Dual-Coding,
Context-Availability, and Concreteness Effects in Sentence Comprehension: An
Electrophysiological Investigation
Phillip J. Holcomb
Tufts
University
John Kounios
University
of Pennsylvania
Jane E. Anderson
Harvard
Medical School
W. Caroline West
MGH
Event-related potentials were
recorded in two experiments while participants read sentences in a word-by-word
congruency judgment task. Sentence final words were either congruent,
semantically anomalous (Experiments 1 and 2) or neutral (Experiment 2) with
respect to sentence context. Half of all final words referred to concrete and
half to abstract concepts. A different scalp distribution of the N400 to
concrete and abstract final words was found for anomalous and neutral, but not
congruent sentences. While the interaction of context and concreteness is
consistent with context-availability model, the differential scalp distribution
of effects for concrete and abstract words, as well as larger context effects
for concrete words was interpreted as being more consistent with an extended
dual-code account of semantic processing.
Theories of how knowledge is stored and processed in the brain have
generally fallen into one of two camps.
The first proposes that all meanings for objects, events, and concepts
are stored and processed by a common a-modal semantic system (e.g., Caramazza,
Hillis, Rapp, & Romani, 1990; Gernsbacher, 1985; Kroll & Potter, 1984; Pylyshyn, 1984). Conversely, the second
class of theories posits that multiple semantic systems independently store and
process semantic information, often redundantly (e.g., Paivio, 1971, 1986,
1991; Shallice, 1988, 1993).
A salient example of this
distinction, and the focus of the present study, has been the debate over the
origin of concreteness effects, which is the observation that words
representing concrete concepts (e.g., table) are processed more quickly and
accurately than words representing comparatively abstract concepts (e.g.,
aptitude). Unfortunately, in spite of
the relative consistency of the experimental findings, there has been
considerable disagreement concerning the source of concreteness effects, the
two major theoretical contenders being dual-coding theory and the context-availability
model (see reviews by Paivio, 1991; Schwanenflugel, 1991).
Dual-coding theory
Dual-coding theory (Paivio, 1986, 1991)
explains concreteness effects by recourse to modality-specific systems for
representation and processing.
According to this theory, a variant of the multiple semantic-systems
view, concrete words are associated with information stored in both a verbal
“linguist” semantic system as well as a nonverbal “imagistic” semantic system.
Abstract words, however, are associated primarily with information stored in
the linguistic system. When one
encounters a concrete word it initially activates linguistic information, but
shortly thereafter it also begins to activate imagistic information via
referential links that interconnect the linguistic and image systems. Abstract words, on the other hand, lack or
have many fewer referential connections between systems and predominantly
activate linguistic representations. Concrete
words have distinct processing advantages over abstract words because they have
access to information from multiple systems. So, for example, in a lexical
decision task participants can classify “hand” as a word faster than
“idea” because “hand” is processed and
represented in both systems while “idea” is processed/represented only in the
linguistic system. This additional semantic activity from dual systems allows
participants to quickly differentiate concrete words from pseudowords
(pseudowords presumably generate little semantic activation). The relatively
lower semantic activity from a single system makes abstract words more
difficult to differentiate from pseudowords resulting in relatively slower
reaction times (RT).
Context-availability model
In contrast, the
context-availability model (Bransford & McCarrell, 1974; Kieras, 1978)
denies the existence of different types of informational codes or processing
systems as determinants of concreteness effects. This theory, a variation of the single semantic-system view,
argues that comprehension is heavily reliant on context supplied by either the
preceding discourse or the comprehender’s own mental knowledge base (semantic
memory). Concrete words are thought to
be more closely associated to relevant “contextual” knowledge in semantic
memory than are abstract words, because concrete words exhibit stronger or more
extensive associative links to this stored material. However, the underlying
nature of the representations for the two word types and the processes that
operate on these representations do not differ according to this account. So,
participants can classify “hand” as a word faster than “idea” because “hand”
activates more semantic information. Where context-availability differs from
dual-coding is in how and where this additional information is stored and
processed. Context-availability argues for a simpler quantitative difference
between word types within a single system, while dual-coding argues for a
qualitative difference based on activity in different systems.
Numerous studies have sought
to empirically invalidate one or the other of these explanations (Paivio, 1986,
1991; Schwanenflugel, 1991).
Unfortunately, many of these experiments exhibit what hindsight suggests
to be methodological and theoretical limitations. At least in the realm of semantic processing (the focus of this
report), neither view can claim, based on previous findings, to be the complete
explanation of concreteness effects. Below, we briefly discuss some of the
relevant research supporting both accounts. Following this, we describe a
paradigm and methodology designed to circumvent some of the difficulties
inherent in previous studies with the aim of providing data capable of
discriminating between the competing theories.
Context and Concreteness
Schwanenflugel
and her colleagues have been the most outspoken proponents of the
context-availability interpretation of concreteness effects in semantic
processing (e.g., Schwanenflugel, Harnishfeger, & Stowe, 1988;
Schwanenflugel & Shoben, 1983; Schwanenflugel & Stowe, 1989; Schwanenflugel,
1991). They have presented two sources of evidence which they argue favor this
model. First, Schwanenflugel and colleagues (e.g., Schwanenflugel, &
Shoben, 1983; Schwanenflugel, et al., 1988) found that participants’ estimates
of the relative difficulty of retrieving associated contextual information for
isolated abstract and concrete words (context availability ratings) were
correlated with concreteness ratings. Moreover, they found that these context
availability ratings were a better predictor of lexical decision performance
than rated concreteness or imageability. When concrete and abstract words were
equated on this factor, the advantage normally seen for concrete words was no
longer significant. However, one potentially serious problem with these studies
is that it is not clear how participants actually made context-availability
ratings. In particular, the authors of these studies apparently did not check
to see if participants might have sometimes used some type of imagery strategy.
For example, it might be that for concrete words and even some abstract words
that many participants used mental images to help determine how easy or how
many different contexts a word can be used in. Thus partialing out rated
concreteness might have missed an important residual dimension of concreteness
or imagery. To eliminate this
possibility participants’ actual generated contexts would have to be monitored
and controlled for image based intrusions.
In a second series of
experiments Schwanenflugel and colleagues (e.g., Schwanenflugel, Harnishfeger,
& Stowe, 1988; Schwanenflugel & Shoben, 1983; Schwanenflugel &
Stowe, 1989) have more convincingly demonstrated that when sufficient
supportive context is provided, either in the form of several or even a single
prior sentence, concreteness effects on accuracy and RT diminish or even vanish
in a variety of tasks including lexical decision, naming and sentence
meaningfulness judgments. This effect takes the form of context producing large
changes in performance on abstract items and little or no change in performance
on concrete items. Schwanenflugel and colleagues argue that this implies that
concreteness effects are reducible to differences in the availability of
context.
In other words, when abstract words are provided with an external
context, such as a supportive sentence stem, of equivalent potency to that
normally available to concrete words from within semantic memory, then they are
processed as efficiently as concrete words. Concrete words do not benefit as
much from an external context because they already have strong built-in
contexts, so an external context does little to change how these items are
processed. Therefore, according to this
view, there is no need to postulate a more architecturally complex separate
system for representing and processing imagistic information.
We believe that the above
conclusion may be premature. This is because the basic dual-coding theory as
proposed by Paivio (1984) does not argue that context cannot facilitate semantic
processing, nor does it argue that such contextual facilitation could not
supersede or mask concreteness effects.
It simply states that there are separate imaginal and linguistic
systems, and that the consequences of this structural configuration can sometimes
be manifested in behavior. With minor augmentation dual-coding theory could be
made to account for context effects such as those reported by Schwanenflugel
and colleagues, while retaining its central feature of multiple systems. One
possibility is that a supportive sentence frame works by “priming” relevant
sentence final words (e.g., Stanovich and West, 1983). The resulting semantic
facilitation within the linguistic system may be sufficient to overcome the
added benefit concrete words normally exhibit in isolation due to referential
processing via the imagistic system.1 This could happen, for
example, because context works faster or earlier than concreteness.
Note that at one level the
above explanation is actually very similar to that offered by
context-availability; external context compensates for richer/stronger internal
associations via priming in the linguistic system. However, upon closer
inspection the two theories remain quite distinct. While context availability
argues that the biggest effects of linguistic context should occur for abstract
words, context-extended dual-coding predicts similar effects of linguistic
context for abstract and concrete words within the verbal system. However, it
also predicts larger effects of context for concrete than abstract words
within the imagistic system. We will return to the discussion of the
predictions of each model in the Discussion section, but for now, suffice it to
say that the finding of a context by concreteness interaction does not
constitute evidence against the existence of multiple systems. Rather it simply
implies that there are two different factors that affect one or more processing stages in common (McClelland, 1979; Sternberg, 1969). If this is true, then one of the major
tenants of the context-availability
critique of dual-coding research would be rendered nugatory.
Event-Related Potentials
The ERP technique involves
measuring the brain's electrical activity (electroence-phalograms or EEGs)
detectable by scalp electrodes after specific stimulus events. These individual EEG waveforms are then
averaged across stimulus presentations to yield a waveform characterizing the
measurable part of the brain's electrical response to the stimulus (i.e., minus
the "noise" representing other brain activity). Researchers have linked the various
components (roughly the peaks) in the ERP waveform to a number of cognitive
processes (see Coles & Rugg [1995] for a recent introduction and review).
The ERP component of most
interest for present purposes is the N400, which is a negative-going wave
peaking at approximately 400 ms after the onset of a stimulus. Numerous studies
have implicated the N400 in some aspect of semantic processing. For example, Kutas and Hillyard (1980,
1984), in what is now the classic N400 paradigm, were the first to show that
this component is larger in amplitude in response to sentence final words that
are semantically anomalous (e.g., "He takes cream and sugar in his attention."),
and is greatly reduced or even absent to high probability congruent sentence
endings (e.g., "He takes cream and sugar in his coffee."). In contrast, the N400 has been shown to be
unaffected by physically anomalous but semantically congruent stimuli (e.g., a
congruent final word in a different type font). Subsequent studies revealed
that semantic anomalies throughout a sentence elicit N400s (e.g., Kutas &
Hillyard, 1983) as do anomalies occurring in sentences presented at very rapid
rates (up to 10 words/sec, Kutas, 1987).
An important study by Kutas,
Lindamood, and Hillyard (1984) showed that robust N400s could be obtained
without the occurrence of a semantic anomaly and that under these conditions
its amplitude is a monotonic, decreasing function of the cloze probability of
the final words of sentences. For
example, N400 amplitude was large in amplitude to less predictable, but
non-anomalous words (e.g., "Captain Sheir wanted to stay with the sinking raft.")
and was smaller in response to more predictable words (e.g., "She called
her husband at his office."). Based on findings such as these and
others it has been argued that the N400 reflects the process of integrating
semantic information into a relatively high level discourse or mental model
type of representation (e.g., Brown & Hagoort, 1993; Holcomb, 1993). In
this formulation larger N400s are taken as being indicative of a more effortful
or involved integration process. A common thread in virtually every account of
the N400 is that it is sensitive to contextual and semantic manipulations which
would appear to make it an ideal choice of dependent variables for use in
searching for the locus of interactions between concreteness and
context-availability.
Experiment 1
Kounios and Holcomb (1994)
demonstrated that ERPs are sensitive to concreteness, particularly when the
task involves deep semantic processing. Specifically, concrete words presented
in a list elicited a more negative ERP between 300 and 500 ms after stimulus
onset than did abstract words, and this difference was larger in a semantic categorization
task (Experiment 2) than in a lexical decision task (Experiment 1). This
suggests that the effects were at least partially mediated by semantic
properties of the words. The ERP
negativity coincided temporally with the classic N400, although the topographic
distribution of the concreteness effect differed from the typical N400 effect
in that it was maximal at anterior scalp locations, whereas the typical N400
effect tends to be centro-parietal (e.g., Kutas & Van Petten, 1988). However, more “anterior N400” distributions
have been observed previously in single-word tasks (e.g., Boddy, 1986; Nobre
& McCarthy, 1994) and in picture-processing tasks (e.g., Holcomb &
McPherson, 1993; Ganis, Kutas, & Sereno, 1996; McPherson & Holcomb, in
press). The most likely explanation for these differing distributions is that
the N400 is actually the product of several underlying neural generators whose
weights vary according to task demands and stimulus properties (Kounios, 1996;
Nobre & McCarthy, 1994). In other
words, the N400 probably does not reflect a unitary process, but rather several
functionally related, but neurally distinct ones. Regardless of whether this or
some other explanation of the differing scalp distributions for the N400 is
correct, the differential scalp distributions of ERPs reported by Kounios and
Holcomb (1994) for concrete and abstract words suggests the involvement of
non-identical neural and cognitive processing systems, which if correct, would
be inconsistent with single-code theories such as the context-availability
model.
The logic of the above
conclusion is based on what we will call the “spatial distinctiveness
principle”, which assumes that two or more different cognitive systems will
tend to be more spatially distinct within the brain than will a single
cognitive system. For example, if concrete and abstract words activate the same
basic cognitive processes and/or representations (a common semantic system)
then, on average, the same population of neurons should be active when these
two types of words are processed and these neurons should produce, on average,
a similar spatial pattern of electrical activity for both types of events. With
electrodes placed on the scalp this activity should show up as a difference in
the size of potentials (i.e., a significant main effect of word type), but not
in a difference in the distribution of potentials across the scalp (i.e., an
absence of a word type by scalp site interaction) . If, however, the two types
of words influence somewhat different cognitive processes/representations
(separate semantic systems) then, on average, somewhat distinct populations of
neurons should be active when these two types of events are processed and these
different populations should produce electrical activity with different scalp
distributions (a word type by scalp site interaction).
The spatial distinctiveness
principle is quite robust and, in theory, can differentiate between a variety
of possible neural organizations.2 For example, a single system
which encompasses an expansive cortical area or even multiple areas could be
differentiated from separate systems with equivalent spatial distributions.
This is because a large or multi-area single system need only be spatially
homogeneous with respect to the factor of interest. Such a single large system
would produce main effects for differences in strength of activity due to the
factor of interest (e.g., word type) that extend across a relatively wide
region of scalp, but no interaction between factor and site. Separate systems
of equivalent spatial distribution would produce the factor by site
interaction. This logic works for much smaller brain regions as well, although
an adequate number of electrodes placed close enough together to differentiate
the systems is necessary.
Another important finding in
the Kounios and Holcomb study was that repetition had a greater effect on the
ERPs to concrete than abstract words.
Furthermore, large repetition effects (decreased N400 amplitude to repeated
words) were observed over both hemispheres in both experiments for concrete
words, but were not observed for abstract words in Experiment 1 and only over
the left hemisphere in Experiment 2.
These results are in direct contrast with the context-availability model
which predicts that added context (in this case in the form of repetition)
should make a bigger difference in the processing of abstract words than
concrete words (Schwanenflugel & Shoben, 1983). This finding could be
interpreted as being consistent with the context-extended dual-coding theory
described above. This model predicts similar effects of linguistic context for
concrete and abstract words within the linguistic system, and larger effects of
context for concrete than abstract words within the imagistic system.
The authors did, however,
acknowledge some caveats concerning the interpretation of their results. First, the repetition effects reported in
Kounios and Holcomb may not have tapped the same type of contextual processes
as the sentence level context effects studied by Schwanenflugel and colleagues
(e.g., Schwanenflugel & Shoben, 1983).
Second, the frontal 300-500 ms negativity that differentiated concrete
and abstract words may not have been a “true” N400 effect (neither of the tasks
used by Kounios & Holcomb were the classic N400 paradigm) and thus may
reflect something other than semantic processing (see Neville, Kutas, Chesney,
& Schmidt, 1986).
The present study was an
attempt to address both of these issues and to replicate the word type by scalp
site interaction that Kounios and Holcomb interpreted as evidence for
dual-coding theory and against the context-availability model. To ensure that effects of context were being measured, a sentence
processing task was utilized rather than a single word task. Furthermore, to
ensure that what was being observed was, in fact, an N400, the classic
anomalous sentence paradigm used to elicit an N400 response (Kutas &
Hillyard, 1980) was employed.
Sentences in which the final
word was either congruent or incongruent (anomalous) were presented to
participants whose task was to decide if each sentence made sense. In the present experiment, the concreteness
of the sentence final words was manipulated in addition to their congruency, thus,
it was designed to examine effects of both concreteness and context. The design is much like one used by
Schwanenflugel and Stowe (1989) in which they found clear differences in
meaningfulness-judgment RTs between concrete and abstract items when these
words formed an anomalous ending of a sentence (concrete faster than abstract),
but no differences in RT when the two word types were congruent final words.
They interpreted this finding as further evidence for the context-availability
model.
The results of Kounios and
Holcomb (1994) suggest the following predictions with regard to ERPs in the
current experiment. First, concrete words should produce ERPs which are more
negative going between 300 and 500 ms (the N400 window) than abstract words.
Second, this difference should be due, at least in part, to the modulation of
the traditional N400 component, which should be revealed by an interaction
between context (a variable known to influence the N400) and concreteness.
Third, supporting the dual-code model, but not the context-availability model,
the distribution across the scalp of the context sensitive N400 effect should
be different for concrete and abstract words. Fourth, consistent with extended
dual-coding theory, but not with the context-availability model, the biggest
effects of context on the N400 should be for concrete words.
Method
Participants. Sixteen students (9 female, 7 male) between 18 and 20 years
(mean: 18.63) of age from the Tufts University community served as
participants. All were right-handed
native speakers of English with normal or corrected-to-normal visual acuity.
Stimuli and procedure. The stimuli for this experiment were 160 sentences, 80 of which
ended in an abstract word (mean concreteness rating: 2.52), the remaining 80 of
which ended in a concrete word (mean concreteness rating: 6.19). The sentences for the two final-word types
did not differ in cloze probability (concrete: .61 (SD .22), abstract: .59 (SD
.27)) and the final words did not differ in frequency (concrete: 65.1 per
million (SD 77), abstract: 69.7 per million (SD 92); Francis & Kucera,
1982) or length (concrete: 5.8 letters (SD 1.75), abstract: 5.9 letters (SD
1.65)). Concreteness and cloze
probability were assessed by having separate groups of participants rate the
materials. For concreteness 35 participants rated the pool of 160 final words
on a scale from 1 (very abstract) to 7 (very concrete). Several examples of each category were given
prior to the test. Cloze probability was calculated by having another group of
15 participants fill in what they thought was the most appropriate final word
for each of the 160 sentence stems. These participants were told to read each
sentence stem quickly and to fill into the final word position the first word
that came to mind. No word generated by any of the 15 cloze participants was
utilized in forming the anomalous sentence endings, thus effectively making the
cloze values for the anomalies zero.
From these sentences, four
lists were formed such that half of the sentences in each list (80) ended in an
appropriate or semantically congruent final word, while the other half
ended in a semantically anomalous final word (See Table 1). The anomalous sentences were counterbalanced
such that half of the 40 sentences that predicted concrete final words were
completed with anomalous abstract words, and half were completed with anomalous
concrete words. For the 40 anomalous
sentences that predicted abstract final words, half were completed with
anomalous concrete words, and the other half were completed with anomalous
abstract words. So, each of the four
lists had 40 sentences with semantically congruent concrete final words, 40
sentences with semantically congruent abstract final words, 40 sentences with
semantically anomalous concrete final words (20 predicting an abstract word and
20 predicting a concrete word), and 40 sentences with semantically anomalous
abstract final words (20 predicting an abstract word and 20 predicting a
concrete word). Each participant read
each of the 160 sentence frames and each of the 160 final words only once. However, across participants, each final
word and each sentence frame appeared in both the congruent and anomalous
conditions.
Table 1
Sample Sentences
|
A. Concrete final word, CONGRUENT |
|
Armed
robbery implies that the thief used a weapon. |
|
|
|
B. Abstract final word, CONGRUENT |
|
Lisa
argued that this had not been the case in one single instance. |
|
|
|
C. Concrete final word, ANOMALOUS |
|
Armed
robbery implies that the thief used a rose. |
|
Lisa
argued that this had not been the case in one single rose. |
|
|
|
D. Abstract final word, ANOMALOUS |
|
Armed
robbery implies that the thief used a fun. |
|
Lisa
argued that this had not been the case in one single fun. |
|
|
|
E. Concrete final word, NEUTRAL |
|
They
said it was because of the rose. |
|
Robert
said it was due to the weapon. |
|
|
|
F. Abstract final word, NEUTRAL |
|
They
said it was because of the fun. |
|
Robert
said it was due to this instance. |
The experiment was
self-paced, each trial beginning after the participant responded to the final
word from the previous sentence. Participant
responses (YES/NO) were registered by a small two-button panel resting in their
lap. Three seconds following the
participant's response, a fixation cross was displayed for 500 ms in the center
of the computer monitor. This served as
a warning that the next trial was about to begin. This was followed by a 300 ms blank screen, after which the first
word of the sentence was displayed. The
first word and each subsequent word in the sentence was sequentially displayed
for 200 ms each. Consecutive words
were separated by a 300 ms blank-screen inter-stimulus-interval (ISI) for a
total word-to-word onset interval of 500 ms.
The final word of each sentence was displayed with a punctuation period
to indicate that it concluded the sentence, and was followed by a 1300 ms
blank-screen ISI. All words were
centered on the display monitor. After
the final-word ISI, the message “RESPOND NOW” was presented in the center of
the display until the participant made his/her response. Participants were instructed to press the
“YES” button if the sentence made sense and the “NO” button if it did not. They were also told not to move or blink
their eyes from the onset of the fixation cross until the “RESPOND NOW” message
was presented. Response hand was counterbalanced across participants. Each participant was given 10 practice
trials prior to the run of 160 experimental sentences.
EEG procedure. Tin electrodes (Electro-Cap International, Inc., Eaton, OH) were placed
at several scalp sites (see the head schematic in Figure 1 for the relative
locations on the head), on the right mastoid bone, below the left eye, and to
the right of the right eye (all referenced to the left mastoid). The scalp sites included standard
International 10‑20 System locations: occipital left (O1) and right (O2);
and frontal left (F7) and right (F8).
Six electrodes were also placed at nonstandard locations over left and
right temporo-parietal cortex (30% of the interaural distance lateral to a
point 13% of the nasion-inion distance posterior to Cz: Wernicke’s left [WL]
and right [WR], right and left temporal cortex (33% of the interaural distance
lateral to Cz: TL and TR), and right and left anterior temporal cortex (50% of
the distance from T3/4 to F7/8: ATL and ATR).
The EEG was amplified with
Grass Model 12 amplifiers (3db cutoffs at .01 and 30 Hz) and was digitized
on-line at 200 Hz. Average ERPs were
formed off-line from correct-response trials free of ocular and movement artifacts
(which averaged less than 10% across conditions).
Data analysis. The ERP data to sentence
final words were quantified by calculating the mean amplitudes (relative to a
100 ms prestimulus baseline) in three latency windows (150-300 ms, 300-500 ms,
and 500-800 ms). These windows were
chosen because they roughly correspond to the latency ranges of the P2, N400,
and the late positivity reported in previous language studies (see Kutas &
Van Petten, 1988; Osterhout & Holcomb, 1995) and because they were also used
in our earlier study comparing concrete and abstract words (Kounios &
Holcomb, 1994).
The approach to statistical analysis involved the
use of a repeated measures analysis of variance (ANOVA) followed by simple
effects tests in the case of significant interactions. There were two levels of Sentence-Type
(congruent vs. anomalous) and two levels of final Word-Type (concrete
vs. abstract). ERPs at midline and
lateral sites were analyzed in separate ANOVAs so that laterality effects could
be assessed. Midline-site analyses
included an Electrode-Site factor (Fz vs. Cz vs. Pz). Lateral-site analyses included the factors
of Electrode-Site (frontal vs. anterior-temporal vs. temporal vs.
Wernicke’s vs. occipital), and Hemisphere (right vs. left). The Geisser-Greenhouse
correction (Geisser & Greenhouse, 1959) was applied to all repeated
measures containing more than one degree of freedom in the numerator. Finally,
analyses with significant interactions of stimulus variables with a topographic
factor (e.g., Electrode-Site or Hemisphere) were repeated after amplitude
values were normalized (using z-scores) separately within each level of the
Word- or Sentence-Type factor (see McCarthy & Wood, 1985). Only
interactions significant after normalization are reported.
Results
Accuracy Data. Subjects were very accurate in deciding if sentences made sense,
averaging 97.5% correct responses (Table 2).
Overall, they were significantly more accurate in their decisions about
anomalies than about congruent sentences (main effect of sentence-type: F[1,
15] = 13.71, MSe = .01, p
< .01). Furthermore, subjects were
more accurate in their responses to concrete than abstract final words in the
congruent-sentence condition, but performed equally well for the two word types
in the anomalous-sentence condition (Sentence-Type by Word-Type interaction: F[1,
15] = 4.87, MSe = .01, p < .05).
Table 2
Experiment
1 -- Percent Correct (Standard Deviation)
Final-Word
Type
|
|
Sentence-Type Concrete Abstract |
|
|
|
Congruent 97.3 (3.5) 95.2
(3.9) |
|
Anomalous 98.8
(1.6) 98.8 (1.6) |
Overview of ERPs. The grand-mean ERPs (averaged
across all 16 subjects) for congruent and anomalous final words are plotted in
Figure 1. The ERPs in this figure show
that there were several relatively early (less than 400 ms) components elicited
in both conditions. These potentials
are generally thought to reflect sensory and early perceptual processes (e.g.,
Rugg & Coles, 1995). They included a broadly-distributed early negativity
(N1) that peaked around 125 ms at all but the most posterior sites (i.e., O1,
O2). At the posterior sites, there was
an early positivity between 100 and 125 ms (P1) followed by a later N1 with a
peak near 200 ms. At most sites, the N1
was followed by a positivity between 200 and 300 ms (P2). Note that, with the possible exception of
the P2, none of the early components appeared to be differentiated according to
sentence-type.
Figure 1. Grand mean ERPs from 13 scalp sites for congruent and anomalous final words in Experiment 1. In this and all subsequent figures, the ERP waveforms for each electrode site are plotted separately, with anterior sites shown at the top of each figure, posterior sites at the bottom, left-hemisphere sites on the left, and right-hemisphere sites on the right. Three sites down the middle of the head are plotted in the middle of the figure. The approximate locations of these sites can be seen in the head schematic located at the top of the figure (note that this is a view looking down at the top of the head with the nose pointed toward the top of the figure). The x-axes display time with the vertical calibration bar placed at the time of the onset of the stimulus. Each x-axis tic represents 100 ms. Note that 100 ms of activity prior to stimulus onset is displayed. This was used as a baseline for equating the post-stimulus portion of each waveform. The y-axes represent voltages on a microvolt scale, with negative voltages plotted up, according to convention. Note that the peaks of the N1, P2, N400 and LPC components have been labeled at representative sites. Finally, the filled area between the ERPs for the congruent and anomalous final words represents the area used to quantify the N400 component (300 to 500 ms).
There were also several
later ERP components visible in the waveforms (see Figure 1). Following the P2, there was a negative-going
wave which peaked around 400 ms. This
negativity, which exhibited a broad scalp distribution, was clearly larger
(i.e., was more negative-going) for anomalous than congruent final words,
suggesting that it was a traditional N400 wave (cf. Kutas & Hillyard,
1980). Following the N400, there was a
late positive component (LPC), which
peaked between 600 and 800 ms over central and posterior sites. At these sites, the LPC was slightly larger
and peaked somewhat later for anomalous final words than for congruent ones.
Analyses by epoch. Differences between anomalous and congruent final words started
in the 150 to 300 ms time window, with anomalous endings producing more
negative-going ERPs than congruent endings (main effect of Sentence-Type, midline:
F[1, 15] = 13.60, MSe = 10.99, p < .01; lateral: F[1,
15] = 14.49, MSe = 9.25, p < .01). However, there was not a
significant main effect for Word Type or interaction between Word Type and
Electrode Site in this epoch.
In the 300 to 500 ms epoch, which
typically encompasses most of the activity of the N400 component (e.g., Kutas
& Hillyard, 1980), anomalous sentences continued to elicit more negative
ERPs than congruent sentences (main effect of Sentence-Type, midline: F[1,
15] = 67.65, MSe = 20.42, p < .0001; lateral: F[1, 15]
= 70.55, MSe = 20.33, p < .0001), and concrete final words
elicited more negative ERPs than abstract words (main effect of Word-Type,
midline: F[1, 15] = 10.46, MSe = 10.06, p < .01; lateral: F[1, 15] = 24.32, MSe =
7.62, p < .0001). As can be
seen in Figure 1 the difference between congruent and anomalous sentences was
largest at centro-parietal scalp sites (Sentence-Type X Electrode-Site interaction, midline: F[2,30] =
11.86, MSe = .08, p < .002;
lateral: F[4,60] = 8.67, MSe
= .33, p < .01), and was also larger over the right hemisphere than
the left (Sentence-Type X Hemisphere interaction: F[1,15] = 13.47, MSe = .41, p < .01).
The difference between
concrete and abstract final words was larger over anterior lateral sites than
posterior lateral sites (Word-Type X Electrode-Site interaction, F[4,60] =14.72, MSe =
.16, p < .0001). There were
also significant Sentence-Type X Word-Type X Electrode-Site interactions
(midline: F[2,30] = 4.64, MSe
= .07, p < .05; lateral: F[4,60]
= 7.36, MSe = .26, p < .01), indicating that the effects of
concreteness (Word-Type) were different for congruent and anomalous final words
(see the difference waves in Figure 2).
Therefore, this latter interaction was followed up by separate ANOVAs for
the two types of sentences. Analyses of the anomalous sentences produced a
significant main effect of Word-Type (midline: F[1,15] = 6.38, MSe
= 20.63, p < .05; lateral: F[1,15] = 13.88, MSe =
21.27, p < .01) with concrete words more negative than abstract (see
Figure 3). Importantly, there was also a significant Word-Type X Electrode-Site
interaction (midline: F[2,30] = 7.09, MSe = .09, p <
.01; lateral: F[4,60] = 18.50, MSe = .22, p < .0001),
indicating that the difference between concrete and abstract words was larger
at more anterior sites. In contrast, for congruent sentences (Figure 4), there
were no significant main effects or interactions involving Word-Type (p’s
> .5), indicating that the concreteness effects revealed by the overall
analyses in the 300 to 500 ms window were due almost exclusively to the
anomalous sentences (compare Figures 3 and 4).
Figure 2. Plotted in this figure are difference waves which were produced by subtracting ERPs to congruent sentences from ERPs to anomalous sentences, for concrete and abstract final words in Experiment 1. The area under the large negative deflection between 200 and 600 ms represents the N400 effect (the difference between the anomalous and congruent final words). Note that this effect is larger for concrete and abstract words, especially at the most anterior sites.
Figure 3. Grand mean ERPs for congruent final words that were concrete or abstract (Experiment 1).
Figure 4. Grand mean ERPs for anomalous final words that were concrete or abstract (Experiment 1).
As can be seen in Figure 1
the effects of Sentence-Type had dissipated by the 500 to 800 ms temporal
window at most electrode sites. There was, however, a small residual effect at right
anterior sites which was revealed in the Sentence-Type X Electrode-Site X
Hemisphere interaction ( F[4,60]
= 4.97, MSe = .07, p. < 05).
However, as in the previous epoch, there continued to be robust effects
of concreteness (Word-Type – see Figure 3) at all anterior sites for anomalous
sentences (Sentence-Type X Word-Type X Electrode-Site interaction midline: F[2,30]
= 13.25, MSe = .05, p < .001; lateral: F[4,60] = 7.33, MSe = .14, p < .01). This was confirmed by separate follow up
analyses on the two types of sentences.
For the anomalous sentences, there was a significant Word-Type X
Electrode-Site interaction (midline: F[2,30] = 9.38, MSe = .06, p
< .01; lateral: F[4,60] = 11.71, MSe = .10, p <
.0001). For the congruent sentences,
again, there were no significant main effects or interactions involving
Word-Type (compare Figures 3 and 4).
Discussion
In this experiment,
participants verified whether congruent and anomalous sentences with either
concrete or abstract final words made sense.
As in previous studies (e.g., Kutas & Hillyard, 1984) ERPs
time-locked to the onset of final words revealed large effects of sentence
context. Sentences with anomalous endings produced more negative-going ERPs
than sentences with congruent endings, particularly in the 300 to 500 ms
window. These effects of context had a central-posterior distribution and were
slightly larger over the right than left hemisphere, which is consistent with
the known distribution of the N400 component (Kutas & Hillyard, 1984). The
most widely accepted view of the N400 is that it reflects differences in the
ease of integrating semantic information into a higher level discourse or
mental model type of representation (e.g., Brown & Hagoort, 1994; Holcomb,
1993); the larger the N400, the more effortful or involved the integration
process. According to this view participants in the current study had more
difficulty integrating the meaning of anomalous final words into the
representation established by the prior sentence context.
As predicted, there were
also clear effects of concreteness. Concrete final words elicited more
negative-going ERPs than abstract final words, most notably within the window
of the N400 (300 to 500 ms), but also extending into the later measurement
epoch (500 to 800 ms). Also as predicted, the concreteness effect had a more
anterior scalp distribution than the overall effects of context. However, of
most importance to the goals of this study, in the 300 to 500 ms window, there
was a clear interaction of concreteness and context which strongly suggests
modulation of at least some of the neural generators associated with the N400
component. Given the large literature linking the N400 to the processing of
meaning (see Osterhout & Holcomb, 1995 for a review), this finding adds
credence to the argument that the observed effects of concreteness and context
are indeed semantic.
Interestingly, there were no
discernible ERP differences in any window between concrete and abstract words
in the congruent sentences. In other words,
a supportive sentence context wiped out all ERP evidence of concreteness
effects, a finding that would appear to be consistent with the central
prediction of the context-availability model. However, two other findings,
which replicate effects reported by Kounios and Holcomb (1994), are
inconsistent with the predictions of this theory. First, in the anomalous
sentences, the differences between concrete and abstract words varied
systematically across the scalp. This concreteness effect was largest at the
most anterior scalp sites, with concrete words producing much larger
negativities than abstract words. This difference gradually decreased moving
towards the back of the head until at the most posterior sites (O1/O2) there
were virtually no concreteness amplitude differences (see Figure 4). Under the
assumptions of the spatial distinctiveness principle outlined in the
Introduction, this pattern of results strongly suggests that non-identical
neural/cognitive systems are responsible for processing the two word types, at
least when they are read outside of a supportive context. In this case, the
labile topography of the N400 also supports the notion that this ERP component
is generated by at least two different neural sources whose relative
contributions to scalp topography vary across tasks and materials (Kounios,
1996; Nobre & McCarthy, 1994).
The above pattern of results
is most consistent with multiple system theories such as dual-coding theory
(Paivio, 1986) which argue that semantic information is represented and
processed by two separate systems, one linguistic and one image based, and that
while concrete words are processed in both systems, abstract words are
processed primarily in the linguistic system. On the other hand, this pattern
of results is clearly at odds with the predictions of single system accounts of
concreteness, such as the context-availability model (Schwanenflugel, 1991),
which argue that both word types are processed and represented within a single
system. This latter type of model predicts only main effects of concreteness
and a flat distribution for the N400 across the scalp (i.e., no interaction of
scalp site and concreteness).
A second finding that was at
odds with the predictions of the context-availability model and data reported
to support it, was that the effects of context in the N400 window were larger
for concrete than abstract words. In other words, when placed in a supportive
context, concrete words revealed a more dramatic decline in N400 amplitude than
abstract words. The context-availability model predicts larger context effects
for abstract words.
In contrast to the above
findings, prior findings using RT as the dependent measure have been
interpreted as supporting the context-availability predictions. For example, in
lexical decision and meaningfulness judgments, abstract words have been shown
to produce large declines in RT going from a non-supportive to a supportive
sentence context, while concrete words, which produce relatively fast
non-supportive context RTs to begin with, show only small or no changes in RT
when placed in a supportive context (Schwanenflugel & Shoben, 1983;
Schwanenflugel & Stowe, 1989). Context-availability proposes that the same
process that underlies faster out-of-context concrete word RTs (built-in
context), also accounts for concrete words’ fast responses within a supportive
sentence (external context) and that it is only the source of the context that
differs. In essence, participants simply trade one source of context for
another, and thus, RTs remain relatively unchanged.
This apparent contradiction
in findings between behavioral measures and ERPs is not without
precedence. Kounios and Holcomb (1992)
also found that RT and N400 amplitude were not correlated in a sentence
verification task and concluded that this is because these measures are not
necessarily sensitive to the exact same set of underlying cognitive operations.
In particular, they argued that RT is much more sensitive to participant’s
decision processes and task dependent strategies than is N400 amplitude. Accordingly, one way to explain the apparent
discrepancy between the RT and N400 concreteness by context interactions is to
assume that the behavioral judgments in the Schwanenflugel studies were
relatively more sensitive to
participant’s decision strategies (in particular a two step decision
process), while the N400s in the current study and in the Kounios and Holcomb
(1994) study were primarily sensitive to changes in a single semantic
integration process and were relatively immune to decision processes. In this
view N400s were larger to out-of-context concrete than abstract words because
concrete words have relatively more semantic information (linguistic and
imagistic) that readers must attempt to integrate into an unrelated context and
therefore integration was more effortful.3 N400s were equivalently
small to both word types following supportive contexts because semantic
information from the final word was easily integrated into the representation
established by the context. The observation that the N400s were equally small
for congruent sentences fits with the fact that the concrete and abstract
sentence stems were matched to produce equivalent levels of contextual support.
In the case of RT, this view
proposes that when participants make lexical decisions or meaningfulness
judgments they first use the strategy of determining if a target item can
easily be integrated into the prior sentence context. If it can, then it’s
likely a word (pseudowords cannot be semantically integrated) or a meaningful
item (non-meaningful items cannot easily be integrated) and RT is similarly
fast for both concrete and abstract words. If, however, the context is
non-supportive and integration does not easily occur, then participants must
fall back on a second strategy to make their judgments. Here it is proposed
that participants now use integration difficulty to aid their decision process.
For example, in a meaningfulness judgment task they might respond to concrete
words in an anomalous context more quickly than abstract words, because they
detect the relatively greater effort involved in the semantic integration
process for concrete words. A similar strategy would work for lexical decision
as it should be relatively easier to discriminate out-of-context concrete words
from pseudowords than out-of-context abstract words from pseudowords due to the
greater effort involved in integrating concrete words into a non-supportive
context. This type of explanation is similar to one offered by Neely and
colleagues (e.g., Neely, 1991) to explain the pattern of RT effects in semantic
priming lexical decision tasks.4
One difference between the
current results and those of Kounios and Holcomb (1994) is that the earlier
study reported a lateral asymmetry for the N400 effect between concrete and
abstract words (larger differences over the right hemisphere) in their second
experiment. No such asymmetry was found here, although there was a slight
(non-significant) trend in this direction (compare the WL and WR sites in
Figure 2). The most likely reason for this discrepancy are differences in the
task used in the two studies. Kounios and Holcomb found the asymmetry in a
concreteness judgment task with single word contexts. No asymmetry was found
here in a sentence meaningfulness judgment task. One possibility is that the
larger right hemisphere effect was due to a more explicit use of imagery in the
concreteness judgment task, although West and Holcomb (submitted) also failed
to find a hemispheric asymmetry between word types in a task where participants
were asked about the ease of imageability.
In summary, the findings of
this experiment support and extend Kounios and Holcomb (1994) showing that the
concreteness factor yields a topographic distribution of ERPs consistent with
the structural assumptions of extended dual-coding theory, but which is not
reconcilable with the notion that concreteness effects are reducible to the
availability of supportive context.
Experiment 2
In Experiment 1, no
difference was observed in the ERPs elicited by congruent concrete and
congruent abstract words. However,
anomalous concrete words produced substantially more negative values in the
time window of the N400 than did abstract words. Dual-coding theory
proposes that this larger effect for concrete words is due to the
activity of two qualitatively different systems (verbal and imagistic)
processing the concrete words in parallel while only one system (the verbal
system) processes abstract words. There
is, however, an alternate explanation, namely, that in the case of the
anomalies, the concrete final words were somehow more anomalous than the
analogous abstract final words. Perhaps the abstract words were inherently more
vague and seemed less anomalous than their concrete counterparts. By this same logic, the concrete words can
be readily identified as sharply incongruent, since they refer to more specific
entities. According to this view, the
larger N400 seen for the concrete words in Experiment 1, and perhaps the more
anterior distribution of this effect may have had nothing specifically to do
with the concreteness of the word, but rather to the degree of anomaly. This is
possible, because while the congruent sentences were carefully matched for
cloze probability across the two word types, anomalies were formed by attaching
final words from high-cloze sentences to another sentence stem. In forming
anomalies two rules were followed. First, none of the 15 individuals that
participated in the cloze procedure filled in the “target” word for the
anomalous sentence stem (i.e., cloze probability = 0). Second, in selecting
items for anomalous sentence stems the experimenters used their best intuitions
in attempting to pair anomalous ending with sentence stems so that each ending
was not related to any acceptable ending for the sentence. This is probably not the best way to equate
level of anomaly between the two word types. Ideally the concrete and abstract
anomalies should have been equated based on some more objective method of
assessment.
Experiment 2 was designed to
circumvent the possibility that the concrete anomalous endings were somehow more anomalous than the
abstract anomalies and that this difference rather than differences in
concreteness was responsible for the N400 concreteness findings in Experiment
1. However, rather than attempting to match the anomalous concrete and abstract
final words on degree of anomaly, a “neutral” condition was added instead. This
was done for two reasons. First, equating for degree of anomaly would
undoubtedly require using a different set of sentences than those used in
Experiment 1 making any between-experiment differences difficult to interpret.
Second, anomaly ratings and ERPs would have had to have been collected in
different groups of participants performing somewhat different tasks (anomaly
detection vs. anomaly rating). This would make it difficult to know if degree
of anomaly had been adequately controlled in the ERP participants. To
circumvent these problems a different approach was taken. Rather than equating
anomaly levels a neutral condition was added to the design. In this condition
concrete and abstract words occurred at the ends of sentences where they were
not anomalous, but also where they would not have been easily predicted.
Schwanenflugel and Stowe (1989) used neutral sentences (e.g., The next word
will be …) in the out-of-context condition of one of their experiments
contrasting concrete and abstract words. These sentences had the desired effect
in their study of producing large
differences in RT between concrete and abstract words. Similar low cloze
probability sentences have been demonstrated by Kutas and colleagues (Kutas et
al., 1984) to produce robust N400s. If, under this condition, concrete words do
not elicit a larger N400 than abstract words, it could be concluded that the
results observed in Experiment 1 may have been due to the concrete words having
been perceived as more anomalous than the abstract words. Conversely, if concrete words still elicit a
larger negativity in the neutral condition, then it can be concluded that the
results of Experiment 1 were not simply due to the degree of anomaly, but
rather reflect inherent differences in the processing of the two word types.
Neutral sentences were
constructed such that the final words were congruent in that they fit into the
sentences, but were of low cloze probability in that the sentence context
provided no evidence on which to predict the final word or even to predict its
concreteness (e.g., “Larry said it must have been the wine.”; “It
happened because of her mood.”). Consistent with the results of
Experiment 1 it was predicted that concrete words at the ends of neutral and
anomalous sentences would produce larger N400s with a more anterior
distribution than abstract words at the ends of these same sentences.
Method
Participants. Twenty-four naïve undergraduates (21 female, 3 male) between 18
and 22 years of age (mean: 18.67) from Tufts University served as
participants. All were right-handed native
speakers of English with normal or corrected-to-normal visual acuity.
Stimuli and procedure. Stimulus materials for congruent and anomalous sentences were
taken from Experiment 1. However, half
of the congruent sentence stems were replaced with neutral stems. Thus,
Experiment 2 consisted of 80 anomalous sentences, 40 congruent sentences, and
40 neutral sentences. Neutral sentence frames were composed in such a way as to
be semantically acceptable but contextually ambiguous (see Table 1 for an example).
To assure that this was the case a separate group of 15 participants was used
to assess the cloze probabilities of these materials. These participants read
the neutral stems and filled in the first sentence ending word that came to
mind. The mean cloze value for neutral sentences was .007 (one participant each
filled in the appropriate final word for each of four of the 40 neutral
sentences).
As in Experiment 1
participants were instructed to press the “YES” button if the sentence made
sense (congruent and neutral) and the “NO” button if it did not (anomalies).
Four lists were created so that anomalous and congruent/neutral sentence frames
were each completed with both a concrete and an abstract final word. The lists were counterbalanced such that each
word appeared in each type of sentence frame.
Thus, each participant saw eight sentence types. These consisted of the same four anomalous
sentence types from Experiment 1, congruent sentences with concrete or abstract
final words, and neutral sentences with concrete or abstract final words.
Both the experimental procedure and the ERP
procedure were identical to that in Experiment 1. Data analysis was also identical to that in Experiment 1, except
for the inclusion of three levels of Sentence-Type (congruent vs. anomalous vs.
neutral). These conditions were compared in a single omnibus ANOVA and were
followed up with separate pair-wise analyses were warranted.
Results
Accuracy data. In this experiment, participants were generally quite accurate in
deciding whether sentences made sense, averaging 91.3% correct responses (Table
3). However, participants were less
accurate in correctly judging the neutral sentences than the congruent or
anomalous sentences (main effect of Sentence-Type, F[2, 46] = 19.36, MSe
= 104.57 , p < .0001). They
also responded more accurately to sentences with abstract final words than to
sentences with concrete final words (main effect of Word-Type, F[1, 23]
= 5.58, MSe = 30.87 , p < .05), but only in the
neutral-sentence condition (Sentence-Type X Word-Type interaction, F[2,
46] = 5.05, MSe = 33.01, p < .05).
Table
3
Experiment
2 -- Percent Correct (Standard Deviation)
|
Final-Word
Type |
|
Sentence-Type Concrete Abstract |
|
|
|
Congruent 95.8 (7.2) 95.5 (7.0) |
|
Anomalous 97.5
(3.0) 96.3 (4.0) |
|
Neutral 82.3 (15.3) 88.5 (10.9) |
Overview of ERPs. The grand-mean ERPs (averaged across all 24 participants) for all
congruent, anomalous, and neutral final words are plotted in Figure 5. In all conditions, the ERPs show early
components (P1, N1, P2) similar to those observed in Experiment 1 (Figure 1). Again, only the P2 component appeared to be
affected by sentence type.
Figure 5. Grand mean ERPs for congruent, anomalous, and neutral final words in Experiment 2.
The later ERP components
were also similar to those in the previous experiment. There was again a negative-going wave which
peaked at approximately 400 ms (N400) that was broadly distributed. This component was clearly larger for
anomalous and neutral final words than for congruent final words. Following the N400, there was again a
positive-going wave (LPC) peaking at 600-800 ms over central and posterior
sites. This late positivity was larger
for anomalous final words and smallest for neutral final words.
Analyses by epoch. In the 150 to 300 ms
time-window, there was a main effect of Sentence-Type (midline: F[2, 46]
= 5.46, MSe = 6.4, p < .01; lateral: F[2, 46] = 5.83, MSe
= 10.3, p < .01). Follow-up analyses indicated that anomalous final
words produced more negative ERPs than either congruent or neutral final words
(Congruent vs. Anomalous, midline: F[1,23] = 10.54, MSe = 6.6, p
< .01; lateral: F[1,23] = 5.41, MSe = 9.2, p < .05;
Anomalous vs. Neutral, midline: F[1,23] = 4.43, MSe = 4.9, p
< .05; lateral: F[1,23]= 14.96, MSe = 7.8, p <
.001).
The main effect of
concreteness was not significant in the 150 to 300 epoch, but there was a
significant interaction between Word-Type and Sentence-Type (midline: F[2,46]
= 6.09, MSe = 13.1, p < .01; lateral: F[2,46] = 3.42, MSe
= 15.8, p < .05). Follow-up analyses indicated that concrete words
yielded more negative ERPs than did abstract words for both anomalous and
neutral sentences when compared to congruent sentences (Anomalous vs.
Congruent, midline: F[1,23] = 12.12, MSe = 10.5, p < .002;
lateral: F[1,23] = 5.96, MSe = 14.1, p < .03; Neutral vs.
Congruent, midline: F[1,23] = 5.60, MSe = 19.7, p < .03; lateral:
F[1,23] = 3.79, MSe = 20.7, p < .06; Anomalous vs. Neutral, p’s
> .7).
In the 300 to 500 ms
time-window there was a main effect of Sentence-Type (midline: F[2, 46]
= 34.57, MSe =25.8, p < .0001; lateral: F[2, 46] =
28.50, MSe = 33.9, p < .0001) and a Sentence-Type X
Electrode-Site interaction (midline: F[2,46] = 11.2, MSe = .10, p
< .0001; lateral: F[4,92] = 25.38, MSe = .31, p <
.0001). Follow-up analyses indicated that both anomalous and neutral final
words elicited more negative ERPs than did congruent final words, and that
these effects tended to be larger over more posterior sites (Sentence-Type X
Electrode-Site interaction: Congruent vs. Anomalous, midline: F[2,46] =
5.52, MSe = .1, p < .05, lateral: F[4,92] = 7.01, MSe
= .3, p < .01; Congruent vs. Neutral, midline: F[2,46] =
19.60, MSe = .1, p < .0001; lateral: F[4,92] = 43.95, MSe
= .3, p < .0001 – see Figure 5).
Figure 6. Grand mean ERPs for congruent final words that were concrete or abstract (Experiment 2).
Figure 7. Grand mean ERPs for anomalous final words that were concrete or abstract (Experiment 2).
Figure 8. Grand mean ERPs for neutral final words that were concrete or abstract (Experiment 2).
During
the 300 to 500 ms epoch, there was also a main effect of Word-Type (midline: F[1,
23] = 23.48, MSe = 19.0, p < .001; lateral: F[1, 23] =
36.28, MSe = 23.7, p < .0001)], a Sentence Type X Word-Type
interaction (midline: F[2, 46] = 9.30, MSe = 11.8, p <
.001; lateral: F[2, 46] = 9.35, MSe = 23.6, p < .0001), and a three-way
interaction between Word-Type, Sentence-Type and Electrode-Site (midline: F[4,
92] = 2.96, MSe = .1, p
< .05; lateral: F[8, 184] = 9.03, MSe = .2, p <
.0001). Follow-up analyses indicated that concrete words produced significantly
more negative-going ERPs than abstract words, but only for the anomalous and
neutral conditions (main effect of Word-Type: Anomalous, midline: F[1,
23] = 32.33, MSe = 8.7, p < .0001; lateral: F[1, 23] =
58.17, MSe = 10.5, p < .0001; Neutral, midline: F[1, 23]
= 27.91, MSe = 13.8, p < .0001; lateral: F[1, 23] =
28.52, MSe = 18.9, p < .0001; Congruent, p’s > .5 –
compare Figures 6, 7 and 8).
Furthermore, for Anomalous and Neutral endings, these effects of
concreteness tended to increase in magnitude toward more anterior sites
(Word-Type X Electrode-Site interaction, Anomalous midline: F[2, 46] =
5.13, MSe = .1, p <
.05; lateral: F[4, 92] = 16.31, MSe = .2, p < .0001; Neutral midline: F[2,46]
= 3.43, MSe = 1.0, p < .05, lateral, p < .1).
However, for Congruent endings, there were differences between the two word
types only at the most posterior lateral sites (O1/O2) where Concrete endings
were more negative-going than Abstract endings (Word-Type X Electrode-Site
interaction, Congruent lateral, F[4,92] = 5.68, MSe = .2, p
< .01).
In the 500 to 800 ms epoch,
there was again a main effect of Sentence-Type (midline: F[2, 46] =
8.58, MSe = 19.53, p < .001; lateral: F[2, 46] = 13.88,
MSe = 30.17, p < .001) and an interaction between
Sentence-Type and Electrode-Site (midline: F[4,92] = 10.10, MSe =
.10, p < .0001; lateral: F[8,184] = 19.54, MSe = .30, p
< .0001). Follow-up analyses revealed that Neutral sentence final words
elicited more negative ERPs than either Congruent or Anomalous final words (Sentence-Type,
Neutral vs. Congruent, midline: F[1,23] = 6.71, MSe = 21.81, p
< .05; lateral: F[1,23] = 12.66, MSe = 41.10, p <
.01; Neutral vs. Anomalous, midline: F[1,23] = 18.16, MSe =
17.71, p < .001, lateral: F[1,23] = 23.38, MSe = 30.79,
p < .0001), and these differences tended to have a posterior
distribution [Sentence-Type X Electrode-Site interaction, Neutral vs.
Congruent, midline: F[2, 46] = 12.62, MSe = .11, p < .001; lateral: F[4, 92]
= 20.44, MSe = .31, p
< .0001; Neutral vs. Anomalous, midline: F[2,46] = 18.14, MSe
= .09, p < .0001; lateral: F[4,92] = 39.51, MSe = .19, p
< .0001).
During the 500 to 800 ms epoch, there was also a main effect of Word-Type (midline: F[1, 23] = 10.75, MSe = 19.5, p < .01; lateral: F[1, 23] = 17.20, MSe = 28.0, p < .001), a Sentence-Type by Word-Type interaction (midline: F[2, 46] = 11.94, MSe = 11.9, p < .001; lateral: F[2, 46] = 11.50, MSe = 15.7, p < .001) and at lateral sites a three-way interaction between Sentence-Type, Word-Type and Electrode Site (F[8,184] = 5.28, MSe = .12, p < .01). Follow-up analyses indicated that concrete words were more negative going than abstract words for anomalous and neutral, but not for congruent final sentences (Word-Type main effect, Anomalous midline: F[1, 23] = 18.83, MSe = 6.24, p <.001; lateral: F[1, 23] = 33.60, MSe = 9.75, p < .0001; Neutral midline: F[1,