The Timing of Anterior Temporal Lobe Involvement - Ricerca sull'intelligenza artificiale specializzata al MIT

The Timing of Anterior Temporal Lobe Involvement
in Semantic Processing

Rebecca L. Jackson, Matthew A. Lambon Ralph, and Gorana Pobric

Astratto

■ Despite indications that regions within the anterior tempo-
ral lobe (ATL) might make a crucial contribution to pan-modal
semantic representation, to date there have been no investiga-
tions of when during semantic processing the ATL plays a crit-
ical role. To test the timing of the ATL involvement in semantic
processing, we studied the effect of double-pulse TMS on
behavioral responses in semantic and difficulty-matched con-
trol tasks. Chronometric TMS was delivered over the left ATL
(10 mm from the tip of the temporal pole along the middle
temporal gyrus). During each trial, two pulses of TMS (40 msec

apart) were delivered either at baseline (before stimulus pre-
sentation) or at one of the experimental time points 100, 250,
400, E 800 msec poststimulus onset. A significant disruption
to performance was identified from 400 msec on the semantic
task but not on the control assessment. Our results not only
reinforce the key role of the left ATL in semantic representa-
tion but also indicate that its contribution is especially impor-
tant around 400 msec poststimulus onset. Together, these facts
suggest that the ATL may be one of the neural sources of the
N400 ERP component. ■

INTRODUCTION

The anterior temporal lobe (ATL) appears to make a crit-
ical contribution to pan-modal semantic representation
(Lambon Ralph, 2014; Lambon Ralph, Sage, Jones, &
Mayberry, 2010; Patterson, Nestor, & Rogers, 2007), Ma
little is known about the timing within this area. Neuro-
psicologia, functional neuroimaging, and repetitive TMS
experiments have identified a three-part network respon-
sible for multimodal semantic representation and con-
trol, including the pFC, temporoparietal region, E
bilateral ATL (Noonan, Jefferies, Visser, & Lambon Ralph,
2013; Visser, Jefferies, Embleton, & Lambon Ralph, 2012;
Visser & Lambon Ralph, 2011; Whitney, Kirk, O’Sullivan,
Lambon Ralph, & Jefferies, 2011; Binney, Embleton,
Jefferies, Parker, & Lambon Ralph, 2010; Hoffman,
Jefferies, & Lambon Ralph, 2010; Binder, Desai, Graves,
& Conant, 2009; Pobric, Jefferies, & Lambon Ralph,
2007; Jefferies & Lambon Ralph, 2006; Wagner, Pare-
Blagoev, Clark, & Poldrack, 2001). In contrasto, the tempo-
ral dynamics of processing within the ATL have not been
studied comprehensively. The temporal resolution of
fMRI studies is poor, and although electrophysiological
techniques have good temporal resolution, spatial resolu-
tion is sacrificed ( Walsh & Cowey, 2000). A long history
of EEG and MEG studies have related semantic process-
ing across a variety of modalities to a negative ERP, IL
N400, found 250 A 550 msec after stimulus onset (Kutas
& Federmeier, 2011B). Although somewhat inconsistent,
attempts to localize the N400 have identified a number of

University of Manchester

sources within the semantic network, including areas in
the temporal lobe (Kutas & Federmeier, 2011B; Helenius,
Salmelin, Service, & Connolly, 1998; McCarthy, Nobre,
Bentin, & Spencer, 1995). Beyond N400-focused studies,
one MEG investigation showed converging auditory-
related and visually related activity for a semantic judg-
ment task within the ATL around 400 msec (Marinkovic
et al., 2003). Tuttavia, other studies have suggested
much earlier semantic influences in reading and visual
object recognition (Liu, Agam, Madsen, & Kreiman,
2009; Pulvermuller, Shtyrov, & Hauk, 2009; Bar et al., 2006;
Halgren et al., 2002). Finalmente, a recent MEG investigation
found that these differential timing effects may be related
to the precision of semantic activation required, with ear-
lier (120 msec) synchronization between anterior and pos-
terior temporal regions for domain-level picture–name
verification and later (260 msec) for basic level decisions
(Clarke, Taylor, & Tyler, 2011).

In contrast to electrophysiological approaches (Dove
data are correlational and therefore could be epiphenom-
enal), TMS assesses the necessity of a specific brain area
for a task (Silvanto & Pascual-Leone, 2012; Sandrini, Umilta,
& Rusconi, 2011B). This may be performed offline (in un
rest period before the task) or online (during processing
within a trial; Sandrini, Umilta, & Rusconi, 2011UN; Pascual-
Leone, Walsh, & Rothwell, 2000). Although the effects of
online TMS are more subtle, they allow increased temporal
specificity ( Walsh & Cowey, 2000). One form of online
TMS involves varying the time at which the pulse is deliv-
ered during the trial. As such, chronometric TMS (cTMS)
assesses when neural activity within a specific brain area is
critical for a task (Silvanto & Pascual-Leone, 2012; Sandrini

Journal of Cognitive Neuroscience 27:7, pag. 1388–1396
doi:10.1162/jocn_a_00788

D
o
w
N
l
o
UN
D
e
D

F
R
o
M

/
j

T
T

F
/

io
T
.

:
/
/

H
T
T
P
:
/
D
/
o
M
w
io
N
T
o
P
UN
R
D
C
e
.
D
S
F
io
R
o
l
M
v
e
H
R
C
P
H
UN
D
io
io
R
R
e
.
C
C
T
.
o
M
M
/
j
e
D
o
tu
C
N
o
/
C
UN
N
R
UN
T
R
io
T
io
C
C
l
e
e
–
P
–
D
P
D
2
F
7
/
7
2
7
1
/
3
7
8
/
8
1
1
3
9
8
4
8
9
/
2
1
9
7
6
8
o
2
C
9
N
2
_
0
UN
/
_
j
0
o
0
C
7
N
8
8
_
UN
P
_
D
0
0
B
7
sì
8
G
8
tu
.
e
P
S
T
D
o
F
N
B
0
sì
8
S
M
e
IO
P
T
e
M
l
io
B
B
e
R
R
UN
2
R
0
2
io
3
e
S

/
j

tu
S
e
R

o
N

1
7

M
UN
sì

2
0
2
1

et al., 2011B). Così, the time at which there is a direct rela-
tionship between the activity of a specific region and a
particular behavior may be identified (Silvanto & Pascual-
Leone, 2012; Duncan, Pattamadilok, & Devlin, 2010).
Concurrent imaging suggests that the disruption caused
by a TMS pulse has an effect on activity lasting around
10–30 msec ( Walsh & Cowey, 2000; Ilmoniemi et al.,
1997). Allo stesso modo, the temporal specificity of cTMS is
considered to be around 10–20 msec ( Walsh & Cowey,
2000). This specificity has allowed detection of behavioral
effects in time windows separated on the order of 10 msec.
This feature of cTMS allows processing to be tracked in
detail over time, either within one area or in different re-
gions (Schuhmann, Schiller, Goebel, & Sacco, 2012; Pitcher,
Walsh, Yovel, & Duchaine, 2007; Jahanshahi & Dirnberger,
1999; Schulter, Rushworth, Mills, & Passingham, 1999; Terao
et al., 1998).

This study investigated the timing of ATL involvement
in semantic processing by applying TMS in a chronomet-
ric fashion. Double-pulse TMS was applied to the left ATL
during a synonym judgment task and a nonsemantic
control task (to assess for any nonspecific effects of
ATL cTMS and to test if the cTMS effect is specific to
semantic processing). This allowed identification of the
time at which the ATL is crucial for semantic processing,
hypothesized to be around 400 msec from stimulus
onset. The ATL may also be active at other time points,
for instance, by contributing to early top–down process-
ing, but it is unclear whether this activation is vital for
semantic processing.

METHODS

Participants

Fifteen healthy, native, English-speaking volunteers with
normal or corrected-to-normal vision (seven women; mean
age = 24.39 years, SD = 5.98 years) completed the exper-
iment, which was approved by the local ethics board.

Materials

The synonym judgment task was adapted from previous
ATL offline rTMS, neuropsychological, and fMRI studies
(Lambon Ralph, Ehsan, Baker, & Rogers, 2012; Binney
et al., 2010; Jefferies, Patterson, Jones, & Lambon Ralph,
2009; Pobric et al., 2007). This paradigm has proved to be
a sensitive probe of semantic processing and has gen-
erated convergent cross-methodology evidence for the
selective role of the ATL in semantic processing. These
studies have not provided information, Tuttavia, Di
the time course of this ATL semantic computation (IL
aim of the current study). As dual-pulse TMS has a small
effect size, we picked a task known to be sensitive to
semantic impairment and tried to maximize the number
of trials per condition. The TMS task was developed in a
series of steps to meet these design goals but to maintain

a minimal level of accuracy and thus relatively stable item
RTs. In the first step, we selected 300 low-imageability
(target words mean imageability = 265.95, SD = 59.30,
using Bird, Franklin, & Howard’s, 2001, ratings) E
low-frequency (target words mean CELEX frequency =
9.85, SD = 5.35) words because past studies have shown
them to be more sensitive to ATL rTMS, to the mild
semantic impairment in patients with unilateral ATL
resection, and to lead to poorer performance in SD
patients (Hoffman, Jones, & Ralph, 2013; Lambon Ralph
et al., 2012; Hoffman & Lambon Ralph, 2011; Jefferies
et al., 2009; Lambon Ralph, Pobric, & Jefferies, 2009;
Pobric, Lambon Ralph, & Jefferies, 2009). In the second
step, we screened these items in a behavioral pilot of
eight postgraduate students and staff (six women; mean
age = 27 years). Only items that reached 75% accuracy
were selected for further consideration, as is commonly
performed in psycholinguistic studies (per esempio., Gibson,
Piantadosi, & Fedorenko, 2011; Aoshima, Phillips, &
Weinberg, 2004; Gibson & Warren, 2004). Di conseguenza,
each task contained 200 experimental and 55 practice tri-
COME. A third and final screening of the items was necessary:
The TMS experiment employed predominantly under-
graduate students (seven women; mean age = 24.39 years)
who displayed a different speed–accuracy trade off on
the two tasks (they were around 10% faster on the syn-
onym task yet less accurate than the participants in the
second item screening step). Accordingly, the least accu-
rate trials were again screened at the 75% accuracy level
to remove the most errorful items and to maintain a low
level of noise within the associated RTs. Seventeen items
in the synonym judgment task and 23 in the control judg-
ment task had a mean accuracy below 75%. These items
were removed from the analyses.

Semantic Task

In each semantic trial, participants were presented with
three words: a probe (per esempio., rhythm), a target synonym
(per esempio., cadence), and an unrelated foil (per esempio., rete).
Participants were asked to select which word was most
related in meaning to the probe. The two options were
matched within trials for frequency (foil mean 10.01,
SD = 11.15, T(199) = −0.22, p > .05), imageability (foil
mean 268.78, SD = 58.00, T(199) = −1.51, p > .05), E
part of speech. The RT and accuracy was examined in a
pilot study (mean RT = 1265.4 msec, mean accuracy =
94.4%).

Intertask and Intratask Controls

The number judgment task was designed to match the
synonym test in overall difficulty (RTs and accuracy: pilot
study, mean RT = 1295.38, mean accuracy = 96.2%).
Participants were asked to choose which three-digit num-
ber was closest to the probe in terms of numerical value
(per esempio., probe, 391; target, 379; foil, 377). This intertask

Jackson, Lambon Ralph, and Pobric

1389

D
o
w
N
l
o
UN
D
e
D

F
R
o
M

/
j

F
/

T
T

io
T
.

:
/
/

/
j

tu
S
e
R

o
N

1
7

M
UN
sì

2
0
2
1

comparison provides, Perciò, an important assessment
for the selectivity of semantic processing in the ATL and
also for any nonspecific effects of ATL cTMS. Following
previous rTMS examinations of ATL function (per esempio., Chiou,
Sowman, Etchell, & Rich, 2013; Pobric et al., 2007), we
expected a slowing of semantic decision times but no
effect on the control task—which would rule out any
alternative explanation of the semantic data in terms of
nonspecific effects of ATL cTMS. Inoltre, a further
potential advantage of cTMS over offline rTMS is that
cTMS can provide an “intratask control” if decision times
are slowed at some but not all of the probed time points
(per esempio., Duncan et al., 2010). As noted above, we hypothe-
sized that cTMS might have its greatest effect on the
semantic task around 400 msec poststimulus presen-
tazione, but not at its onset. If this timing pattern was
coupled with no effect of TMS on the control task at
any time point, then the intertask and intratask data
would provide evidence for both task and time selectivity
of semantic processing in the ATL.

Procedure

A PC running ePrime (Psychology Software Tools, Inc.,
Pittsburgh, PAPÀ) was used to present the items and record
participant’s responses. The participants completed two
sessions (one for each task) almeno 1 week apart. IL
order of sessions was counterbalanced across participants.
The order of trials was randomized. At the start of
every trial, a fixation point was presented in the middle
of the screen for 500 msec. Then the target and foil

choices appeared at the top of the screen and remained
for 2500 msec. These items were replaced by a fixation
cross at the bottom of the screen, which remained for
200 msec before the probe item appeared in its place.
The target and foil item returned at the same time. Tutto
three items remained on screen for 2500 msec or until
the participant’s button-press response (Guarda la figura 1).
They were instructed to respond as quickly and accurate-
ly as possible. Displaying the foil and target before the
probe allowed us to measure RT and to compute stimu-
lation times against a single stimulus event (presentation
of the probe item) rather than the complexities involved
in timing from dual presentation of the target and foil
items.

Design

The experiment employed a 2 × 5 repeated-measures
design with Task (semantic vs. controllo) and TMS time
(−40 msec vs. 100 msec vs. 250 msec vs. 400 msec vs.
800 msec) as the within-participant factors. The −40 msec
time point was employed as a baseline. This is superior to
comparison against a no-TMS condition, because TMS
can produce generalized alerting effects (Pobric et al.,
2007; Dräger, Breitenstein, Helmke, Kamping, & Knecht,
2004). Interleaving trials without TMS stimulation has also
been shown to affect the online TMS results and our own
pilot study found slowing in the trials immediately after
no TMS trials, perhaps reflecting increased attention to
the stimulation following its absence (Kapoula, Yang,
Coubard, Daunys, & Orssaud, 2005). Accordingly, we

Figura 1. The structure and
timing of a trial. In both
compiti, a target and a foil item
appeared after a fixation
cross. Participants had time
to read these items before
presentation of the probe
item in place of a fixation
cross. The participants were
then required to indicate
which item was closer
numerically or semantically.

1390

Journal of Cognitive Neuroscience

Volume 27, Numero 7

D
o
w
N
l
o
UN
D
e
D

F
R
o
M

/
j

T
T

F
/

io
T
.

:
/
/

/
j

tu
S
e
R

o
N

1
7

M
UN
sì

2
0
2
1

adopted two types of control/baseline: (UN) comparison to
stimulation at −40 msec when semantic processing of the
probe item had not yet started and (B) an RT-matched non-
semantic control task used to detect potential nonsemantic
variation of decision times after stimulation at different
SOAs. In both sessions, participants completed a practice
Di 55 trials. They then completed 200 trials with TMS deliv-
ered at five different time points. These trials were split into
blocks of 40, allowing participants to take a break in
between.

Stimulation Parameters

TMS was delivered using a Magstim Rapid2 stimulator
(Magstim Co., Whitland, UK) and a figure-of-eight coil
with a diameter of 50 mm. Stimulation was performed
at 100% of the individual’s motor threshold, measured
before the start of each session. The resting motor
threshold of the relaxed contralateral abductor pollicis
brevis muscle was measured as the lowest stimulation in-
tensity able to cause a visible twitch in the muscle 5 fuori
Di 10 times (Sandrini et al., 2011B). Motor thresholds
ranged from 40% A 66% of stimulator output (mean =
57.2, SD = 7.06).

Double-pulse TMS was used as the effects of two
pulses summate while maintaining temporal specificity
(Pitcher et al., 2007). This inhibitory effect has been dem-
onstrated in a variety of domains including language
processing (Sliwinska, Khadilkar, Campbell-Ratcliffe,
Quevenco, & Devlin, 2012; Duncan et al., 2010; O’Shea,
Johansen-Berg, Trief, Gobel, & Rushworth, 2007; Pitcher
et al., 2007; Juan & Walsh, 2003). Two TMS pulses were
delivered 40 msec apart in each trial. This gap is the smal-
lest possible with the TMS equipment used and has been
consistently employed in double pulse studies (Sliwinska
et al., 2012; O’Shea et al., 2007; Pitcher et al., 2007; Juan
& Walsh, 2003). The two pulses were applied at −40 and
0 msec, 100 E 140 msec, 250 E 290 msec, 400 E
440 msec, E 800 E 840 msec following presentation
of the probe number or word. Participants received stim-
ulation in every trial, but the stimulation time was ran-
domized. These stimulation times were designed to
sample a full range of potentially important times at
which crucial semantic processing might occur in the
ATL, including the hypothesized time of 400 msec as well
as earlier and later time points.

Selection of TMS Site

A Phillips MR Achieva scanner (Phillips Electronics,
Amsterdam, The Netherlands) was used to acquire high-
resolution T1-weighted anatomical images of each par-
ticipant. The scan had an in-plane resolution of 1 mm
with a slice thickness of 1.8 mm. The acquisition matrix
era 256 × 256 voxels. Full head coverage was maintained,
causing the number of slices acquired to vary depending
on head size.

An Ascension Minibird magnetic tracking system
(Ascension Technology Co., Burlington, VT) was used
to coregister the participant’s scalp and T1-weighted
MRI scan on MRIreg (www.MRIcro.com/mrireg.html).
The individual’s ATL coordinates were determined by
measuring 10 mm posterior along the middle temporal
gyrus from the tip of the left temporal pole. The average
MNI coordinates were [−50, 12, −29].

Every effort was taken to minimize the potential dis-
comfort of stimulating the ATL. Following the procedures
developed in our previous studies (Pobric, Jefferies, &
Lambon Ralph, 2010UN; Pobric et al., 2007), coil orienta-
tion was manipulated for maximum comfort and stimulus
intensity was reduced if the participant considered the
stimulation unpleasant. As noted above, nonspecific
effects of online TMS (such as muscle twitches) on RTs
were evaluated using the difficulty-matched nonsemantic
control task as well as intratask comparisons (different
time points during the semantic task).

Analyses
A composite RT–accuracy measure was used as the pri-
mary indicator of overall performance, because it allows
for speed–accuracy trade-off variation across participants.
The measure is commonly used in experimental psychol-
ogy for this reason and is also useful in TMS studies
Dove, across participants, the effects of TMS can be
found in RTs, errors, or both (Cattaneo, Vecchi, Pascual-
Leone, & Silvanto, 2009; Chambers, Stokes, & Mattingley,
2004; Townsend & Ashby, 1983). Following the stan-
dard method, the composite measure was computed as
RT/accuracy (Townsend & Ashby, 1983). For each partici-
pant and each time point, trials with RTs more than 2 SDs
from the mean were considered outliers and removed,
causing a loss of 4.42% of the remaining semantic and
4.4% of the control trials.

The effects of double-pulse TMS at different time
points on the composite performance was assessed using
UN 2 × 5 within-subject ANOVA with the repeated-measures
factors Task (synonym judgment, number judgment) E
TMS time (−40, 100, 250, 400, 800 msec). To assess the
time points at which there was a greater effect of TMS on
the semantic task, the ANOVA was repeated for two sub-
sets of time points. The change in performance caused by
TMS at time points implicated in these ANOVAs was com-
puted by subtracting the individual’s mean composite
score at these time points from their mean composite
score at the baseline time point on the each task. Questo
allowed comparison of the effect of TMS at each time
point on the two different tasks.

RESULTS

The results for the two tasks at each time point are
shown in Figure 2, with a clear effect of cTMS arising

Jackson, Lambon Ralph, and Pobric

1391

D
o
w
N
l
o
UN
D
e
D

F
R
o
M

/
j

T
T

F
/

io
T
.

:
/
/

/
j

tu
S
e
R

o
N

1
7

M
UN
sì

2
0
2
1

Figura 2. Composite score
(RT/accuracy) for the semantic
and control tasks at each
different TMS time point.
Error bars denote SEM,
corrected for a within-
participant design (Loftus &
Masson, 1994). A significant
TMS effect was found for
the later time points (denoted
by the asterisk). A borderline,
weak effect was detected at
250 msec (see main text).

D
o
w
N
l
o
UN
D
e
D

F
R
o
M

/
j

F
/

T
T

io
T
.

:
/
/

/
j

tu
S
e
R

o
N

1
7

M
UN
sì

2
0
2
1

for the semantic task but no effect at any time point for
the control task. UN 2 ( Task; control vs. semantic) × 5
(Stimulation time point; −40 vs. 100 vs. 250 vs. 400 vs.
800 msec) repeated-measures ANOVA found no signifi-
cant main effects, Ma, crucially, there was an interaction
of Task and TMS time point, F(4, 56) = 2.6, p = .046, par-
tial η2 = .156. The nature of this TMS interaction was con-
firmed in the following way. As expected, given the pilot
data and careful RT matching of the tasks for general dif-
ficulty, performance was not significantly different be-
tween the two tasks at the −40 msec baseline time
point, T(14) = −.632, p = .538, two-tailed; così, this time
point provided a suitable baseline reference to compare
changes in performance across the other time points. Ac-
cordingly, the relative effect of cTMS at each time point was
extracted by subtracting the baseline (−40 msec) compos-
ite score from the composite score at each experimental
time point. The two tasks were then compared directly
by computing direction-specific, one-tailed t tests as we ex-
pected ATL TMS to slow semantic decision times, as found
in numerous previous ATL offline rTMS studies (per esempio., Chiou
et al., 2013; Pobric et al., 2007). As is clear from Figure 2,
this analysis confirmed that there was significant slowing of
the semantic over control task at 400 msec, T(14) = −2.101,
p = .027, E 800 msec, T(14) = −2.038, p = .030. The dif-
ference at 250 msec was of borderline significance ( p = .15).

There were no significant effects at any of the other time
points ( p > .05).

A second additional analysis confirmed these same
risultati. We used an interaction contrast to confirm the
significant effects of cTMS at 400 E 800 msec on the
semantic task alone. Specifically, we averaged the data
across these two time points for each task and contrasted
them against the combined data for the earlier time
points. Again, following the pattern shown in Figure 2,
there was no change in performance on the control task
between the earlier and later time points, T(14) = .224,
p = .826, whereas there was a significant slowing for
the semantic task, T(14) = 9.536, P < .001. We also for- mally compared the early-to-late changes in performance across the two tasks and confirmed that the early-to-late slowing on the semantic task was significantly greater than the null effect on the control task, t(14) = 4.891, p < .001. Accuracy and RT scores were also analyzed separately (see Table 1). Accuracy was relatively stable across condi- tions and tasks. The ANOVA on these data demonstrated no significant results, although numerically the greatest TMS effects were apparent at the 400 and 800 msec time points in the semantic task. RT changes mirrored those in the composite score, and the ANOVA on these data confirmed the same interaction between Task and TMS Table 1. Mean RT (msec) and Accuracy per TMS Time Point TMS Time (msec) RT (SD) Accuracy (SD) RT (SD) Accuracy (SD) Semantic Task Control Task −40 100 250 400 800 1177.31 (231.58) 1150.57 (261.07) 1178.56 (310.07) 1206.56 (291.9) 1234.15 (310.09) .924 (.06) .919 (.08) .907 (.04) .895 (.08) .917 (.05) 1149.58 (297.16) 1141.11 (288.99) 1108.46 (292.72) 1125.34 (327.71) 1145.72 (303.90) .922 (.05) .911 (.05) .906 (.06) .912 (.08) .939 (.04) 1392 Journal of Cognitive Neuroscience Volume 27, Number 7 time, F(4, 56) = 2.556, p = .049, partial η2 = .154. We explored this interaction in the same way as described above for the composite score. The same pattern emerged, with a significant slowing in the semantic compared to control task at 400 msec, t(14) = −2.694, p = .009, and 800 msec, t(14) = −2.109, p = .026. As before, the TMS effect at these time points was not significantly different to the −40 msec baseline for the control task, t(14) = −.127, p = .901, but was for the semantic task, t(14) = −2.50, p = .025. Again, this difference between the two tasks was significant, t(14) = 2.528, p = .024. DISCUSSION cTMS was used to elucidate the time at which the left ATL is crucial for semantic processing. TMS had a significant effect on semantic performance at 400 and 800 msec poststimulus onset. No significant effects of TMS were observed at any point during the control task. These results add to the convergent evidence for a critical role of the ATL in semantic processing (from neuro- psychological, offline TMS, and neuroimaging studies: Visser et al., 2012; Visser & Lambon Ralph, 2011; Binney et al., 2010; Patterson et al., 2007; Pobric et al., 2007) and reveal the temporal dynamics of this processing for the first time. MEG studies demonstrate two stages of processing in semantic tasks: early processing within sensory areas and then a large degree of interactivity between higher-order pan-modal areas (Marinkovic et al., 2003; Halgren et al., 2002; Dale et al., 2000). A translational phase between modality-specific and pan-modal processing is thought to start around 230 msec poststimulus presentation (Marinkovic et al., 2003). ATL involvement has been iden- tified within the second pan-modal stage, peaking around 400 msec (Shimotake et al., 2014; Marinkovic et al., 2003; Halgren et al., 2002). The current study not only provides convergent evidence for these hypotheses but goes fur- ther to demonstrate that ATL activity at this time point is critical for semantic processing, which neuroimaging studies alone cannot establish. Although this has only been demonstrated here in a single modality using visu- ally presented abstract words, the evidence of a more general necessity from rTMS and the demonstration of a multimodal processing stage support the likelihood that the critical role of the ATL occurs at a similar time for different modalities. Theories that limit the role of the ATL to social entities (e.g., Ross & Olson, 2010; Olson, Ploaker, & Ezzyat, 2007; Moll, Zahn, de Oliveira- Souza, Krueger, & Grafman, 2005), unique entities (e.g., Tranel, 2009), or combinatorial processes (Lau, Phillips, & Poeppel, 2008; Hickok & Poeppel, 2007) cannot easily explain the current and prior rTMS studies that used a range of stimuli including single basic-level, nonsocial concepts and found significant effects of TMS in all cases (see Lambon Ralph, 2014, for a more detailed review and discussion). Our results indicate that there was a contribution from the left ATL to semantic processing (as probed by syno- nym judgements), which began to emerge at 250 msec and became statistically reliable from 400 msec after stim- ulus presentation. This fits the timing of the N400 in elec- trophysiological studies, suggesting the ATL as one potential source. Source localization of the EEG signal in previous studies has generated conflicting results about the N400 source, although a number of studies have implicated a distributed frontotemporal network (Kutas & Federmeier, 2011b; Lau et al., 2008; Van Petten & Luka, 2006). In addition, intracortical recordings have localized an N400-like ERP to areas including anterior fusiform gyrus and the temporal pole (McCarthy et al., 1995; Nobre & McCarthy, 1995; Halgren, Baudena, Heit, Clarke, & Marinkovic, 1994; Nobre, Allison, & McCarthy, 1994), and MEG studies indicate a pan-modal role for the ATL at this time point as well (Maess, Herrmann, Hahne, Nakamura, & Friederici, 2006; Marinkovic et al., 2003; Halgren et al., 2002). Finally, damage to left or right ATL can result in a loss of the N400 (Kotz, Opitz, & Friederici, 2007). One interpretation of the N400 is that it reflects semantic access regardless of input modality (Kutas & Federmeier, 2011b; Kutas & Federmeier, 2000). This implies that the areas involved are responsible for pan-modal processing (Kutas & Federmeier, 2011b; Holcomb & Anderson, 1993). Within the hub-and-spoke semantic model, the ATL hub is responsible for pan-modal representation, whereas the “spokes” represent modality-specific information (Pobric, Jefferies, & Lambon Ralph, 2010b; Patterson et al., 2007). Thus, the modality-invariant processing within the ATL could be reflected in the N400, a notion consistent with the current cTMS findings. Instead of viewing the N400 as representing semantic processing per se, some researchers have suggested that it is an index of violations of expectation, reflecting a pro- cess whereby words or other constituent parts are inte- grated into a context (Brown & Hagoort, 1993; Kutas & Hillyard, 1980). This violation requires semantic and lex- ical access, however, and so it is unclear that these expla- nations are mutually exclusive. The left ATL may be one of the N400 sources responsible for access and integra- tion of pan-modal semantic representations. To assess whether the ATL is a source of the N400, future studies could assess the effect of ATL TMS in eradicating the N400 component. The left ATL seems to remain involved in the semantic task at 800 msec after stimulus presenta- tion. This extends beyond the time of the N400, although studies of the N400 typically use simpler stimuli and sin- gle items (for a review, see Kutas & Federmeier, 2011a). This longer involvement of the left ATL in semantic pro- cessing might reflect continued semantic processing of the items and comparison between them. In keeping with most TMS explorations of higher cog- nition, we observed an effect on RT and the combined efficiency measure, rather than on accuracy alone (e.g., Sliwinska et al., 2012; Ishibashi, Lambon Ralph, Saito, & Jackson, Lambon Ralph, and Pobric 1393 D o w n l o a d e d f r o m l l / / / / j t t f / i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e d o u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 7 / 7 2 7 1 / 3 7 8 / 8 1 1 3 9 8 4 8 9 / 2 1 9 7 6 8 o 2 c 9 n 2 _ 0 a / _ j 0 o 0 c 7 n 8 8 _ a p _ d 0 0 b 7 y 8 g 8 u . e p s t d o f n b 0 y 8 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j . t / f u s e r o n 1 7 M a y 2 0 2 1 Pobric, 2011; Duncan et al., 2010; Hoffman et al., 2010; Stoeckel, Gough, Watkins, & Devlin, 2009; Gough, Nobre, & Devlin, 2005; Dräger et al., 2004; Devlin, Matthews, & Rushworth, 2003). Two possible interpretations of this outcome are possible. One explanation is that double- pulse TMS does not stop processing in the target region but instead “injects noise” into the local computation undertaken by that area, resulting in inefficient rather than deficient processing. The second is that TMS might halt local computation, but this is transient in nature and limited in coverage (e.g., like a small lesion in some neuro- psychological patients—which can generate changes in RTs rather than accuracy). The second possibility is con- sistent with the facts that TMS disruption is transient (around 10–20 msec) and relatively focal (around 20 mm). The precise mechanism by which TMS affects behavior is not well understood. Both hypotheses have been proposed, before; that is, TMS might inhibit activity (the traditional “virtual lesion” view) or inject noise into the system (Miniussi, Ruzzoli, & Walsh, n.d.; Sandrini et al., 2011a; Harris, Clifford, & Miniussi, 2008; Walsh & Cowey, 2000). In this context, it is perhaps worth noting that even the effect resulting from partial removal of neural tissue can be considered in both ways: for example, partial removal of units or connections in computational models of semantic memory generates a combination of reduced flow of activation and noisy processing (e.g., Schapiro, McClelland, Welbourne, Rogers, & Lambon Ralph, 2013; Lambon Ralph, Lowe, & Rogers, 2007). Even if one con- ceives dual-pulse TMS as injecting transient noise into local processing, then the main conclusions from this study hold: namely, the left ATL is directly implicated in semantic cognition and its involvement (at least in verbal tasks such as synonym judgment) is maximally important 400 msec after stimulus onset. Finally, we note that, although we only obtained a borderline, minimal effect of cTMS at 250 msec, some neuroimaging studies have implicated this and earlier time points. Superordinate semantic differences have been shown in the phase-locking of the ATL from 120 msec and in activity level from 170 msec (Clarke et al., 2011). Similarly, intracortical electrode recordings have shown category-sensitive responses in inferior anterior temporal areas less than 200 msec poststimulus presentation (Liu et al., 2009). There are at least three possible explanations. First, electrophysiological data reflect changes in activity level, whereas TMS might elucidate the time at which an area becomes necessary (Walsh & Cowey, 2000). Thus, it may be that the left ATL starts to become involved before 250 msec, but its contribution does not become crucial until around 400 msec. A second possibility is that the early activity may be critical in certain conditions, such as more general semantic (domain/category) distinctions than those probed in this cTMS study (Clarke et al., 2011) or in tasks using impoverished stimuli that may promote greater top–down processing (e.g., Bar et al., 2006). Finally, an alternative possibility is that there is an earlier critical phase of ATL involvement but that this is much smaller and transient in nature, making it much harder to detect with cTMS (the borderline effect observed at 250 msec is consistent with this hypothesis). Acknowledgments R. L. J. was supported by an EPSRC-funded studentship. The research was supported by an MRC program grant to M. A. L. R. (MR/J004146/1). Reprint requests should be sent to Dr. Gorana Pobric or Prof. Matthew A. Lambon Ralph, Neuroscience and Aphasia Research Unit, School of Psychological Sciences (Zochonis Building), University of Manchester, Brunswick Street, Manchester, M13 9PL, United Kingdom, or via e-mail: gorana.pobric@manchester. ac.uk, matt.lambon-ralph@manchester.ac.uk. REFERENCES Aoshima, S., Phillips, C., & Weinberg, A. (2004). Processing filler-gap dependencies in a head-final language. Journal of Memory and Language, 51, 23–54. Bar, M., Kassam, K. S., Ghuman, A. S., Boshyan, J., Schmidt, A. M., Dale, A. M., et al. (2006). Top–down facilitation of visual recognition. Proceedings of the National Academy of Sciences, U.S.A., 103, 449–454. Binder, J. R., Desai, R. H., Graves, W. W., & Conant, L. L. (2009). Where is the semantic system? A critical review and meta-analysis of 120 functional neuroimaging studies. Cerebral Cortex, 19, 2767–2796. Binney, R. J., Embleton, K. V., Jefferies, E., Parker, G. J. M., & Lambon Ralph, M. A. (2010). The ventral and inferolateral aspects of the anterior temporal lobe are crucial in semantic memory: Evidence from a novel direct comparison of distortion-corrected fMRI, rTMS, and semantic dementia. Cerebral Cortex, 20, 2728–2738. Bird, H., Franklin, S., & Howard, D. (2001). Age of acquisition and imageability ratings for a large set of words, including verbs and function words. Behavior Research Methods Instruments & Computers, 33, 73–79. Brown, C., & Hagoort, P. (1993). The processing nature of the N400—Evidence from masked priming. Journal of Cognitive Neuroscience, 5, 34–44. Cattaneo, Z., Vecchi, T., Pascual-Leone, A., & Silvanto, J. (2009). Contrasting early visual cortical activation states causally involved in visual imagery and short-term memory. European Journal of Neuroscience, 30, 1393–1400. Chambers, C. D., Stokes, M. G., & Mattingley, J. B. (2004). Modality-specific control of strategic spatial attention in parietal cortex. Neuron, 44, 925–930. Chiou, R., Sowman, P. F., Etchell, A. C., & Rich, A. N. (2013). A conceptual lemon: Theta burst stimulation to the left anterior temporal lobe untangles object representation and its canonical color. Journal of Cognitive Neuroscience, 26, 1066–1074. Clarke, A., Taylor, K. I., & Tyler, L. K. (2011). The evolution of meaning: Spatio-temporal dynamics of visual object recognition. Journal of Cognitive Neuroscience, 23, 1887–1899. Dale, A. M., Liu, A. K., Fischl, B. R., Buckner, R. L., Belliveau, J. W., Lewine, J. D., et al. (2000). Dynamic statistical parametric mapping: Combining fMRI and MEG for high- resolution imaging of cortical activity. Neuron, 26, 55–67. Devlin, J. T., Matthews, P. M., & Rushworth, M. F. S. (2003). Semantic processing in the left inferior prefrontal cortex: A combined functional magnetic resonance imaging and 1394 Journal of Cognitive Neuroscience Volume 27, Number 7 D o w n l o a d e d f r o m l l / / / / j t t f / i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e d o u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 7 / 7 2 7 1 / 3 7 8 / 8 1 1 3 9 8 4 8 9 / 2 1 9 7 6 8 o 2 c 9 n 2 _ 0 a / _ j 0 o 0 c 7 n 8 8 _ a p _ d 0 0 b 7 y 8 g 8 u . e p s t d o f n b 0 y 8 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j . f / t u s e r o n 1 7 M a y 2 0 2 1 transcranial magnetic stimulation study. Journal of Cognitive Neuroscience, 15, 71–84. Dräger, B., Breitenstein, C., Helmke, U., Kamping, S., & Knecht, S. (2004). Specific and nonspecific effects of transcranial magnetic stimulation on picture-word verification. European Journal of Neuroscience, 20, 1681–1687. Duncan, K. J., Pattamadilok, C., & Devlin, J. T. (2010). Investigating occipito-temporal contributions to reading with TMS. Journal of Cognitive Neuroscience, 22, 739–750. Gibson, E., Piantadosi, S., & Fedorenko, K. (2011). Using mechanical turk to obtain and analyze English acceptability judgments. Language and Linguistics Compass, 5, 509–524. Gibson, E., & Warren, T. (2004). Reading-time evidence for intermediate linguistic structure in long-distance dependencies. Syntax, 7, 55–78. Gough, P. M., Nobre, A. C., & Devlin, J. T. (2005). Dissociating linguistic processes in the left inferior frontal cortex with transcranial magnetic stimulation. Journal of Neuroscience, 25, 8010–8016. Halgren, E., Baudena, P., Heit, G., Clarke, M., & Marinkovic, K. (1994). Spatiotemporal stages in face and word-processing. 1. Depth recorded potentials in the human occipital and parietal lobes. Journal of Physiology-Paris, 88, 1–50. Halgren, E., Dhond, R. P., Christensen, N., Van Petten, C., Marinkovic, K., Lewine, J. D., et al. (2002). N400-like magnetoencephalography responses modulated by semantic context, word frequency, and lexical class in sentences. Neuroimage, 17, 1101–1116. Harris, J. A., Clifford, C. W., & Miniussi, C. (2008). The functional effect of transcranial magnetic stimulation: Signal suppression or neural noise generation? Journal of Cognitive Neuroscience, 20, 734–740. Helenius, P., Salmelin, R., Service, E., & Connolly, J. F. (1998). Distinct time courses of word and context comprehension in the left temporal cortex. Brain, 121, 1133–1142. Hickok, G., & Poeppel, D. (2007). The cortical organization of speech processing. Nature Reviews Neuroscience, 8, 393–402. Hoffman, P., Jefferies, E., & Lambon Ralph, M. A. (2010). Ventrolateral prefrontal cortex plays an executive regulation role in comprehension of abstract words: Convergent neuropsychological and repetitive TMS evidence. Journal of Neuroscience, 30, 15450–15456. Hoffman, P., Jones, R. W., & Ralph, M. A. L. (2013). Be concrete to be comprehended: Consistent imageability effects in semantic dementia for nouns, verbs, synonyms and associates. Cortex, 49, 1206–1218. Hoffman, P., & Lambon Ralph, M. A. (2011). Reverse concreteness effects are not a typical feature of semantic dementia: Evidence for the hub-and-spoke model of conceptual representation. Cerebral Cortex, 21, 2103–2112. Holcomb, P. J., & Anderson, J. E. (1993). Cross-modal semantic priming—A time-course analysis using event-related brain potentials. Language and Cognitive Processes, 8, 379–411. Ilmoniemi, R. J., Virtanen, J., Ruohonen, J., Karhu, J., Aronen, H. J., Näätänen, R., et al. (1997). Neuronal responses to magnetic stimulation reveal cortical reactivity and connectivity. NeuroReport, 8, 3537–3540. Ishibashi, R., Lambon Ralph, M. A., Saito, S., & Pobric, G. (2011). Different roles of lateral anterior temporal lobe and inferior parietal lobule in coding function and manipulation tool knowledge: Evidence from an rTMS study. Neuropsychologia, 49, 1128–1135. Jahanshahi, M., & Dirnberger, G. (1999). The left dorsolateral prefrontal cortex and random generation of responses: Studies with transcranial magnetic stimulation. Neuropsychologia, 37, 181–190. Jefferies, E., & Lambon Ralph, M. A. (2006). Semantic impairment in stroke aphasia versus semantic dementia: A case-series comparison. Brain, 129, 2132–2147. Jefferies, E., Patterson, K., Jones, R. W., & Lambon Ralph, M. A. (2009). Comprehension of concrete and abstract words in semantic dementia. Neuropsychology, 23, 492–499. Juan, C. H., & Walsh, V. (2003). Feedback to V1: A reverse hierarchy in vision. Experimental Brain Research, 150, 259–263. Kapoula, Z., Yang, Q., Coubard, O., Daunys, G., & Orssaud, C. (2005). Contextual influence of TMS on the latency of saccades and vergence. Neuroscience Letters, 376, 87–92. Kotz, S. A., Opitz, B., & Friederici, A. D. (2007). ERP effects of meaningful and non-meaningful sound processing in anterior temporal patients. Restorative Neurology and Neuroscience, 25, 273–284. Kutas, M., & Federmeier, K. D. (2000). Electrophysiology reveals semantic memory use in language comprehension. Trends in Cognitive Sciences, 4, 463–470. Kutas, M., & Federmeier, K. D. (2011a). Thirty years and counting: Finding meaning in the N400 component of the event-related brain potential (ERP). In S. T. Fiske, D. L. Schacter, & S. E. Taylor (Eds.), Annual review of psychology (Vol. 62, pp. 621–647). Palo Alto, CA: Annual Review, Inc. Kutas, M., & Federmeier, K. D. (2011b). Thirty years and counting: Finding meaning in the N400 component of the event-related brain potential (ERP). Annual Review of Psychology, 62, 621–647. Kutas, M., & Hillyard, S. A. (1980). Reading senseless sentences— Brain potentials reflect semantic incongruity. Science, 207, 203–205. Lambon Ralph, M. A. (2014). Neurocognitive insights on conceptual knowledge and its breakdown. Royal Society Proceedings B, 369, 20120392. Lambon Ralph, M. A., Ehsan, S., Baker, G. A., & Rogers, T. T. (2012). Semantic memory is impaired in patients with unilateral anterior temporal lobe resection for temporal lobe epilepsy. Brain, 135, 242–258. Lambon Ralph, M. A., Lowe, C., & Rogers, T. T. (2007). Neural basis of category-specific semantic deficits for living things: Evidence from semantic dementia, HSVE and a neural network model. Brain, 130, 1127–1137. Lambon Ralph, M. A., Pobric, G., & Jefferies, E. (2009). Conceptual knowledge is underpinned by the temporal pole bilaterally: Convergent evidence from rTMS. Cerebral Cortex, 19, 832–838. Lambon Ralph, M. A., Sage, K., Jones, R. W., & Mayberry, E. J. (2010). Coherent concepts are computed in the anterior temporal lobes. Proceedings of the National Academy of Sciences, U.S.A., 107, 2717–2722. Lau, E. F., Phillips, C., & Poeppel, D. (2008). A cortical network for semantics: (De)constructing the N400. Nature Reviews Neuroscience, 9, 920–933. Liu, H. S., Agam, Y., Madsen, J. R., & Kreiman, G. (2009). Timing, timing, timing: Fast decoding of object information from intracranial field potentials in human visual cortex. Neuron, 62, 281–290. Loftus, G. R., & Masson, M. E. J. (1994). Using confidence intervals in within-subject designs. Psychonomic Bulletin & Review, 1, 476–490. Maess, B., Herrmann, C. S., Hahne, A., Nakamura, A., & Friederici, A. D. (2006). Localizing the distributed language network responsible for the N400 measured by MEG during auditory sentence processing. Brain Research, 1096, 163–172. Marinkovic, K., Dhond, R. P., Dale, A. M., Glessner, M., Carr, V., & Halgren, E. (2003). Spatiotemporal dynamics of modality- specific and supramodal word processing. Neuron, 38, 487–497. Jackson, Lambon Ralph, and Pobric 1395 D o w n l o a d e d f r o m l l / / / / j f / t t i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e d o u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 7 / 7 2 7 1 / 3 7 8 / 8 1 1 3 9 8 4 8 9 / 2 1 9 7 6 8 o 2 c 9 n 2 _ 0 a / _ j 0 o 0 c 7 n 8 8 _ a p _ d 0 0 b 7 y 8 g 8 u . e p s t d o f n b 0 y 8 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j t f / . u s e r o n 1 7 M a y 2 0 2 1 McCarthy, G., Nobre, A. C., Bentin, S., & Spencer, D. D. Sandrini, M., Umilta, C., & Rusconi, E. (2011b). The use of (1995). Language-related field potentials in the anterior- medial temporal lobe. 1. Intracranial distribution and neural generators. Journal of Neuroscience, 15, 1080–1089. Miniussi, C., Ruzzoli, M., & Walsh, V. (n.d.). The mechanism of transcranial magnetic stimulation in cognition. Cortex, 46, 128–130. Moll, J., Zahn, R., de Oliveira-Souza, R., Krueger, F., & Grafman, J. (2005). The neural basis of human moral cognition. Nature Reviews Neuroscience, 6, 799–809. Nobre, A. C., Allison, T., & McCarthy, G. (1994). Word recognition in the human inferior temporal lobe. Nature, 372, 260–263. Nobre, A. C., & McCarthy, G. (1995). Language-related field potentials in the anterior-medial temporal-lobe. 2. Effects of word type and semantic priming. Journal of Neuroscience, 15, 1090–1098. Noonan, K. A., Jefferies, E., Visser, M., & Lambon Ralph, M. A. (2013). Going beyond inferior prefrontal involvement in semantic control: Evidence for the additional contribution of dorsal angular gyrus and posterior middle temporal cortex. Journal of Cognitive Neuroscience, 25, 1824–1850. Olson, I. R., Ploaker, A., & Ezzyat, Y. (2007). The enigmatic temporal pole: A review of findings on social and emotional processing. Brain, 130, 1718–1731. O’Shea, J., Johansen-Berg, H., Trief, D., Gobel, S., & Rushworth, M. F. S. (2007). Functionally specific reorganisation in human premotor reorganization cortex. Neuron, 54, 479–490. Pascual-Leone, A., Walsh, V., & Rothwell, J. (2000). Transcranial magnetic stimulation in cognitive neuroscience—Virtual lesion, chronometry, and functional connectivity. Current Opinion in Neurobiology, 10, 232–237. Patterson, K., Nestor, P. J., & Rogers, T. T. (2007). Where do you know what you know? The representation of semantic knowledge in the human brain. Nature Reviews Neuroscience, 8, 976–987. Pitcher, D., Walsh, V., Yovel, G., & Duchaine, B. (2007). TMS evidence for the involvement of the right occipital face area in early face processing. Current Biology, 17, 1568–1573. Pobric, G., Jefferies, E., & Lambon Ralph, M. A. (2007). Anterior temporal lobes mediate semantic representation: Mimicking semantic dementia by using rTMS in normal participants. Proceedings of the National Academy of Sciences, U.S.A., 104, 20137–20141. Pobric, G., Jefferies, E., & Lambon Ralph, M. A. (2010a). Amodal semantic representations depend on both anterior temporal lobes: Evidence from repetitive transcranial magnetic stimulation. Neuropsychologia, 48, 1336–1342. Pobric, G., Jefferies, E., & Lambon Ralph, M. A. (2010b). Category-specific versus category-general semantic impairment induced by transcranial magnetic stimulation. Current Biology, 20, 964–968. Pobric, G., Lambon Ralph, M. A., & Jefferies, E. (2009). The role of the anterior temporal lobes in the comprehension of concrete and abstract words: rTMS evidence. Cortex, 45, 1104–1110. Pulvermuller, F., Shtyrov, Y., & Hauk, O. (2009). Understanding in an instant: Neurophysiological evidence for mechanistic language circuits in the brain. Brain and Language, 110, 81–94. Ross, L. A., & Olson, I. R. (2010). Social cognition and the anterior temporal lobes. Neuroimage, 49, 3452–3462. Sandrini, M., Umilta, C., & Rusconi, E. (2011a). The use of transcranial magnetic stimulation in cognitive neuroscience: A new synthesis of methodological issues. Neuroscience and Biobehavioral Reviews, 35, 516–536. transcranial magnetic stimulation in cognitive neuroscience: A new synthesis of methodological issues. Neuroscience and Behavioural Reviews, 35, 516–536. Schapiro, A. C., McClelland, J. L., Welbourne, S. R., Rogers, T. T., & Lambon Ralph, M. A. (2013). Why bilateral damage is worse than unilateral damage to the brain. Journal of Cognitive Neuroscience, 25, 2107–2123. Schuhmann, T., Schiller, N. O., Goebel, R., & Sack, A. T. (2012). Speaking of which: Dissecting the neurocognitive network of language production in picture naming. Cerebral Cortex, 22, 701–709. Schulter, N. D., Rushworth, M. F., Mills, K. R., & Passingham, R. E. (1999). Signal-, set-, and movement-related activity in the human premotor cortex. Neuropsychologia, 37, 233–243. Shimotake, A., Matsumoto, R., Ueno, T., Kunieda, T., Saito, S., Hoffman, P., et al. (2014) Direct exploration of the ventral anterior temporal lobe in semantic memory: Cortical stimulation and local field potential evidence from subdural grid electrodes. Cerebral Cortex. doi: 10.1093/cercor/bhu262. Silvanto, J., & Pascual-Leone, A. (2012). Why the assessment of causality in brain-behavior relations requires brain stimulation. Journal of Cognitive Neuroscience, 24, 775–777. Sliwinska, M. W., Khadilkar, M., Campbell-Ratcliffe, J., Quevenco, F., & Devlin, J. T. (2012). Early and sustained supramarginal gyrus contributions to phonological processing. Frontiers in Psychology, 3, 161. Stoeckel, C., Gough, P. M., Watkins, K. E., & Devlin, J. T. (2009). Supramarginal gyrus involvement in visual word recognition. Cortex, 45, 1091–1096. Terao, Y., Fukuda, H., Ugawa, Y., Hikosaka, O., Hanajima, R., Furubayashi, T., et al. (1998). Visaulisation of the information flow through human occulomotor cortical regions by transcranial magnetic stimulation. Journal of Neurophysiology, 80, 936–946. Townsend, J. T., & Ashby, F. G. (1983). Stochastic modelling of elementary psychological processes. London: Cambridge University Press. Tranel, D. (2009). The left temporal pole is important for retrieving words for unique concrete entities. Aphasiology, 23, 867–884. Van Petten, C., & Luka, B. J. (2006). Neural localization of semantic context effects in electromagnetic and hemodynamic studies. Brain and Language, 97, 279–293. Visser, M., Jefferies, E., Embleton, K. V., & Lambon Ralph, M. A. (2012). Both the middle temporal gyrus and the ventral anterior temporal area are crucial for multimodal semantic processing: Distortion-corrected fMRI evidence for a double gradient of information convergence in the temporal lobes. Journal of Cognitive Neuroscience, 24, 1766–1778. Visser, M., & Lambon Ralph, M. A. (2011). Differential contributions of bilateral ventral anterior temporal lobe and left anterior superior temporal gyrus to semantic processes. Journal of Cognitive Neuroscience, 23, 3121–3131. Wagner, A. D., Pare-Blagoev, E. J., Clark, J., & Poldrack, R. A. (2001). Recovering meaning: Left prefrontal cortex guides controlled semantic retrieval. Neuron, 31, 329–338. Walsh, V., & Cowey, A. (2000). Transcranial magnetic stimulation and cognitive neuroscience. Nature Reviews Neuroscience, 1, 73–79. Whitney, C., Kirk, M., O’Sullivan, J., Lambon Ralph, M. A., & Jefferies, E. (2011). The neural organization of semantic control: TMS evidence for a distributed network in left inferior frontal and posterior middle temporal gyrus. Cerebral Cortex, 21, 1066–1075. 1396 Journal of Cognitive Neuroscience Volume 27, Number 7 D o w n l o a d e d f r o m l l / / / / j t t f / i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e d o u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 7 / 7 2 7 1 / 3 7 8 / 8 1 1 3 9 8 4 8 9 / 2 1 9 7 6 8 o 2 c 9 n 2 _ 0 a / _ j 0 o 0 c 7 n 8 8 _ a p _ d 0 0 b 7 y 8 g 8 u . e p s t d o f n b 0 y 8 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j t . f / u s e r o n 1 7 M a y 2 0 2 1 The Timing of Anterior Temporal Lobe Involvement image

Scarica il pdf