Clinical Linguistics & Phonetics, November 2014; 28(11): 812–825 ß 2014 Informa UK Ltd. ISSN: 0269-9206 print / 1464-5076 online DOI: 10.3109/02699206.2014.910555

An electrophysiological investigation of discourse coherence in healthy adults YAEL NEUMANN1, BAILA EPSTEIN2, YAN H. YU3, APRIL A. BENASICH4, & VALERIE SHAFER5 1

Department of Linguistics and Communication Disorders, Queens College, City University of New York, USA, 2Department of Speech Communication Arts and Sciences, Brooklyn College, City University of New York, USA, 3Department of Communication Disorders and Sciences, William Paterson University of New Jersey, USA, 4Center for Molecular and Behavioral Neuroscience, Rutgers University, The State University of New Jersey, USA, and 5Department of Speech-Language-Hearing Sciences, The Graduate Center, City University of New York, USA (Received 21 August 2013; revised 26 March 2014; accepted 28 March 2014)

Abstract This study used event-related potentials (ERPs) to investigate discourse-coherence processing. Because there are scant data on ERP indices of discourse coherence in typical adults, it is important to study a non-clinical population before examining clinical populations. Twelve adults listened to a story with sentences in a coherent versus incoherent order. Sequences of nonsense syllables served as a control. ERPs in the 200–400 ms time window, reflecting phonological and lexical processing, and in the 600–900 ms time window, reflecting later discourse processing for integration, were investigated. Results revealed a right anterior and posterior positivity that was greater for coherent than for incoherent discourse during the 600–900 ms time window. These findings point to an index of discourse coherence and further suggest that ERPs can be used as a clinical tool to study discourse-processing disorders in populations with brain damage, such as aphasia and traumatic brain injury.

Keywords: Aphasia, discourse coherence, event-related potentials, lateralized anterior positivity (LAP)

Introduction Discourse is the term used to describe the use of spoken or written language for communication that includes any unit longer than a sentence. Coherence describes the overall relatedness of elements of a linguistic text. Discourse coherence is a complex cognitive and social phenomenon in language communication that requires the individual to interpret a speaker or writer’s intended meaning in generating discourse (Brown, 1983). This macro-linguistic skill involves not only processing information at many levels, from perception to construction of the message, but also

Correspondence: Yael Neumann, Department of Linguistics and Communication Disorders, Queens College, City University of New York, 65-30 Kissena Boulevard, Queens Hall, Room 315-F, Queens, NY 11367, USA. Tel: +71 89975061. Fax: +71 89972873. E-mail: [email protected]

ERPs of discourse coherence 813 integration of one’s socio-cultural knowledge about the world within a given situational context while making appropriate inferences about the speaker’s meaning. These features change fluidly based on particular contexts and may rely less on linguistic aspects, such as grammar, and more on social rules and analysis of sequences of actions (Labov, 1970). Of particular interest to the current study, coherent discourse is not an unordered concatenation of linguistic units (specifically clauses and sentences). Speakers/writers order sentences in such a manner to allow the listener to retrieve a coherent message. Theoretical models of discourse processing There are three main models proposed in the psycholinguistic literature to account for discourse processing, namely, memory-based (McKoon, Gerrig, & Greene, 1996; Myers & O’Brien, 1998), constructionist (Graesser, Singer, & Trabasso, 1994), and construction-integration (Kintsch, 1998; van den Broek, Young, Tzeng, & Linderholm, 1999) models. The memory-based model describes how information in memory that matches the discourse content is quickly and automatically activated. This activation is broad-based, activating multiple related concepts, and is unrestricted, in that it does not require strategic processing. The degree of activation of the concepts in memory depends on how much they overlap with the discourse content. In contrast, the constructionist model proposes that there is strategic processing involved in the memory search. Thus, particular concepts are actively searched for in memory so that inferences and comprehension of the discourse can be enhanced. The current view, the construction-integration model, proposes a two-phase model because both theories are important in accounting for inferences made in discourse processing. The first phase involves broad activation of linguistic information in memory, as explained in the memorybased view, and the second phase involves an active search of only the most relevant information from the broad-based information activated in the first phase, as proposed in the constructionist view. Under this integrated model, a mismatch between expectations for the discourse generated by prior knowledge, specifically, the prior utterances, and the current input, should be reflected in event-related potentials (ERPs). Event-related potential (ERP) studies of discourse processing Few ERPs studies have focused on discourse processing; those that have, examined either the lateralized anterior positivity (LAP) or N400 components. ERPs are thought to reflect certain linguistic features and the LAP is a component that is thought to reflect discourse processing. On the other hand, modulation of the N400, a relative negativity peaking around 400 ms, is thought to be linked to the processing of meaning (Kutas & Hillyard, 1980). The LAP is a slow potential that begins at approximately 200 ms post-stimulus onset and can continue for several hundred milliseconds (Shafer, Kessler, Schwartz, Morr, & Kurtzberg, 2005; Neumann, Epstein, and Shafer, in preparation). Shafer and colleagues observed a left and right LAP time-locked to sentence onsets when young adult participants were told to attend to an auditory story. The left and right LAP were attenuated when participants listened to nonsense syllables. In contrast, when participants were told to attend to a silent movie while ignoring the auditory story, the right LAP was attenuated whereas the left LAP was maintained. This pattern suggested that the right LAP is an index of discourse processing, and the left LAP is an index of a more automatic process of structure building. Furthermore, the modulation of the right LAP showed a similar pattern when attended versus ignored and in story versus nonsense contexts whether time-locked to the function word ‘‘the’’ or to the content word ‘‘cats’’ at sentence onset (Neumann et al., in preparation). This supported the use of the right LAP as an index of discourse processing, which

814 Y. Neumann et al. is distinct from the N400 component, as the N400 is differentially modulated by function versus content words (Neville, Mills, & Lawson, 1992). Another body of research on discourse processing, although taking a less direct view than the LAP studies by using stimuli of only a few sentences in length, has used a design that results in modulation of a posterior negativity, the N400 (Kutas & Federmeier, 2011). N400 modulation is seen as less negativity to words that are more predictable on the basis of semantic or discourse information (DeLong, Urbach, & Kutas, 2005; Federmeier & Kutas, 1999; Federmeier & Laszlo, 2009; Federmeier, McLennan, De Ochoa, & Kutas, 2002; Kutas & Federmeier, 2011; Kutas, Federmeier, Staab, & Kluender, 2007; Laszlo & Federmeier, 2009; van Berkum, Brown, Zwitserlood, Kooijman, & Hagoort, 2005; van Berkum, 2008; Wicha, Moreno, & Kutas, 2004). Of particular importance, N400 modulation can be used to infer the difficulty of lexical access and/or semantic integration for any word. For example, Holcomb, Coffey and Neville (1992) showed decreased negativity to words across a sentence, presumably because word meaning becomes increasingly more predictable across a sentence. Modulation of the N400 can also occur from both local and relatively global cues. For example, St. George, Manes and Hoffman (1994) had participants read ambiguous paragraphs that seemed illogical unless provided with a disambiguating title. In both the titled and untitled conditions, the N400 was modulated by prior information. The difference, however, was that the N400 amplitude was smaller for the titled than the untitled condition because the title constrained the expected meaning of the stimuli, making it more predictable. This finding suggested that discourse schema facilitated integration of each word. Similarly, other studies have found N400 modulation to contextual effects. This was measured by manipulating semantic, syntactic, phonological, and/or orthographic information in discourse processing. For example, when a participant is provided with the sentential context, one is able to predict information about upcoming words, thereby accelerating lexical access and semantic integration (DeLong, Urbach, & Kutas, 2005; Federmeier & Kutas, 1999; Federmeier et al., 2002; Laszlo & Federmeier, 2009; Wicha, Moreno, & Kutas, 2004; van Berkum et al., 2005). The predictable words become activated in the brain even before they are presented, thus facilitating comprehension and reducing processing demands (Kamide, Altmann, & Haywood, 2003; Lau, Stroud, Plesch, & Phillips, 2006; Schwanenflugel & LaCount, 1988). In sum, there is limited research reporting on discourse coherence processing using ERPs. However, findings from two bodies of literature indicate: (1) a right LAP related to meaningful discourse processing, and (2) an N400 effect in response to the predictability of sentential context. Although the N400 has been more extensively studied than the LAP, research has shown that this posterior negativity, i.e. the N400, can be examined across sentences using a number of different designs, including the design used to elicit the anterior positivity, i.e. the LAP. A goal of the current study was to further examine the LAP to determine to what extent this component is sensitive to more fine-grained aspects of discourse processing. Importance of discourse coherence in clinical populations Clinical populations with brain damage, such as aphasia and traumatic brain injury (TBI), demonstrate impaired discourse coherence processing, which negatively impacts their overall communicative competence. Aphasia is a language disorder experienced post-stroke and TBI is a cognitive-communication disorder due to intra-cranial injury. Language skills secondary to brain deficits like these can be difficult to assess, specifically because of the impairment to communication. Research has shown that adults with aphasia have difficulties in understanding details in discourse (Wegner, Brookshire, & Nicholas, 1984) and their verbal output is highly fragmented and tangential, with minimal connections between discourse units (Coelho &

ERPs of discourse coherence 815 Flewellyn, 2003; Glosser & Deser, 1990). Adults with TBI show difficulty understanding and producing standard communication acts and non-literal language, such as irony (Angeleri et al., 2008; Martin & McDonald, 2005). They also produce incoherent narratives with frequent interruptions and extraneous utterances, which makes their discourse vague and inefficient (Hartley & Jensen, 1992; Marini et al., 2011). Furthermore, they have difficulties identifying communication breakdowns, engaging in conversational jokes and asking questions (Bogart, Togher, Power, & Docking, 2012). There is a need for further research to advance our understanding of discourse coherence in these clinical populations, but such research presents several challenges. One is the need for a more refined view of how to conceptualize coherence using testable models (Armstrong, 2000). This is important, as it will allow researchers to construct hypotheses that can be tested against a proposed model of discourse processing. The second issue relates to the lack of a systematic investigation of the psychometric strength of a variety of tools (e.g. rating scales, total counts, and coherence violations) used in assessing this abstract and complex construct of discourse coherence (Christiansen, 1995; Coelho & Flewellyn, 2003; Glosser & Deser, 1990; Olness, Metteson, & Stewart, 2010; Stark, 2010; Ulatowska, Olness, & Williams, 2004; Ulatowska, Reyes, & Santos, 2010). The inconsistency of findings from investigations of discourse processing in clinical populations might be due to differences in the testing measures used rather than to true differences across studies. One reason for inconsistent findings is that behavioral assessment of discourse skills requires a number of high-level processes (e.g. working memory, attention, language comprehension) and deficits to any of these could result in poor performance. In addition, clinical populations with language deficits present with difficulties in understanding task directions or even in completing tasks. Thus, performance on tasks might be confounded by a number of factors unrelated to discourse processing itself. Electrophysiology is a valuable tool that can address the methodological and task issues in studying discourse coherence in clinical populations, as it measures continuous sensory and cognitive processing without requiring an overt behavioral response. Brain processing data can be collected while participants simply read or listen for comprehension without needing discrete behavioral measures or the use of tasks that might comprise secondary aspects other than that of the variable of interest. The purpose of this study was to examine the timing and topography of brain activity associated with discourse coherence using discourse-level stimuli. More specifically, our goal was to examine modulation of ERPs in coherent versus less-coherent sentences in a discourse context. The discourse paradigm is an innovative design in comparison to prior ERP studies of discourse integration, and may be more ecologically valid for examining discourse processing in disordered populations. Most previous ERP studies of language processing have used single sentences, or at most, two to three sentences. We focused on the LAP component observed in a previous study using this type of design (Shafer et al., 2005). Two discourse conditions were examined: one in which the utterances of the discourse were in a coherent sequence (Normal order) and a second condition wherein the order of the utterances was randomized (Random order), resulting in an incoherent sequence of utterances. Meaningless nonsense syllables were included as a control condition in order to compare coherent and incoherent processing to brain processing for a condition requiring no semantic processing. We also examined posterior sites because it was possible to observe N400 modulations given that the lexical words were more predictable in the coherent compared to incoherent discourse. Because the LAP has been examined in only one published study using a natural-discourse paradigm, in the current experiment, we focused on typical adult individuals with no history of speech or language disorders. The aim of this experiment was to determine whether clear differences in processing coherent and incoherent text would be found in this healthy, adult group.

816 Y. Neumann et al. ERPs at the anterior and posterior sites were examined in early (200–400 ms) and later (600–900 ms) time windows to gauge the time course of processing. The earlier time window was expected to reflect phonological and lexical processing and the later time window to reflect discourse integration. We predicted a stronger right than left hemisphere effect for the later time window given that discourse processing appears to have stronger right hemisphere sources (Beeman & Chiarello, 1998; Marini, 2012; Robertson et al., 2000; St. George, Kutas, Martinez, & Sereno, 1999; Wlotko & Federmeier, 2007). Within the right hemisphere, we predicted that for the discourse context there would be a condition effect, characterized by a greater LAP for the coherent (normally-ordered sentences), as compared to the incoherent (randomly ordered sentences). If seen, the increased LAP would indicate integration of the semantic information. Absence of the LAP would indicate that participants have recognized that the sentences are not related and will not attempt to integrate semantics across them. For the nonsense control context, no LAP was expected, since the sentences were meaningless. An additional prediction was that we might see greater negativity (N400) over posterior sites to incoherent as compared to coherent sentences, because lexical access and semantic integration within a sentence would be more difficult in the condition where there were no semantic cues from the prior sentence. Methods Participants Twelve healthy young adults (3 males, 9 females), ranging in age from 23 to 41 years of age (M ¼ 30.08 years, SD ¼ 6.46 years), participated in the study. An equal number of males and females were not included as there was no reason to expect gender differences in the absence of literature indicating male-female differences in discourse processing. All participants were native American-English speakers, passed a hearing screening, and had no reported history of speech, language, or learning disorders. Stimuli and experimental conditions Discourse material consisted of a popular children’s story about a curious little kitten exploring different rooms in a house (Hayward, 1982; Neumann et al., in preparation; previously recorded for use in discourse processing studies by Shafer, Shucard, Shucard, & Gerken, 1998; Shafer, Schwartz, Morr, Kessler, & Kurtzberg, 2000; Shafer et al., 2005). The story was read in a natural story-telling style in a woman’s voice. Stimuli consisted of 77 phrases and sentences that varied in length from two to ten words. The total duration of the story was under 10 minutes and the total duration of the study (including coherent and incoherent conditions and nonsense contexts) was approximately 28 minutes. In order to maintain participants’ attention to the story, the story was divided into four approximately equal sections with one question at the end of each section. Additionally, session length and stimulus complexity were geared for an early elementary grade level and were gender-neutral in anticipation for future use with both adult and child clinical populations. Stimuli were recorded by a female native speaker of American-English. In order to control for co-articulation effects, editing was conducted so that the word the was followed by a voiceless stop (/p, b, t, k/) or fricative-initiated consonant. The same exemplar of the was used at the onset of sentences, across both the discourse and nonsense conditions, to reduce variability in ERPs related to acoustic-phonetic properties. Naı¨ve adult listeners judged the edited discourse version as natural sounding. In the nonsense context, five different syllables, ko, ki, gu, po, bu, excised from a

ERPs of discourse coherence 817 1) Normal-order Condition The curious little kitten noticed a piercing ringing sound. * She saw another tiny door * The piercing noise was coming out the tiny door * The cat was curious about that sound *… 2) Random-order Condition The bedsit was cluttered with things she had not seen before * The curious little kitten noticed a piercing ringing sound * A tall lamp * A plushy slipper *… Note: *=1500 ms Figure 1. Samples of ‘‘The Curious Little Kitten’’ story presented in Normal-order and Random-order story conditions. Only the in sentence initial position was time-locked for later analysis.

nonsense word version of the discourse, were used to construct nonsense syllable sequences that followed the function word the (e.g. the ki ko po bu the bo gu ki po etc.). These nonsense strings had the same length as that of phrases/sentences in the discourse condition, which were approximately 4–7 syllables in length. The inter-stimulus interval was 1.5 seconds before the at sentence onset. The discourse was presented in two conditions: (1) Normal-order, in which sentences were meaningfully ordered, and (2) random-order, in which sentences were randomly ordered. Note that the order of the sentences with nonsense syllables, which served as a control, could not be judged to be in normal or random order. All stimuli were recorded in the same session so that pitch range, loudness and quality of voice were closely matched. The electroencephalogram (EEG) was time-locked to the stimulus the at sentence initial position for later off-line analysis. There were 31 trials for each condition. The loudness level of the discourse stimuli ranged from 65 to 80 dB SPL and the word the was 72 dB SPL (Figure 1 shows stimulus samples.)

EEG recording A 65-channel Geodesic Sensor Net (Electrical Geodesics Inc.; EGI, Eugene, OR), consisting of 65 silver/silver-chloride (Ag/AgCL) plated electrodes in sponges, was applied to the scalp at relative locations indicated in Figure 2. The EEG was amplified using an EGI 200 amplifier. A Geodesic software system (NetStation version 4.1, Eugene, OR) in continuous mode was used to acquire the data at a sampling rate of 250 Hz per channel with a bandpass filter of 0.1–100 Hz for later off-line processing. The vertex (Cz) served as the reference. Electrode impedances were kept under 40 k s, ensuring adequate contact with the scalp (Ferre, Luu, Russell, & Tucker, 2001). During acquisition, the participant was observed via a video camera to monitor the participant’s state and artifacts due to excessive muscle movement, defective electrode contact, or electrical interference. The continuous EEG was processed off-line using a low-pass filter of 0.3–30 Hz and segmented into epochs with an analysis time of 900 ms post-stimulus and 100 ms pre-stimulus baseline. Epochs were baseline corrected, followed by rejection of epochs with excessive artifacts (greater than +/100 mV) (Figure 2).

Procedure After signing an informed consent form, participants were fitted with a 65-channel Geodesic Sensor Net. The electrodes were pre-soaked in a saline solution for approximately five minutes

818 Y. Neumann et al.

Figure 2. A 65-channel Geodesic Sensor net configuration demonstrating relative scalp locations. The sites of interest (left anterior 16; left posterior 28; right anterior 57; and right posterior 46) are shaded.

and then placed on the scalp. Participants were seated in a comfortable chair in a 90  100 electrically shielded booth. Participants were asked to listen to a four-part story presented free-field with two speakers placed approximately 130 cm apart above and in front of the speaker. They were also presented with one content-related question after each part (e.g. What did the little kitten see in the bedroom?) followed by a picture of four items with the instruction to point to the correct object (e.g. ‘‘lamp’’). E-prime 1.1 software (Schneider, Eschman, & Zuccolotto, 2002) was used to present the stimuli. There were two experimental conditions for the discourse context (Normalversus Random-order), and there was a nonsense control context. Participants were presented with one discourse-order condition (e.g. Normal) and related questions followed by a nonsense condition, and then the second discourse-order condition (e.g. Random) and related questions followed by a nonsense condition. The order of presentation of the experimental conditions was counterbalanced across participants.

ERPs of discourse coherence 819 Analysis procedures Analyses were designed to measure ERPs following processing of the initial word the at each sentence onset in each of the ERP conditions (Normal- versus Random-order; Nonsense). As there is scant information in the literature about the sites of interest related to discourse coherence, we determined our choice of electrodes for analysis based on the findings of Shafer et al. (2005) and Neumann et al. (in preparation) and by examining spline-interpolated topographical plots and selecting the regions of most prominent activity (Bentin, MouchetantRostaing, Giard, Echallier, & Pernier, 1999). In selecting sites, we examined correlations among pairs of neighboring electrodes but found that they did not have sufficiently high correlations (of at least r ¼ 0.80) in both Normal- and Random-order conditions to justify averaging across them. Thus, for statistical analyses we selected one electrode site per region that was closest to each foci and that had the best signal-to-noise ratio (relative to baseline noise) from the given site cluster. These sites were: left anterior 16; left posterior 28; right anterior 57; and right posterior 46. Note that these four sites are close to the 10–10 electrode sites used in Shafer et al. (2005). Examination of standard deviations across participants suggested greater variance in response to the sentences of the Random-order condition. To test this, the variance of both conditions in all four regions (left anterior, left posterior, right anterior, right posterior) was examined in an F-test of variance. Results indicated a significant difference between the Normal- and Random-order conditions at the left anterior (p ¼ 0.006) and left posterior (p ¼ 0.01) regions, with the Randomorder condition showing greater variance, but not at the right anterior and right posterior regions (p40.05). Given this finding and the expectation of observing discourse processing over the right hemisphere, further analyses were conducted at the right hemisphere sites only. The previous paper (Shafer et al., 2005) used a nose reference, whereas the current paper used an average reference (and did not include a nose electrode site). In Shafer et al. (2005), the anterior sites were more positive than the mastoid sites in the discourse conditions, but in the nonsense condition the site difference was smaller or reversed. Thus, the best way to determine whether the pattern of processing in the current paper was similar to that found in the previous paper was to include both the anterior and mastoid sites in an ANOVA with site as a factor. ANOVAs with Condition (Normal- versus Random-order)  Time (200–300 and 300– 400 ms)  Site (right anterior, right posterior, and right mastoid), and Condition (Normalversus Random-order)  Time (600–700, 700–800, and 800–900 ms)  Site (right anterior, right posterior, and right mastoid) were performed. Additionally, a Condition: (Discourse versus Nonsense)  Time (600–700, 700–800, and 800–900 ms)  Site (right anterior, right posterior, and right mastoid) repeated measures ANOVA was computed to determine whether the processing of the discourse context was significantly different than that for the nonsense context.

Results Behavioral analyses Participants demonstrated at least 90% accuracy in answering the questions related to the ‘‘The Curious Little Kitten’’ story, thereby demonstrating that they were attending to the story. Statistical analyses Early processing For the discourse comparisons, the ANOVA on the 200–400 ms time window revealed no significant findings including condition (p40.05).

820 Y. Neumann et al. Late processing For the discourse comparisons, the ANOVA on the 600–900 ms time window revealed a significant interaction of Condition  Time  Site (F (4, 44) ¼ 6.59, p ¼ 0.0003, p2 ¼ 0.375). Tukey’s post-hoc comparisons of this three-way interaction revealed that this was due to a significantly larger positivity for the Normal-order relative to the Random-order condition from 600–700 ms in the right posterior region (p50.0005) and from 800–900 ms in the right anterior region (p50.0005), whereas the Random-order condition was more positive at the right mastoid during each of the three time windows (p50.002). Eight out of 12 participants demonstrated this pattern of a larger positivity for the Normal- relative to the Random-order condition in at least one of the two regions. No other main effects or interactions were significant (p40.05). Figure 3 depicts the grand average waveforms, using an average reference, of the Normal- and Random-order Discourse conditions at the anterior and posterior sites and Figure 4 demonstrates their corresponding Nonsense control conditions and the mastoid comparison. Meaningful versus nonsense processing The comparison of the Normal-order Discourse condition to that of the Nonsense (control) condition revealed a significant interaction of Condition  Time  Site (F (4, 44) ¼ 4.95, p ¼ 0.002, p2 ¼ 0.311) (Figure 4). Tukey’s post-hoc test of this three-way interaction revealed that this effect was due to a significantly larger negativity for the Normal- relative to the Nonsense condition from 800–900 ms in the right posterior region (p50.0005) and in each of the three time windows at the right mastoid (p50.002). No other main effects or interactions were significant (p40.05). A comparison of the Random-order Discourse condition to that of the Nonsense (control) condition revealed no significant differences (p40.05). In summary, in comparing the Normal-order versus Random-order Discourse conditions, there was no significant difference between these conditions in the early 200–400 ms time window, yet there was a greater positivity for the Normal-order compared to the Random-order condition from 600–700 ms at the right posterior site and from 800–900 ms at the right anterior site. The Random-order condition was more positive than the Normal-order condition in all three time windows at the right mastoid. Additionally, a comparison of the Discourse conditions with

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Figure 3. Grand average waveforms (n ¼ 12), using an average reference, of the Normal-order and Random-order Discourse conditions in the anterior and posterior scalp regions in the right hemisphere. A significantly larger positivity for the Normal-order relative to the Random-order condition is apparent from 600–700 ms in the right posterior region and from 800–900 ms in the right anterior region. (Note: Waveforms were downsampled by 40 ms for visualization.)

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Figure 4. Grand average waveforms (n ¼ 12), using an average reference, of the Normal-order and Random-order Discourse conditions and their corresponding Nonsense control conditions in the anterior and posterior scalp regions in the right hemisphere. A significantly larger negativity is apparent for the Normal-order Discourse relative to the Nonsense (Control) condition from 800–900 ms in the right posterior region and in each of the three time windows at the right mastoid. The right anterior site is clearly more positive than the right mastoid in the Normal-order Discourse relative to the Nonsense (Normal-order Control) condition. (Note: Waveforms were downsampled by 40 ms for visualization.)

the Nonsense (control) condition revealed greater negativity for the Normal-order relative to the Nonsense comparison from 800–900 ms at the right posterior site and in each of the three time windows at the right mastoid. The Random-order Discourse comparison with the Nonsense condition, however, did not reveal any significant condition effects.

Discussion The time course of discourse coherence processing in healthy young adults was investigated using event-related potentials. Our findings revealed a significant difference in the pattern of processing coherently and incoherently ordered sentences at right hemisphere sites. Specifically, increased negativity was found over the right posterior site and positivity over the right mastoid site to the incoherent (random ordered) compared to the coherent (normal ordered) discourse sentences. In addition, the normal-order discourse sentences showed a different pattern of processing from the nonsense condition, whereas the random-order sentences did not. These differences in patterns of processing coherent and incoherent discourse suggest that this type of paradigm could be used to investigate discourse processing in disordered populations. Below we provide explanations for the current findings.

822 Y. Neumann et al. Phonological processing No differences in processing were found in the early time interval (200–400 ms) at the right anterior, posterior or mastoid sites, suggesting that listeners were performing similar processing of these speech stimuli in the cortical regions indexed by these sites. We did not expect differences in phonological processing between the normal and random ordered sentence conditions, because these conditions consisted of the same phonological material. However, we did expect to see a difference between the discourse conditions and the nonsense condition during this time window because the phonological patterns are somewhat different (short consonant-vowel syllables for the nonsense condition). Shafer and colleagues (2005) observed a significant difference between the discourse and nonsense conditions from 200–400 ms to the same stimuli. However, more trials were delivered in that study because the discourse was presented twice, and thus the signal to noise ratio may have been better, allowing for more subtle differences in processing to be observed. Additionally, the previous study from 2005 used a nose reference. We re-referenced the data from the previous study to an average reference and found that this diminished the difference between the ERPs in the discourse and nonsense contexts at the lateral anterior sites (e.g. from 2.1 mV to 1.1 mV at 200 ms FC6), but the difference was at the mastoid sites. Phonological modulation of ERPs is most likely to be observed at frontocentral sites and invert at the mastoid sites, since these sites best reflect processing in the superior temporal plane of auditory cortex. Our re-referencing from the nose to the average reference revealed that the ERPs recorded at the nose around 200 ms patterned with the mastoids and inferior posterior sites. One reason we chose to include the mastoids in our analysis is because the absolute difference between any two sites is the same regardless of reference choice. In addition, since we did not find an interaction in the early time interval (200–400 ms) that included the mastoids (where phonological differences would be accentuated), we can claim that the differences between conditions were greater for the later than the earlier time intervals. An advantage to using an average reference when ERPs are recorded from a large number of sites, evenly distributed across the scalp is that the average of all sites approaches zero (Dien, 1998). However, no matter which reference is chosen, it is important to consider the effect of reference choice on the data.

Semantic and discourse processing Our finding of an anterior positivity during the 600–900 ms interval appears to be a specific index of discourse-coherence processing. This is likely related to the LAP index for discourse-level processing, as the anterior versus right mastoid findings of this study matched the pattern of processing previously found in Shafer et al. (2005), namely more positivity at anterior, as compared to mastoid, sites in the discourse conditions. The prior studies, however, reported an earlier effect between discourse and nonsense beginning around 200 ms (Shafer et al., 2005; Neumann et al., in preparation). In the current study the comparison was between meaningful utterances in coherent versus incoherent order, and thus, it is not surprising that it took longer from utterance onset to determine that the meaning could not be integrated with the previous utterance. The posterior positivity which we observed in the current study was not apparent in the previous studies comparing discourse to nonsense conditions. This finding could be related to the P600, which is typically found in processing sentences that do not make sense for grammatical or structural reasons. More recently, P600 findings have been reported for processing a broader range of linguistic phenomena requiring integration of sentence meaning (Bornkessel-Schlesewsky &

ERPs of discourse coherence 823 Schlesewsky, 2008; Hagoort, Brown, & Osterhout, 1999). It is important to replicate the posterior positivity using a similar design, but to also include utterance types that are known to modulate P600 amplitude, to explore whether this posterior positivity reflects similar processes indexed by the classic P600. There were several limitations to our study. First, our analyses were restricted to only a few electrode sites in the right hemisphere. This was due to the high variance in the data at left hemisphere sites. This may be related to the open-ended nature of the task, which likely engendered greater variability in how participants processed the stimuli. However, it is important to recognize that increased variability was found for the random stimuli, suggesting that the meaningful discourse engaged participants, whereas the random stimuli did not engage them to the same extent. Second, the study included a relatively small number of participants (n ¼ 12). An increased n is needed to determine the variability of patterns found in healthy participants. Thirdly, the analysis focused on processing up to 900 ms post-stimulus onset. In future studies, longer epochs should be used to determine how long the anterior processing persists. To examine processing across a longer time period, the discourse could be extended to longer discourse units (e.g. sequences of four coherent utterances). Future studies should attempt to decrease variance by adding more trials and/or exploring the use of various tasks (e.g. identifying auditory targets) or props (e.g. including images that support the story). It would also be important to further examine whether the anterior and posterior positivity we obtained are modulated by different levels of discourse complexity (e.g. three-five sequences of coherent utterances, contributing to larger stories) and structural complexity (e.g. variation of sentence structure). Future studies might also examine whether modulation of the N400 and the anterior positivity are correlated. Lastly, studies should be designed to test the theoretical discourse models proposed by constraining some words locally via sentence meaning while others are constrained by the discourse more globally.

Conclusion The current study revealed a late anterior and posterior positivity between 600–900 ms, reflecting discourse-coherence processing. The results of this study are significant as they demonstrate that discourse comprehension can be examined in a passive listening task that does not place demands on the listeners’ ability to perform a behavioral or verbal task. This has important implications for clinical populations with disordered language processing, such as aphasia and TBI, as the challenge of task completion can often interfere with assessment of the behavior of interest. ERPs can allow for a direct investigation of discourse processing in real time with minimal outside influencing variables. For example, clinical populations of aphasia and TBI, despite their linguistic and/or cognitive deficits, can be assessed for comprehension of coherent versus incoherent discourse. Furthermore, ERPs can be used to investigate how behavioral therapeutic remediation to improve discourse processing in individuals with aphasia and TBI impacts neural processing pre- and post-therapy.

Acknowledgements We would like to thank the Benasich lab at Rutgers University, Cecylia Chojnowska, the adults who participated in the study, and Queens College students Judith Schwartz, Gianina Giangrande, and Dawn Lau for assistance with data and reference organization.

824 Y. Neumann et al. Declaration of interest The authors report no conflict of interest. This research was supported by a High Risk/High Impact grant (No. 5664) from Autism Speaks (PI: April Benasich, subcontract to Valerie Shafer).

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