Beyondthesentencegiven.pdf

doi: 10.1098/rstb.2007.2089
, 801-811362 2007 Phil. Trans. R. Soc. B

Peter Hagoort and Jos van Berkum

Beyond the sentence given

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Phil. Trans. R. Soc. B (2007) 362, 801–811

doi:10.1098/rstb.2007.2089

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Beyond the sentence given

Published online 3 April 2007
Peter Hagoort
1,2,* and Jos van Berkum

1,2,3
One co
processe

* Autho
1
F.C. Donders Centre for Cognitive Neuroimaging, Radboud University Nijmegen,

PO Box 9101, 6500 HB Nijmegen, The Netherlands
2
Max Planck Institute for Psycholinguistics, PO Box 310, 6500 AH Nijmegen, The Netherlands

3
Department of Psychology, University of Amsterdam, Roeterstraat 15,

1018 WB Amsterdam, The Netherlands

A central and influential idea among researchers of language is that our language faculty is organized
according to Fregean compositionality, which states that the meaning of an utterance is a function of
the meaning of its parts and of the syntactic rules by which these parts are combined. Since the
domain of syntactic rules is the sentence, the implication of this idea is that language interpretation
takes place in a two-step fashion. First, the meaning of a sentence is computed. In a second step, the
sentence meaning is integrated with information from prior discourse, world knowledge, information
about the speaker and semantic information from extra-linguistic domains such as co-speech gestures
or the visual world. Here, we present results from recordings of event-related brain potentials that are
inconsistent with this classical two-step model of language interpretation. Our data support a one-
step model in which knowledge about the context and the world, concomitant information from
other modalities, and the speaker are brought to bear immediately, by the same fast-acting brain
system that combines the meanings of individual words into a message-level representation.
Underlying the one-step model is the immediacy assumption, according to which all available
information will immediately be used to co-determine the interpretation of the speaker’s message.
Functional magnetic resonance imaging data that we collected indicate that Broca’s area plays an
important role in semantic unification. Language comprehension involves the rapid incorporation of
information in a ‘single unification space’, coming from a broader range of cognitive domains than
presupposed in the standard two-step model of interpretation.

Keywords: language; event-related brain potentials; functional magnetic resonance imaging;
discourse; semantic unification; Broca’s area
1. INTRODUCTION
As a result of the Chomskyan revolution in linguistics
(Chomsky 1957), theories about human language
comprehension often assume that the sentence is not
only the core unit of syntactic analysis, but also the core
unit of language interpretation. The assumption
follows from the fact that the sentence is the domain
of syntactic analysis coupled with two dominant ideas
in mainstream generative grammar: (i) the truly
relevant combinatorics of language are coded in the
syntax and (ii) the semantic interpretation of an
expression is derived from its syntactic structure. The
latter idea is what Culicover & Jackendoff (2006) have
recently referred to as Fregean compositionality, the
claim that the overall meaning of an utterance is a
function of the meaning of its parts and of the syntactic
rules by which they are combined.

The implication of this idea is that language
interpretation takes place in a two-step fashion. First,
the context-free meaning of a sentence is computed by
combining fixed word meanings in ways specified by
the syntax. In a second step, the sentence meaning is
integrated with information from prior discourse,
ntribution of 14 to a Discussion Meeting Issue ‘Mental
s in the human brain’.

r for correspondence ([email protected]).

801
world knowledge, information about the speaker and

semantic information from extra-linguistic domains

such as co-speech gestures or the visual world. The

latter step is needed because interpretation is clearly

shaped by factors beyond the sentence given. That is,

listeners interpret language not only by combining

stored word meanings in accordance with the gram-

mar, but also by taking into consideration their

knowledge about the speaker (Clark 1996), their

knowledge of the world ( Jackendoff 2003) and the

available information from the other input modalities

( Tanenhaus et al. 1995).
There is widespread agreement that such additional

‘contextual’ factors help to fix the final interpretation

of a sentence. However, there is disagreement over

whether such factors can also immediately co-

determine the initial interpretation of sentence-level

expressions. The standard two-step model of interpre-

tation prohibits such immediate contextualization of

meaning (e.g. Grice 1975; Fodor 1983; Sperber &

Wilson 1995; Cutler & Clifton 1999; Lattner &

Friederici 2003). For instance, in their blueprint of

the listener, Cutler & Clifton (1999) assume that,

based on syntactic analysis and thematic processing,

utterance interpretation takes place first, in a next

processing step integration into a discourse model

follows. Along similar lines, Lattner & Friederici (2003)
This journal is q 2007 The Royal Society

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distribution
of effect in
300–500 ms

–

discourse-semantic N400 effect
(a)

anomalous
coherent

4 µV

– 4 µV

0 400 800

Pz

CW

1200 ms

distribution
of effect in
300–500 ms

–

(b)
sentence-semantic N400 effect

anomalous
coherent

0 400 800 1200 ms

CW

Pz

Figure 1. N400 effects triggered by (a) discourse-related and (b) sentence-related anomalies. Waveforms are presented for a
representative electrode site ( Pz). The latencies of the N400 effect in discourse and sentence contexts (both onset and peak
latencies) are the same (after Van Berkum et al. 2003).

802 P. Hagoort & J. van Berkum Beyond the sentence given

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recently argued that mismatches between spoken
message and speaker are detected relatively late, in
slow pragmatic computations that are different from the
rapid semantic computations in which word meanings
are combined. Adherents of a one-step model of language
interpretation, in contrast, take the immediacy assump-
tion as their starting point (cf. Just & Carpenter 1980),
i.e. the idea that every source of information that
constrains the interpretation of an utterance (syntax,
prosody, word-level semantics, prior discourse, world
knowledge, knowledge about the speaker, gestures, etc.)
can in principle do so immediately (e.g. Crain &
Steedman 1985; Garrod & Sanford 1994; MacDonald
et al. 1994; Tanenhaus & Trueswell 1995; Clark 1996;
Altmann 1997; Van Berkum et al. 1999; Jackendoff 2002;
Zwaan 2004).

In our contribution, we review the results of a
number of studies that aimed to determine the
processing principles of language understanding
beyond the sentence level and that are directly relevant
to the issue of one- versus two-step language interpre-
tation. We looked at the influence of discourse, world
knowledge and co-speech gestures on the integration of
lexical information into a coherent mental model of
what is being talked about (‘situation model’; Zwaan &
Radvansky 1998). In most of these studies, we made
use of event-related brain potentials ( ERPs), an
average measure of electroencephalogram (EEG)
activity associated with particular critical events.
Because ERPs provide a direct and qualitative
informative record of neuronal activity, with almost
0 ms delay, they allow one to keep track of the various
processes in language comprehension with high
temporal resolution. For several of the studies dis-
cussed below, we also briefly report functional mag-
netic resonance imaging (fMRI ) data collected with the
same experimental design to identify crucial cortical
contributions to language interpretation.
2. THE DOMAIN OF SEMANTIC UNIFICATION:
SENTENCE VERSUS DISCOURSE
To investigate the different claims of the one-step and the
two-step models empirically, we first conducted an ERP
Phil. Trans. R. Soc. B (2007)
study aiming to unravel how and when the language

comprehension system relates an incoming spoken word

to semantic representations of the unfolding local

sentence and the wider discourse ( Van Berkum et al.
2003). For this and most of the other studies discussed
here, we exploited the characteristics of the so-called

N400 component in the ERP waveform. Kutas &

Hillyard (1980) were the first to observe this negative-

going potential with an onset at approximately 250 ms

and a peak at approximately 400 ms (hence the N400),
whose amplitude was increased when the semantics of

the eliciting word (i.e. socks) mismatched with the
semantics of the sentence context, as in He spread his
warm bread with socks.

Since its original discovery in 1980, much has been

learned about the processing nature of the N400 (for

extensive overviews, see Kutas & Van Petten 1994;

Osterhout & Holcomb 1995; Kutas et al. 2006;
Osterhout et al. in press). In particular, as Hagoort &
Brown (1994) and many others have observed, the

N400 effect does not depend on a semantic violation.

For example, subtle differences in semantic expect-

ancy, as between mouth and pocket in the sentence
context ‘Jenny put the sweet in her mouth/pocket after
the lesson’, can also modulate the N400 amplitude

(Hagoort & Brown 1994). Specifically, as the degree of

semantic fit between a word and its context increases,

the amplitude of the N400 goes down. Owing to such
subtle modulations, the word-elicited N400 is generally

viewed as reflecting the processes that integrate the

meaning of a word into the overall meaning represen-

tation constructed for the preceding language input

(Osterhout & Holcomb 1992; Brown & Hagoort 1993).
In our discourse experiment ( Van Berkum et al.

2003; see Van Berkum et al. (1999) for a written-
language variant), listeners heard short stories of which

the last sentence sometimes contained a critical word
that was semantically anomalous with respect to the

wider discourse (e.g. Jane told the brother that he was
exceptionally slow in a discourse context where he had in
fact been very quick). Relative to a discourse-coherent

counterpart (e.g. quick), these discourse-anomalous
words (slow in the example sentence) elicited a large

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N400 effect (i.e. a negative shift in the ERP that began
at approximately 150–200 ms after spoken word onset
and peaked around 400 ms; figure 1a).

Next to the discourse-related anomalies, standard
sentence-semantic anomaly effects were elicited under
comparable experimental conditions (figure 1b). The
ERP effects elicited by both types of anomalies were
highly similar. Relative to their coherent counterparts,
discourse- and sentence-anomalous words elicited an
N400 effect with an identical time course and scalp
topography (figure 1). The similarity of these effects,
particularly in polarity and scalp distribution, is
compatible with the claim that they reflect the activity
of a largely overlapping or identical set of underlying
neural generators, indicating similar functional pro-
cesses. In related studies, we have furthermore found
that like sentence-dependent N400 effects, discourse-
dependent N400 effects can also be elicited by coherent
words that are simply somewhat less expected ( Van
Berkum et al. 2005; Otten & Van Berkum in press).

In line with other work (e.g. St George et al. 1994),
our discourse ERP studies provide no indication
whatsoever that the language comprehension system
is slower in relating a new word to the semantics of the
wider discourse than in relating it to local sentence
context. Our findings thus do not support the idea that
new words are related to the discourse model after
they have been evaluated in terms of their contribution
to local sentence semantics. Furthermore, the speed
with which discourse context affects processing of the
current sentence appears to be at odds with estimates
of how long it would take to retrieve information about
prior discourse from long-term memory. In the
material of Van Berkum and colleagues, the relative
coherence of a critical word usually hinged on rather
subtle information that was implicit in the discourse
and required considerable inferencing about the
discourse topic and the situation it described. Kintsch
( Ericsson & Kintsch 1995; Kintsch 1998) has
suggested that during online text comprehension,
such subtle discourse information is not immediately
available and must be retrieved from memory when
needed. This is estimated to take some 300–400 ms at
least. However, the results of our experiments suggest
that the relevant discourse information can sometimes
be brought to bear on local processing within a mere
150 ms after spoken word onset.

As discussed elsewhere ( Van Berkum et al. 1999,
2003), the observed identity of discourse- and
sentence-level N400 effects can be accounted for in
terms of a processing model that abandons the
distinction between sentence- and discourse-level
semantic unification. One viable way to do this (in our
view) is by invoking the notion of ‘common ground’
(Stalnaker 1978, Clark 1996). Linguistic analyses have
demonstrated that the meaning of utterances cannot be
determined without taking into account the knowledge
that speaker and listener share and mutually believe
they share. This common ground includes a model of
the discourse itself (i.e. a situation model as well as a
record of the exchange, ‘a discourse record’ or
‘textbase’; Clark 1996), which is continually updated
as the discourse unfolds. If listeners and readers always
immediately evaluate new words relative to the
Phil. Trans. R. Soc. B (2007)
discourse model and the associated information in
common ground (i.e. immediately compute ‘contextual
meaning’), the identity of the ERP effects generated by
sentence- and discourse anomalies has a natural
explanation. With a single sentence, the relevant
common ground only includes whatever discourse
and world knowledge has just been activated by the
sentence fragment presented so far. With a sentence
presented in discourse context, the relevant common
ground will be somewhat richer, now also including
information elicited by the specific earlier discourse.
But the unification process that integrates incoming
words with the relevant common ground should not
really care about where the interpretive constraints
came from. We suspect that the N400 effects observed
by Van Berkum et al. (2003) reflect the activity of this
single conceptual unification process.

Of course, this is not to deny the relevance of
sentential structure for semantic interpretation. In
particular, how the incoming words are related to the
discourse model is co-constrained by sentence-level
syntactic devices (such as word , case marking,
local phrase structure or agreement) and the associated
mapping onto thematic roles. However, this is fully
compatible with the claim that there is no separate
stage during which word meaning is exclusively
evaluated with respect to ‘local sentence meaning’,
independent of the discourse context in which that
sentence occurs.

The idea that language interpretation involves the
immediate mapping of incoming word meanings onto the
widest interpretive domain available has also received
supported from eye tracking data with readers (e.g. Hess
et al. 1995) and listeners (e.g. Altmann & Kamide 1999;
Hanna et al. 2003; see Trueswell & Tanenhaus (2005) for
review). However, unlike eye movements, brain
potentials provide clear cues to the identity of the
processes involved, and therefore allow for stronger
inferences about whether or not two sources of
information are recruited by the same neuronal system
(Van Berkum 2004). It is due to this feature that ERP
data can make a unique contribution to debates about the
(non)equivalence of specific processes.

Particularly strong ERP evidence for the immediate
integration of lexical-semantic information into
a discourse model has recently been provided by
Nieuwland & Van Berkum (2006). They had subjects
listening to short stories in which the inanimate
protagonist was attributed with different animacy
characteristics. Here is an example of the materials,
with the critical words in italics:
A woman saw a dancing peanut who had a big smile on

his face. The peanut was singing about a girl he had just

met. And judging from the song, the peanut was totally

crazy about her. The woman thought it was really cute

to see the peanut singing and dancing like that. The

peanut was salted/in love, and by the sound of it, this was

definitively mutual. He was seeing a little almond.
As can be seen in figure 2, the canonical inanimate
predicate (salted) for this inanimate object (peanut)
elicited a larger N400 than the locally anomalous, but
contextually appropriate predicate (i.e. a peanut that
is in love).

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salted
3 µV

–3 µV P3

0 500 1000 ms

Pz

0 500 1000 ms 0 500 1000 ms

300– 600 ms

in love

P4

inanimate predicate
animate predicate

A woman saw a dancing peanut who had a big smile
on his face. The peanut was singing about a girl he
had just met. And judging from the song, the peanut
was totally crazy about her. The woman thought
it was really cute to see the peanut singing and
dancing like that. The peanut was salted / in love, and
by the sound of it, this was definitely mutual. He
was seeing a little almond.

A discourse-semantic N400 effect that overrules local animacy

Figure 2. N400 effects triggered by a correct predicate (salted ) that is, however, contextually disfavoured in comparison to an
incorrect predicate (in love). Waveforms are presented for representative electrode sites, time locked to the onset of the critical
inanimate/animate predicate in the fifth sentence (after Nieuwland & Van Berkum 2006).

an N400 effect of speaker-message inconsistency

3 µV

–3 µV P3

0 500 1000 ms

Pz

0 500 1000 ms

P4

0 500 1000 ms

“If only I looked like Britney
Spears in her latest video”

“I have a large tattoo on my
back”

“Every evening I drink some
wine before I go to sleep”

male/ female :

upper- / lower-class :

young child / adult : –1.0
µV

1.0
µV200 –700 ms

Britney
tattoo
wine

Figure 3. N400 effects triggered by a critical word (in bold) that rendered the spoken sentence inconsistent with voice-based
inferences about the speaker. Three representative electrode sites are shown (speaker-inconsistent waveforms are in red) as well
as the topographic distribution of the N400 effect ( Van Berkum et al. submitted).

804 P. Hagoort & J. van Berkum Beyond the sentence given

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These results show that discourse context can
completely overrule constraints provided by animacy, a
feature claimed to be part of the evolutionary hardwired
aspects of conceptual knowledge (Caramazza & Shelton
1998), and often mentioned as a prime example of the
semantic primitives involved in the computation of
context-free sentence meaning (cf. Fregean composi-
tionality). As such, these ERP results provide strong
evidence against the standard two-step model of language
interpretation.
Phil. Trans. R. Soc. B (2007)
3. KNOWLEDGE OF THE SPEAKER
In interpreting a speaker’s utterance, we not only take
the preceding utterances into consideration, but also
our knowledge of the speaker. For instance, we know
that a toddler is unlikely to say ‘I studied quantum
physics during my holidays’, and that it is really odd for
a man to say ‘I think I am pregnant because I feel sick
every morning’. As examples such as these reveal, at
some point during language comprehension, people
combine the information that is represented in the

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semantic
N400 effect

(a)

(b)

300 – 550 ms

semantic violation:

The Dutch trains are sour and very crowded.

The Dutch trains are white and very crowded.

correct:

world knowledge violation:

world knowledge
N400 effect

300 – 550 ms

–3 µV

3 µV

– 3.0
µV

3.0
µV

– 3.0
µV

3.0
µV

L

R

RL L

sour
white
yellow

0 200 400 600 ms

Cz

N400

The Dutch trains are yellow and very crowded.

Figure 4. (a) Grand average ERPs for a representative electrode site (Cz) for correct condition (black line), world knowledge
violation (green dotted line) and semantic violation (red dashed line). ERPs are time locked to the presentation of the critical
words (in italic). Spline-interpolated isovoltage maps display the topographic distributions of the mean differences from 300 to
550 ms between semantic violation and control (left); and between world knowledge violation and control (right). Topographic
distributions of the N400 effect are not significantly different between semantic and world knowledge violation ( pZ0.9). (b) The
common activation for semantic and world knowledge violations compared with the correct condition based on the results of a
minimum-T-field conjunction analysis. Both violations resulted in a single common activation ( pZ0.043, corrected) in the
LIFG (in, or in the vicinity of, Brodmann’s area 45 ([x, y, z]Z[K44, 30, 8]; ZZ4.87) and brain area (BA 47) ([x, y, z]Z
[K48, 28, K12]; ZZ4.15). The cross hair indicates the voxel of maximal activation and has the following coordinates [x, y, z]Z
[K44, 30, 8] (left BA 45).

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contents of a sentence with the information they have
about the speaker. The question again concerns exactly
when the pragmatic information about the speaker is
having its impact on the unfolding interpretation of
the utterance.

In an ERP experiment ( Van Berkum et al. sub-
mitted), people listened to sentences, some of which
contained a speaker inconsistency, a specific word at
which the message content became at odds with
inferences about the speaker’s sex, age and social
Phil. Trans. R. Soc. B (2007)
status, as inferred from the speaker’s voice. One
example was: ‘I have a large tattoo on my back’ spoken
in an upper-class accent. For comparison, other
sentences contained a standard semantic anomaly, a
specific word whose meaning did not fit the semantic
context established by the preceding words, as in ‘The
Earth revolves around the trouble in a year’.

If voice-based inferences about the speaker are
recruited by the same early unification process that
combines word meanings, then speaker inconsistencies

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806 P. Hagoort & J. van Berkum Beyond the sentence given

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and semantic anomalies should elicit the same N400
effect (though not necessarily of the same size). But if,
as predicted by the two-step model of semantic
interpretation, contextual information about the
speaker is handled in a distinct second phase of
interpretation (cf. Lattner & Friederici 2003), then
speaker inconsistencies should elicit a delayed and
possibly quite different ERP effect. As can be seen in
figure 3, speaker inconsistencies elicited a small but
clear N400 effect with a classical posterior maximum.
Moreover, its onset latency is the same as for the
standard N400 effect. Importantly, reliable effects of
speaker inconsistency were already found in the 200–
300 ms latency range after word onset. The same
latency effects were obtained in this experiment for the
straightforward semantic anomalies.

According to our ERP results, the brain integrates
message content and speaker information within some
200–300 ms after the acoustic onset of a relevant word.
Also, speaker inconsistencies elicited the same type of
brain response as semantic anomalies, an N400 effect.
That is, voice inferred information about the speaker is
taken into account by the same early language
interpretation mechanisms that construct ‘sentence-
internal’ meaning based on just the words. These
findings therefore demonstrate again that linguistic
meaning depends on the pragmatics of the commu-
nicative situation right from the start. However, by
revealing an immediate impact of what listeners infer
about the speaker, the present results add a distinctly
social dimension to the mechanisms of online language
interpretation. What we see is that language users
immediately model the speaker to help determine
what is being said. This ERP finding converges with
linguistic analyses of conversation (Clark 1996) as well
as with evidence from eye movements for the rapid use
of speaker-related information during comprehension
(e.g. Hanna et al. 2003; Trueswell & Tanenhaus 2005).

In addition, in an fMRI version of this experiment,
we found that the increased unification load of
combining incompatible speaker information and
message content resulted in increased activation of
the left inferior frontal gyrus (LIFG), the area that has
been found to be of importance for unification
operations in many other neuroimaging studies
(cf. Hagoort 2005).
4. WORLD KNOWLEDGE VERSUS
SEMANTIC KNOWLEDGE
At least since Frege (1892, see Seuren 1998), theories
of meaning make a distinction between the semantics of
an expression and its truth-value in relation to our
mental representation of the state of affairs in the world
( Jackendoff 2002). For instance, the sentence ‘The
present Queen of England is divorced’ has a coherent
semantic interpretation, but contains a proposition that
is false in the light of our knowledge in memory that
Her Majesty is married to Prince Phillip. The situation
is different for the sentence ‘The favorite palace of
the present Queen of England is divorced’. Under
default interpretation conditions, this sentence has no
coherent semantic interpretation, since the predicate
is divorced requires an animate argument. This sentence
Phil. Trans. R. Soc. B (2007)
mismatches with our representation of the world in
memory, because the descriptive features of the
purported state of affairs are inherently in conflict.
The difference between these two sentences points to
the distinction that can be made between facts of the
world and the words of our language, including their
meaning (lexical semantics). In the standard two-step
model of interpretation, only the latter type of knowl-
edge feeds into the construction of initial sentence
meaning; the integration of pragmatic or world knowl-
edge information would be delayed and handled by a
different system (e.g. Sperber & Wilson 1986).

Hagoort et al. (2004) performed a combined EEG/
MRI study that speaks to this issue. While participants’
brain activity was recorded, they read three versions of
sentences such as: ‘The Dutch trains are yellow/white/
sour and very crowded.’ (the critical words are in
italics). It is a well-known fact among Dutch people
that Dutch trains are yellow and, therefore, the first
version of this sentence is correctly understood as true.
However, the linguistic meaning of the alternative
colour term white applies equally well to trains as the
predicate yellow. It is world knowledge about trains in
Holland that makes the second version of this sentence
false. This is different for the third version, where
(under standard interpretation conditions) the core
semantic features of the predicate sour do not fit the
semantic features of its argument trains. One could thus
argue that the third sentence is false or incoherent for
semantic-internal reasons: it is our knowledge about
the words of our language and their linguistic meaning
that poses a problem. If semantic interpretation
precedes verification against world knowledge, the
effects of the semantic violations should be earlier and
might invoke other brain areas than the effects of the
world knowledge violations.

Figure 4 presents an overview of the results. As
expected, …