’ in line with the
accuracy instructions. None of the other main effects, 2-way or 3-way interactions were
significant.
Median reaction times from each participant were entered in a 2 (visual: present vs. absent)
x 2 (auditory context: present vs. absent) x 3 (IPS-TMS vs. Occ-IPS vs. Sham-TMS) RM-A-
NOVA that revealed only a significant interaction between auditory context and visual input
(F
(1,7)
= 9.000; p= 0.020). More specifically, auditory context shortened reaction times pre-
dominantly when the visual signal was absent, than when it was present. This suggests that the
auditory signal served as a precise temporal cue for response preparation, when the target was
not presented leading to faster ‘no’ responses. None of the main effects or other 2-way or
3-way interactions was significant (main effects of TMS: F
(1,7)
= 0.418; p= 0.642, main effect of
visual input: F
(1,7)
= 0.342; p= 0.577; main effect of auditory context: F
(1,7)
= 3.873; p= 0.090,
interaction between the TMS and auditory context: F
(1,7)
= 0.169; p= 0.842, interaction
between TMS and visual input: F
(1,7)
= 0.328; p= 0.683, interaction between the three factors:
F
(1,7)
= 0.622; p= 0.524).
Importantly, in line with previous concurrent TMS-fMRI studies [12,50], our TMS manip-
ulation did not elicit any behavioural changes in terms of % correct or reaction times. Further,
additional analyses using d’ statistics from signal detection theory or participant-specific mean
rather than median response times did not reveal any significant effect of TMS. Hence, our
TMS manipulation functioned as a purely physiological perturbation method that allowed us
to examine the influences of local perturbations on remote interconnected brain areas uncon-
founded by behavioural differences.
Neuroimaging data
Main effects of task-relevant visual input. We evaluated the main effects of task-relevant
visual input by pooling over auditory contexts and TMS conditions. Visual target presentation
suppressed activations in the left precuneus, but this effect was only marginally significant
when corrected for multiple comparisons within the entire brain (p= 0.09; [x = -14, y = -60,
z = 42]; peak t-value: 4.91, number of voxels in cluster: 666). Further, we observed significant
Table 1. Behavioural responses averaged across participants (±SD).
TMS Sites % Correct Reaction Times (ms)
A Present A Absent A Present A Absent
V Present V Absent V Present V Absent V Present V Absent V Present V Absent
IPS 75 ±21 98 ±1 75 ±25 98 ±2 708 ±75 692 ±76 707 ±73 711 ±63
Occ 68 ±24 99 ±1 67 ±25 98 ±1 707 ±90 700 ±85 716 ±100 720 ±90
Sham 77 ±13 99 ±1 79 ±11 99 ±1 695 ±88 677 ±103 701 ±91 698 ±94
https://doi.org/10.1371/journal.pone.0181438.t001
Methodological considerations on the comparison between occipital and parietal TMS
PLOS ONE | https://doi.org/10.1371/journal.pone.0181438 August 2, 2017 11 / 20
activations in the intraparietal sulcus (p
IPS
= 0.012; [x = 32, y = -64, z = 48]; peak t-value:
10.40). Comparing visual target present relative to visual target absent did not reveal any sig-
nificant effects.
Effects of TMS. We evaluated the effects of TMS by individually comparing IPS-TMS and
Occ-TMS relative to Sham-TMS pooled over sensory conditions.
As previously reported [15], the right parietal cortex showed increased activations for IPS-
relative to Sham-TMS (p
IPS
= 0.09; [x = 30, y = -54, z = 58]; peak t-value: 5.80; see also Fig 2).
The opposite comparisons did not yield significant results. Likewise, comparing Occ-TMS
with Sham-TMS did not result in any significant effects.
As shown in the parameter estimate plots (Fig 2), we observed only small (or even no) acti-
vations for task relative to fixation conditions during Occ- and IPS-TMS, but pronounced
task-induced deactivations during Sham-TMS conditions. However, as previously argued [15],
the comparison between task and fixation conditions should not be further interpreted, as this
comparison may be confounded by differences in eye movements which are known to affect
IPS activations. Importantly, there were no significant differences in eye movements between
the different task or TMS conditions, so that the comparison between Occ, IPS and Sham-
TMS and their interactions are not confounded by differences in eye movements and can
therefore be interpreted.
State-dependent TMS effects: Interaction effects between visual input and TMS. Inter-
action effects between the task-relevant visual input and TMS were evaluated separately for (i)
IPS-TMS vs. Sham-TMS and (ii) Occ-TMS vs. Sham-TMS.
The modulatory effect of IPS-TMS on visual processing was evaluated by testing for the
interaction between IPS- vs. Sham-TMS and visual target present vs. absent. The results are in
line with those reported in our previous communication, with a marginally significant interac-
tion found in the right insula extending to the right temporal pole (p= 0.06; [x = 52, y = 6, z =
-16], peak t-value:14.83; number of voxels in cluster: 794; for further discussion see [15]). The
opposite interaction showed significant effects with the intraparietal sulcus (p
IPS
= 0.012;
[x = 44, y = -58, z = 42]; peak t-values: 10.45). We did not observe significant interaction effects
between Occ- vs. Sham-TMS and visual target present vs. absent.
Fig 2. Main effects of TMS. (left panel) Activations induced by IPS- relative to Sham-TMS (red) and Occ- relative to Sham-TMS (yellow) are
rendered on an inflated SPM template of the entire brain. For illustrational purposes only, effects are displayed at a height threshold of p= 0.01
uncorrected and an extent threshold of 100 voxels. (right panel) Parameter estimates (mean ±standard error of the mean) are displayed at the given
peak coordinates within the parietal cortex. Parameter estimates are pooled (i.e. summed) over auditory contexts. The bar graphs represent the size
of the effect in non-dimensional units (corresponding to % whole-brain mean).
https://doi.org/10.1371/journal.pone.0181438.g002
Methodological considerations on the comparison between occipital and parietal TMS
PLOS ONE | https://doi.org/10.1371/journal.pone.0181438 August 2, 2017 12 / 20
Discussion
Classical fMRI studies in patients enable us to investigate the effect of permanent lesions on
functional brain organization. Yet, variability in lesion location, extent and long-term func-
tional reorganization often limit the interpretation of patient fMRI studies. Concurrent TMS-
fMRI has been advocated as a transient perturbation method to provide complementary
insights into the functional contributions of regions within a brain network. Yet, despite its
potential, to our knowledge this is the first concurrent TMS-fMRI study that compared the
effects of parietal and occipital TMS on visual target responses under sustained spatial atten-
tion in an attempt to ‘mimick’ neglect and hemianopia. Starting from the interpretational limi-
tations and challenges of our own study we will provide guidance on how to optimize
experimental design and TMS protocol when comparing TMS effects in primary sensory (e.g.
visual) and higher order association areas (e.g. parietal), which differ profoundly in their
computational principles [51], neural dynamics [52] and connectivity architecture.
In principle, TMS can induce four sorts of effects: i) neural effects locally under the coil, ii)
remote neural effects via trans-synaptic spread of activation (measured as changes in effective
connectivity in fMRI), iii) changes in behavioural performance and iv) physical side effects
(e.g. clicking noise, tickling sensation), which again are associated with confounding neural
and behavioural changes. Concurrent TMS-fMRI studies enable us to infer TMS-induced
changes in functional network architecture or remote activations (i.e. type ii effects) uncon-
founded by any of the other effects. Thus, in our study we focused on TMS induced perturba-
tions of parietal and occipital cortices controlled for behavioural effects [53]. In contrast to the
careful behavioural matching, our study was less successful in matching the local neural effects
for IPS and occipital TMS perturbation. While IPS-TMS increased activations relative to
Sham-TMS in parietal cortices underneath the coil, Occ-TMS did not induce TMS-effects on
the BOLD-response directly underneath the coil. The absence of direct activations underneath
the coil is not unusual in concurrent TMS-fMRI studies [14,28,32,50,54–56]. Yet, it limits
the interpretation of differences between Occ and IPS-TMS perturbation on the neural pro-
cessing systems.
In the following, we will discuss and provide guidance on how future studies should opti-
mize experimental design and TMS protocol to match local neural and behavioural effects and
thereby enable strong interpretations.
Optimizing experimental design and TMS protocol with respect to local
neural effects
First, to promote effective Occ- and IPS-TMS neural perturbations the experimental design
should elicit reliable neural activity in both primary and higher-order association areas. In our
current study we employed a sustained spatial attention paradigm that presented a small visual
stimulus with the visual contrast fine-tuned individually for each participant to obtain 70%
detection rate (for studies using a similar approach see IPS-TMS: [17], or Occ-TMS: [18,24,
26,36,47,57–61]). This low contrast visual stimulus placed high attentional demands thereby
maximizing our chances to reveal direct IPS-TMS effects on neural responses in parietal corti-
ces. Yet, the visual stimulus did not induce reliable visual activations in striate or extrastriate
cortices even in the absence of TMS. Thus, our paradigm may have been sub-optimal for
unravelling direct or modulatory effects of Occ-TMS on visual evoked activations. To maxi-
mize TMS effects simultaneously on bottom-up driven visual activations and direct and top-
down modulatory effects of IPS, future studies should therefore combine high contrast stimuli
to drive visual processing with a demanding attentional task to tax attentional processing [12,
37].
Methodological considerations on the comparison between occipital and parietal TMS
PLOS ONE | https://doi.org/10.1371/journal.pone.0181438 August 2, 2017 13 / 20
Second, concurrent TMS-fMRI studies need to optimize the TMS protocol for perturbing
primary sensory and higher order association areas that differ profoundly in their temporal
scales of neural dynamics [62–64]. While primary sensory areas show brief transient responses
to sensory inputs, association areas exhibit more sustained activity by integrating inputs over
time. In principle, one could use two different TMS protocols. For instance, following the
TMS protocols from previous behavioural studies one could apply a single TMS pulse at a spe-
cific latency in occipital cortices [25,35,36], but 10 Hz bursts of 4 TMS pulses in parietal corti-
ces [24,31,32,34]. However, the use of different TMS protocols would introduce
interpretational limitations, because the TMS BOLD-effects are known to scale with the num-
ber of TMS pulses applied [65]. Therefore, in the current study we used one TMS protocol that
optimized the timing of the first TMS pulse for occipital regions, but the number of TMS
pulses according to the parietal area exhibiting longer sustained neural activity (i.e. 4 TMS
pulses at 10 Hz).
Nevertheless, based on the absence of a TMS effect on the BOLD-response locally under the
coil for Occ-TMS, one may argue that the protocol was not equally effective for Occ- and
IPS-TMS. Yet, in the light of variability in neurovascular coupling across regions we would
caution against using the BOLD-response as the gold standard parameter to match TMS effec-
tiveness across regions. Instead, we would suggest applying the same basic TMS protocol, but
adjust TMS intensity individually to each TMS site. For some target regions it may be feasible
to adjust TMS intensity in terms of the phosphene or motor threshold. In others regions, TMS
intensity is adjusted individually to each TMS site based on published scaling factors that
account for differences in coil-cortex distances between the cortical sites [66–69] or even
based on modelling of electromagnetic fields [70,71], which additionally accounts for the
impact of gyrifications. Further, to account for the fact that TMS effects are strongly context-
sensitive and state-dependent, one may also characterize the relation between local BOLD
effects on TMS intensity in input-output curves during initial pilot experiments. Finally, the
use of new RF coil designs will likely also prove advantageous, as they are more sensitive
directly underneath the TMS coil [72].
Optimizing experimental design and TMS with respect to behavioural
effects
Matching TMS in term of local neural effectiveness could potentially lead to different beha-
vioural effects across TMS sites. For instance, TMS to primary visual areas may impact visual
detection more strongly than TMS to parietal areas. As previously discussed in the context of
patient fMRI studies [73,74], these differences in behavioural effects limit the interpretation of
activation differences across conditions. For instance, in the most extreme case, participants
will not respond to visual stimuli they are not aware of during Occ-stimulation, leading to
reduced neural activations in widespread systems including prefrontal and occipito-temporal
cortices associated with visual perception, response selection and motor response. To avoid
these behavioural confounds we should either adjust the experimental paradigm or the TMS
intensity. For instance, in studies of visual perception we could increase the stimulus intensity
or focus on implicit processing where participants do not explicitly respond to the dimension
of interest [75]. In the current paradigm our threshold stimuli allowed us to characterize TMS
induced differences in neural activations in the absence of behavioural effects. Yet, the absence
of behavioural effects does not provide direct insights into the functional relevance of the
TMS-induced activation changes. Therefore, we would suggest that future experiments should
combine conditions where neural effects are or are not associated with behavioural changes.
For instance, to compare TMS to parietal and primary visual areas experimental designs may
Methodological considerations on the comparison between occipital and parietal TMS
PLOS ONE | https://doi.org/10.1371/journal.pone.0181438 August 2, 2017 14 / 20
i) present threshold and strong supra-threshold visual stimuli, ii) focus on explicit and implicit
stimulus processing [75] or iii) include two levels, i.e. sub- and supra-threshold, of TMS
intensity.
Optimizing TMS to control for physical TMS-side effects
In addition to true neural TMS effects, studies focusing on visual, auditory or somatosensory
processing need to control for somatosensory and auditory TMS side effects across different
TMS stimulation sites. Previous studies have suggested that low intensity TMS may act as a
control condition. Yet, a recent study by Leitão et al. [14] demonstrated that low intensity
TMS is not an appropriate control condition, as it is not matched in terms of auditory ampli-
tude to high TMS. This does not only affect studies in the auditory system, but also somatosen-
sory and visual processing because of crossmodal interactions such as crossmodal
deactivations [76,77]. Indeed, high intensity TMS leads to greater deactivations in primary
and higher order visual system than low intensity TMS, thereby confounding the interpreta-
tion of nearly any statistical comparison [14]. To resolve these interpretational ambiguities, we
have developed a Sham condition, where we fixed 2 cm thick plastic plates between the TMS
coil and the skull. Given the quadratic decay of the TMS-induced magnetic field, this Sham
condition precluded the effects of direct brain stimulation. Yet, the Sham-TMS condition
tightly controlled for the TMS side effects such as the TMS-noise and feelings of vibrations.
Indeed, comparing IPS-TMS or Occ-TMS with Sham-TMS did not reveal significant activa-
tions in the auditory cortex. However, it is worth mentioning that this Sham condition has
limited effectiveness in studies that stimulate positions for which the side effects result mainly
from nerve or muscle stimulation rather than vibrations, such as when TMS is applied to over
temporal muscles or some more lateral and inferior regions of the occipital cortex (M.
occipitalis).
Conclusions
To compare TMS perturbations to low level sensory and higher order association areas we
would suggest matching the TMS protocols in terms of number and timing of pulses, but
adjust TMS intensity individually across sites to control for differences in coil-cortex distances.
Further, the experimental paradigm should be designed to elicit strong activations in both neu-
ral systems that one hopes to perturb. It should ideally include one condition that is associated
with behavioural TMS effects to assess regional contributions to behavioural performance and
one condition that is not associated with behavioural TMS effects to allow assessment of
regional neural contributions and effective connectivity between regions unconfounded by
differences in behavioural performance.
Supporting information
S1 File. Aggregate data. Aggregate data containing behavioural data and beta values used in
the parameter plots of Fig 2.
(ZIP)
Author Contributions
Conceptualization: Joana Leitão, Uta Noppeney.
Data curation: Joana Leitão.
Formal analysis: Joana Leitão, Uta Noppeney.
Methodological considerations on the comparison between occipital and parietal TMS
PLOS ONE | https://doi.org/10.1371/journal.pone.0181438 August 2, 2017 15 / 20
Funding acquisition: Uta Noppeney.
Investigation: Joana Leitão, Johannes Tuennerhoff.
Methodology: Joana Leitão, Axel Thielscher, Uta Noppeney.
Project administration: Joana Leitão, Uta Noppeney.
Resources: Axel Thielscher, Uta Noppeney.
Software: Joana Leitão, Axel Thielscher.
Supervision: Uta Noppeney.
Visualization: Joana Leitão.
Writing – original draft: Joana Leitão.
Writing – review & editing: Joana Leitão, Axel Thielscher, Uta Noppeney.
References
1. Driver J, Mattingley JB. Parietal neglect and visual awareness. Nat Neurosci. 1998; 1(1):17–22. https://
doi.org/10.1038/217 PMID: 10195103.
2. Verdon V, Schwartz S, Lovblad KO, Hauert CA, Vuilleumier P. Neuroanatomy of hemispatial neglect
and its functional components: a study using voxel-based lesion-symptom mapping. Brain. 2010; 133
(Pt 3):880–94. https://doi.org/10.1093/brain/awp305 PMID: 20028714.
3. Corbetta M, Shulman GL. Spatial neglect and attention networks. Annu Rev Neurosci. 2011; 34:569–
99. https://doi.org/10.1146/annurev-neuro-061010-113731 PMID: 21692662.
4. Umarova RM, Saur D, Kaller CP, Vry MS, Glauche V, Mader I, et al. Acute visual neglect and extinction:
distinct functional state of the visuospatial attention system. Brain. 2011; 134(Pt 11):3310–25. https://
doi.org/10.1093/brain/awr220 PMID: 21948940.
5. Karnath HO. Spatial attention systems in spatial neglect. Neuropsychologia. 2015; 75:61–73. https://
doi.org/10.1016/j.neuropsychologia.2015.05.019 PMID: 26004064.
6. Zihl J, Kennard C. Disorders of Higher Visual Function. In: Brandt T. C L, Dichgans J., Diener C. & Ken-
nard C., editor. Neurological Disorders: Course and Treatment, 2nd edition. New York: Academic
Press; 2003. p. 255–63.
7. Frassinetti F, Bolognini N, Bottari D, Bonora A, Ladavas E. Audiovisual integration in patients with visual
deficit. J Cogn Neurosci. 2005; 17(9):1442–52. https://doi.org/10.1162/0898929054985446 PMID:
16197697.
8. Leo F, Bolognini N, Passamonti C, Stein BE, Ladavas E. Cross-modal localization in hemianopia: new
insights on multisensory integration. Brain. 2008; 131(Pt 3):855–65. https://doi.org/10.1093/brain/
awn003 PMID: 18263626.
9. Passamonti C, Frissen I, Ladavas E. Visual recalibration of auditory spatial perception: two separate
neural circuits for perceptual learning. Eur J Neurosci. 2009; 30(6):1141–50. https://doi.org/10.1111/j.
1460-9568.2009.06910.x PMID: 19735289.
10. Ruff CC, Blankenburg F, Bjoertomt O, Bestmann S, Freeman E, Haynes JD, et al. Concurrent TMS-
fMRI and psychophysics reveal frontal influences on human retinotopic visual cortex. Curr Biol. 2006;
16(15):1479–88. https://doi.org/10.1016/j.cub.2006.06.057 PMID: 16890523.
11. Ruff CC, Bestmann S, Blankenburg F, Bjoertomt O, Josephs O, Weiskopf N, et al. Distinct causal influ-
ences of parietal versus frontal areas on human visual cortex: evidence from concurrent TMS-fMRI.
Cereb Cortex. 2008; 18(4):817–27. https://doi.org/10.1093/cercor/bhm128 PMID: 17652468.
12. Blankenburg F, Ruff CC, Bestmann S, Bjoertomt O, Josephs O, Deichmann R, et al. Studying the role
of human parietal cortex in visuospatial attention with concurrent TMS-fMRI. Cereb Cortex. 2010; 20
(11):2702–11. https://doi.org/10.1093/cercor/bhq015 PMID: 20176690.
13. Feredoes E, Heinen K, Weiskopf N, Ruff C, Driver J. Causal evidence for frontal involvement in memory
target maintenance by posterior brain areas during distracter interference of visual working memory.
Proc Natl Acad Sci U S A. 2011; 108(42):17510–5. https://doi.org/10.1073/pnas.1106439108 PMID:
21987824.
14. Leitao J, Thielscher A, Werner S, Pohmann R, Noppeney U. Effects of parietal TMS on visual and audi-
tory processing at the primary cortical level—a concurrent TMS-fMRI study. Cereb Cortex. 2013; 23
(4):873–84. https://doi.org/10.1093/cercor/bhs078 PMID: 22490546.
Methodological considerations on the comparison between occipital and parietal TMS
PLOS ONE | https://doi.org/10.1371/journal.pone.0181438 August 2, 2017 16 / 20
15. Leitao J, Thielscher A, Tunnerhoff J, Noppeney U. Concurrent TMS-fMRI Reveals Interactions between
Dorsal and Ventral Attentional Systems. J Neurosci. 2015; 35(32):11445–57. https://doi.org/10.1523/
JNEUROSCI.0939-15.2015 PMID: 26269649.
16. Pascual-Leone A, Gomez-Tortosa E, Grafman J, Alway D, Nichelli P, Hallett M. Induction of visual
extinction by rapid-rate transcranial magnetic stimulation of parietal lobe. Neurology. 1994; 44(3 Pt
1):494–8. PMID: 8145921.
17. Hilgetag CC, Theoret H, Pascual-Leone A. Enhanced visual spatial attention ipsilateral to rTMS-
induced ’virtual lesions’ of human parietal cortex. Nat Neurosci. 2001; 4(9):953–7. https://doi.org/10.
1038/nn0901-953 PMID: 11528429.
18. Romei V, Gross J, Thut G. On the role of prestimulus alpha rhythms over-parietal areas in visual input
regulation: correlation or causation? J Neurosci. 2010; 30(25):8692–7. https://doi.org/10.1523/
JNEUROSCI.0160-10.2010 PMID: 20573914.
19. Bolognini N, Convento S, Rossetti A, Merabet LB. Multisensory processing after a brain damage: clues
on post-injury crossmodal plasticity from neuropsychology. Neurosci Biobehav Rev. 2013; 37(3):269–
78. https://doi.org/10.1016/j.neubiorev.2012.12.006 PMID: 23253947.
20. Watson AB, Pelli DG. QUEST: a Bayesian adaptive psychometric method. Percept Psychophys. 1983;
33(2):113–20. PMID: 6844102.
21. Algazi R, Duda RO, Thompson DM, Avendano C, editors. The CIPIC HRTF database. WASSAP ’01—
IEEE ASSP Workshop on Applications of Signal Processing to Audio and Acoustics; 2001; Mohonk
Mountain House, New Paltz, NY.
22. Brainard DH. The Psychophysics Toolbox. Spat Vis. 1997; 10(4):433–6. PMID: 9176952.
23. Kleiner M, Brainard DH, Pelli DG. What’s new in Psychtoolbox-3? Perception 36 ECVP Abstract Sup-
plement. 2007.
24. Oliver R, Bjoertomt O, Driver J, Greenwood R, Rothwell J. Novel ’hunting’ method using transcranial
magnetic stimulation over parietal cortex disrupts visuospatial sensitivity in relation to motor thresholds.
Neuropsychologia. 2009; 47(14):3152–61. https://doi.org/10.1016/j.neuropsychologia.2009.07.017
PMID: 19651149.
25. de Graaf TA, Koivisto M, Jacobs C, Sack AT. The chronometry of visual perception: review of occipital
TMS masking studies. Neurosci Biobehav Rev. 2014; 45:295–304. https://doi.org/10.1016/j.neubiorev.
2014.06.017 PMID: 25010557.
26. Thielscher A, Reichenbach A, Ugurbil K, Uludag K. The cortical site of visual suppression by transcra-
nial magnetic stimulation. Cereb Cortex. 2010; 20(2):328–38. https://doi.org/10.1093/cercor/bhp102
PMID: 19465739.
27. Eickhoff SB, Stephan KE, Mohlberg H, Grefkes C, Fink GR, Amunts K, et al. A new SPM toolbox for
combining probabilistic cytoarchitectonic maps and functional imaging data. Neuroimage. 2005; 25
(4):1325–35. https://doi.org/10.1016/j.neuroimage.2004.12.034 PMID: 15850749.
28. Bestmann S, Baudewig J, Frahm J. On the synchronization of transcranial magnetic stimulation and
functional echo-planar imaging. J Magn Reson Imaging. 2003; 17(3):309–16. https://doi.org/10.1002/
jmri.10260 PMID: 12594720.
29. Moisa M, Pohmann R, Ewald L, Thielscher A. New coil positioning method for interleaved transcranial
magnetic stimulation (TMS)/functional MRI (fMRI) and its validation in a motor cortex study. J Magn
Reson Imaging. 2009; 29(1):189–97. https://doi.org/10.1002/jmri.21611 PMID: 19097080.
30. Duecker F, Sack AT. Pre-stimulus sham TMS facilitates target detection. PLoS One. 2013; 8(3):
e57765. https://doi.org/10.1371/journal.pone.0057765 PMID: 23469232.
31. Chambers CD, Stokes MG, Mattingley JB. Modality-specific control of strategic spatial attention in pari-
etal cortex. Neuron. 2004; 44(6):925–30. https://doi.org/10.1016/j.neuron.2004.12.009 PMID:
15603736.
32. Heinen K, Ruff CC, Bjoertomt O, Schenkluhn B, Bestmann S, Blankenburg F, et al. Concurrent TMS-
fMRI reveals dynamic interhemispheric influences of the right parietal cortex during exogenously cued
visuospatial attention. Eur J Neurosci. 2011; 33(5):991–1000. https://doi.org/10.1111/j.1460-9568.
2010.07580.x PMID: 21324004.
33. Ruff CC, Blankenburg F, Bjoertomt O, Bestmann S, Weiskopf N, Driver J. Hemispheric differences in
frontal and parietal influences on human occipital cortex: direct confirmation with concurrent TMS-fMRI.
J Cogn Neurosci. 2009; 21(6):1146–61. https://doi.org/10.1162/jocn.2009.21097 PMID: 18752395.
34. Sack AT, Kohler A, Bestmann S, Linden DE, Dechent P, Goebel R, et al. Imaging the brain activity
changes underlying impaired visuospatial judgments: simultaneous FMRI, TMS, and behavioral stud-
ies. Cereb Cortex. 2007; 17(12):2841–52. https://doi.org/10.1093/cercor/bhm013 PMID: 17337745.
Methodological considerations on the comparison between occipital and parietal TMS
PLOS ONE | https://doi.org/10.1371/journal.pone.0181438 August 2, 2017 17 / 20
35. Amassian VE, Cracco RQ, Maccabee PJ, Cracco JB, Rudell A, Eberle L. Suppression of visual percep-
tion by magnetic coil stimulation of human occipital cortex. Electroencephalogr Clin Neurophysiol.
1989; 74(6):458–62. PMID: 2480226.
36. Kammer T, Puls K, Strasburger H, Hill NJ, Wichmann FA. Transcranial magnetic stimulation in the
visual system. I. The psychophysics of visual suppression. Exp Brain Res. 2005; 160(1):118–28.
https://doi.org/10.1007/s00221-004-1991-1 PMID: 15368086.
37. Reichenbach A, Whittingstall K, Thielscher A. Effects of transcranial magnetic stimulation on visual
evoked potentials in a visual suppression task. Neuroimage. 2011; 54(2):1375–84. https://doi.org/10.
1016/j.neuroimage.2010.08.047 PMID: 20804846.
38. Corthout E, Barker AT, Cowey A. Transcranial magnetic stimulation. Which part of the current wave-
form causes the stimulation? Exp Brain Res. 2001; 141(1):128–32. https://doi.org/10.1007/
s002210100860 PMID: 11685417.
39. Moisa M, Pohmann R, Uludag K, Thielscher A. Interleaved TMS/CASL: Comparison of different rTMS
protocols. Neuroimage. 2010; 49(1):612–20. https://doi.org/10.1016/j.neuroimage.2009.07.010 PMID:
19615453.
40. Friston KJ, Holmes AP, Worsley KJ, P J-P., Frith C, Frackowiak R. Statistical Parametric Maps in Func-
tional Imaging: A General Linear Approach Hum Brain Mapp. 1995; 2:189–210.
41. Friston KJ, Holmes AP, Price CJ, Buchel C, Worsley KJ. Multisubject fMRI studies and conjunction
analyses. Neuroimage. 1999; 10(4):385–96. https://doi.org/10.1006/nimg.1999.0484 PMID: 10493897.
42. Nichols TE, Holmes AP. Nonparametric permutation tests for functional neuroimaging: a primer with
examples. Hum Brain Mapp. 2002; 15(1):1–25. PMID: 11747097.
43. Nichols TE, Holmes AP. Nonparametric Permutation Tests for Functional Neuroimaging. In: Ashburner
J, Friston KJ, Penny W, editors. Human Brain Function. 2nd ed2003.
44. Kamitani Y, Shimojo S. Manifestation of scotomas created by transcranial magnetic stimulation of
human visual cortex. Nat Neurosci. 1999; 2(8):767–71. https://doi.org/10.1038/11245 PMID:
10412068.
45. Sparing R, Dambeck N, Stock K, Meister IG, Huetter D, Boroojerdi B. Investigation of the primary visual
cortex using short-interval paired-pulse transcranial magnetic stimulation (TMS). Neurosci Lett. 2005;
382(3):312–6. https://doi.org/10.1016/j.neulet.2005.03.036 PMID: 15925110.
46. Deblieck C, Thompson B, Iacoboni M, Wu AD. Correlation between motor and phosphene thresholds: a
transcranial magnetic stimulation study. Hum Brain Mapp. 2008; 29(6):662–70. https://doi.org/10.1002/
hbm.20427 PMID: 17598167.
47. Kastner S, Demmer I, Ziemann U. Transient visual field defects induced by transcranial magnetic stimu-
lation over human occipital pole. Exp Brain Res. 1998; 118(1):19–26. PMID: 9547074.
48. Kammer T, Puls K, Erb M, Grodd W. Transcranial magnetic stimulation in the visual system. II. Charac-
terization of induced phosphenes and scotomas. Exp Brain Res. 2005; 160(1):129–40. https://doi.org/
10.1007/s00221-004-1992-0 PMID: 15368087.
49. Kammer T. Phosphenes and transient scotomas induced by magnetic stimulation of the occipital lobe:
their topographic relationship. Neuropsychologia. 1999; 37(2):191–8. PMID: 10080376.
50. Moisa M, Siebner HR, Pohmann R, Thielscher A. Uncovering a context-specific connectional fingerprint
of human dorsal premotor cortex. J Neurosci. 2012; 32(21):7244–52. https://doi.org/10.1523/
JNEUROSCI.2757-11.2012 PMID: 22623669.
51. Rohe T, Noppeney U. Distinct Computational Principles Govern Multisensory Integration in Primary
Sensory and Association Cortices. Curr Biol. 2016; 26(4):509–14. https://doi.org/10.1016/j.cub.2015.
12.056 PMID: 26853368.
52. Hasson U, Yang E, Vallines I, Heeger DJ, Rubin N. A hierarchy of temporal receptive windows in
human cortex. J Neurosci. 2008; 28(10):2539–50. https://doi.org/10.1523/JNEUROSCI.5487-07.2008
PMID: 18322098.
53. Bestmann S, Feredoes E. Combined neurostimulation and neuroimaging in cognitive neuroscience:
past, present, and future. Ann N Y Acad Sci. 2013; 1296:11–30. https://doi.org/10.1111/nyas.12110
PMID: 23631540.
54. Blankenburg F, Ruff CC, Bestmann S, Bjoertomt O, Eshel N, Josephs O, et al. Interhemispheric effect
of parietal TMS on somatosensory response confirmed directly with concurrent TMS-fMRI. J Neurosci.
2008; 28(49):13202–8. https://doi.org/10.1523/JNEUROSCI.3043-08.2008 PMID: 19052211.
55. Baudewig J, Siebner HR, Bestmann S, Tergau F, Tings T, Paulus W, et al. Functional MRI of cortical
activations induced by transcranial magnetic stimulation (TMS). Neuroreport. 2001; 12(16):3543–8.
PMID: 11733708.
Methodological considerations on the comparison between occipital and parietal TMS
PLOS ONE | https://doi.org/10.1371/journal.pone.0181438 August 2, 2017 18 / 20
56. Hanakawa T, Mima T, Matsumoto R, Abe M, Inouchi M, Urayama S, et al. Stimulus-response profile
during single-pulse transcranial magnetic stimulation to the primary motor cortex. Cereb Cortex. 2009;
19(11):2605–15. https://doi.org/10.1093/cercor/bhp013 PMID: 19234068.
57. Chambers CD, Payne JM, Stokes MG, Mattingley JB. Fast and slow parietal pathways mediate spatial
attention. Nat Neurosci. 2004; 7(3):217–8. https://doi.org/10.1038/nn1203 PMID: 14983182.
58. Koch G, Oliveri M, Torriero S, Carlesimo GA, Turriziani P, Caltagirone C. rTMS evidence of different
delay and decision processes in a fronto-parietal neuronal network activated during spatial working
memory. Neuroimage. 2005; 24(1):34–9. https://doi.org/10.1016/j.neuroimage.2004.09.042 PMID:
15588594.
59. Dambeck N, Sparing R, Meister IG, Wienemann M, Weidemann J, Topper R, et al. Interhemispheric
imbalance during visuospatial attention investigated by unilateral and bilateral TMS over humanparietal
cortices. Brain Res. 2006; 1072(1):194–9. https://doi.org/10.1016/j.brainres.2005.05.075 PMID:
16426588.
60. de Graaf TA, Cornelsen S, Jacobs C, Sack AT. TMS effects on subjective and objective measures of
vision: stimulation intensity and pre- versus post-stimulus masking. Conscious Cogn. 2011; 20
(4):1244–55. https://doi.org/10.1016/j.concog.2011.04.012 PMID: 21632262.
61. Railo H, Koivisto M. Two means of suppressing visual awareness: a direct comparison of visual mask-
ing and transcranial magnetic stimulation. Cortex. 2012; 48(3):333–43. https://doi.org/10.1016/j.cortex.
2010.12.001 PMID: 21232737.
62. Werner S, Noppeney U. The contributions of transient and sustained response codes to audiovisual
integration. Cereb Cortex. 2011; 21(4):920–31. https://doi.org/10.1093/cercor/bhq161 PMID:
20810622.
63. Chaudhuri R, Knoblauch K, Gariel MA, Kennedy H, Wang XJ. A Large-Scale Circuit Mechanism for
Hierarchical Dynamical Processing in the Primate Cortex. Neuron. 2015; 88(2):419–31. https://doi.org/
10.1016/j.neuron.2015.09.008 PMID: 26439530.
64. Lee H, Noppeney U. Temporal prediction errors in visual and auditory cortices. Curr Biol. 2014; 24(8):
R309–10. https://doi.org/10.1016/j.cub.2014.02.007 PMID: 24735850.
65. Bohning DE, Shastri A, Lomarev MP, Lorberbaum JP, Nahas Z, George MS. BOLD-fMRI response vs.
transcranial magnetic stimulation (TMS) pulse-train length: testing for linearity. J Magn Reson Imaging.
2003; 17(3):279–90. https://doi.org/10.1002/jmri.10271 PMID: 12594717.
66. Stokes MG, Chambers CD, Gould IC, English T, McNaught E, McDonald O, et al. Distance-adjusted
motor threshold for transcranial magnetic stimulation. Clin Neurophysiol. 2007; 118(7):1617–25. https://
doi.org/10.1016/j.clinph.2007.04.004 PMID: 17524764.
67. Stokes MG, Chambers CD, Gould IC, Henderson TR, Janko NE, Allen NB, et al. Simple metric for scal-
ing motor threshold based on scalp-cortex distance: application to studies using transcranial magnetic
stimulation. J Neurophysiol. 2005; 94(6):4520–7. https://doi.org/10.1152/jn.00067.2005 PMID:
16135552.
68. Trillenberg P, Bremer S, Oung S, Erdmann C, Schweikard A, Richter L. Variation of stimulation intensity
in transcranial magnetic stimulation with depth. J Neurosci Methods. 2012; 211(2):185–90. https://doi.
org/10.1016/j.jneumeth.2012.09.007 PMID: 23000723.
69. Janssen AM, Oostendorp TF, Stegeman DF. The effect of local anatomy on the electric field induced by
TMS: evaluation at 14 different target sites. Med Biol Eng Comput. 2014; 52(10):873–83. https://doi.
org/10.1007/s11517-014-1190-6 PMID: 25163822.
70. Windhoff M, Opitz A, Thielscher A. Electric field calculations in brain stimulation based on finite ele-
ments: an optimized processing pipeline for the generation and usage of accurate individual head mod-
els. Hum Brain Mapp. 2013; 34(4):923–35. https://doi.org/10.1002/hbm.21479 PMID: 22109746.
71. Thielscher A, Antunes A, Saturnino GB. Field modeling for transcranial magnetic stimulation: A useful
tool to understand the physiological effects of TMS? Conf Proc IEEE Eng Med Biol Soc. 2015;
2015:222–5. https://doi.org/10.1109/EMBC.2015.7318340 PMID: 26736240.
72. Navarro de Lara LI, Windischberger C, Kuehne A, Woletz M, Sieg J, Bestmann S, et al. A novel coil
array for combined TMS/fMRI experiments at 3 T. Magn Reson Med. 2015; 74(5):1492–501. https://doi.
org/10.1002/mrm.25535 PMID: 25421603.
73. Noppeney U, Friston KJ, Price CJ. Degenerate neuronal systems sustaining cognitive functions. J
Anat. 2004; 205(6):433–42. https://doi.org/10.1111/j.0021-8782.2004.00343.x PMID: 15610392.
74. Price CJ, Friston KJ. Degeneracy and cognitive anatomy. Trends Cogn Sci. 2002; 6(10):416–21. PMID:
12413574.
75. Price CJ, Crinion J, Friston KJ. Design and analysis of fMRI studies with neurologically impaired
patients. J Magn Reson Imaging. 2006; 23(6):816–26. https://doi.org/10.1002/jmri.20580 PMID:
16649208.
Methodological considerations on the comparison between occipital and parietal TMS
PLOS ONE | https://doi.org/10.1371/journal.pone.0181438 August 2, 2017 19 / 20
76. Werner S, Noppeney U. Distinct functional contributions of primary sensory and association areas to
audiovisual integration in object categorization. J Neurosci. 2010; 30(7):2662–75. https://doi.org/10.
1523/JNEUROSCI.5091-09.2010 PMID: 20164350.
77. Werner S, Noppeney U. Superadditive responses in superior temporal sulcus predict audiovisual bene-
fits in object categorization. Cereb Cortex. 2010; 20(8):1829–42. https://doi.org/10.1093/cercor/bhp248
PMID: 19923200.
Methodological considerations on the comparison between occipital and parietal TMS
PLOS ONE | https://doi.org/10.1371/journal.pone.0181438 August 2, 2017 20 / 20
