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Mem Cogn
https://doi.org/10.3758/s13421-017-0766-4
On the predictability of event boundaries
in discourse: An ERP investigation
Francesca Delogu1·Heiner Drenhaus1·Matthew W. Crocker1
© The Author(s) 2017. This article is an open access publication
Abstract When reading a text describing an everyday
activity, comprehenders build a model of the situation
described that includes prior knowledge of the entities, loca-
tions, and sequences of actions that typically occur within
the event. Previous work has demonstrated that such knowl-
edge guides the processing of incoming information by
making event boundaries more or less expected. In the
present ERP study, we investigated whether comprehen-
ders’ expectations about event boundaries are influenced
by how elaborately common events are described in the
context. Participants read short stories in which a common
activity (e.g., washing the dishes) was described either in
brief or in an elaborate manner. The final sentence contained
a target word referring to a more predictable action mark-
ing a fine event boundary (e.g., drying) or a less predictable
action, marking a coarse event boundary (e.g., jogging). The
results revealed a larger N400 effect for coarse event bound-
aries compared to fine event boundaries, but no interaction
with description length. Between 600 and 1000 ms, how-
ever, elaborate contexts elicited a larger frontal positivity
compared to brief contexts. This effect was largely driven by
less predictable targets, marking coarse event boundaries.
We interpret the P600 effect as indexing the updating of the
situation model at event boundaries, consistent with Event
Segmentation Theory (EST). The updating process is more
Electronic supplementary material The online version of this
article (https://doi.org/10.3758/s13421-017-0766-4) contains sup-
plementary material, which is available to authorized users.
Francesca Delogu
delogu@coli.uni-saarland.de
1Department of Language Science & Technology, Building
C7.1, Saarland University, 66123 Saarbruecken, Germany
demanding with coarse event boundaries, which presumably
require the construction of a new situation model.
Keywords Situation models ·Event boundaries ·Event
Segmentation Theory ·Model updating ·ERPs
Introduction
A great deal of research indicates that knowledge about
real-world events or everyday activities, also called event
schemata or script knowledge (Schank & Abelson, 1977),
is rapidly activated and influences online processing at the
level of individual words (e.g., Chwilla & Kolk, 2005;
Hare, Jones, Thomson, Kelly, & McRae, 2009; McRae,
Hare, Elman, & Ferretti, 2005), sentences (e.g., Altmann
& Kamide, 1999; Bicknell, Elman, Hare, McRae, & Kutas,
2010; Matsuki et al., 2011), and wider discourse (e.g.,
Camblin, Gordon, & Swaab, 2007; Metusalem, Kutas, Hare,
McRae, & Elman, 2012; Otten & van Berkum, 2007). In
particular, research on discourse comprehension has shown
that event knowledge plays a crucial role in building incre-
mental representations of the situation described in a text,
so-called mental or situation models (Johnson-Laird, 1983;
Van Dijk & Kintsch, 1983; Zwaan & Radvansky, 1998). Sit-
uation models arise through the integration of information
explicitly presented in the text with reader’s prior knowl-
edge about the participants, locations, and sequences of
actions that typically occur within the event described (e.g.,
Kintsch & van Dijk, 1978). Incoming information is evalu-
ated against the current state of the situation model: When
it is consistent with it, it is integrated and the current rep-
resentation remains active; when a topic shift, or a change
in character, location, time, or activity signals an event
boundary, the current model is updated, and/or a new model
Mem Cogn
initiated (Bestgen & Vonk, 2000; Gernsbacher, 1990). A
number of studies provide evidence that updating situation
models involves extra processing operations, as evidenced
by increased reading times (e.g., Bestgen & Vonk, 2000;
Rinck & Weber, 2003; Speer & Zacks, 2005; Zacks, Speer,
& Reynolds, 2009; Zwaan, 1996; Zwaan, Magliano, &
Graesser, 1995) and neural activity (Speer, Reynolds, Swal-
low, & Zacks, 2009; Speer, Zacks, & Reynolds, 2007;
Whitney et al., 2009).
Speer et al. (2007), for example, presented participants
with narrative texts about everyday events while brain activ-
ity was recorded with functional magnetic resonance imag-
ing (fMRI). Participants subsequently segmented the text
into sub-events at a fine-grained level (i.e., marking the
smallest units of activity that seemed natural and meaning-
ful) or at a coarse-grained level (i.e., marking the largest
units of activity that seemed natural and meaningful). The
results revealed increased neural activity in a network of
brain regions at the points that were later identified as
boundaries between events. Interestingly, in the majority
of these regions, larger responses were evoked by coarse-
grained than fine-grained boundaries, suggesting that brain
activity was modulated by the hierarchical structure of the
events. This sensitivity to event structure has also been
observed when people view videos of everyday activities
(Zacks et al., 2001; Zacks & Swallow, 2007).
These findings indicate that the effort required to update
a situation model is sensitive to the structure of events.
However, why should updating at coarse event boundaries
be more effortful than it is at fine event boundaries? One
possible answer to this question is provided by Event Seg-
mentation Theory (EST; Zacks, Speer, Swallow, Braver, &
Reynolds, 2007), an approach originally developed for event
perception but extended to account for narrative compre-
hension as well (Zacks et al., 2009). According to EST,
comprehenders use their knowledge of events to predict
what might happen next. Most of the time, these predic-
tions turn out to be accurate. At event boundaries, however,
future activity becomes less predictable, causing an increase
in prediction error. Higher levels of prediction error trig-
ger the reset and updating of the current situation model.
Zacks (2010) describes these mechanisms using the follow-
ing example: if you are watching a person putting on a
pair of shoes, you can use your representation of the shoe-
tying event to predict that after the first shoe has been tied,
the person will move to the second one. Once both shoes
have been tied, however, this event representation will no
longer be helpful to generate accurate predictions, causing
levels of prediction error to increase. At this point the sys-
tem triggers an updating process in which a new set of event
representations is formed and an event boundary perceived.
Hence, the processing difference between fine and coarse
event boundaries may simply reflect a difference in levels
of prediction error. Fine event boundaries mark predictable
events continuing the current activity (in a chronological
sequence), and are therefore associated with lower levels of
prediction error; coarse event boundaries, by contrast, are
associated with higher levels of prediction error as they ini-
tiate new, unpredictable events. EST predicts that coarse
event boundaries will trigger a global update of the cur-
rent situation model, resulting in a processing cost. At fine
event boundaries, by contrasts, the current situation model
is maintained, or, presumably, only updated with respect to
the individual incoming event (see the difference between
incremental and global updating postulated by e.g., Kurby
& Zacks, 2012).
If this hypothesis correctly characterizes processing in
real-time, incoming events marking coarse event boundaries
(i.e., events initiating less predictable, new activity) should
be more difficult to process than incoming events marking
fine event boundaries (i.e., more predictable events, contin-
uing the current activity). For example, a situation model
representing a washing-the-dishes scenario should be easier
to update with a drying-the-dishes event than with a jogging
event because, based on script knowledge about washing-
the-dishes activities, drying the dishes is more predictable
than jogging (cf. findings from Sitnikova, Holcomb, Kiyon-
aga, & Kuperberg, 2008, in the context of filmed events).
Integrating a more predictable event involves maintaining
the current situation model and updating it with the indi-
vidual dimension that changed (which, in turn, leads to
interpret the incoming event as part of the ongoing episode).
On the other hand, a less predictable jogging event requires
a more demanding global updating process, in which the
old model is reset and a new one constructed. This should
lead the incoming event to be interpreted as part of a new
story episode (Bailey & Zacks, 2015; Kurby & Zacks, 2012;
Magliano, Miller, & Zwaan, 2001).
Beyond this quite uncontroversial prediction, the present
study further examined whether comprehenders’ expecta-
tions for fine vs. coarse event boundaries are modulated by
how elaborately the scenario is described in the context. A
washing-the-dishes activity can be described by introducing
just one salient action (e.g., washing the plates) or multiple
typical actions of the superordinate (dish-washing) activ-
ity (e.g., washing cups, cutlery and plates), and this may
in turn influence the degree to which incoming information
is expected to mark a fine or a coarse event boundary. We
expect that, relative to a brief context describing a single
action, an elaborate context—introducing an event involv-
ing multiple actions—should lead to higher expectations
that the activity is completed, thereby triggering the updat-
ing of the current situation model. This is because, while
script knowledge about the ongoing activity is still relevant to
generate expectations for subordinate actions in brief contexts
(e.g., we know that washing the dishes involves washing
Mem Cogn
plates, but also cups, cutlery, etc.), it contributes less to
shape expectations following elaborate contexts, where the
ongoing activity has been described at greater length. Notice
that our distinction between brief and elaborate contexts
parallels the one outlined by Zacks (2010) between the per-
ception of a partial event (when only one shoe has been
tied) vs. a complete event (when both shoes have been
tied). In a similar vein, elaborate contexts should be associ-
ated with higher uncertainty about what might happen next,
anticipating that a new event representation will need to be
constructed as soon as incoming information is encountered.
We tested these hypotheses in an event-related poten-
tial (ERP) study manipulating two factors: The length of
the event description in the context (brief vs. elaborate)
and whether the target word referred to a more predictable,
related activity (fine event boundary) or a less predictable
event, initiating new activity (coarse event boundary).
We focus on two ERP components that are reported to
be modulated during discourse comprehension. The first
one is the N400, a negative-going wave peaking approxi-
mately 400 ms post stimulus onset, more pronounced over
centro-parietal sites. The amplitude of the N400 is sensi-
tive to a variety of factors, including the degree to which
a word is expected given its sentential or discourse con-
text (e.g., Federmeier & Kutas, 1999; George, Mannes, &
Hoffman, 1997;Otten&vanBerkum,2007; van Berkum,
Hagoort, & Brown, 1999, see Kutas & Federmeier, 2011 for
a review). For example, Otten and van Berkum (2007) found
that highly expected words (e.g., meeting) in a supportive
context (e.g., The manager thought that the board of direc-
tors should assemble to discuss the issue. He planned a . . . )
elicit lower N400 amplitudes relative to less expected words
(e.g., session in the same context). Based on these findings,
we expect the N400 elicited by (more predictable) fine event
boundaries in the current study to have lower amplitude than
that elicited by (less predictable) coarse event boundaries,
reflecting easier retrieval processes (e.g., Lau, Phillips, &
Poeppel, 2008). Under an integration account of the N400
(e.g., Hagoort, 2003), however, we might also expect an
interaction with description length, to the extent that brief
contexts provide greater support for fine event boundaries.
The other relevant component is the P600, a positive
shift starting at about 500 ms post stimulus onset and last-
ing for several hundreds of milliseconds. While initially
linked to syntactic revision or repair (e.g., Hagoort, Brown,
& Groothusen, 1993), P600 effects have been also observed
in response to discourse-level processing (see Brouwer,
Fitz, & Hoeks, 2012, for a review). In particular, late pos-
itivities have been associated with processing of discourse
reorganization or discourse model updating and the inte-
gration of new referents into the discourse representation
(e.g., Brouwer et al., 2012; Burkhardt, 2007; Schumacher
& Hung, 2012). In the current study, P600 effects should be
seen in response to updating processes like those associated
with elaborate contexts. Furthermore, if coarse boundary
targets lead to more effortful global updating processes
compared to fine boundary targets requiring only incremen-
tal updating, we might expect the P600 effect to be stronger
at coarse boundary targets.
Method
Participants Twenty-four Saarland University students
volunteered to participate in the experiment.1They were
all right-handed native German speakers with normal or
corrected-to-normal vision and without any history of neuro-
logical disorders. All participants provided written informed
consent and were paid 15 Euros to take part in the experi-
ment. Four participants were excluded from analysis due to
excessive artifacts in the electroencephalogram (EEG).
Materials The experimental materials consisted of 120 items in
four conditions crossing the factors length (brief vs. elabo-
rate) of the event description and type of boundary (fine vs.
coarse) marked by the target (see Supplemental Material).
An example of the materials is given in Table 1(see also
the Appendix).
After a short introductory sentence, the context sentence
introduced a common activity by mentioning its typical
location and either one typical action (brief event descrip-
tion), or a sequence of actions that typically occur within
the activity (elaborate event description). The action in the
brief description was always the last action mentioned in the
elaborate description, so that immediately prior to the target
sentence the same action was mentioned across conditions.
The final sentence always started with the expression “Then
he starts”, which served as a cue that an event was about to
be mentioned. The target word referred to an action that was
either naturally continuing the current activity (e.g., drying),
thereby marking a fine event boundary, or initiating a new,
less predictable activity (e.g., jogging), thereby marking a
coarse event boundary.
To ensure that the target words in the fine boundary
conditions were perceived as natural continuations of brief
as well as elaborate contexts, two groups of 17 students
from Saarland University performed cloze norming on these
passages. They were presented with one version of each
passage pair (brief and elaborate) up to the word preced-
ing the critical word and were asked to fill in the first word
that came to mind. The target word in the fine boundary
condition was selected in such a way that it appeared as
a completion in both types of contexts. The average cloze
probability for fine boundary targets was .24 (SD = .18) in
brief contexts and .21 (SD = .17) in elaborate contexts. The
1Sample size was determined on the basis of previous ERP literature
on language; Luck (2014).
Mem Cogn
Tabl e 1 A sample item in each condition (with English translation)
Intro
J¨
orn ist mit dem Fr¨
uhst¨
uck fertig. Er geht in die K¨
uche, ...
(J¨
orn has finished breakfast. He goes to the kitchen, ... )
Brief event description - Fine event boundary
... wo er Teller abw¨
ascht. Dann beginnt er mit dem Abtrocknen,[...].
(... where he washes plates. Then he starts to dry, [...])
Elaborate event description - Fine event boundary
...wo er erst Tassen, dann Besteck und dann Teller abw¨
ascht. Dann beginnt er mit dem Abtrocknen, [...]
(... where he first washes cups, then cutlery and then plates. Then he starts to dry, [...])
Brief event description - Coarse event boundary
... wo er Teller abw¨
ascht. Dann beginnt er mit dem Joggen,[...]
(... where he washes plates. Then he starts to jog, [...])
Elaborate event description - Coarse event boundary
... wo er erst Tassen, dann Besteck und dann Teller abw¨
ascht. Dann beginnt er mit dem Joggen,[...]
(... where he first washes cups, then cutlery and then plates. Then he starts to jog, [...])
NB: The target word is underlined for illustrative purposes
difference was marginally significant (t=1.96, p<0.06), but
it did not produce effects on the N400 amplitude. The events
in the coarse boundary condition were chosen to be unrelated to
the activity described in the context (for example, by involving
a different location than the one mentioned in the context). We
also made sure that they were unattested in the cloze com-
pletions (cloze probability was 0 in both contexts) so that
they were less predictable than the fine boundary targets.
To estimate whether elaborate contexts were indeed more
likely to be perceived as describing completed events, and
therefore be associated with coarser event boundaries com-
pared to brief contexts, we asked two independent native
speakers of German to rate on a scale from 1 to 5 how
closely related each completion in the cloze study was to the
activity described in the context. For each item and condi-
tion, we then computed the percentage of completions rated
as more closely (i.e., rated as 1 or 2) vs. less closely (i.e.,
rated as 3,4, or 5) related to the activity described in the
context. The data showed that unrelated completions were
indeed more likely to appear following elaborate contexts
(36% of completions) than brief contexts (28% of com-
pletions). Both raters showed this pattern, with moderate
agreement on specific items (Cohen’s kappa = .44, z = 4.75,
p<0.0001).
We also assessed the (word-form) frequency of fine
and coarse event boundary targets, which was in general
very low. Fine event boundary targets occurred on average
5.41 times per million words, while coarse event bound-
ary targets 2.54. The difference was marginally significant
(t=-1.97, p<0.06). It is well known that, when all other
factors are constant, the N400 amplitude is modulated by
word frequency (e.g., Rugg, 1990). However, the N400 fre-
quency effect interacts with other factors, including the
position of the word in the sentence and its predictability.
Van Petten and Kutas (1990), for example, showed that
low-frequency words elicit higher N400 amplitudes only
when they occur in sentence initial positions. The interac-
tion between word frequency and word position was taken
as evidence that the frequency effect can be overridden
by contextual constraint (or predictability). Consistent with
this, Dambacher, Kliegl, Hofmann, and Jacobs (2006) found
interactions of predictability and frequency as well as of
position and frequency, with predictability accounting bet-
ter for N400 effects than word position. Furthermore, they
found that the effect of predictability was larger for low-
frequency than for high-frequency words (i.e., frequency
modulates the strength of the predictability effect on the
N400). Since the target words in the present study had low
frequency and appeared towards the end of relatively con-
straining passages, we take any observed N400 modulation
to the targets to reflect contextual predictability rather than
marginal differences in frequency.
Four counterbalanced lists were created in such a way
that each item appeared in only one condition per list, but
in all conditions equally often across lists. Within each list,
the experimental items were mixed with 120 filler pas-
sages of an unrelated experiment. The final sentence of the
filler passages always started with a causal or a concessive
connector (e.g., therefore,however) and continued with an
event description that was either congruent or incongruent
with the expectations driven by the connector type.
Procedure Participants were seated in a sound-proof, electro-
magnetically shielded chamber. Stimuli were presented with
E-prime software (Psychology Software Tools, Inc.) in black
fonts ona white background. After a short training session of
four trials, the items were presented in pseudo-randomized
order, in six blocks with breaks after each block.
Mem Cogn
Each trial started with a screen prompting participants
to press a button to start reading the passages. Each con-
text sentence was presented in its entirety until participants
pressed a button. Then a fixation cross appeared for 500 ms,
after which the target sentence was presented word-by-
word in the center of the screen, for 350 ms plus 100 ms
inter-stimulus interval (RSVP).
In 25% of cases, a simple comprehension question
requiring a yes/no-answer appeared (e.g., Did J¨
orn go to
the kitchen?). Participants responded by pressing one of two
buttons within a maximal interval of 5000 ms. Participants
were instructed to read the passages for comprehension and
to avoid blinking during the word-by-word presentation of
the target sentence.
Electrophysiological recording and processing The EEG
was recorded by means of 26 Ag/AgCl scalp electrodes
placed according to the 10–20 system. The signal was refer-
enced and digitized at a sampling rate of 500 Hz. Data were
recorded using FCz as reference and AFz as ground. The
horizontal electro-oculogram (EOG) was monitored with
two electrodes placed at the outer canthus of each eye and
the vertical EOG with two electrodes above and below the
right eye. Electrode impedance was kept below 5 kfor
all scalp electrode sites, and below 10 kfor the EOG
electrodes. During recording, no on-line filters were used.
The EEG data were band-pass filtered offline with 0.03–
30 Hz (slope 12 dB) and re-referenced to the average of the
left and right mastoid electrodes. Epochs time-locked to the
target words were extracted with an interval of 200 ms pre-
ceding and 1200 ms following the onset of the target word
and semi-automatically screened for electrode drifts, ampli-
fier blocking, eye and muscle artifacts. Approximately 11%
of target word epochs were rejected due to artifacts, with no
significant differences between conditions. Averaged ERPs
time-locked to the critical word in each condition and for
each participant were computed on the artifact-free epochs
using a 200 ms pre-stimulus baseline.
Analyses
Nine representative electrode sites from anterior (F3, Fz,
F4), central (C3, Cz, C4), and parietal (P3, Pz, P4) regions
were included in the analyses. Based on previous reports
and visual inspection of the data, we computed mean ampli-
tudes for each condition and electrode in the 350-550 ms
(N400) time window and the 600–1000 ms (P600) time win-
dow. Within each time window, we performed ANOVAs
with length of event description (two levels: brief, elabo-
rate), type of boundary marked by the target (two levels:
fine, coarse), anterior-posterior (AP) distribution (three lev-
els: anterior, central, posterior sites) and lateral distribution
(three levels: left, midline, right sites) as within-subject fac-
tors. The Greenhouse-Geisser correction was applied to all
repeated measures with greater than one degree of free-
dom in the numerator. In such cases, the corrected pvalue
is reported.
Results
On average participants answered over 90% of the questions
correctly, indicating that they were engaged in the task. The
grand average waveforms at electrodes Cz and Fz are shown
in Figs. 1and 2, respectively. The results of the ANOVAs in
the N400 and P600 time windows are reported in Table 2.2
In the N400 time window, coarse boundary targets
elicited larger N400 amplitudes (M = -0.48 μV, SD = 3.06)
than fine boundary targets (M = 0.78 μV, SD = 2.85). The
ANOVA revealed a main effect of boundary type, and no
interactions with length or electrode sites (see Table 2). The
analysis also revealed a length ×AP ×laterality interaction,
possibly reflecting the onset of the P600 effect for elaborate
descriptions (see below). Follow-up analyses on the relevant
subsets of electrodes revealed that this effect was mostly
driven by midline electrodes (midline sites: length ×AP
interaction, F(2, 38) = 3.15, p<0.078, η2
p.14).
The analyses in the P600 time window revealed a length
×AP interaction. As shown by the topographic maps in
Fig. 2, elaborate contexts elicited a larger positivity than
brief contexts in anterior sites. The analysis of frontal elec-
trodes showed a significant effect of length (F(1,19) = 6.30,
p= 0.021, η2
p.25), with a larger positivity for elaborate
descriptions (M = 1.733 μV, SD = 3.59) compared to brief
descriptions (M = 0.625 μV, SD = 4.11). This main effect
was qualified by a length ×boundary ×laterality interac-
tion (F(2,38) = 3.74, p= 0.047, η2
p.16). Follow-up compar-
isons showed a significant main effect of length (F(1,19) =
5.66, p= 0.028, η2
p.23) and a length ×laterality interaction
(F(2,38) = 10.31, p<0.001, η2
p.35) for coarse boundary
targets, but no significant effects for fine boundary targets
(ps>0.1).3Central electrodes revealed only a main effect
2A linear mixed-effects model analysis of the data showed similar
effects. We report ANOVAs in line with common practices in the ERP
literature on language.
3Note that the fact that the two elaborate conditions seem not to differ
from each other in the P600 time window is likely due to compo-
nent overlap. Since the processes underlying the N400 and the P600
may overlap in time, the amplitudes of the two components are likely
to affect each other, as noticed in the literature (Brouwer & Crocker,
2017; Brouwer & Hoeks, 2013; Hagoort, 2003; Kutas, van Petten, &
Kluender, 2006; Thornhill & van Petten, 2012, for a related proposal,
see Tarren & Hell, 2014). In the 350-550 ms time window, coarse
boundary targets are more negative than fine boundary targets (the
N400 effect). This enhanced negativity may actually lead to a reduc-
tion of the positivity for coarse boundary targets in the 600–1000 ms
time window. In other words, it is likely that, any P600 effect for coarse
boundary targets compared to fine boundary targets is masked by the
presence of an N400 effect.
Mem Cogn
200 0 200 400 600 800 1000 1200
6420 24
Cz
Brief context / Fine boundary target
Brief context / Coarse boundary target
Elaborate context / Fine boundary target
Elaborate context / Coarse boundary target
Brief contexts Elaborate contexts
Coarse boundary target
minus
Fine boundary target
Coarse boundary target
minus
Fine boundary target
Fig. 1 Grand average ERP responses at electrode Cz. The topographic maps show the N400 effect of event boundary in brief and elaborate contexts
200 0 200 400 600 800 1000 1200
6420 2 4
Fz
Brief context / Fine boundary target
Brief context / Coarse boundary target
Elaborate context / Fine boundary target
Elaborate context / Coarse boundary targe
t
Fine boundary targets Coarse boundary targets
Elaborate context
minus
Brief context
Elaborate context
minus
Brief context
Fig. 2 Grand average ERP responses at electrode Fz. The maps show the frontal effect of description length for fine and coarse boundary targets.
Mem Cogn
Tabl e 2 ANOVAs on ERPs to target words across the N400 time
window and the P600 time window
Effect F(df) p η2
p
N400 time window: 350-550 ms
Boundary 32.90 (1, 19) .000 .63
Boundary ×AP 1.61 (2, 38) .221 .08
Boundary ×Lat 2.55 (2, 38) .091 .12
Boundary ×AP ×Lat 1.97 (4, 76) .137 .09
Length 0.61 (1, 19) .445 .03
Length ×AP 0.94 (2, 38) .355 .05
Length ×Lat 0.07 (2, 38) .936 <.01
Length ×AP ×Lat 3.74 (4, 76) .008 .16
Boundary ×Length 0.10 (1, 19) .761 <.01
Boundary ×Length ×AP 0.75 (2, 38) .409 .04
Boundary ×Length ×Lat 0.30 (2, 38) .749 .02
Boundary ×Length ×AP ×Lat 1.23 (4, 76) .307 .06
P600 time window: 600-1000 ms
Boundary 3.16 (1, 19) .092 .14
Boundary ×AP 0.26 (2, 38) .683 .01
Boundary ×Lat 0.39 (2, 38) .682 .02
Boundary ×AP ×Lat 1.59 (4, 76) .208 .08
Length 1.49 (1, 19) .238 .07
Length ×AP 4.66 (2, 38) .038 .20
Length ×Lat 0.55 (2, 38) .584 .03
Length ×AP ×Lat 2.92 (4, 76) .026 .13
Boundary ×Length 0.01 (1, 19) .918 <.01
Boundary ×Length ×AP 0.52 (2, 38) .515 .03
Boundary ×Length ×Lat 1.69 (2, 38) .207 .08
Boundary ×Length ×AP ×Lat 1.42 (4, 76) .234 .07
AP anterior–posterior distribution, Lat lateral distribution
of boundary (F(1, 19) = 4.41, p= 0.049, η2
p.19), with a
larger negativity for coarse boundary targets (M = 1.91 μV,
SD = 3.46) compared to fine boundary targets (M = 2.39
μV, SD = 3.24), suggesting that the N400 effect of bound-
ary type was long-lasting in central electrodes. Posterior
electrodes did not show any significant effect.
To summarize, the analyses revealed a broadly dis-
tributed N400 effect of event boundary type, with continu-
ing events eliciting a reduced N400 amplitude compared to
events initiating new activity. In addition, frontal electrodes
showed a positive shift that was sensitive to the length of the
event description and the type of boundary marked by the
target. In particular, elaborate contexts elicited a larger pos-
itivity compared to brief contexts. This effect was largely
driven by target events initiating new activity: the difference
between elaborate and brief contexts was significant for
coarse boundary targets, while it did not reach significance
for fine boundary targets.
Discussion
The goal of this ERP study was to examine the processing
of event boundaries during online language comprehension.
We tested short narratives in which the context introduced
an everyday activity by mentioning just one salient event
vs. multiple typical events of the superordinate activity.
The final sentence contained a target word referring either
to an event that could be expected to continue the cur-
rent activity (i.e., marking a fine event boundary) or to
a less predictable, unrelated event initiating new activity
(i.e., marking a coarse event boundary). The results revealed
an N400 effect of event boundary, with coarse boundaries
eliciting larger N400 amplitudes than fine boundaries. In
addition, there was an extended frontal positivity for elab-
orate descriptions involving multiple events compared to
brief ones mentioning just one sub-event. This effect was
largely driven by coarse event boundaries, that is, by target
words referring to less predictable, unrelated events.
We interpret the two effects as indexing two stages of
situation model construction: Retrieval of lexical semantic
information (N400) and updating/revision of the situation
model (P600) (see Brouwer et al., 2012).
While the functional interpretation of the N400 is still
a matter of debate (e.g., Lau, Namyst, Fogel, & Delgado,
2016; Lau et al., 2008, for an overview see Kutas & Feder-
meier, 2011), there is growing consensus that N400 ampli-
tude indexes processes associated with the ease of accessing
and retrieving conceptual knowledge stored in long-term
memory (e.g., Brouwer et al., 2012; Federmeier & Kutas,
1999; Kutas & Federmeier, 2000; Lau, Almeida, Hines, &
Poeppel, 2009; Thornhill & van Petten, 2012). According
to this view, N400 effects of predictability are generated
by retrieval mechanisms and reflect the degree to which
the preceding context activates conceptual knowledge asso-
ciated with the eliciting word though mechanisms such as
lexical or event schemas priming (e.g., Chow & Phillips,
2013; Chwilla & Kolk, 2005; Lau et al., 2016). In the cur-
rent study, the N400 effect of event boundary suggests that
the conceptual knowledge activated by the context primes
fine boundary targets more than coarse boundary targets.
Interestingly, the lack of an interaction with the type of
event description suggests that the two types of descrip-
tion activate the same amount of knowledge (i.e., the same
scripts or event schemas). It is this knowledge that facilitates
retrieval of related (i.e., marking fine event boundaries) as
opposed to unrelated (i.e., marking coarse event boundaries)
events.
Rather than modulating the N400 amplitude, the length
of the description influenced a late positive component,
which has been associated with processes involved in
discourse model updating (e.g. Brouwer et al., 2012;
Burkhardt, 2006,2007; Jouravlev et al., 2016; Schumacher,
Mem Cogn
2009, see also Donchin & Coles, 1988; Polich, 2007).
More specifically, according to Brouwer et al. (2012), late
positive components reflect the “construction, revision, or
updating of a mental representation of what is being com-
municated” (Brouwer et al., 2012, p. 137; see also Brouwer,
Crocker, Venhuizen, & Hoeks, 2016). Differences in ampli-
tude, latencies, or scalp distributions reflect the different
sub-processes that may underlie the construction of these
mental representations (e.g., Brouwer & Hoeks, 2013).
Frontal positivities have been found to be elicited in situ-
ations where comprehenders’ predictions about upcoming
lexical items are disconfirmed (DeLong, Urbach, Groppe,
&Kutas,2011; Federmeier, Kutas, & Schul, 2010; Feder-
meier, Wlotko, Ochoa-Dewald, & Kutas, 2007; Thornhill
& van Petten, 2012; Van Petten & Luka, 2012). In the
present study, however, both brief and elaborate contexts
were quite low-constraining. They did not generate high
expectations for a specific word, possibly because they
consisted of relatively brief (three-sentence) stories rather
than rich and elaborate narratives.4Furthermore, previous
findings from research on predictive inferences in text com-
prehension (i.e., inferences about what should occur next in
a story) have shown that such inferences are not typically
constructed online, unless the predictable event is highly
constrained by the context (e.g., Magliano, Baggett, John-
son, & Graesser, 1993; McKoon & Ratcliff, 1986; see also
Graesser, Singer, & Trabasso, 1994). The frontal positivity
in the current study is more likely related to expectations
for a type of event boundary rather than for a specific event
marking that boundary. Our cloze data show that unrelated
events appeared more often following elaborate compared
to brief contexts, suggesting that the activity described in
elaborate contexts was more likely to be perceived as com-
pleted. Similar to what has been described for the perception
of partial vs. complete events in Zacks (2010), in elabo-
rate contexts script knowledge about the current activity
becomes less helpful to generate accurate predictions about
future events. It is in these situations that comprehenders
anticipate they will need to initiate an updating process as
soon as new information is encountered, as predicted by
Event Segmentation Theory (Zacks et al., 2007). Consis-
tent with this, we found that elaborate contexts elicited a
(frontal) P600 effect compared to brief contexts, starting as
early as 350 ms, that is, already in the N400 time window
(see Fig. 2). We interpret this effect as indexing aspects of
the updating process, consistent with previous work (see
4Contextual constraint is defined as the cloze probability of the most
highly preferred (or best) completion (e.g., Kutas & Hillyard, 1984),
which in our items was only 35% following brief contexts and 32%
following elaborate contexts.
also Burmester, Spalek, & Watenburger, 2014; Kaan, Dal-
las, & Barkley, 2007; Wang & Schumacher, 2013). The fact
that the effect becomes stronger for coarse event bound-
aries compared to fine event boundaries suggests that the
updating process is more demanding when the target is fully
unrelated to the activity described. This leads comprehen-
ders to reset the old model and construct a new one (similar
to the global updating processes outlined, for example, in
Bailey & Zacks, 2015; Kurby & Zacks, 2012). For fine
boundary targets, in contrast, the updating process is less
demanding, either because the new model will contain more
predictable information (recall that the cloze data showed
a higher percentage of related compared to unrelated con-
tinuations in elaborate contexts, although unrelated events
were produced more often than in brief contexts), or because
comprehenders realize that the old model is still related to
the new one and requires only incremental updating (see
also, e.g., Zwaan, Langston, & Graesser, 1995; Zwaan et al.,
1995).
Brief contexts, on the other hand, did not produce visible
effects in the P600 component. This is consistent with the
observation that brief contexts are more strongly predictive
of events continuing the current activity, and are therefore
less likely to trigger anticipation of (global) updating pro-
cesses. Encountering an unexpected coarse boundary target
in these contexts results in a more sustained N400 effect rela-
tive to fine boundary targets (see Fig. 1), reflecting enhanced
difficulty in accessing and retrieving the unexpected event
from long-term memory. This might have masked or, at the
very least, delayed any updating process indexed by the
P600. Thus, while EST makes no clear predictions for the
mechanisms involved in this particular case, we suggest that
our results are still broadly consistent with it.
In sum, the present findings provide electrophysiologi-
cal support for EST (Zacks et al., 2007), which proposes
that, for both event perception and narrative comprehen-
sion, mental representations of ‘what is happening now’
are updated in response to event boundaries (e.g., Speer &
Zacks, 2005; Speer et al., 2007; Zacks et al., 2009).
The current results add to the growing body of evidence
that processes associated with the construction and revision
of situation models are reflected in the family of late pos-
itive components, as proposed by Brouwer et al. (2012).
Future work is required to assess whether the (frontal) dis-
tribution of the effect can be taken to reflect one of the
different sub-processes involved in the construction of these
mental representations (see also Brouwer & Hoeks, 2013).
On a more general level, the present study shows that com-
prehenders are sensitive to the structure of events, providing
further evidence that stereotyped knowledge about every-
day activities, so-called event schemata or scripts (Schank
& Abelson, 1977), influences comprehenders’ expectations
at early stages of processing.
Mem Cogn
Acknowledgments This research was supported by the SFB/CRC
1102 “Information density and linguistic encoding” (Project A1)
awarded to MC by the Deutsche Forschungsgemeinschaft (DFG).
We thank Joseph Magliano and three anonymous reviewers for their
helpful comments and suggestions.
Open Access This article is distributed under the terms of the
Creative Commons Attribution 4.0 International License (http://
creativecommons.org/licenses/by/4.0/), which permits unrestricted
use, distribution, and reproduction in any medium, provided you give
appropriate credit to the original author(s) and the source, provide a
link to the Creative Commons license, and indicate if changes were
made.
Appendix
Sample items with English translation
We report only elaborate contexts. Brief contexts included
only the final action mentioned in elaborate contexts (see
Table 1). Target words: fine boundary / coarse boundary.
(1) Sebastian ist sehr hungrig. Er geht in die K ¨
uche,
wo er sich erst H¨
uhnchen, dann Sauce und dann
Nudeln kocht. Dann beginnt er mit dem Verzehren
/W
¨
aschewaschen, wof¨
ur er 30 Minuten braucht.
(Sebastian is very hungry. He goes to the kitchen,
where he cooks first chicken, then sauce, and then
noodles. Then he begins to eat / do the laundry, for
which he needs 30 minutes.)
(2) Christine ist mit der Vorlesung fertig. Sie geht in die
Bibliothek, wo sie erst Magazine, dann Kataloge und
dann B¨
ucher einsortiert. Dann beginnt sie mit dem
Lesen / Einkaufen, wof¨
ur sie ... (Christine has fin-
ished the lecture. She goes to the library, where she
sorts first magazines, then catalogues, and then books.
Then she begins to read / to shop, for which ...)
(3) Katrin kommt von einer WG-Party. Sie geht in das
Bad, wo sie erst ihren Nagellack, dann ihren Lid-
schatten und dann ihren Lippenstift entfernt. Dann
beginnt sie mit dem Duschen / B¨
ugeln, wof¨
ur sie ...
(Katrin comes home from a WG-Party. She goes to
the bathroom, where she removes first her nail polish,
then her eye shadow, and then her lipstick. Then she
starts to shower / to iron ...)
(4) Brigittes Bettw¨
asche ist schmutzig. Sie geht in
Schlafzimmer, wo sie erst die Bettdecke, dann das
Kopfkissen und dann die Matratze neu bezieht. Dann
beginnt sie mit dem Waschen / Blumengießen, . . .
(The bedclothes of Brigitte are dirty. She goes to the
bedroom, where she re-covers first the blanket, then
the pillow, and then the mattress. Then she starts to
do the laundry / to water the flowers, ...)
(5) Christian muss f ¨
ur eine Klausur lernen. Er setzt sich
an den Schreibtisch, wo er sich erst ein Skript, dann
ein Paper und dann ein Lehrbuch durchliest. Dann
beginnt er mit dem Notieren / Kartenspielen, . . .
(Christian has to study for an exam. He sits down at
his desk, where he reads first a script, then a paper,
and then a textbook. Then he starts to take notes / to
playcards, ...)
(6) Mayte hat sich am Knie verletzt. Sie geht in die
Apotheke, wo sie sich erst ein Desinfektionsmit-
tel, dann eine Wundauflage und dann einen Verband
kauft. Dann beginnt sie mit dem Verarzten / Eisessen,
. . . Hat Mayte sich am Arm verletzt? (Mayte has
injured her knee. She goes to the pharmacy, where she
buys first a germicide, then mull, and then a bandage.
Then she starts to patch up / to eat an ice cream, .. .
Has Mayte injured her arm?)
(7) Sabine bereitet das Weihnachtsessen vor. Sie geht in
die K¨
uche, wo sie erst das Rotkraut, dann die Kartof-
feln und dann die Gans vorbereitet. Dann beginnt sie
mit dem F¨
ullen / H¨
akeln, . . . (Sabine prepares the
Christmas dinner. She goes to the kitchen, where she
prepares first red cabbage, then potatoes, and then
the goose. Then she starts to stuff / crochet, ...)
(8) Hans m ¨
ochte seine Frau ¨
uberraschen. Er geht in
die K¨
uche, wo er erst das Besteck, dann die Gl¨
aser
und dann die Teller sp¨
ult. Dann beginnt er mit dem
Weg r ¨
aumen / Briefschreiben, . . . (Hans wants to
surprise his wife. He goes to the kitchen, where he
cleans first the cutlery, then the glasses, and then the
plates. Then he starts to clear /writealetter, ...)
(9) Jan ist vom Laufen ganz verschwitzt. Er geht in die
Dusche, wo er sich erst die F¨
uße, dann die Arme
und dann die Haare w¨
ascht. Dann beginnt er mit dem
Rasieren / Saugen, . . . (Jan is all sweaty from run-
ning. He goes to the shower, where he washes first his
feet, then his arms, and then his hair. Then he starts
to shave/hoover, ...)
(10) Sophia f¨
ahrt in Urlaub. Sie geht zum Kleiderschrank,
wo sie erst ihren Bikini, dann ihren Sommerrock und
dann ihre Flip-Flops herausnimmt. Dann beginnt sie
mit dem Packen / Fensterputzen, . . . (Sophia goes on
holidays. She goes to the wardrobe, where she takes
first her bikini, then her skirt, and then her flip-flops.
Then she starts to pack / clean the windows, ...)
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