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See discussions, stats, and author profiles for this publication at: http://www.researchgate.net/publication/8931460
Grammar Processing Outside the Focus of
Attention: An MEG Study
ARTICLE in JOURNAL OF COGNITIVE NEUROSCIENCE · DECEMBER 2003
Impact Factor: 4.69 · DOI: 10.1162/089892903322598148 · Source: PubMed
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Yury Shtyrov
Aarhus University
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Friedemann Pulvermüller
Freie Universität Berlin
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Risto J Ilmoniemi
Aalto University
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Grammar Processing Outside the Focus of Attention:an MEG Study
Yury Shtyrov 1, Friedemann Pulvermüller 1, Risto Näätänen3,4,and Risto J. Ilmoniemi2,4
Abstract
& To address the cerebral processing of grammar, we used
whole-head high-density magnetoencephalography to record
the brain’s magnetic fields elicited by grammatically correct
and incorrect auditory stimuli in the absence of directed
attention to the stimulation. The stimuli were minimal short
phrases of the Finnish language differing only in one single
phoneme (word-final inflectional affix), which rendered them
as either grammatical or ungrammatical. Acoustic and lexicaldifferences were controlled for by using an orthogonal design
in which the phoneme’s effect on grammaticality was inverted.
We found that occasional syntactically incorrect stimuli elicited
larger mismatch negativity (MMN) responses than correct
phrases. The MMN was earlier proposed as an index of pre-
attentive automatic speech processing. Therefore, its modu-
lation by grammaticality under nonattend conditions suggests
that early syntax processing in the human brain may take place
outside the focus of attention. Source analysis (single–dipole
models and minimum-norm current estimates) indicated
grammaticality dependent differential activation of the leftsuperior temporal cortex suggesting that this brain structure
may play an important role in such automatic grammar
processing. &
INTRODUCTION
For over a century, the processing of language in the
brain has remained one of the most intriguing issues in
science. Although its many aspects have been tackled by numerous studies, little is still known of how our centralnervous system goes about processing grammar. Gram-
mar is one of the main intrinsic properties of the human
language. The very presence of a grammatical system
distinguishes our ability of verbal communication fromall signaling systems used by animals. Earlier investiga-tions of the neurophysiology of syntactic processing
(e.g., Hagoort, Brown, & Groothusen, 1993; Osterhout
& Holcomb, 1992; Neville, Nicol, Barss, Forster, & Gar-
rett, 1991) have led to important insights into this issue.
Three major syntax-related phenomena have been
described on the basis of the brain’s electric responsesto language stimuli. The first one is the so-called early
left anterior negativity (ELAN) occurring, with a latency
of ¹125 msec, in response to function words1 whose
placement in a phrase violates sentence structure rules
(Neville et al., 1991). Secondly, grammatically relatedfrontal negativities with longer latencies (over 250 msec)
have been found, for example, for different morpholog-
ical or syntactic errors (Gunter, Friederici, & Schriefers,
2000; Münte, Schiltz, & Kutas, 1998). Finally, a late
positive shift (often termed P600), reaching its maxi-
mum at ¹600 msec and maximal at centro-parietal
recording sites, has been considered the most robustneurophysiological response to ungrammatical sen-
tences because it could be observed in many linguisticexperiments (for review, see Osterhout, McLaughlin, &
Bersick, 1997; Osterhout & Hagoort, 1999).
When studying the processing of grammar in the brain,
it seems important to control for a number of issues. For
instance, in such studies, subjects are typically asked toattend to presented sentences (e.g., Friederici, Wang,
Herrmann, Maess, & Oertel, 2000; Osterhout & Swinney,
1993; Neville et al., 1991); often, the task is to judge the
sentence grammaticality. In such cases, as attention is
required, one cannot be sure to what extent the regis-tered responses are influenced by brain correlates of
attention rather than by the language-related activity as
such. Attention-related phenomena are known to mod-
ulate a variety of the brain’s evoked responses in a
substantial span of time after stimulus onset and to
involve a number of brain structures including thoseclose to, or overlapping with, the core language areas
(see, e.g., Yamasaki, LaBar, & McCarthy, 2002; Yantis
et al., 2002; Escera, Alho, Winkler, & Näätänen, 1998;
Tiitinen, May, & Näätänen, 1997; Woods, Alho, & Algazi,
1993; Woods, Knight, & Scabini, 1993; Alho, 1992; Picton
& Hillyard, 1974). It also appears possible that subjectspay more attention to incorrect sentences as they try to
1 Medical Research Council, Cognition and Brain Sciences Unit,
Cambridge, UK, 2 Biomag Laboratory, Helsinki University
Central Hospital, 3 University of Helsinki, 4 Helsinki Brain
Research Center
© 2003 Massachusetts Institute of Technology Journal of Cognitive Neuroscience 15:8, pp. 1195–1206
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make some sense of them or that they process grammat-
ical and ungrammatical items using different strategies.
These different strategies and attention variation may
find their reflection in the event-related measures, over-
lapping with true syntax-related activity. Therefore, lim-iting the attention-related effects seems to be necessary
at this stage for further investigation of the neural
processing of syntax.
A methodologically important aspect in such experi-ments is stimulus selection. Grammatically correct andincorrect phrases would inevitably differ in many other
features: e.g., sound onset times and durations in
acoustic stimulation, as well as visual geometry and
overall luminance in visual tasks, would change when
words or affixes are added, removed, or relocated to
modulate grammaticality. Differences even in basicphysical features may lead to differential brain activation
(Korth & Nguyen, 1997; Näätänen & Picton, 1987) that
could in principle overlap with or be misinterpreted as
language-related effects. For example, it was shown that
word-elicited responses are highly dependent on the word length (Osterhout, Bersick, & McKonnon, 1997;
Assadollahi & Pulvermüller, 2003), suggesting the ne-
cessity to control for such factors. Furthermore, the
physical stimulus parameters are of crucial importance
for obtaining ERP effects of syntactic processes (Gunter,Friederici, & Hahne, 1999). It seems most logical to us
to apply an experimental design in which physical
differences between the grammatical and ungrammati-
cal items are controlled for by presenting the same
physical contrasts to the subjects both in ungrammatical
and grammatical contexts; this sort of an orthogonaldesign would help to disentangle purely syntactic effectsfrom those related to the physical stimulus features.
So, in sum, it appears crucial to limit the influence of
attention and different processing strategies on the
brain response to grammatical and ungrammaticalstrings as well as to apply maximal control over stimulus
features using a counterbalanced stimulus design. Con-
trolling for these issues simultaneously in a single study
can be a challenging task, which, as to our knowledge,
has not been realized so far. The present study repre-sents an attempt to achieve this goal.
Here, we addressed brain activity related to grammat-ical processing in the absence of directed attention
towards stimuli and without an active task which would
possibly invite subjects to invent a strategy for dealing
with unusual stimuli. We used a counterbalanced stim-ulus design, which allowed us to control for effects of
the physical and lexical parameters of the stimuli. To
gain high temporal resolution necessary in such an
experiment, we opted for multichannel magnetoence-
phalographic (MEG) recording of brain responses, which can also provide information about the spatial
location of the registered activity.
We utilized the so-called mismatch negativity (MMN),a unique indicator of automatic cerebral processing of
acoustic stimuli, which can be used to investigate the
cerebral processing of speech and language (Shtyrov,
Kujala, Palva, Ilmoniemi, & Näätänen, 2000; Shtyrov &
Pulvermüller, 2002a, 2002b; Näätänen & Winkler, 1999;
Näätänen, 2001; Pulvermüller et al., 2001). MMN, withits major sources of activity in both the supratemporal
and frontal cortices, is a brain response elicited by rare
(deviant) stimuli occasionally presented in a sequence
of frequent (standard) stimuli (Opitz, Rinne, Mecklinger, von Cramon, & Schröger, 2002; Picton, Alain, Otten,Ritter, & Achim, 2000; Alho, 1995). It can be registered
as a negative deflection in the scalp electroencephalo-
graphic recording (EEG), or, as a component in the
brain’s magnetoencephalogram. Importantly, MMN (and
its magnetic counterpart, MMNm, or mismatch field),
can be elicited in the absence of the subject’s attention(Näätänen, 1995; Näätänen & Escera, 2000). It is con-
sidered to reflect the brain’s automatic discrimination of
changes in the auditory sensory input and, furthermore,
to provide an index of experience-dependent memory
traces in the human brain (Näätänen, 2001; Shtyrov et al., 2000; Kraus, McGee, Carrell, & Sharma, 1995).
Recent evidence suggests that the MMN reflects brain
processing of such language elements as phonemes
(Näätänen et al., 1997; Näätänen, 1999, 2001), syllables
(Shtyrov et al., 2000; Alho et al., 1998), and words(Shtyrov & Pulvermüller, 2002b; Korpilahti, Krause,
Holopainen, & Lang, 2001; Pulvermüller et al., 2001).
Importantly, we have recently found a specific pattern
of MMN responses to inflectional affixes (Shtyrov &
Pulvermüller, 2002a), which is best explained by the
activation of distinct cortical memory traces for suchaffixes realized as distributed strongly connected pop-ulations of neurons (Pulvermüller, 1999, 2001). Inflec-
tional (functional) affixes are important tools utilized in
many languages for realizing syntax and conveying
grammatical information. This suggests that the MMNcould be a sensitive tool for probing neural elements
responsible for the processing of grammar in the brain.
We have therefore set out to investigate the cerebral
processing of syntax using a whole-head high-density
MEG system, and recorded MMNm elicited by either grammatically correct or ungrammatical phrases, while
the subjects were distracted from the auditory stimula-tion by engaging in a different activity. The stimuli were
short pronoun–verb phrases differing only in their final
phoneme, which rendered them either as grammatical
or as grammatically incorrect (see Figure 1, Table 1, andMethods section for details). Any possible effects of
acoustic (phonetic) differences were ruled out by using
an orthogonal design reversing the effect of the pho-
neme and word combination on grammaticality.
RESULTS
Magnetic MMN responses were elicited in all conditions.The overall analysis of single equivalent current dipole
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(ECD) sources showed that the grammaticality of the
deviant stimuli had a significant effect on the MMNm
dipole moment, F (1,8) = 6.35, p < .04. Separate
analyses for each hemisphere showed that the gram-
maticality had no effect for the right hemisphere alone
( p > .65), whereas in the left hemisphere its effect wassignificant, F (1,8) = 6.67, p < .04: syntactically incor-rect phrases elicited stronger MMNm activity than didthe correct ones (see Figures 2, 3, and 4a). This effect
also became manifest as a significant Pronoun £ Suffix
interaction ( p < .04). It neither depended on the
direction of the acoustic contrast between the suffixes
( p > .12) nor on the preceding pronoun ( p > .63) as
such, but solely on the correctness of the phrase as a
whole (Figure 4a).The L1 minimum-norm current estimate (MCE)
analysis of the MEG signal suggested activation of distributed cortical sources spread out over the left
Figure 1. Spectrograms of acoustic Finnish-language stimuli used in the four experimental conditions. The standard and deviant stimuli in each
pair are indiscriminable up to the divergence point (marked with white arrowheads) at their end. The standard–deviant contrasts are identical
across all experimental conditions. Grammatically incorrect phrases are marked with an asterisk (*). See Table 1 for more details.
Table 1. Auditory Finnish-Language Stimuli Used in the Four Experimental Sessions
Condition 1a Condition 1b Condition 2a Condition 2b
Deviant Mä tuo n * Mä tuot * Sä tuo n Sä tuot
(‘‘I bring’’) (‘‘*I bring’’) (‘‘*you bring’’) (‘‘you bring’’)
Standard * Mä tuot Mä tuo n Sä tuot * Sä tuo n
(‘‘*I bring’’) (‘‘I bring’’) (‘‘you bring’’) (‘‘*you bring’’)
English translations are given in parentheses, ungrammatical phrases are marked with (*). The standard and deviant stimuli in each pair areindiscriminable up to the divergence point at their end. The standard–deviant contrasts are identical across all experimental conditions. Criticalcontrasts are in bold.
Shtyrov et al. 1197
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temporal cortex (see Figure 5). This activation was
significantly stronger (Figure 4b) for the syntactically
incorrect than for correct deviant phrases, F (1,11) =
9.46, p < .011. Again, this difference was clearly
affected by the grammaticality, but neither by the pro-
noun context ( p > .25) nor by the suffix ( p > .8).
No differences between conditions were found in the
right hemisphere.
As one could notice in Figure 5 (upper left panel),
some additional activation could be suggested to appear
also in the left inferior frontal cortex, which would be
consistent with earlier results (Neville et al., 1991). We
Figure 3. Waveforms
(magnetic field gradient) of
MMNm responses in the left
hemisphere (grand average).
Both ungrammatical deviant
stimuli produced stronger
MMNm than the corresponding
correct phrases regardless of
the acoustic, phonetic,
phonological, or lexical
properties of the stimuli.
Temporal gradiometer with the
most prominent responses
(channel 0242) was used for
producing this diagram.
Figure 2. ECD models of MMNm activity in the left hemisphere (grand average). Both ungrammatical deviant stimuli produced stronger MMNm
source than the corresponding correct phrases regardless of the acoustic, phonetic, phonological, or lexical properties of the stimuli. Red and blue
contour lines indicate positive and negative values of the normal component of the magnetic field on the helmet-shaped MEG-array surface,respectively. The arrows show the dipole location and are proportional in relative size to the response magnitude. The view is from the left side of
the head.
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analyzed activity in this area as well, but although we
found that, similarly to the supratemporal source, it was
somewhat increased for the ungrammatical deviant
phrases, this effect was not significant.
In the current study, the grammaticality affected theMMNm responses, but had no significant effect on the
responses to the standard stimuli only (cf. Figures 3
and 6). We also found no effects of grammaticality on
the latency of the MMNm responses, the mean latency in
the left hemisphere being 213 msec after the divergencepoint (mean SEM 19 msec). We also looked for significant
differences between the conditions in later time intervals
(>350 msec) but did not find any. Specifically, we would
like to note that no late deflection of the magnetic
response, which could be related to the P3- or P600-like
components of the EEG signal (Osterhout, McLaughlin
et al., 1997; Donchin, 1981), could be detected (seeFigures 3 and 6). We also noticed that the [n]-ending
stimuli produced larger MMNm dipole moment than did
the [t]-ending ones. However, this independent of the
grammaticality effect (which could in principle be due
to differences in attack and voicedness between the twophonemes) was only significant for comparison between
Conditions 2a and 2b ( p < .02; but p > .95 for
Figure 4. Grand-average mean
and standard error of mean of
the MMNm dipole-moment
magnitude (nanoamperemeter,
nAm) in the left hemisphere:
(A) calculated for single
equivalent current sources
(ECD), (B) calculated for L1
MCE (calculated as a sum of
dipole moments of all
simultaneously activatedadjacent current sources). Both
analyses indicated that the
ungrammatical deviant stimuli
produced a stronger MMNm
source than the corresponding
correct phrases regardless of
the acoustic, phonetic,
phonological, or lexical
properties of the stimuli.
Figure 5. Grand-average L1
MCEs of MMNm in the left
hemisphere. The MCE solutions
are projected unto
triangularized gray matter
surface. Both ungrammatical
deviant stimuli produced
stronger MMNm source than
the correct phrases regardless
of the acoustic, phonetic,
phonological, or lexical
properties of the stimuli.
Shtyrov et al. 1199
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Conditions 1a and 1b) and only in ECD but not in MCE
analysis, so it does not seem to present a solid finding.
Finally, we found no topographical effects of any of the
factors.
DISCUSSION
In the present study, mismatch responses were elicited
by grammatically correct or incorrect pronoun–verb
phrases. The choice of the single final phoneme in allphrases rendered the whole structure as syntactically
correct or as ungrammatical. To exclude confounding
effects, the phonetic and lexical contrasts were counter-
balanced over the experimental conditions using a fully orthogonal stimulus design. The subjects were instructed
not to attend to the stimuli; they did not perform any stimulus-related language task.
We found that MMNm responses to the syntactically
incorrect phrases were always larger than those to the
correct phrases ending in the same word regardless of thedirection of the acoustic contrast or of the preceding
pronoun. That is, neither the choice of the final phoneme
nor that of the pronoun in the sentence altered this effect,
which was present in both conditions in which the
deviant stimuli were grammatically inconsistent.
The present data are consistent with earlier results onthe cerebral processing of syntactic violations (see In-
troduction), which suggested negative-going compo-nents of brain responses at time delays of 125 msec or
more following syntactic errors. The present modifica-
tion of the MMN may be related to this early negativity.There are, however, important differences between the
present study and the earlier ones. Importantly, we were
able to find syntactically related effects in the absence of
directed attention towards the stimuli as subjects were
engaged in a different task and were instructed to ignorethe stimulation. The violations in this study modulated
the MMN response, which is considered to reflect a pre-
attentive automatic level of auditory processing in the
cerebral cortex (Näätänen & Alho, 1995; Näätänen &Escera, 2000; Tiitinen et al., 1997). This suggests that the
brain may be capable of automatic syntactic analysis of
the incoming language signals already at relatively early
stages of speech processing. This conclusion is support-ive of the earlier suggestion that early negativities, such
as ELAN, may reflect automatic stages of syntactic pro-cessing (Friederici, 2002; Gunter et al., 2000; Hahne &
Friederici, 1999).
The ELAN/N125 component reported in the previous
studies was found in response to phrase structure
violations (examp le: mathematician’s *of proof thetheorem ) and has been difficult to replicate (Takazawa
et al., 2002; Neville et al., 1991), whereas in the present
study the MMN modulation was elicited at a similar
latency by agreement violations ( mä tuo*t, sä tuo*n ),suggesting that a larger variety of grammatical violations,
including agreement violations, could be reflected by early left-lateralized neurophysiological responses.
An established view in psycholinguistics is that sen-
tence comprehension is incremental, that is, a substantialamount of processing occurs immediately after a word in
a sentence is perceived, prior to the perception of the
following word (Pulvermüller, 2001; Traxler & Pickering,
1996; Marslen-Wilson & Tyler, 1975; Marslen-Wilson,
1987). This implies that by the time a violation occurs, a
certain amount of analysis has been carried out by the
parsing system, a position largely shared by severalsyntactic parsing models that may substantially differ
otherwise (e.g., Friederici, 2002; van Gompel & Pickering,2001; Spivey & Tanenhaus, 1998; MacDonald, Pearlmut-
ter, & Seidenberg, 1994; Trueswell, Tanenhaus, & Kello,
1993; Ferreira & Henderson, 1990; Frazier, 1987; Mitchell,1987). During such analysis, an expectation for syntac-
tically possible subsequent morphemes may have built
up. When this expectation fails to realize and the parser
therefore encounters a syntactic error (i.e., a mismatchbetween preceding and incoming morphemes), it sends
an ‘‘error signal’’. Such an error signal may be due to a
lack of neuronal links between lexical representations
which results in a failure to provide priming between the
representations of morphemes that do not match syntac-tically (Pulvermüller, 2002). In our case, the memory trace
Figure 6. Waveforms
(magnetic field gradient)
of auditory responses to
standard stimuli in the left
hemisphere (grand
average). Although the
MMNm responses were
affected by grammaticality,
there was no significant
effect on the standard
responses (cf. Figure 3).Temporal gradiometer
with the most prominent
responses (channel 0242)
was used for producing
this diagram.
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(neuronal assembly) representing the expected correct
affix (Shtyrov & Pulvermüller, 2002a) would have been
primed by the preceding context. Language-related
priming effects are known to reduce negative-going
components of the event-related potentials (e.g., Hol-comb & Neville, 1990; Bentin, McCarthy, & Wood, 1985).
In ungrammatical conditions, this priming would be
absent which should lead to an increased response as
compared with grammatically consistent stimuli. Thus,the parser’s error signal, the unprimed activation of morpheme-related neuron ensembles, may be the basis
of syntactically related early left-lateralized responses,
including the larger MMN response to grammatical viola-
tions observed here. Interestingly again, this putative
process seems to occur outside the focus of attention
(i.e., at least to some degree automatically).The strongest activation produced by the syntactic
abnormalities in the current study was located in the left
temporal cortex. We take this as an indication that there
is a distributed neuronal system in the left superior
temporal lobe that contributes to grammar processing.This area has been repeatedly suggested as a neural
substrate for a variety of language functions such as
phonetic/phonological processing, lexical access, seman-
tic and syntactic processing (e.g., Shtyrov et al., 2000;
Shtyrov & Pulvermüller, 2002a, 2002b; Martin & Chao,2001; Pulvermüller et al., 2001; Friederici et al., 2000;
Price, 2000; Helenius, Salmelin, Service, & Connolly,
1998; Näätänen et al., 1997; Binder et al., 1995), which
is in line with the current results. There probably could
be an overlap between these functions with respect to
underlying neuroanatomical structures, but it seemsreasonable to suggest that they are carried out by atleast partially distinct neuronal networks (Pulvermüller,
2002). It also appears justified to suggest that the left-
lateralized neural systems contributing to the grammat-
ically related MMN in the superior temporal lobe may bedistinct from those responsible for classical bilateral
acoustic-related MMNs.
Interestingly, although we found the strongest activa-
tion in the temporal cortex, a left anterior-frontal re-
sponse was reported earlier (Neville et al., 1991;Pulvermüller & Shtyrov, in press). As we found no
significant grammatically dependent variation for theinferior frontal activity, we conclude that in the present
data the frontal source did not seem to play a major role
in syntactic processing. There could be several possible
explanations for this: in principle, it could be that theadvanced source analysis algorithm used in this study,
MCE, provides more accurate source localization than
potential mappings used earlier. As a viable alternative
explanation, one could suggest that the anterior source
might not be detectable in MEG due to its spatialorientation (and/or, vice versa, that the posterior source
may be difficult to image using EEG). Both of these
explanations are supported by earlier MEG research, which has also demonstrated more temporal than frontal
activity to syntactic violations when subjects were asked
to judge grammaticality of auditory presented sentences
(Friederici et al., 2000). However, a frontal ELAN gener-
ator was reported in MEG, although this was also accom-
panied by a temporal one (Gross et al., 1998). Finally, it ispossible that the absence of directed attention to the
stimuli and of an active task may have reduced the frontal
activity. This would imply that the inferior frontal source
is of smaller importance for automatic syntactic parsing.To fully answer the question of the cortical generator(s)for the syntactic MMN modulation observed here and
their relation to ELAN activation, further studies using
similar paradigm would be needed.
Finally, we could not find brain dynamics that might
relate to the late centro-parietal positive shift (P600)
reported earlier in ERP studies of grammatical violations. Again, one could suggest that cortical generators of late
slow positive shifts are not optimal for MEG recordings,
although, among late positivities, at least the P3 was
successfully registered using MEG (Berg, Kakigi, Scherg,
Dobel, & Zobel, 1999; Mecklinger et al., 1998; Tarkka,Stokic, Basile, & Papanicolaou, 1995). However, the latter
still does not rule out the possibility that the syntactically
related P600 response has no clear magnetic correlate.
Another possible reason for the absence of a late gram-
maticality effect in our present data set is the absence of an attention-demanding task. It has been proposed
earlier that the positive shifts to grammatical violations
reflect attention-dependent processes, for example, at-
tempts at a structural reanalysis of a sentence fragment
(Osterhout & Holcomb, 1992). In this view, the present
absence of clear dynamics in P600 time range (alsoconfirmed in a separate EEG study, Pulvermüller &Shtyrov, in press) might suggest a role of attention in
the generation of the late positivity. Because subjects did
not focus their attention on language in this study, they
most likely did not engage in re-parsing the deviantstrings, and thus the centro-parietal positive shift did
not occur. This would be consistent with notions that
P600 reflects phrase reanalysis and repair (Friederici,
1997; Osterhout, Holcomb, & Swinney, 1994) and may
not reflect specific syntactic processes per se (Münte,Heinze, Matzke, Wieringa, & Johannes, 1998).
In conclusion, the present results suggest that the early syntax parsing of spoken language may not require
focused attention and therefore could probably be auto-
matic to a certain extent. The cortical structures in the left
superior temporal lobe appear to play an important rolein carrying out such automatic grammar processing.
METHODS
Subjects
Twelve healthy right-handed (handedness assessed
according to Oldfield, 1971; no left-handed family mem-bers) native Finnish speakers (age 21–29, 7 women)
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wi th norm al hea ring an d no rec ord of neurol ogi-
cal diseases were presented with four sets of spoken
native-language stimuli in four separate experimental
conditions.
Stimuli
The four short-phrase stimuli (see Figure 1 and Table 1)
were prepared with requirements that the acoustic,phonetic, and phonological difference between thestandard and the deviant stimuli is identical in each
condition and that the stimuli themselves are as similar
acoustically as possible. These Finnish stimuli were:
(1a) Mä tuon (‘‘I bring,’’ syntactically correct),
(1b) * Mä tuot (‘‘*I bring,’’ syntactically incorrect: the verb tuot is in the second person inflection form, while
the pronoun mä, ‘‘I,’’ requires the first person); here
and throughout we use linguistic convention of marking
ungrammatical phrases with an asterisk (*),
(2a) * Sä tuon (‘‘*you bring,’’ syntactically incorrect:the verb tuon is in the first person form, while the
pronoun sä, ‘‘you,’’ requires the second person);
(2b) Sä tuot (‘‘you bring,’’ syntactically correct).2
Therefore, it is the single final phoneme, inflec-tional affix [n] or [t], which may render the whole phrase
as syntactically correct or as ungrammatical. Remarkably,
for ‘‘mä’’-stimuli (1a and 1b), the final [n] means that
the phrase is grammatical, while for the ‘‘sä’’-stimuli
(2a and 2b) the combination is exactly the opposite:
[t] is needed in the end for the whole phrase to becorrect. This orthogonal design is implemented inorder to control for purely acoustic, phonetic, and pho-
nological effects on mismatch responses as well as
for putative lexical and semantic differences between
the words. As seen in Table 1 presenting the complete stimulus
design, the stimuli starting with the same pronoun were
always presented in the same experimental condition,
one of them serving as deviant and the other one as
standard stimulus. Thus, the standard–deviant acoustic– phonetic contrast, the critical variable determining the
MMN (Näätänen & Alho, 1997), was the same in allconditions. However, in each pair of conditions (1a, b
and 2a, b) the responses were elicited either by correct
or incorrect deviant forms. Furthermore, while the
acoustic contrasts were identical in the corresponding
conditions ( tuon/tuot in 1a–2a and tuot/tuon in 1b–2b),the syntactic contrast (determined by the pronoun) was
the opposite: stimuli ending in tuon were correct in
conditions 1a and 1b, whereas tuot -ending phrases were
correct in Conditions 2a and 2b. This fully orthogonaldesign, therefore, allowed us to control not only for
possible acoustic/phonetic effects of the verb contrast,
but even for an unlikely late differential effect of the twopreceding pronouns.
For stimulus preparation, we recorded multiple rep-
etitions of each word uttered by a female native speaker
of Finnish. With great care we selected a combination of
recordings, whose vowels matched in their fundamental
frequency (F0) and whose overall length and maximalsound energy were identical both for sä and mä and for tuon and tuot . We then combined the four words in the
four abovementioned phrases with a 50-msec gap be-
tween the pronoun and the verb; all phrases were766 msec in duration. Thus, the two stimuli in eachcondition were perceptually identical up to a time point
(referred to as divergence point) shortly before their
end (see Figure 1). In order to determine this diver-
gence point, a gating experiment was performed, in
which initial fragments of increasing duration of bothtuon and tuot were presented to the subjects who wereasked whether they could perceive any difference be-
tween the two. In average, they could identify the
difference only when the first 336 msec ( SEM 9 msec)
of the words were presented (which equals to 636 msec
after the onset of the complete phrase). This perceiveddivergence point is therefore considered as the onset
of the perceptual standard/deviant contrast and a zero
time reference in the current study. Importantly, it is
the same in all pairs of stimuli due to their design.
All stimuli were normalized to have the same peaksound energy. For the analysis and production of the
stimuli, we used the Cool Edit 96 program (Syntrillium
Software, AZ).
Acoustic Stimulation
All four experimental conditions (Table 1) were per-formed with every subject, their order being counter-
balanced across the subject group. The stimuli were
binaurally presented at 50 dB above the individual
hearing threshold (determined using the experimentalstimuli) via headphones connected to an STIM setup
(Neuroscan Labs, VA). The interstimulus (stimulus
onset asynchrony, SOA) interval was 1450 msec. In each
condition, the deviant stimulus was presented with a
probability of 16.7% among the repetitive standardstimuli: A pseudorandom sequence of stimuli was cre-
ated so that there were always at least two standardstimuli between any two deviants. During the stimula-
tion, the subjects were seated in a magnetically shielded
chamber and instructed to watch a silent video film
of their own choice and to pay no attention to theauditory stimulation.
Magnetoencephalographic Recording
The evoked magnetic field was recorded (passband0.03–200 Hz, sampling rate 600 Hz) with 204 planar
gradiometer channels of a whole-head Neuromag Vec-
torview MEG system (Elekta Neuromag, Helsinki) duringthe auditory stimulation (Ahonen et al., 1993). The
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recordings started 100 msec before stimulus onset
and ended 1450 msec thereafter. The responses were
on-line averaged separately for the standard and devi-
ant stimuli in each condition. Epochs with voltage
variation exceeding 150 m V at either of two bipolar eye-movement electrodes or magnetic-field gradient
variation exceeding 3000 femtotesla per centimeter (fT/
cm) at any gradiometer channel were excluded from
averaging. The recordings for each condition containedat least 120 accepted responses to deviant stimuli (cor-responding to ¹600 standard responses) in order to
achieve satisfactory averaged signal quality. This require-
ment led to slight variations in overall recording dura-
tion, which in average constituted 2 hr per subject.
MEG Data Processing
The averaged responses were filtered off-line (passband
1–20 Hz). The period of 50 msec before the divergence
point was used as the baseline. The MMNm was ob-
tained by subtracting the averaged response to thestandard stimuli from that to the deviant ones. The
responses were evaluated separately for each subject
for all experimental conditions. Two approaches were
used for analyzing the neuromagnetic data.
Single-Dipole Fit
Fifty-four gradiometer channels on each side of the
magnetometer helmet were used for assessing cortical
responses in the left and right cerebral hemispheres. By
means of Neuromag sequential single-dipole fittingsoftware (Elekta Neuromag), the generator sources(equivalent current dipoles [ECDs]) of the MMNm were
estimated (Ilmoniemi, 1993). Only dipole models ex-
plaining more than 65% of the field gradients were
selected for statistical analysis; otherwise, the dipole-moment value was set to 0 nAm. The range of latencies
(as determined from peak dipole moment) accepted for
the MMNm responses was 100–350 msec after the
divergence point and the best fit (maximal goodness
of fit/dipole moment) was entered into analysis. Thedipole moments of the MMNm generators were calcu-
lated and compared between the experimental condi-tions. ECD fits were successfully constructed only for
nine subjects, suggesting that the single-dipole model
may not be optimal for explaining the syntactically
related activity. We therefore performed minimum-norm current analysis, which uses a distribution of
multiple current sources for modeling the neuromag-
netic signal.
L1 Minimum-Norm Current Estimate
The estimation of the cortical sources of the measured
neuromagnetic activity was performed using L1 MCEson the basis of recordings from all 204 gradiometer
channels equally distributed over the entire scalp. The
minimum-norm method provides a solution to the in-
ver se probl em of localizing neu ral activ ity in the
brain from its external recordings by revealing the
unique constellation of active neuronal current ele-ments that models the recorded magnetic field distri-
bution with the smallest amount of overall activity
(Uutela, Hämälä inen, & Somersalo, 1999; Ilmoniemi,
1993; Hämäläinen & Ilmoniemi, 1984, 1994). Among theinfinitely many current source combinations that canexplain a given scalp topography of the magnetic
field, this technique finds one that does so with the
least amount of overall activity. This minimal solution
should be preferred for the sake of parsimoniousness.
The L1 MCE minimizes the integral of the current
amplitude and reveals a realistic and robust constellationof localized generators. It is applicable when it can be
assumed a priori that the source distribution consists of
discrete areas of neuronal activity (in contrast with a
situation when no essential a priori information is
available, in which case L2 minimum norm estimate would be preferable). This assumption of local ized
sources is justified in the investigation of language
because neuroimaging results obtained with different
methodologies proved the activation of discrete cortical
areas during a variety of language tasks (Pulvermüller,2001; Price, 2000). A triangularized gray matter surface
was used for projecting MCE solutions for the each
subject individually and for the grand average magnetic
field. The dipole moments of the MMNm generators
were calculated (as a sum of dipole moments of all
simultaneously activated adjacent current sources) andcompared between the experimental conditions. TheMCE source analysis was successfully carried out for all
12 subjects, which suggests that it could be a better
method for analyzing distributed neural activity (as in
case of language-related phenomena) than ECD.
Statistical Analysis
The data were subjected to analyses of variance (AN-
OVA). Parameters of current sources constructed for each hemisphere were analyzed separately for ECD
and MCE. We compared them between conditions usingthe factors grammaticality (syntactically correct vs. in-
correct deviant stimulus), pronoun ( sä vs. mä ), and
suffix ([t] vs. [n]).
Ethical Considerations
All subjects gave their written informed consent to
participate in the experiments and were paid for
their participation. The experiments were performedin accordance with the Helsinki Declaration. Ethical
permission for the experiments was issued by the Re-
search Ethics Committee of Helsinki University CentralHospital.
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Acknowledgments
We thank Olaf Hauk, Vadim Nikulin, Maritta Maltio-Laine, SimoMonto, Tuomas Murdoch, Christopher Bailey, Jussi Nurminen,
Johanna Salonen, Anthea Hills, Seppo Kähkönen, and WilliamMarslen-Wilson for their contribution at different stages of this
work. We would also like to thank three anonymous refereesfor their helpful comments and constructive critique.
Reprint requests should be sent to Dr. Yury Shtyrov, Medical
Research Council, Cognition and Brain Sciences Unit, 15Chaucer Road, CB2 2EF Cambridge, UK, or via e-mail: [email protected].
Notes
1. Function words are grammatical words, such as articles,conjunctions, auxiliary verbs, and so on and so forth, whichhave no concrete meaning by themselves and are utilized for grammatical purposes.2. These spoken-language stimuli represent the most usualcolloquial pronunciation used in the Helsinki area; therefore,
we only used Finnish subjects who had lived in the Helsinkiarea for a minimum of 6 years before the experiment.
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