Executive Semantic Processing Is Underpinned by
a Large-scale Neural Network: Revealing the
Contribution of Left Prefrontal, Posterior
Temporal, and Parietal Cortex to
Controlled Retrieval and
Selection Using TMS

Carin Whitney1, Marie Kirk1, Jamie OʼSullivan1,
Matthew A. Lambon Ralph2, and Elizabeth Jefferies1

Abstract

■ To understand the meanings of words and objects, we need
to have knowledge about these items themselves plus executive
mechanisms that compute and manipulate semantic information
in a task-appropriate way. The neural basis for semantic control
remains controversial. Neuroimaging studies have focused on
the role of the left inferior frontal gyrus (LIFG), whereas neuro-
psychological research suggests that damage to a widely distrib-
uted network elicits impairments of semantic control. There is
also debate about the relationship between semantic and execu-
tive control more widely. We used TMS in healthy human volun-
teers to create “virtual lesions” in structures typically damaged in
patients with semantic control deficits: LIFG, left posterior mid-
dle temporal gyrus (pMTG), and intraparietal sulcus (IPS). The

influence of TMS on tasks varying in semantic and nonsemantic
control demands was examined for each region within this
hypothesized network to gain insights into (i) their functional
specialization (i.e., involvement in semantic representation, con-
trolled retrieval, or selection) and (ii) their domain dependence
(i.e., semantic or cognitive control). The results revealed that
LIFG and pMTG jointly support both the controlled retrieval
and selection of semantic knowledge. IPS specifically participates
in semantic selection and responds to manipulations of non-
semantic control demands. These observations are consistent
with a large-scale semantic control network, as predicted by le-
sion data, that draws on semantic-specific (LIFG and pMTG) and
domain-independent executive components (IPS). ■

INTRODUCTION

Semantic cognition refers to the ability to assign and use
the meanings of words, sounds, objects, and faces to
interact with the environment. This capacity relies on both
stored semantic knowledge (semantic representations)
and executive control mechanisms that shape semantic
activation in line with current goals and constraints (se-
mantic control). We know a vast amount about any given
concept—yet only particular aspects of our knowledge will
be relevant in a given situation. For example, we know
many different things about bananas, including that they
are peeled before being eaten and that they can make
you slip when dropped on the ground. To understand
the relationship between “banana” and “slip,” it is necessary
to focus on a relatively obscure aspect of meaning (i.e., that
a banana has a slimy texture) as opposed to more domi-
nant aspects that are thought to be retrieved automati-

1University of York, 2University of Manchester

cally (Corbett, Jefferies, & Lambon Ralph, 2009; Badre
& Wagner, 2007; Jefferies, Baker, Doran, & Lambon
Ralph, 2007; Jefferies & Lambon Ralph, 2006; Badre,
Poldrack, Pare-Blagoev, Insler, & Wagner, 2005; Wagner,
Pare-Blagoev, Clark, & Poldrack, 2001; Thompson-Schill,
DʼEsposito, Aguirre, & Farah, 1997). Semantic control pro-
cesses therefore are a principle component of semantic
cognition and interact with stored semantic knowledge
during meaning retrieval.

Neuroimaging and neuropsychological research inves-
tigating the brain mechanisms underpinning semantic con-
trol have highlighted the importance of the left inferior
frontal gyrus (LIFG). LIFG activation typically increases
when weak or unusual relationships need to be identified
in an association task, subordinate meanings of an ambig-
uous word need to be accessed, or the number of response
options is increased, strengthening competition among
potential target items in the semantic network (e.g., Badre
et al., 2005; Noppeney, Phillips, & Price, 2004; Wagner
et al., 2001; Thompson-Schill et al., 1997). Moreover, LIFG

© 2011 Massachusetts Institute of Technology
Published under a Creative Commons Attribution 3.0 Unported (CC-BY 3.0) license

Journal of Cognitive Neuroscience 24:1, pp. 133–147

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lesions in patients with stroke aphasia (SA) produce im-
pairments on similar tasks, establishing a causal relation-
ship between LIFG and semantic control deficits (Noonan,
Jefferies, Corbett, & Lambon Ralph, 2010; Corbett, Jefferies,
Ehsan, & Lambon Ralph, 2009; Corbett, Jefferies, & Lambon
Ralph, 2009; Novick, Kan, Trueswell, & Thompson-Schill,
2009; Soni et al., 2009; Jefferies, Patterson, & Lambon Ralph,
2008). These studies show that individuals with SA have
difficulty selecting appropriate concepts in the face of po-
tent distracters—for example, they have difficulty retrieving
the subordinate meanings of ambiguous words and strug-
gle to reject highly associated distractor words in synonym
judgment. Moreover, they profit from cues provided to re-
duce the requirement for internally generated semantic
control (e.g., /t/ to cue “tiger” during picture naming), dem-
onstrating that semantic knowledge itself is preserved in
the face of impaired semantic control.

Contradictory conclusions, however, have been drawn
about the broader semantic control network, extending
beyond LIFG. One source of controversy follows from the
fact that semantic control deficits are associated with le-
sions to both LIFG and/or temporo-parietal cortex (Novick
et al., 2009; Jefferies & Lambon Ralph, 2006). Although
this suggests a large-scale distributed network, the patientsʼ
lesions are typically extensive, encompassing potentially
separable sites—for example, posterior middle temporal
gyrus (pMTG; BA 21/BA 37) and parietal areas (e.g., intra-
parietal sulcus [IPS] and BA 39/BA 40; Noonan et al., 2010).
Moreover, individuals rarely have specific behavioral impair-
ments but are likely to have damage to more than one
cognitive function. Performance is impaired on a variety
of standard assessments probing attentional/executive skills
outside the verbal domain (e.g., deficits occurred on the
WCST and the Brixton Spatial Rule Attainment task; Novick
et al., 2009; Jefferies & Lambon Ralph, 2006), suggest-
ing that some of the regions affected in SA might serve a
domain-independent control function.

Neuroimaging studies offer higher spatial resolution, but
the interpretation of brain activation remains ambiguous.
For example, in most fMRI investigations, high semantic
control demands are confounded with the number of po-
tential target concepts; thus, these conditions might gen-
erate greater activation in the semantic store (cf. Snijders
et al., 2009; Gennari, MacDonald, Postle, & Seidenberg,
2007; Noppeney et al., 2004). In line with this, pMTG has
been described as a store for semantic knowledge that re-
ceives modulatory signals from prefrontal cortex during
the process of meaning retrieval (Binder, Desai, Graves,
& Conant, 2009; Hickok & Poeppel, 2004; Indefrey &
Levelt, 2004; Gold & Buckner, 2002). This interpretation
is in stark contrast to the neuropsychological profile of
semantically impaired patients with SA: Irrespective of
whether they have left prefrontal or posterior damage
(encompassing pMTG plus other posterior temporal and
inferior parietal areas), SA patients are able to retrieve con-
ceptual knowledge when the control demands of semantic
tasks are reduced, suggesting that this region does not

constitute a key semantic store (e.g., Jefferies & Lambon
Ralph, 2006).

Although pMTG is specifically implicated in semantic
processing, the left IPS, in contrast, does not appear to
be specific for semantic operations, as neural activity in
this area is modulated by a variety of cognitive tasks that
probe executive or attention processes, including spatial
orientation, tone discrimination, finger movement sequenc-
ing, and categorization of faces, as well as tasks using seman-
tic stimuli (Hedden & Gabrieli, 2010; Ciaramelli, Grady,
& Moscovitch, 2008; Collette, Hogge, Salmon, & Van der
Linden, 2006; Duncan, 2006; Wager, Jonides, & Reading,
2004). Because of this domain independence, IPS has
been implicated in the “multiple-demand” (MD) network
alongside medial and dorsal prefrontal structures (Duncan,
2006, 2010; Cristescu, Devlin, & Nobre, 2006; Duncan &
Owen, 2000; Owen, Schneider, & Duncan, 2000). Some of
the impairments seen after temporo-parietal infarcts in SA
patients might, thus, be a consequence of damage to a MD
region (i.e., IPS) rather than lesions to a semantic-specific
control area. We propose that semantic control draws on
both areas that are selectively engaged during tasks that
require manipulation of conceptual knowledge (i.e., LIFG
and pMTG) plus regions that serve a more general purpose
(i.e., the allocation of attention; IPS). However, patient
studies cannot investigate the separate roles of pMTG and
IPS in these aspects of semantic cognition and attention,
because SA patients with posterior lesions typically have
damage to both of these structures.

The aim of this study was to explore the contribution
of LIFG, pMTG, and IPS to control processes focusing
on (i) semantic knowledge and (ii) perceptual decisions
with low conceptual content (i.e., “nonsemantic” control).
To resolve some of the ambiguities arising from previous
research, we utilized TMS, which induces a focal and tran-
sient disruption of neural processing when applied re-
petitively (i.e., a “virtual lesion”; Pascual-Leone, Walsh, &
Rothwell, 2000; Walsh & Cowey, 2000; Walsh & Rushworth,
1999; Pascual-Leone et al., 1998). Although this technique
has been successfully used to complement neuroimag-
ing and neuropsychological studies of semantic process-
ing (Lambon Ralph, Pobric, & Jefferies, 2009; Devlin &
Watkins, 2007; Pobric, Jefferies, & Lambon Ralph, 2007;
Devlin, Matthews, & Rushworth, 2003; Wassermann et al.,
1999), there are next-to-no TMS studies specifically fo-
cused on semantic control. The TMS method enabled us
to explore the individual contribution of relatively small
cortical fields, which cannot be easily separated in studies
of neuropsychological cases (i.e., sites such as pMTG and
inferior parietal lobe). Furthermore, TMS is an interfer-
ence technique and can establish whether stimulated re-
gions play an essential role in particular functions, unlike
fMRI. For example, pMTG shows activation during high-
control semantic tasks in fMRI, but this activation may
not be necessary for semantic control—instead, it may re-
flect the retrieval of a greater number of concepts in these
conditions. However, if TMS to pMTG disrupts semantic

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control, this would be powerful evidence that this region
does play a critical role.

To investigate the specific function of each of the target
areas, we employed two manipulations of semantic con-
trol. There were two tasks with high semantic control de-
mands, which were compared with a condition involving
minimal control requirements (see Figure 1). Both control
manipulations have been shown to produce greater activa-
tion in LIFG, plus pMTG and/or IPS (Badre et al., 2005;
Thompson-Schill et al., 1997; Wagner et al., 2001), making
these tasks ideal to assess the extent of the semantic con-
trol network outside LIFG. In the first of the high-control
tasks, participants had to choose a target concept that was
weakly related to the cue word, as opposed to strongly re-
lated (e.g., salt–grain vs. salt–pepper). In these situations,
additional executive resources are required to retrieve the
target concept from memory (i.e., “controlled semantic
retrieval”), because the cue will not effectively activate
the target via spreading activation in the semantic network
(Wagner et al., 2001; Masson, 1991; Collins & Loftus, 1975).
In the other task, participants were asked to attend to
specific, typically less salient features of word meaning
(e.g., color: salt–dove; both concepts are white) while ignor-
ing strong but task-irrelevant semantic associations at the
same time (e.g., pepper was also presented as a distractor;
see Figure 1). This semantic control process differed from
controlled semantic retrieval in two ways: First, participants
had to select a particular semantic feature, which was task rel-
evant over competing prepotent but irrelevant information

(i.e., “semantic selection”; Badre et al., 2005; Thompson-
Schill et al., 1997). Second, the task required a strategic
top–down approach for meaning recovery, evoked by spe-
cific task instructions (i.e., “associate: color!”). Theories that
differentiate between strategic (top–down) and stimulus-
driven (bottom–up) forms of attention have linked IPS
to conditions where prior information biases task perfor-
mance, for example, when cues indicate the position of
the target on the screen versus no cues (Ciaramelli et al.,
2008). In the feature selection task, the instruction biased
participantsʼ attention toward a specific semantic dimen-
sion and away from strong associations, which acted as dis-
tractors. Hence, we predicted that TMS over IPS would
disrupt the feature selection task, but not the retrieval of
weak associations, for which no biases/cues were neces-
sary. In contrast, TMS to pMTG was expected to disrupt
both tasks tapping semantic control, because fMRI has
revealed activation increases during both conditions (i.e.,
during attention to specific features and for weakly related
cue–target pairs; Wagner et al., 2001; Thompson-Schill et al.,
1997).

To explore the roles of LIFG, pMTG, and IPS in con-
trol functions beyond the semantic domain, a perceptual
matching task was designed using compound letters (e.g.,
an A made of small Bs), with two different levels of execu-
tive/attentive demand (Navon, 1977). Task demands were
higher when participants had to match a cue letter to the
local elements of a compound letter as opposed to its over-
all shape (see Figure 1). This process required inhibition

Figure 1. Example trials for
the semantic tasks and the
Navon tasks. Participants had
to select the target word that
was either strongly related to
the cue shown above (high
relatedness), weakly related
(low relatedness), or unrelated
but similar to the cue in
one of the following semantic
dimensions: color, shape, size,
or texture (feature selection).
In the Navon tasks, participants
had to choose the target
compound letter that
resembled the cue letter
either in its global shape
(global Navon) or in its local,
smaller elements (local Navon).
Target items are underlined,
and compound letters are
enlarged for illustration
purposes.

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Whitney et al.

135

of the visually dominant global shape of the compound
letter plus top–down attention directed toward selective,
subordinate features of the stimulus. As such, the condi-
tion was comparable to the semantic feature selection task
with the exception that participants had to orient toward
spatial/perceptual properties as opposed to semantic fea-
tures of the stimulus (e.g., color). fMRI and TMS studies
have shown parietal cortex to be crucial for the Navon task
(Hedden & Gabrieli, 2010; Billington, Baron-Cohen, &
Bor, 2008; Mevorach, Shalev, Allen, & Humphreys, 2008;
Mevorach, Humphreys, & Shalev, 2005), which is consis-
tent with the view that this region serves an MD function
not limited to semantic processes. The Navon task was,
therefore, used to probe the domain independence of po-
tential semantic control regions. We predicted that TMS
over IPS would impair performance on the Navon task—
because of its function in the MD network mediating top–
down control—but that no TMS effects would emerge
after stimulation of LIFG nor pMTG because of the low
semantic content of the Navon stimuli.

METHODS

Participants

Sixteen right-handed native English speakers from the
University of York participated in this study (eight women;
mean age = 22.25 years, SD = 3.55). All subjects passed
TMS and MRI safety screening (Wassermann, 1998), were
free of medication, and did not have any personal or family
history of neurological or psychiatric illness. Participants
had normal or corrected-to-normal vision and gave in-
formed consent before the beginning of the study. A re-
imbursement of £40 was paid for participation. The study
was approved by the local ethics committee.

Tasks

Three semantic judgment tasks requiring different levels
of executive semantic demand were employed (i.e., judg-
ments involving high relatedness, low relatedness, and
feature selection; see Figure 1). In each task, a cue word
appeared above a row of three potential target words. Par-
ticipants were asked to decide which target was related to
the cue by pressing one of three buttons with their right
hand, corresponding to the position of the response item
(left, middle, and right).

In the high relatedness task, the target was strongly re-
lated to the cue and appeared with two unrelated distractor
items (salt–pepper, machine, land). Semantic control de-
mands were minimal because target retrieval benefitted
from automatic spreading activation (Masson, 1991; Neely,
1990; Collins & Loftus, 1975). In the low relatedness condi-
tion, cue–target associations were weak (salt–grain, radio,
adult) and consequently target retrieval required addi-
tional executive resources that helped to direct the search
and recovery of the relevant item, that is, “controlled se-

mantic retrieval” (Badre et al., 2005; Wagner et al., 2001).
In the feature selection task, the target shared a particular
semantic dimension (color, size, shape, or texture) with
the cue (e.g., color: salt–dove, corn, pepper). The target ap-
peared together with a strong semantic associate and an
unrelated distractor. Target retrieval required the explicit
selection of the appropriate semantic feature (e.g., white)
and the suppression of the dominant but irrelevant asso-
ciate (pepper; “semantic selection”; Badre et al., 2005;
Thompson-Schill et al., 1997). Participantsʼ attention was
biased toward a particular semantic feature before stim-
ulus presentation (via an instruction slide, for example,
“associate: color!”). Therefore, the feature selection task
and the low relatedness task tapped two different forms of
semantic control.

Nonsemantic control tasks were constructed from the
global–local Navon letter-matching task (Navon, 1977).
We produced easy and difficult versions of this task to
establish whether rTMS effects over LIFG/pMTG/IPS re-
mained specific to the semantic domain when control de-
mands were increased. In both Navon conditions, a cue
letter appeared above three larger compound letters,
which were composed of smaller letters (e.g., a large letter
S made of small Bs; see Figure 1). In the easy condition,
participants were asked to decide which compound letter
matched the cue in global shape, irrespective of the letters
that appeared as smaller elements inside the compound.
Cognitive control demands were expected to be minimal
in these trials because the global shape is visually dominant
over local features (Navon, 1977). Moreover, neither dis-
tractor was related to the cue, that is, neither global shape
nor local letter features matched the cue in this condition
(see Figure 1). In contrast, the more difficult local Navon
task required participants to match the cue letter to the
local elements of one of the compounds, hence, to dis-
regard the dominant, global shape of the stimuli. Cognitive
control demands were further increased by presenting a
compound letter whose global shape was identical to the
cue, thus generating a strong task-irrelevant competitor
(see Figure 1). The local Navon task was therefore com-
parable to the feature selection condition, because both
required top–down control processes to direct attention
away from dominant targets and toward selective, sub-
ordinate attributes of the stimulus.

Design and Procedure

A within-subject factorial design was used, with stimula-
tion SITE (LIFG, pMTG, IPS), TMS (stimulation vs. no stimu-
lation), and TASK (three semantic tasks, two Navon tasks)
as within-subject factors. Each site was stimulated on a dif-
ferent day, with test sessions separated by at least 1 week.
The sequence of stimulation site was counterbalanced
across sessions. Furthermore, each session included re-
cordings of task performance immediately after TMS and
without any TMS intervention (“baseline” performance)
to identify the influence of TMS on cognitive behavior

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(TMS effect). Baseline performance was measured either
before TMS intervention or 30 min after TMS offset by
which time no TMS effect remains (Pobric, Jefferies, &
Lambon Ralph, 2010; Lambon Ralph et al., 2009; Pobric,
Lambon Ralph, & Jefferies, 2009; Pobric et al., 2007). The
order of baseline assessment was counterbalanced across
sessions.

The six experimental runs—that is, baseline and post-
TMS performance for each stimulation site (LIFG, pMTG,
IPS)—lasted about 6 min each (M = 5.93 min, SD = 0.49)
and included 30 trials per condition. Two miniblocks of
15 consecutive trials were created for each condition and
presented in a pseudorandomized order to control for
effects that relate to the fading of the TMS effect over time.
At the beginning of each block, an instruction slide was
shown, followed by a fixation cross for 500 msec in the
center of the screen. This was replaced by the first experi-
mental trial, which displayed the cue above three response
options for a maximum of 5 sec (Figure 1). As soon as
a response was made, the fixation cross appeared again,
followed by the next trial. A computer running E-prime
(Psychology Software Tools) was used to present the
stimuli and record the responses.

Stimuli
Each of the semantic conditions consisted of 180 cue–
target–distractor trials. The trials were arranged into six
matched sets of 30 trials each, used for each experimen-
tal run, and then split into miniblocks of 15 trials, which
were equated for word length, frequency, and cue–target
association strength. Stimuli were based on Badre et al.
(2005) but restricted to nouns only, and some trials were
amended to make them suitable for U.K. participants.
Words in all three conditions were matched in length in
letters (low relatedness: M = 5.1, SD = 1.4; high related-
ness: M = 5.2, SD = 1.8; feature selection: M = 5.5, SD =
1.8) and frequency (Kucera & Francis, 1967; low related-
ness: M = 54.3, SD = 105.1; high relatedness: M = 48.1,
SD = 90.4; feature selection: M = 44.5, SD = 103.6).

The high and low relatedness tasks were arranged such
that the same cue word was matched with a high or low
semantic associate, using several sets of association norms
(Moss & Older, 1996; Postman & Keppel, 1970). Associa-
tion strength was defined as the proportion of subjects
that named the target in response to the cue in free asso-
ciation. Each cue word was also paired with two unrelated
distractor items, for which no entry in the association norms
was found (e.g., high: salt–pepper, machine, land; low:
salt–grain, radio, adult). The mean association strength for
high and low related cue–target pairs differed significantly
(paired t test: high = 0.24, SD = 0.18; low = 0.04, SD =
0.10; t = 15.00; p < .001). For the feature selection task, cue words were paired with an unrelated target word that shared a particular semantic dimension with the cue (i.e., color, shape, size, or texture), a strong semantic associate (mean association strength = 0.22, SD = 0.76) and a new, unrelated distractor noun (e.g., color: salt–dove, pepper, cone). Sixteen percent of the cues and strong semantic associates were taken from the cue–target pairs in the high relatedness condition and paired with a new target and a new unrelated noun. Twelve percent of the trials in the feature selection task needed to be repeated but never within the same experimental session. For the nonsemantic control conditions, 180 trials of the global and local version of the Navon task were con- structed and, again, broken down into sets of 15 trials. Navon stimuli were taken from Hills and Lewis (2007). These depicted 21 upper-case letters (excluding M, N, Q, V, W) composed of smaller capital letters with a differ- ent identity (e.g., an A made out of small Bs). The local elements (width × length: 7 × 7 pixels) were arranged densely in the shape of the larger compound letter (69 × 166 pixels), with no gap in between. There were between 3 and 10 different versions of each of the 21 upper-case letters (made up of different local letters), yielding a total of 125 unique compound letters. The cues in the Navon task were 21 lower-case letters that matched the local elements or global shape of the target compound letter. To increase the number of trials and to delay response times, varying script fonts were used (Blackadder, Curlz MT, Bradleyhand, Edwardian Script, and Pristina), yielding 74 individual cue letters. No cue letters were repeated in a single experimental run. TMS Protocol A standard off-line “virtual lesion” rTMS protocol was used, which was compatible with established TMS safety guidelines (Rossi, Hallett, Rossini, & Pascual-Leone, 2009; Wassermann, 1998). In the absence of any behavioral task, repetitive trains of TMS were delivered at 1 Hz to the tar- get brain area for 10 min. This repetitive stimulation results in a temporary and reversible disruption of neural process- ing in the underlying tissue, which interferes with tasks that rely on the stimulated area (Lambon Ralph et al., 2009; Pobric et al., 2007, 2009; Pascual-Leone et al., 1998). The resulting behavioral deficits are typically reflected in a delay in response times rather than a decline in accuracy (Devlin et al., 2003; Pascual-Leone et al., 2000; Walsh & Cowey, 2000). A 50-mm figure-of-eight coil, attached to a Magstim Rapid2 stimulator, was used for the repetitive delivery of magnetic pulses. The center of the coil was aligned to the point that marked the stimulation site on a tight-fitting elastic cap, worn by the participant. The coil was held firmly against the scalp throughout stimulation. Stimulation in- tensity was determined before each rTMS administration as 120% of active motor threshold (MT). MT was identified as the lowest intensity that produced a visible muscle twitch in the tense right hand when intensity was gradually decreased during single-pulse stimulation of left motor cortex. Intensity threshold was set to a maximum of 65% of stimulator output (mean intensity = 62.40%, SD = 3.20). Whitney et al. 137 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 4 / 1 2 4 1 / 3 1 3 / 1 1 9 3 4 3 3 / 4 1 2 7 9 8 o 0 c 2 n 6 _ 9 a / _ j 0 o 0 c 1 n 2 3 _ a p _ d 0 0 b 1 y 2 g 3 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 i 2 3 e s / j . f / t u s e r o n 1 7 M a y 2 0 2 1 Coil orientation was manipulated to minimize partici- pantsʼ discomfort during rTMS (particularly over LIFG), as previous research found behavioral effects were insen- sitive to the orientation of the coil (Niyazov, Butler, Kadah, Epstein, & Hu, 2005). Also, six participants received a slightly lower intensity for rTMS over this site, ranging from 109% to 116% of individual MT (M = 113%). Despite these adaptations, LIFG stimulation yielded the strongest perfor- mance deficits, which were comparable in size to the in- terference observed in previous rTMS studies that used the same stimulation protocol and similar semantic tasks (e.g., Lambon Ralph et al., 2009; Pobric et al., 2007). More- over, differences in sensory experiences across stimulation sites (e.g., in general discomfort, noise, or muscle twitches, which were highest during LIFG stimulation) cannot ac- count for the TMS effects because (i) performance was always measured in the absence of any ongoing brain stimulation and (ii) various control tasks were used to de- tect any task-independent consequences of TMS (i.e., the high relatedness and Navon tasks, which were meant to have no effect after LIFG stimulation). Localization of Stimulation Sites Structural T1-weighted MRI scans of each participant were used to guide coil positioning using the Ascension Minibird magnetic tracking device and MRIreg software. Five ana- tomical landmarks (tip and bridge of the nose, left and right tragus and vertex) were identified to coregister the partici- pantʼs head, stabilized on a chin rest, with the MRI image on the screen. Our stimulation sites were derived from peak activa- tions identified in fMRI studies that employed the same stimulus set and/or the same tasks (i.e., low and high relat- edness, feature selection; Badre et al., 2005; Wagner et al., 2001; Thompson-Schill et al., 1997). One of these studies reported activation in all three target sites during increased executive semantic demands (Badre et al., 2005). Coordi- nates were transformed into individual subject space using the transformation matrix from the “segment” function implemented in SPM5, after the origin of each individual image was realigned to the anterior commissure. Visual inspection ensured that coordinates referred to the tar- get areas by making reference to anatomical landmarks (Figure 2). Activation peaks within LIFG, observed during previous fMRI studies of semantic control, were typically large and widely distributed, comprising both anterior and posterior segments of this structure. We used the Montreal Neuro- logical Institute (MNI) coordinates for LIFG (−54 21 12) from Badre et al. (2005). This area (BA 44/45) in the pars triangularis (cf. Keller, Crow, Foundas, Amunts, & Roberts, 2009) has been found to be sensitive to several executive Figure 2. Stimulation sites. rTMS was delivered to the pars triangularis of LIFG, pMTG, and IPS. Images on the right include probability maps, which were available for target regions in BA 44 and BA 45 and the superior (SPL) and inferior parietal lobe (IPL). Stimulation sites are displayed on axial and saggital slices in MNI space, with reference to y and x coordinates, respectively. orange = pars triangularis, yellow = inferior and superior temporal sulcus, purple = Sylvian fissure, blue = IPS. 138 Journal of Cognitive Neuroscience Volume 24, Number 1 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 4 / 1 2 4 1 / 3 1 3 / 1 1 9 3 4 3 3 / 4 1 2 7 9 8 o 0 c 2 n 6 _ 9 a / _ j 0 o 0 c 1 n 2 3 _ a p _ d 0 0 b 1 y 2 g 3 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 i 2 3 e s / j / t . f u s e r o n 1 7 M a y 2 0 2 1 semantic manipulations including low vs. high related- ness, feature selection (as opposed to decisions based on low relatedness), and a task that manipulated target congruency during feature selection. Moreover, circum- scribed lesions to this area resulted in poor performance during executively demanding semantic tasks in aphasic patients (Novick et al., 2009). The location for left pMTG stimulation (−56 −50 3) lay between the superior and inferior temporal sulcus and was slightly anterior to an imaginary line perpendicular to the most posterior horizontal segment of the Sylvian fissure (cf. Gennari et al., 2007; Figure 2). This site, in BA 21, was identified from the average MNI coordinates of two studies (Badre et al., 2005; Wagner et al., 2001), which both reported increased pMTG peak activity in response to verbal low vs. high relatedness judgments and when the number of response options was large as opposed to small. This area is frequently affected in pa- tients with semantic control deficits following temporo- parietal infarcts (Noonan et al., 2010). MNI coordinates for left parietal lobe (−23 −73 48) were mean values based on Thompson-Schill and colleaguesʼ study (1997) and referred to an area close to the posterior bank of the IPS (BA 7; Figure 2). Enhanced parietal activa- tion was observed during feature selection as opposed to high relatedness and when the response set was increased (see also Badre et al., 2005). Furthermore, damage to the inferior parietal lobule, reaching up to IPS, has been observed in some patients with SA (e.g., Noonan et al., 2010; Soni et al., 2009). Data Analysis The primary performance measure was RT because RT is sensitive to rTMS effects even in the absence of any decline in accuracy (cf. Lambon Ralph et al., 2009; Pobric et al., 2007; Devlin et al., 2003). RT data were screened for errors and outliers (±2 SD). We then employed two complemen- tary analyses. In the first, we used ANOVAs to compare the impact of TMS across pairs of brain regions (i.e., LIFG vs. pMTG, LIFG vs. IPS, pMTG vs. IPS) for the semantic and Navon tasks separately. This is useful because a three-way interaction would confirm, in line with our pre- dictions, that the impact of TMS was task- and site-specific, hence, that brain areas were functionally dissociable within the control network being tested. Second, we used t tests to test specific hypotheses regarding the specificity of the TMS effects, establishing (i) which task(s) were significantly impaired and (ii) at what site(s). For this analysis, differ- ence scores were calculated from post-TMS and baseline sessions for each subject in each condition at each site (i.e., the TMS effect). These planned t test comparisons determined whether rTMS-induced effects were present (two-tailed one-sample t test) and whether these effects were site-specific and task-specific (two-tailed paired t tests). Error rates were analyzed using the same model. RESULTS RT ANOVAs We first considered data from the semantic conditions (high relatedness, low relatedness, feature selection) to ex- amine which areas worked together to underpin semantic control. There was a significant three-way interaction be- tween Site (n = 2), Task (n = 3), and TMS (baseline vs. post-TMS) when IPS was compared with LIFG and when IPS was compared with pMTG (see Table 1 and Figure 3). However, there were no interactions with Site when LIFG and pMTG were compared, suggesting that these regions are functionally dissociable from IPS but similar to each other in terms of their contribution to semantic control. The second ANOVA compared the stimulation sites in a pairwise fashion for the two Navon tasks to establish whether any of the brain regions contributed to nonseman- tic forms of control. Again, the results showed a three-way interaction between Site (n = 2), Task (n = 2), and TMS (baseline vs. post-TMS) for IPS versus LIFG and IPS versus pMTG, but not when LIFG and pMTG were compared (see Table 1 and Figure 3). These results suggest that IPS also dissociates from LIFG and pMTG in terms of nonsemantic functions. TMS Effects across Tasks We computed the size of the TMS effect for each task at each stimulation site (i.e., RT for post-TMS minus baseline performance; see Figure 4), allowing us to draw specific inferences about the functional role played by each area. LIFG rTMS over LIFG slowed performance during the low related- ness task (one-sample t(15) = 4.24, p = .001) but not the high relatedness task (one-sample t(15) < 1). Surprisingly, there was no significant TMS effect for the feature selection task (one-sample t(15) < 1). Also, none of the Navon tasks was impaired after TMS (one-sample t(15) < 1). The direct comparison between the effects for the high versus low re- latedness condition was significant (paired t(15) = 3.35, p = .004), supporting a role of LIFG in controlled semantic re- trieval. Comparison between the two semantic tasks with high-control demands however revealed that these tasks were not dissociable (low relatedness vs. feature selection: paired t(15) = 1.13, p = .28). pMTG Stimulation of pMTG disrupted both semantic tasks with high-control demands (low relatedness: one-sample t(15) = 2.51, p < .05; feature selection: one-sample t(15) = 2.92, p = .01). There was no TMS effect for the semantic task with low-control demands (high relatedness: one-sample t(15) < 1). Again, both Navon tasks remained unaffected Whitney et al. 139 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 4 / 1 2 4 1 / 3 1 3 / 1 1 9 3 4 3 3 / 4 1 2 7 9 8 o 0 c 2 n 6 _ 9 a / _ j 0 o 0 c 1 n 2 3 _ a p _ d 0 0 b 1 y 2 g 3 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 i 2 3 e s / j f / . t u s e r o n 1 7 M a y 2 0 2 1 Table 1. F and p Values for the ANOVA for RT Site TMS Task Site × TMS Site × Task TMS × Task Site × TMS × Task Semantic Conditions Only (High Relatedness, Low Relatedness, Feature Selection) df 1, 15 LIFG, IPS <1 p .89 1, 15 7.31 .02 2, 30 1, 15 371.14 <1 <.001 .97 pMTG, IPS <1 13.88 486.93 <1 p .74 .002 <.001 .42 LIFG, pMTG <1 12.61 420.01 <1 p .58 .003 <.001 .48 Nonsemantic Conditions Only (Global and Local Navon Task) df 1, 15 1, 15 LIFG, IPS <1 <1 p .74 pMTG, IPS <1 p .94 .46 1.23 .29 1, 15 99.32 <.001 1, 15 <1 .89 108.07 <1 <.001 .67 LIFG, pMTG <1 <1 121.45 <1 p .78 .39 <.001 .69 2, 30 <1 .64 <1 .63 1.84 1.76 1, 15 <1 .97 2.27 .15 4.44 .052 2, 30 3.27 .069a 4.99 .014 4.55 .03a 1, 15 4.34 .055 <1 .53 4.78 .045 2, 30 3.44 .045 3.26 .05 <1 .44 1, 15 10.01 .006 17.84 .001 1.91 .19 Pairs of brain regions that were compared are listed in the first column. The three-way interaction omnibus ANOVA, including all sites and conditions, was also significant (F(8, 120) =2.36; p (Huynh–Feldt). by TMS (> .09). The size of the TMS effects did not differ
between the two high-control semantic conditions (paired
t(15) < 1), but both effects were larger compared with trials requiring minimal semantic control, indicating the importance of pMTG for various types of semantic control (low vs. high relatedness: paired t(15) = 2.41, p = .03; feature selection vs. high relatedness: paired t(15) = 3.41, p = .004). IPS rTMS over IPS interfered with the feature selection task (one-sample t(15) = 3.35, p < .005) and the global Navon task (one-sample t(15) = 3.86, p < .005). The feature selec- tion task was more impaired than the other two semantic conditions (feature selection vs. high relatedness: paired t(15) = 2.99, p = .01; feature selection vs. low relatedness: paired t(15) = 2.24, p = .04), consistent with the specific function of IPS in top–down mediated selection. The global Navon task was also more affected than the local version (paired t(15) = 3.28, p = .005). TMS Effects across Sites The TMS effects for LIFG and pMTG in the low relatedness task were larger than the effect of TMS over IPS, which is in line with our prediction that IPS does not support con- trolled semantic retrieval (LIFG vs. IPS: paired t(15) = 2.55, p = .02; pMTG vs. IPS: paired t(15) = 2.00, p = .06). There was no difference in the effect of TMS across LIFG and pMTG (paired t(15) < 1), suggesting that both of these sites play a critical role in the controlled retrieval of seman- tic information (unlike IPS). In contrast, the TMS effect for the feature selection task did not differ across the three sites, implying that all targeted brain areas contribute to semantic selection (IPS vs. LIFG: paired t(15) = 1.41, p = .18; pMTG vs. LIFG: paired t(15) = 1.15, p = .27; IPS vs. MTG: paired t(15) < 1; see Figure 4). Finally, the TMS ef- fect for the global Navon task was larger for IPS compared with LIFG or pMTG (IPS vs. LIFG: paired t(15) = 2.59, p = .02; IPS vs. pMTG: paired t(15) = 3.05, p = .008). This suggests, together with the findings from the ANOVA, that IPS contributes to nonsemantic decisions as well as to aspects of semantic control, unlike LIFG or pMTG. In summary, the results of the ANOVAs showed that LIFG and pMTG performed similar functions, while IPS dissociated from both regions during semantic and non- semantic control tasks (see Figures 3 and 4). Moreover, in line with our predictions, planned comparisons revealed that LIFG and pMTG exclusively mediated semantic control functions, while IPS contributed to control processes in both domains (semantic and nonsemantic; Figure 4). Dif- ferences also emerged regarding the type of semantic con- trol that was supported by LIFG and pMTG as opposed to 140 Journal of Cognitive Neuroscience Volume 24, Number 1 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 4 / 1 2 4 1 / 3 1 3 / 1 1 9 3 4 3 3 / 4 1 2 7 9 8 o 0 c 2 n 6 _ 9 a / _ j 0 o 0 c 1 n 2 3 _ a p _ d 0 0 b 1 y 2 g 3 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 i 2 3 e s / j / f t . u s e r o n 1 7 M a y 2 0 2 1 highly competitive but irrelevant response (e.g., when “c” was the cue and a large “C” was the distractor). If the auto- matic association between globally identical cue and target letters was reduced by the use of different fonts, strong inhibition processes may have no longer been required, which might explain the lack of a TMS effect for the local Navon task. Error Rates ANOVAs Table 2 lists the error rates that were entered into the ANOVAs. These analyses revealed that no effects were driven by Site in any of the six ANOVAs, which compared pairs of brain regions separately for semantic and Navon tasks (as in the RT analysis; Table 3). Instead, TMS effects were dependent on the tasks in the semantic conditions (i.e., the TMS × Task interaction was significant in all three ANOVAs comparing pairs of brain regions), while TMS had no influence on performance of the Navon tasks (i.e., no main effects or interactions with TMS were observed; F < 1). Planned Comparisons Planned comparisons on the difference scores between post-TMS and baseline performance were used to test specific predictions about the impact of TMS on task per- formance, separately for each target area. Two effects 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 4 / 1 2 4 1 / 3 1 3 / 1 1 9 3 4 3 3 / 4 1 2 7 9 8 o 0 c 2 n 6 _ 9 a / _ j 0 o 0 c 1 n 2 3 _ a p _ d 0 0 b 1 y 2 g 3 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 i 2 3 e s / j t f / . u s e r o n 1 7 M a y 2 0 2 1 Figure 4. TMS effect. Difference scores between post-TMS and baseline performance (TMS–no TMS) for reaction time. Positive values indicate a decline in performance after brain stimulation, whereas negative values indicate improvement. High = high relatedness; Low = low relatedness; Feat = feature selection. *p < .05. Error bars denote SEM. Whitney et al. 141 Figure 3. Reaction times. Performance at baseline (no TMS) and post-TMS following stimulation of LIFG, pMTG, and IPS. High = high relatedness; Low = low relatedness; Feat = feature selection. Error bars denote SEM. IPS: IPS was the only region that did not engage in con- trolled semantic retrieval but contributed to feature selec- tion only. Unexpectedly, TMS over IPS disrupted the easier global Navon task, although fMRI studies have shown increased brain activity in the left IPS when participants attended to local and less-salient dimensions of Navon letters (corre- sponding to the Local Navon task; Mevorach et al., 2008). One possibility is that the intended automatic mapping of cue and target letter during the global Navon task was hindered by our use of different fonts, which meant that sometimes the shape of the cue deviated significantly from the global shape of the target compound and could be ambiguous (e.g., a lower-case “e” in font “Curlz” could be mistaken for a “c”). Therefore, the global Navon task might have required a stronger level of cognitive control than expected. Simultaneously, these manipulations had the opposite effect on the control requirements of the local Navon task. Here, a globally related letter was used as one of the distractor items, which was meant to act as a Table 2. Error Rates High Relatedness Low Relatedness Feature Selection Global Navon Local Navon LIFG No TMS TMS Difference pMTG No TMS TMS Difference IPS No TMS TMS Difference 2.00 (2.42) 3.13 (2.99) 1.13 (3.74) 2.94 (2.59) 3.25 (3.66) 0.31 (3.94) 2.81 (3.97) 5.38 (4.21) 2.57 (6.03) 5.75 (4.91) 11.25 (6.44) 5.50 (8.63) 7.44 (6.31) 11.25 (5.69) 3.81 (7.47) 9.06 (8.81) 9.06 (4.93) 0.00 (6.68) 17.31 (10.01) 12.25 (8.51) −5.06 (11.32) 2.63 (3.07) 1.81 (2.97) 4.75 (12.31) 4.38 (3.50) −0.82 (4.82) −0.37 (12.96) 15.06 (7.86) 13.13 (8.37) −1.93 (8.23) 20.94 (10.85) 15.81 (15.01) −5.13 (10.76) 1.19 (2.04) 1.50 (1.55) 0.31 (2.82) 3.44 (5.25) 2.81 (2.48) −0.63 (4.47) 1.81 (2.46) 1.94 (2.62) 0.13 (3.52) 7.38 (13.16) 4.00 (5.27) −3.38 (13.68) Percentage of errors committed during performance at baseline (no TMS) and after TMS (TMS) to LIFG, pMTG, and IPS for each task separately. Difference scores (TMS–no TMS) reflect the TMS effect, with positive values indicating a decline in performance after brain stimulation whereas negative values signal improvement. Standard deviation is given in parentheses. Table 3. F and p Values for the ANOVA for Error Rate Site TMS Task Site × TMS Site × Task TMS × Task Site × TMS × Task Semantic Conditions Only (High Relatedness, Low Relatedness, Feature Selection) df LIFG, IPS p pMTG, IPS p 1, 15 1, 15 2.89 .11 3.12 .10 <1 .86 <1 .94 LIFG, pMTG <1 <1 p .70 .44 2, 30 35.49 <.001a 27.75 <.001 41.34 <.001a 1, 15 1.05 .32 <1 <1 .34 .89 Nonsemantic Conditions Only (Global and Local Navon Task) df 1, 15 1, 15 LIFG, IPS <1 <1 p pMTG, IPS p LIFG, pMTG p .76 2.44 .14 1.49 .24 .36 1.82 .20 <1 6.66 .02 6.31 .02 4.65 .72 .048 <1 <1 <1 .67 .46 .82 2, 30 <1 .44 2.65 .09 <1 .68 1, 15 <1 .56 1.27 .28 <1 .77 2, 30 6.29 .014a 4.42 .036a 7.58 .008a 1, 15 <1 .51 1.30 .27 <1 .89 2, 30 2.07 .16a 44.74 .10 1.01 .38 1, 15 <1 <1 <1 .51 .57 .68 Pairs of brain regions that were compared are listed in the first column. aSphericity-corrected (Huynh–Feldt). 142 Journal Cognitive Neuroscience Volume 24, Number 1 D o w n l o a d e d f r o m l l > words;
Heim et al., 2005; Fiebach et al., 2002). Activation in BA 45
also fluctuated with the degree of semantic processing
involved (e.g., semantic vs. phonological fluency or deci-
sions; Heim, Eickhoff, Ischebeck, et al., 2009; Amunts
et al., 2004). In contrast, changes in phonological stim-
ulus attributes or task demands altered activity in BA 44,
which is a brain region implicated in the dorsal language
pathway (“phonological route”; Heim, Eickhoff, & Amunts,
2009; Saur et al., 2008; Hickok & Poeppel, 2004). In line
with these data, a previous study has shown that TMS
over BA 44 impaired phonological judgments and spared

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semantic decisions, while the reverse behavioral pattern
was observed after stimulation of BA 45/BA 47 (Gough,
Nobre, & Devlin, 2005). Our study extends these findings,
showing that activity in BA 45 is causally linked to the level
of semantic control needed to retrieve the target concept.

The Role of Left pMTG in Semantic Control

The performance deficits observed after left pMTG stimu-
lation were indistinguishable from the effects of TMS over
LIFG, suggesting that pMTG and LIFG work together as
part of a distributed executive semantic network support-
ing semantic selection and controlled retrieval. These re-
sults are consistent with neuropsychological studies of
patients with SA, who show similar performance deficits
on tasks that tap semantic control following either damage
to temporo-parietal areas, including pMTG, or in combina-
tion with LIFG (Corbett, Jefferies, & Lambon Ralph, 2011;
Noonan et al., 2010; Jefferies & Lambon Ralph, 2006).
Using voxel-based lesion symptom mapping, Schwartz and
colleagues (2009) demonstrated that naming deficits in
aphasia patients could not be attributed to damage in LIFG
or posterior temporal cortex once executive semantic con-
trol processes were controlled for. In contrast, the contribu-
tion of other “semantic” regions in more anterior temporal
lobe was not linked to semantic control. Both of these
lines of research suggest that left pMTG and LIFG perform
similar semantic control functions; however, up until now,
there was little direct evidence that selective disruption
of pMTG and LIFG can produce equivalent deficits in
semantic control.

The TMS results further resolve some of the ambiguity
from the neuroimaging literature regarding pMTG function-
ing, which has linked activation in this area to confound-
ing increases in representational processes during tasks
with high semantic control requirements (Bedny, McGill, &
Thompson-Schill, 2008; Badre et al., 2005; Gold & Buckner,
2002; Wagner et al., 2001). For example, in the feature selec-
tion task, strongly associated but task-irrelevant concepts
are activated alongside the target item (via automatic spread-
ing of activation in the semantic store). Because in our
study, deficits in semantic control were observed as a direct
consequence of temporary disruption to pMTG, it is no
longer plausible to suggest that brain activation in pMTG
during fMRI is a by-product rather than a causal consequence
of manipulations in semantic control processes. Further sup-
port is provided by severely aphasic patients with lesions to
pMTG who are asked to perform sentence–picture match-
ing tasks with different levels of difficulty. Comprehension
is best when the meaning of the sentence can be derived
from the high-frequency nouns alone, hence demonstrat-
ing spared semantic knowledge, compared with sentences
where understanding the more complex verb/verb ar-
gument structure is crucial (Dronkers, Wilkins, Van Valin,
Redfern, & Jaeger, 2004).

An alternative proposal is that pMTG acts as a semantic
store that encodes specific semantic attributes, associated

only with a subset of the stimuli tested in our experiment
(i.e., motion attributes; Wallentin et al., 2011; Dick,
Goldin-Meadow, Hasson, Skipper, & Small, 2009; Martin,
2007; Damasio, Grabowski, Tranel, Hichwa, & Damasio,
1996). It seems unlikely that this could explain why pMTG
stimulation specifically disrupted the control-demanding
semantic tasks and not the low-control condition, because
all three semantic tasks included stimuli from a wide range
of categories. Moreover, pMTG showed activation during
fMRI for the same stimuli, suggesting that even if pMTG
activation is modulated by semantic category/feature, this
site does not have a single role tightly restricted to a spe-
cific category. Further research is clearly needed to estab-
lish whether the same pMTG region responds to semantic
control demands and feature manipulations, such as ac-
tion judgments, and if so, why.

Apart from pMTG, other parts of temporal cortex have
been linked to storing semantic representation, including
more anterior and inferior temporal cortex (for reviews,
see Binder et al., 2009; Patterson, Nestor, & Rogers, 2007).
Bilateral atrophy focused on anterior inferior temporal
cortex results in a gradual degradation of semantic knowl-
edge, as seen in patients with semantic dementia (Binney,
Embleton, Jefferies, Parker, & Lambon Ralph, 2010; Hodges
& Patterson, 2007; Jefferies & Lambon Ralph, 2006; Mummery
et al., 2000; Hodges, Patterson, Oxbury, & Funnell, 1992).
The impairment in these patients is highly consistent across
tasks with varying control demands and depends on fac-
tors that describe the complexity of the semantic represen-
tation being retrieved, such as familiarity and typicality. In
contrast, in individuals with semantic control deficits, le-
sions affect left prefrontal, posterior temporal, and parietal
structures, while the anterior temporal lobe is spared, and
conceptual knowledge remains accessible once semantic
control requirements are reduced (e.g., Jefferies et al.,
2008; Jefferies & Lambon Ralph, 2006). This double dis-
sociation between executive and representational aspects
of semantic cognition in the left temporal cortex was con-
firmed in a recent fMRI investigation (Whitney, Jefferies, &
Kircher, 2011). Semantic selection requirements were linked
to LIFG, pMTG, and parietal cortex, while manipulations of
the number of meanings likely to be activated in a trial
loaded onto more anterior and inferior parts of left temporal
lobe (i.e., BA 20). Together, these observations imply that
semantic representation and control processes rely on dif-
ferent regions within left temporal cortex.

The Role of Left IPS in Semantic and Nonsemantic
Forms of Control

The function of left IPS in the control network was distinct
from that of LIFG and pMTG in two ways. First, IPS was
the only brain region that responded solely to manipu-
lations in semantic selection requirements as opposed to
controlled meaning retrieval. This response pattern was ex-
pected based on studies of attention that implicated IPS
in tasks that required top–down control, elicited by explicit

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cues meant to bias behavior even before stimulus presen-
tation (here: e.g., attend to color), as opposed to control
functions that are driven by the stimulus and are not cued
(Ciaramelli et al., 2008). Second, participation of IPS was
independent of whether semantic or nonsemantic stimuli
were used. rTMS affected response times in both the fea-
ture selection and the global Navon task, indicating that IPS
plays a wider role in cognition than either LIFG or pMTG.
Neuroimaging data reveals that IPS, unlike LIFG and
pMTG, is a brain region that forms part of a fronto-parietal
MD network, supporting tasks that require high executive
control, independently of stimulus modality (although se-
mantic control, as it is examined here, has not been explic-
itly tested; Duncan, 2010; Duncan & Owen, 2000; Owen
et al., 2000). Furthermore, semantically impaired patients
with lesions to temporo-parietal cortex, including IPS, suf-
fer from executive deficits that go far beyond the semantic
domain (Corbett, Jefferies, Ehsan, et al., 2009; Jefferies &
Lambon Ralph, 2006). The strongest support, however,
for a distinction between MD regions (in and around IPS)
and semantic-specific control areas (situated in inferior
frontal and posterior temporal cortex) comes from fMRI
research that has directly compared semantic and non-
semantic executive functions. Consistently, these results
point toward an engagement of the left IPS in any form
of control (Binney et al., 2010; Nagel, Schumacher, Goebel,
& DʼEsposito, 2008; Cristescu et al., 2006). In contrast,
activation in LIFG and pMTG is limited to tasks with high
semantic control demands. Using TMS, we were able to
verify these observations and clearly establish a dissocia-
tion between components in the semantic control network:
Although all three areas (LIFG, pMTG, IPS) were important
for semantic aspects of control, only IPS contributed to
executive functions beyond the semantic domain.

Acknowledgments
This work was supported by a Wellcome project grant (078734/
Z05/Z to E. J. and M. A. L. R.). We thank David Badre, Peter Hills,
and Michael Lewis for supplying their stimulus materials.

Reprint requests should be sent to Carin Whitney or Elizabeth
Jefferies, Department of Psychology, University of York, YO10 5DD,
York, United Kingdom, or via e-mail: c.whitney@psych.york.ac.uk;
ej514@york.ac.uk.

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