Not every pseudoword disrupts word recognition: An ERP study

Abstract

If all available acoustic phonetic information of words is used during lexical access and consequently stored in the mental lexicon, then all pseudowords that deviate in a single acoustic feature from a word should hamper word recognition. By contrast, models assuming underspecification of redundant phonological information in the mental lexicon predict a differential disruption of word recognition dependent on the phonological structure of the pseudoword. Using neurophysiological measures, the present study tested the predicted asymmetric disruption by assuming that coronal place of articulation for consonants is redundant.
Event-related potentials (ERPs) were recorded during a lexical decision task. The focus of interest was on word medial consonants. The crucial pseudowords were created by replacing the place of articulation of the medial consonant in German disyllabic words. We analyzed the differential temporal characteristics of the N400 pseudoword effect.
N400 amplitudes for pseudowords were enhanced compared to words. As the uniqueness and deviation points differ for coronal and non-coronal items, the ERPs had to be correspondingly adjusted. The adjusted ERPs revealed that the N400 pseudoword effect starts earlier for coronal than for non-coronal pseudoword variants. Thus, non-coronal variants are accepted as words longer than the coronal variants.
Our results indicate that lexical representations of words containing medial coronal consonants are initially activated by their corresponding non-coronal pseudowords. The most plausible explanation for the asymmetric neuronal processing of coronal and non-coronal pseudoword variants is an underspecified coronal place of articulation in the mental lexicon.

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Behavioral and Brain Functions
Open Access
Research
Not every pseudoword disrupts word recognition: an ERP study
Claudia K Friedrich*
1,2
, Carsten Eulitz
1
and Aditi Lahiri
1
Address:
1
Department of Linguistics, University of Konstanz, Germany and
2
Biological Psychology and Neuropsychology, University of Hamburg,
Germany
Email: Claudia K Friedrich* - Claudia.Friedrich@uni-hamburg.de; Carsten Eulitz - carsten.eulitz@uni-konstanz.de;
Aditi Lahiri - aditi.lahiri@uni-konstanz.de
* Corresponding author
Abstract
Background: If all available acoustic phonetic information of words is used during lexical access
and consequently stored in the mental lexicon, then all pseudowords that deviate in a single
acoustic feature from a word should hamper word recognition. By contrast, models assuming
underspecification of redundant phonological information in the mental lexicon predict a
differential disruption of word recognition dependent on the phonological structure of the
pseudoword. Using neurophysiological measures, the present study tested the predicted
asymmetric disruption by assuming that coronal place of articulation for consonants is redundant.
Methods: Event-related potentials (ERPs) were recorded during a lexical decision task. The focus
of interest was on word medial consonants. The crucial pseudowords were created by replacing
the place of articulation of the medial consonant in German disyllabic words. We analyzed the
differential temporal characteristics of the N400 pseudoword effect.
Results: N400 amplitudes for pseudowords were enhanced compared to words. As the
uniqueness and deviation points differ for coronal and non-coronal items, the ERPs had to be
correspondingly adjusted. The adjusted ERPs revealed that the N400 pseudoword effect starts
earlier for coronal than for non-coronal pseudoword variants. Thus, non-coronal variants are
accepted as words longer than the coronal variants.
Conclusion: Our results indicate that lexical representations of words containing medial coronal
consonants are initially activated by their corresponding non-coronal pseudowords. The most
plausible explanation for the asymmetric neuronal processing of coronal and non-coronal
pseudoword variants is an underspecified coronal place of articulation in the mental lexicon.
Background
Despite the fact that we perceive speech in an apparently
involuntary fashion, one requires several processing
stages to extract the meaning of an utterance. Acoustic-
phonetic features that build up the signal have to be
extracted and mapped onto knowledge stored in the lis-
teners' long-term memory in the form of lexical represen-
tations [1]. Mental representations must be capable of
successfully handling the tremendous amount of variabil-
ity in the speech signal with which the recognition system
is confronted. A frequent source of variation is assimila-
tion where segments take on the properties of other
sounds in close proximity. A common assimilation dis-
cussed frequently in the literature involves consonants
Published: 24 October 2006
Behavioral and Brain Functions 2006, 2:36 doi:10.1186/1744-9081-2-36
Received: 17 August 2006
Accepted: 24 October 2006
This article is available from: http://www.behavioralandbrainfunctions.com/content/2/1/36
© 2006 Friedrich et al; licensee BioMed Central Ltd.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0
),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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with a CORONAL place of articulation (PLACE; e.g., /t, d,
n/), which appear to borrow the PLACE information of
the segment that immediately follows. The /n/ in rain, for
example, can take on the PLACE of the following LABIAL
/b/ in rainbow resulting in *raimbow (note that here and in
the following examples an asterisk marks pseudowords).
Different accounts have been proposed to explore the fact
that assimilated *raim does not disrupt recognition of rain
[2-16]. One of these approaches is the assumption of a
featurally underspecified lexicon (FUL) [2-4]. In an under-
specified lexicon feature value slots can be left empty par-
ticularly for feature values that frequently show variation.
Leaving the PLACE slot for coronal feature values empty
(underspecified representation) allows activation from
systematic variants that are specified for PLACE, as these
will not mismatch with the underspecified value in the
lexical representation. Thus, *raim can activate the word
rain. Invariant feature values, e.g. [LABIAL] and [DOR-
SAL] PLACE, are specified in the lexical representation
because they can reliably contribute to word identifica-
tion. Consider for example the dorsal /K/ in long days that
will not become a coronal /n/ even if it is followed by a
coronal /d/. The extraction of features from the signal, and
the presence or absence of those features in the represen-
tation of words predicts asymmetric activation patterns.
Words are activated if signal and representation contain
the same information, or if an extracted feature is not rep-
resented in the lexicon. In contrast, words are rejected if
signal and representation contain incompatible features.
Alternative approaches to the FUL model strengthen the
importance of context for the correct recognition of assim-
ilated forms. Gaskell and Marslen-Wilson assume that
mapping speech onto lexical representations involves on-
line phonological inference that detects systematic varia-
tion [5,6]. In this approach it is proposed that listeners
cope with assimilation by inverting phonological rules in
a given context. Accordingly, when presented with raim-
bow, listeners infer that a labial followed by another labial
may be an underlying coronal. Evidence for contextual
sensitivity in the analysis of feature changes has been pro-
vided in cross-modal priming experiments [5-7]. Further-
more, a combined impact of context and phonetic detail
has been proposed by Gow [8-10]. He argues that assimi-
lation does not change a feature completely, but provides
information about both the underlying form of the assim-
ilated segment and the surface form of the following seg-
ment. According to this point of view listeners detect
assimilated features, use this information to anticipate the
upcoming segment, and align the assimilated feature to
this subsequent element. Indeed, some empirical evi-
dence suggests that context in combination with phonetic
detail drives compensation for assimilation [8-12].
However, the representational-cum-mapping hypothesis
of FUL also received support from psycholinguistic as well
as from neurolinguistic studies. Behavioral priming exper-
iments showed that only non-coronal variants (e.g.,
*wickib) activate associates of coronal words (e.g., wicked),
whereas coronal variants (e.g., *sanctun) do not activate
associates of non-coronal words (e.g., sanctum) [4]. More-
over, recent cross-modal priming studies challenged the
impact of context by showing that lexical activation of
underlying coronal entries appears to be equally tolerant
to contextually appropriate and inappropriate changes of
coronal elements [13,14]. Finally, mismatch negativity
(MMN) observed in event related brain potentials (ERPs)
provides evidence for FUL. MMN is elicited by infrequent
deviant stimuli that are presented after a random number
of frequent standard stimuli (see [17] for an overview).
Earlier latency and higher amplitude MMN values were
found for coronal deviants among non-coronal standards,
as compared to non-coronal deviants among coronal
standards. This suggests that the representations activated
by the coronal standards do not have PLACE specified
[18].
Psycholinguistic research on underspecified entries largely
looked at assimilation contexts occurring in word final
position. Here one could argue that all assimilation vari-
ants are stored, since they occur in predictable environ-
ments and will be part of the listener's experience.
However, if lexical underspecification is part of the mental
representation, then asymmetric activation should also
occur for other positions within a word. Despite the fact
that variants in word medial position can never occur due
to the context of another word FUL expects asymmetric
acceptance: a labial or dorsal variant of an underlying
underspecified coronal would be tolerated but not vice
versa. For example, *wimmer will be accepted as a variant
of winner, but *tunny is an impossible variant of the word
tummy. Such an asymmetry also affects the rejection of
alternates as possible variants. The prediction would be
that variants like *tunny should be rejected as a word since
they conflict immediately with tummy. In contrast, it is
possible that *wimmer is more difficult to reject since it is
acceptable as a variant of the real word winner.
In the present experiment we tested the neurophysiologi-
cal validity of an underspecified lexicon with underspeci-
fied word medial coronal consonants, utilizing the high
temporal resolution of ERPs recorded in a lexical decision
task. Previous ERP research suggests that a specific nega-
tive ERP component, the N400, is sensitive to the time-
course of cognitive processes underlying word recogni-
tion. Since its first description [19], the N400 has not only
been correlated to aspects of semantic processing in sen-
tence and priming contexts, but also to single word
processing (see [20] for a review). The N400 pseudoword

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effect is characterized by larger and longer lasting negative
amplitudes for isolated spoken or written pseudowords as
compared to words, and is understood to reflect enhanced
lexico-semantic memory search for pseudowords that
have no lexical representation (e.g., [21-25]). Indeed,
using magnetoencephalograhpy (MEG) and magnetic res-
onance imaging, generators for the scalp-recorded N400
have been localized among others in the left temporal
lobe, comprising brain areas supporting long-term mem-
ory functions [26,27].
However, it appears as if ERP effects in the time course of
the N400 component reflect several temporally and cog-
nitively distinct processes [28]. In sentence context, pat-
terns of N400 amplitude change prior to and after the
minimum duration required to identify a word [29-32].
Even N400 amplitudes elicited by single words and pseu-
dowords diverge as a function of the amount of informa-
tion provided by the temporally unfolding speech signal
[33]. Words and pseudowords do not differ for the initial
N400 component, presumably because the speech signal
activates several alternatives in the listeners' mental lexi-
con. Different N400 patterns occur as soon as the signal
discriminates a pseudoword from all other entries in a
given language (deviation point). Therefore, only the ini-
tial part of the N400 pseudoword effect might be related
to normal fast word processing, whereas the later sus-
tained negativity for pseudowords might reflect subse-
quent top-down guided evidence checking.
In this study we presented spoken words and pseudoword
variants that differed only in their medial consonant,
which either had a coronal PLACE (/d/, /t/, /n/), or a non-
coronal PLACE (LABIAL: /b/, /p/, /m/; DORSAL: /g/, /k/;
see Figure 1 for an illustration of example stimuli).
According to the FUL model lexical representations of
words with word medial coronals like Horde ('horde')
have no word medial place represented in the lexicon. A
non-coronal variant like *Horbe cannot mismatch this
empty PLACE slot and therefore activates Horde. Although
CORONAL PLACE is not represented in the lexicon, this
feature can be perceived in the signal and can be used for
lexical mapping. For example, a coronal pseudoword var-
iant like *Prode mismatches the specified [LABIAL] PLACE
of the German word Probe 'test' and therefore cannot acti-
vate this word. If the assumption of underspecification
holds, lexico-semantic memory search processes would be
successful when a non-coronal variant is presented (first
activating the corresponding coronal target word), but not
when a coronal variant is presented (immediate correct
rejection as a non-existing lexical item). Thus, we expect
an asymmetry at least for the initial N400 pseudoword
effect, which most likely is related to lexico-semantic
processing. Related to the point in time where pseudow-
ords diverge from their respective words (deviation
points) initial N400 should be reduced for non-coronal
variants as compared to coronal variants.
Method
Participants
Sixteen (eight females, eight males) undergraduate stu-
dents from the University of Konstanz participated in the
experiment. All participants were native speakers of Ger-
man with no discernible uncorrected deficits in hearing.
Participants were paid for their participation or received
course credit points. Only right-handers were included, as
ascertained by the Edinburgh Handedness Questionnaire
[34].
Stimuli
Ninety familiar German disyllabic nouns, with a medial
stop or nasal consonant, and with stress on the first sylla-
ble were selected. Half of the words had a coronal conso-
Experimental ManipulationFigure 1
Experimental Manipulation. Examples of words (Above)
and pseudoword variants (Below) are illustrated by respec-
tive speech sounds (Upper) and spectropraphic displays
(Lower). Left: example for a presented coronal word (Horde
[Engl. horde]) and its non-coronal variant (*Horbe). Right:
Example for a presented non-coronal word (Probe [Engl.
test]) and its coronal variant (*Prode).

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nant and the other half a non-coronal consonant as onset
of the second syllable. A pseudoword with the opposite
medial PLACE feature was formed for each word. Fre-
quency of coronal and non-coronal words was matched
using an on-line dictionary of German [35].
As neighborhood density is known to modify N400
amplitudes [36], we determined phonological neighbors
of the words and pseudowords by using the CELEX data-
base [37]. A neighbor is any word which differs from the
stimulus by replacing, deleting or adding one phoneme in
any position (cf. [38]). Only monomorphemic, disyllabic
neighbors with stress on the first syllable were included. A
two-way ANOVA with repeated measures factors Lexical
Status (words vs. pseudoword variants), and Coronality
(coronal words, and their variants vs. non-coronal words
and their variants) only revealed a significant effect of Lex-
ical Status [F(1,44) = 32.41, p < .001]. Words had on aver-
age 3.4 (S [tandard] D [eviation] 2.6) neighbors,
pseudoword variants had 2.2 (SD = 1.8) neighbors.
Neighborhood density did not differ for coronal words
(M [ean] = 3.4, SD = 2.3) and non-coronal words (M =
3.4, SD = 2.8) [t(44) = 0.01, n.s.], nor for coronal pseu-
dowords (M = 2.4, SD = 2.0) and non-coronal pseudow-
ords (M = 2.0, SD = 1.6) [t(44) = 0.84, n.s.].
All words and pseudowords were spoken by a male native
speaker of German in a sound attenuating chamber. The
speaker was naïve with respect to the experimental manip-
ulation and the hypotheses of the study. He read the stim-
uli in a fluent style from lists in which a word was
immediately followed by the respective pseudoword vari-
ant. The speaker was instructed to pronounce the variants
in the same way as the words. Stimuli were recorded on a
DAT recorder at a sampling rate of 44.1 kHz using a high
quality microphone. The recordings were then transferred
to a computer, the volume equalized, and edited into
individual tokens using the Cooledit 2000 waveform
manipulation software package. Where possible, single
periods of voiced speech sounds were deleted from either
the word or the variant to equalize the duration of the
stimuli. This resulted in the same mean length of coronal
words and their non-coronal pseudoword variants (M =
678 ms, SD = 97 for both), and of the same mean length
for non-coronal words and their coronal pseudoword var-
iants (702 ms, SD = 102 for both).
Uniqueness points of the words and deviation points of
the pseudowords were established using the CELEX lexical
database [37]. Scanning from left to right, we determined
the first phoneme of the words that made them unique
with respect to all other entries in the CELEX database,
and also the first phoneme of the pseudowords that made
them distinguishable from any monomorphemic, disyl-
labic, first-syllable stressed word in the database. For 40
non-coronal words, 40 coronal words, 41 non-coronal
pseudowords, and 40 coronal pseudowords this unique-
ness or deviation point was the phoneme for which the
Neurophysiological results time-locked to word onsetFigure 2
Neurophysiological results time-locked to word onset. (A) plots the grand average ERPs for non-coronal words (blue
lines) and coronal pseudoword variants (magenta lines) for selected electrode sites. (B) shows the grand average ERPs for
coronal words (black lines) and non-coronal pseudoword variants (red lines) for selected electrode sites. For illustration pur-
poses only ERPs were low-pass filtered (20 Hz).

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place of articulation was manipulated. For the remaining
4 to 5 stimuli per group the uniqueness/deviation pho-
neme appeared later in the word. Next, the onset of the
deviating phonemes, which was the onset of the closure
period for plosives and the onset of the first period for
nasals, was determined in the acoustic signal. Mean
uniqueness points were 335 ms (SD = 107) for coronal
words and 366 ms (SD = 104) for non-coronal words.
Mean deviation points were 355 ms (SD = 98) for coronal
pseudoword variants and 322 ms (SD = 104) for non-
coronal pseudoword variants. These uniqueness and devi-
ation points were used to adjust the ERP and behavioral
data.
Procedure
Sintered silver-silver chloride electrodes were held in place
on the scalp with an elastic cap (EASY Cap). Scalp loca-
tions included 62 standard International 10–10 system
locations. Two additional electrodes to control for eye
movements were placed below both eyes. All electrodes
were online referenced to Cz. The data were re-referenced
offline to the algebraic average of the left and the right
mastoids. All electrode impedances were less than 5 KΩ.
The electroencephalogram (EEG) was recorded with a
sampling rate of 250 Hz.
Subjects sat in a sound attenuated booth and made
speeded lexical decisions to stimuli presented at a com-
fortable listening level (Sony loudspeakers). A trial started
with a fixation point presented in the center of a computer
screen. 200 ms after the onset of the fixation point a spo-
ken stimulus was presented. The fixation point remained
throughout the spoken stimulus and was terminated with
the subject's response. Subjects were told not to blink and
to look at the fixation point as long as it appeared on the
screen. Following the fixation point there was a 1500 ms
blank screen intertrial-interval. Subjects were told they
could blink during this interval. Half the subjects made
yes-responses with the thumb of their left hand and no-
responses with the thumb of their right hand. For the
remaining subjects, the response hands were reversed.
Speed and accuracy were stressed equally. Subjects were
given a break after half of the trials.
Data analysis
Error rates were calculated for all stimuli. Reaction times
and ERPs were only calculated for correctly responded tri-
als. Eye blinks and movements were systematically
recorded from each subject before the experimental task
started. Characteristic scalp topographies of eye artifacts
were corrected from the experimental data using Brain
Electrical Source Analysis (BESA;
®
MEGIS Software
GmbH). Word onset ERP data were quantified by calculat-
ing the mean amplitudes (relative to a 200 ms prestimulus
baseline) in a latency window between 500 and 1000 ms
(N400 pseudoword effect). ERPs time-locked to unique-
ness and deviation points were quantified by calculating
the mean amplitudes (relative to a 200 ms pre uniqueness
and deviation point baseline) in two latency windows
(early N400 pseudoword effect: 100–250 ms; late N400
pseudoword effect: 250–750 ms) according to 50 ms
time-step analyses (see 3C).
As there were virtually no interhemispheric effects, two
regions of interest (ROIs) each including 20 lateral and
midline electrode positions were defined. An anterior ROI
included electrodes AF7, AF3, AFz, AF4, AF8, F5, F1, Fz,
F2, F6, FC3, FC1, FCz, FC2, FC4, C5, C3, Cz, C4 and C6;
a posterior ROI included electrodes CP5, CP3, CP1, CPz,
CP2, CP4, CP6, P7, P3, P1, Pz, P2, P4, P8, T7, TP7, TP8,
T8, PO1 and PO2. Two factors entered the repeated meas-
ures ANOVAs for behavioral data: Lexical Status (words vs.
pseudoword variants), and Coronality (coronal words, and
their variants vs. non-coronal words and their variants).
An additional repeated measures factor Region (anterior
vs. posterior electrode leads) was included in the ANOVA
with the mean ERP amplitudes as the dependent variable.
Scalp topographies were generated using BESA.
Results
Behavioral results
Mean reaction times from stimulus onset and from
uniqueness/deviation points as well as error rates are
shown in Table 1. Starting from stimulus onset subjects
needed 976 ms to correctly identify words, and 1003 ms
to correctly reject pseudoword variants. As shown by the
main effect of Lexical Status [F(1,15) = 27.64, p < .001] this
difference was statistically significant. A main effect of
Coronality [F(1,15) = 17.84, p < .001] indicated that
responses were faster for coronal words and their respec-
tive pseudoword variants than for non-coronal words and
their pseudoword variants. This might well be caused by
the longer duration of the former as compared to the latter
stimuli (see Methods section). Factors Lexical Status and
Coronality did not interact [F(1,15) = 0. 05, n.s.].
In order to control for different word lengths across both
Coronality conditions, individual uniqueness points were
subtracted from individual reaction times to words and
deviation points were subtracted from reaction times to
pseudowords. After this correction, only the main effects
of Lexical Status remained significant [F(1,15) = 39.79, p <
.001]. Words were identified 615 ms after their unique-
ness point, pseudoword variants were identified 674 ms
after their deviation points. The interaction of Lexical Sta-
tus and Coronality remained to be not significant [F(1,15)
= 0.03]. It took subjects the same time to reject coronal or
non-coronal pseudowords after the appearance of their
respective deviation points.

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Neurophysiological results time-locked to uniqueness and deviation pointsFigure 3
Neurophysiological results time-locked to uniqueness and deviation points. (A) plots the grand average ERPs for
non-coronal words (blue lines) and coronal pseudoword variants (magenta lines) for selected electrode sites. (B) shows the
grand average ERPs for coronal words (black lines) and non-coronal pseudoword variants (red lines) for selected electrode
sites. (C) illustrates ERPs for all four experimental conditions for a representative electrode lead and summarizes outcomes of
50 ms time-steps analyses. Time windows yielding significant effects or trends (p < .10) of the factor Lexical Status (Lex.) or
interactions of Lexical Status and Coronality (Lex. X Cor.) are indicated by an asterisk. (D) shows subtraction waves (variant-
word) and respective scalp topography maps (180 ms after the uniqueness/deviation points). Across (A), (B) and (D) the part
of the N400 pseudoword effect that is sensitive to different PLACE mismatches, is highlighted in light grey. For illustration pur-
poses only ERPs were low-pass filtered (20 Hz).
AF3
AFz
AF4
F1
Fz
F2
CP1
CPz
CP2
P1
Pz
P2
AF3
AFz
AF4
F1
Fz
F2
CP1
CPz
CP2
P1
Pz
P2
-5 µV
5 µV
-200 400 800ms
non-coronal word
coronal variant
-200 400 800ms
-5 µV
5 µV
coronal word
non-coronal variant
FCz
-5 µV
-200 200 400 600 800 ms
Lex.
Lex. x Cor.
***
**
*
**
**
*
*
*
*
A
B
C
D
Fz
FCz
-200 400 800ms
2.5 -2.5 µV
coronal variant -
non-coronal word
-2 µV
2 µV
non-coronal variant
- coronal word
Table 1: Summarized in this table are mean reaction times (RT) in ms from stimulus onset and from uniqueness/deviation points (UP/
DP), and error rates in percent for all conditions (with standard deviations).
RT Error Rates
Stimulus Onset UP/DP
Noncoronal words 980 (98) 613 (97) 6.7 (4.3)
Coronal variant 1026 (125) 671 (125) 2.2 (2.1)
Coronal words 951 (96) 616 (95) 7.5 (4.8)
Non-coronal variant 1001 (107) 676 (107) 4.9 (3.1)

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Analysis of error rates revealed that speeded responses to
words were associated with lower accuracy. Subjects made
7% errors for words and 3.5% errors for pseudoword var-
iants [F(1,15) = 13.51, p < .01]. Furthermore, a main effect
of Coronality was observed for error rates [F(1,15) = 5.23 p
< .05]. Subjects made more errors for coronal words and
their variants (6.1%, SD = 4.2) than for non-coronal
words and their variants (4.4%, SD = 4.0). No significant
interactions of Lexical Status and Coronality were observed
for reaction times or error rates [F(1,15) = 1.41, n.s.].
ERPs time-locked to stimulus onset
The ERP grand mean waveforms time-locked to the onsets
of words and pseudoword variants for selected anterior
and posterior electrode sites are plotted in Figure 2. For all
the ERPs, the first visible component was a negative-going
deflection peaking at 130 ms after stimulus onset (N1).
This was followed by a positive deflection occurring at
approximately 200 ms (P2). Starting at 300 ms a broad
negativity was observed, which was enhanced for pseu-
doword variants as compared to words and is henceforth
referred to as the N400 pseudoword effect. Additionally, a
late positivity ranging between 600 and 1500 ms was
observed for posterior electrode leads. A time window
ranging from 500 to 1000 ms was used to further establish
the N400 pseudoword effect time-locked to stimulus
onset.
Time window 500 to 1000 ms
Significant main effects for the factors Region [F(1,15) =
46.46, p < .001] and Lexical Status [F(1,15) = 8.21, p = .01]
were observed in the time window of the N400 pseudow-
ord effect time-locked to stimulus onset. ERPs were more
negative for frontal electrode leads than for posterior elec-
trode leads, and more negative for pseudowords than for
words. An interaction of the factors Lexical Status and
Coronality did not reach significance [F(1,15) = 2.75, p =
.11].
Overall, an N400 pseudoword effect could be established
in the present experiment. However, temporal analysis of
this effect has to consider different uniqueness and devia-
tion points within and across conditions. Next we
adjusted the N400 pseudoword effect to the point in time
where differences between the words and their respective
pseudoword variants occurred in the acoustic signal.
ERPs time-locked to uniqueness and deviation points
The ERP grand mean waveforms time-locked to the
uniqueness points of the words and to the deviation
points of the pseudoword variants for selected anterior
and posterior electrode sites are plotted in Figure 3. The
ERPs zoom into the N400 effect and the posterior positiv-
ity. 50 ms time-steps analyses suggest an earlier differenti-
ation of N400 effects for coronal and non-coronal
pseudowords (see Figure 3C). A time window ranging
from 100 to 250 ms was analyzed to investigate the early
pseudoword N400 effect for ERPs adjusted to uniqueness
and deviation points. The later N400 effect was analyzed
in a time window ranging from 250 to 750 ms.
Time window 100 to 250 ms
Early N400 amplitudes showed a main effect of Region
[F(1,15) = 8.46, p = .02], which did not interact with any
other factor. ERPs were more negative over posterior than
over anterior electrode leads. Crucially, an interaction of
the factors Lexical Status and Coronality licensed differenti-
ation of coronal and non-coronal pseudoword effects
[F(1,15) = 6.22, p = .02]. Mean amplitudes for coronal
pseudoword variants were more negative than mean
amplitudes for their non-coronal base words [t(15) =
6.19, p = .02]. By contrast, ERPs for non-coronal variants
did not differ from their base words in this initial part of
the N400 pseudoword effect [t(15) = 0.26, n.s.]. Further-
more, a significant difference between both types of pseu-
doword variants [t(15) = 12.21, p < .01] but not between
both types of words [t(15) = 0.23, n.s.] relates this early
ERP deflection to mismatch detection in the case of coro-
nal pseudowords.
Time window 250 to 750 ms
Significant main effects for the factors Region [F(1,15) =
98.42, p < .001] and Lexical Status [F(1,15) = 11.66, p <
.01] were observed in the second time window of the ERPs
time locked to uniqueness and deviation points. ERPs
were more negative for frontal electrode leads and more
positive for posterior electrode leads. No interaction effect
reached significance revealing that both types of pseudow-
ord variants were differentiated in a same way from their
respective base words in the later time window of the
N400 pseudoword effect.
Discussion
This paper examined neurophysiological correlates of
spoken word identification, by means of ERPs recorded
during a lexical decision task. The question we asked was
how the recognition system copes with pseudowords that
differ only slightly from existing words, namely in word
medial place of articulation (PLACE). Assuming an under-
specified coronal PLACE, we predicted asymmetric effects
for pseudowords being either coronal or non-coronal var-
iants. In accordance with our hypotheses the N400 pseu-
doword effect starts earlier for coronal than for non-
coronal pseudowords.
Our results support assumptions of the FUL model of spo-
ken word recognition [2-4]. In this model coronal words
are proposed to have an empty feature value slot for
PLACE in the mental lexicon. Even though a LABIAL or
DORSAL PLACE is extracted from non-coronal pseudow-

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ords they can activate lexical representations of coronal
words (i.e. *Horbe can activate Horde). Hence, non-coro-
nal pseudowords ought to behave like words at the initial
activation period. The opposite hypothesis prevails for
non-coronal words. FUL assumes that non-coronal entries
have PLACE specified. Coronal variants, for which a
CORONAL PLACE is extracted from the signal, cannot
activate non-coronal words (i.e., *Prode cannot activate
Probe). That is, coronal variants should be regarded as
nonwords earlier than non-coronal variants. In line with
these assumptions, coronal variants elicited an earlier
N400 pseudoword effect than non-coronal variants.
The fact that it took subjects the same time to reject both
types of pseudoword variants, together with the finding
that pseudoword rejection took longer than word accept-
ance, point to a process that detects pseudowords and
guides responses in the lexical decision task independ-
ently of initially asymmetric lexical activation. The present
ERP results also provide evidence for an additional proc-
ess in the lexical decision task. Both types of pseudoword
variants elicited enhanced negativity in a later time win-
dow of the N400 pseudoword effect. The FUL model may
account for this later ERP effect and for the behavioral
results by assuming phonological parsing mechanisms
that are independent of initial lexical activation [4]. One
could surmise that a post-lexical mechanism rejects both
coronal and non-coronal pseudoword variants. Whether
this evidence checking operation is mandatory in spoken
word recognition or whether it is especially recruited to
solve the lexical decision task has to be clarified in future
research.
A separation of lexical and post-lexical processing in the
N400 time window has already been suggested in previ-
ous ERP research on speech recognition. Specifically it has
been argued that pseudowords undergo some additional
post-lexical processing that is reflected in the sustained
N400 pseudoword effect [33,39]. Similarly it has been
shown that negative going ERP effects in spoken sentence
comprehension are at least two-fold [29-32]. An early neg-
ativity starting 150 ms after word onset is equally reduced
for words that fit into the semantic context of a spoken
sentence (e.g., She illuminated the dark room with her can-
dle.), as well as for words that semantically do not fit into
a spoken sentence context, but match the initial pho-
nemes of the fitting word (e.g., She illuminated the dark
room with her candy.). Only later, starting at 300 ms,
semantically acceptable words diverge from those that
had initial phoneme overlap. Hagoort and coworkers
argue that the early interaction of word-form and content
information is related to ongoing lexical selection,
whereas the later N400 effect is associated to semantic
integration of selected candidates.
In sum, we separate an early from a later part of the N400
pseudoword effect. Integrating current and previous ERP
findings we conclude that the initial part of the N400
pseudoword effect closely relates to lexical activation pat-
tern in spoken word recognition. We argue that the asym-
metry of this effect reflects that pseudoword variants can
only activate underspecified cortical word form represen-
tations in the listeners' mental lexicon. The early onset of
the N400 pseudoword effect (100 ms after the deviation
point) might reflect that PLACE information is already
exploited at the vowel that precedes the deviating pho-
neme [40]. Crucially, however, the early onset of the
N400 pseudoword effect for coronal variants suggests that
the CORONAL PLACE is immediately used to prevent lex-
ical activation of non-coronal words.
Our findings add important arguments on theoretical
accounts to spoken word recognition. First, the early
asymmetric N400 pseudoword effect challenges context
based models of assimilated speech recognition [5,6,8-
10]. The fact that the pseudoword N400 effect for coronal
variants starts 100 ms after the onset of the coronal speech
sound reveals that initial lexical activation does not wait
until contextual information is available. Second, asym-
metric lexical activation is observed for the first time in
pseudowords created by replacing medial consonants in
monomorphemic words. Such pseudowords cannot be
the result of regular assimilation patterns with final con-
sonants like green bag > *gree [m] bag, and thus listeners
are never exposed to such variants. That is, there could be
no variant exemplars stored for medial stops and nasals,
and therefore an exemplar based model (e.g. [41]) cannot
account for the observed asymmetry. Third, asymmetric
pseudoword effects for coronal and non-coronal pseu-
dowords cannot be captured by models of spoken word
recognition that assume that all segments, usually pho-
nemes, equally contribute to lexical activation (e.g., [42-
44]). The fact that we have observed different ERP effects
for coronal and non-coronal pseudowords, which start
immediately after the deviation is present in the signal
and which are in the direction proposed by the FUL
model, supports our assumption that underspecification
is a basic principle of the functional organization of the
mental lexicon.
Conclusion
The FUL model of spoken word recognition [2-4] pro-
vides excellent theoretical underpinning for the discovery
of neurophysiological mechanisms underlying human
speech comprehension. Former studies showed that pho-
nological features are extracted early from the signal and
that cortical representations of speech are based on those
features [45-47]. Furthermore, the asymmetric mapping
of features onto specified and underspecified cortical
vowel representations has been established in a previous

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ERP study that used an MMN paradigm [18]. The present
findings are in accordance with this line of neurophysio-
logical evidence. Using a different ERP component and
more complex linguistic stimuli, the present study sup-
ports the notion of specified and underspecified cortical
word form representations and an asymmetric mapping
of features extracted from word medial positions onto
those lexical representations.
Authors' contributions
CF designed and conducted the study, analyzed the ERP
data, and wrote the initial drafts. CE contributed to the
ERP analysis. AL provided the theoretical background. All
authors contributed to the selection of the stimulus mate-
rials, experimental design and worked on the manuscript.
Acknowledgements
This research was supported by the Leibniz science prize and a grant from
the Ministry of Science, Research, and the Arts of Baden-Württemberg
awarded to Aditi Lahiri, and by grants from the Deutsche Forschungsgemein-
schaft (SFB 471 and FOR 348) to Aditi Lahiri and Carsten Eulitz. We are
much obliged to Verena Felder and Barbara Awiszus for help in data acqui-
sition.
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