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. Author manuscript; available in PMC: 2019 Nov 1.
Published in final edited form as: Psychol Med. 2019 Jan 15;49(7):1195–1206. doi: 10.1017/S0033291718004087

Parsing Components of Auditory Predictive Coding in Schizophrenia Using a Roving Standard Mismatch Negativity Paradigm

Amanda McCleery 1,2,†,*, Daniel H Mathalon 3,4,†, Jonathan K Wynn 2,1, Brian J Roach 3, Gerhard S Hellemann 1,2, Stephen R Marder 1,2, Michael F Green 1,2
PMCID: PMC6499668  NIHMSID: NIHMS1007637  PMID: 30642411

Abstract

Background:

Mismatch negativity (MMN) is an event-related potential (ERP) component reflecting auditory predictive coding. Repeated standard tones evoke increasing positivity (“repetition positivity”; RP), reflecting strengthening of the standard’s memory trace and the prediction it will recur. Likewise, deviant tones preceded by more standard repetitions evoke greater negativity (“deviant negativity”; DN), reflecting stronger prediction error signaling. These memory trace effects are also evident in MMN difference wave. Here, we assess group differences and test-retest reliability of these indices in schizophrenia patients (SZ) and healthy controls (HC).

Methods:

Electroencephalography was recorded twice, 2-weeks apart, from 43 SZ and 30 HC, during a roving standard paradigm. We examined ERPs to the 3rd, 8th, and 33rd standards (RP), immediately subsequent deviants (DN), and the corresponding MMN. Memory trace effects were assessed by comparing amplitudes associated with the three standard repetition trains.

Results:

Compared to controls, SZ showed reduced MMNs and DNs, but normal RPs. Both groups showed memory trace effects for RP, MMN, and DN, with a trend for attenuated DNs in SZ. Intraclass correlations obtained via this paradigm indicated good to moderate reliabilities for overall MMN, DN and RP, but moderate to poor reliabilities for components associated with short, intermediate, and long standard trains, and poor reliability of their memory trace effects.

Conclusion:

MMN deficits in SZ reflected attenuated prediction error signaling (DN), with relatively intact predictive code formation (RP) and memory trace effects. This roving standard MMN paradigm requires additional development/validation to obtain suitable levels of reliability for use in clinical trials.

Keywords: mismatch negativity, predictive coding, prediction error signaling, psychotic disorders, memory trace, repetition negativity, deviant negativity

Introduction

Mismatch negativity (MMN) is an event-related potential (ERP) component that has been studied extensively in schizophrenia (SZ). MMN is elicited in response to an unexpected, low probability deviant stimulus that is presented after a repeated train of high-probability standard stimuli (e.g., an oddball paradigm) (Näätänen et al., 2007). The MMN is a negative deflection in the ERP that peaks approximately 100–150ms after stimulus onset and is maximal at fronto-central scalp sites (Garrido et al., 2009b; Näätänen et al., 2007; Todd et al., 2013). MMN is traditionally measured in the deviant-standard ERP difference wave to facilitate distinguishing it from the earlier and partially overlapping N100 component evoked by both standards and deviants. Diminished MMN amplitude is a reliable finding in SZ, with meta-analytic reviews reporting large effect sizes (Erickson et al., 2016; Umbricht and Krljes, 2005). Notably, MMN amplitude is also related to functional outcomes in patients (Friedman et al., 2012; Hamilton et al., 2017; Kiang et al., 2007; Light et al., 2015; Light and Braff, 2005; Thomas et al., 2017; Wynn et al., 2010).

MMN has been viewed within several related conceptual frameworks, including echoic memory (Winkler et al., 1993), short-term neuroplasticity (Breen et al., 2014; Garrido et al., 2009a; Näätänen, 2008; Perez et al., 2017; Stephan et al., 2006), and predictive coding (Baldeweg, 2007; Garrido et al., 2009b; Wacongne, 2016; Wacongne et al., 2012; Winkler and Czigler, 2012). Predictive coding may be an especially useful framework to understand important features of SZ, including auditory hallucinations and delusions (Adams et al., 2013; Fletcher and Frith, 2009; Horga et al., 2014; Schmack et al., 2015), and some aspects of impaired cognition and reward processing (Friston et al., 2014; Lalanne et al., 2012; Stephan et al., 2009). Predictive coding is a hierarchical information processing model that posits interactions between lower-order perceptual signals and higher-order cognitive processes in a dynamic, iterative fashion to generate predictions about the environment and compare incoming stimuli with these predictions (Fletcher and Frith, 2009; Nazimek et al., 2012). According to this model, neural responses to stimuli that match predictions are suppressed, whereas stimuli that are unexpected, violating these predictions, trigger a mismatch “prediction error” signal (Friston, 2005; Garrido et al., 2009a; Schultz and Dickinson, 2000). The prediction error signals that updating of expectations is required to accommodate the discrepant stimuli.

From a sensory echoic memory perspective, the elicitation of MMN by a “deviant” stimulus depends on formation and maintenance of a memory trace for what has been “standard” in the recent auditory stream. The predictive coding framework extended this perspective by demonstrating that there is a positive voltage deflection in the standard ERP that increases with successive repetitions of the standard stimulus. This positivity, referred to as the “repetition positivity” (RP), is hypothesized to not only reflect the strength of the memory trace for the standard stimulus, but also the associated prediction that the standard stimulus will recur (Baldeweg, 2007; Baldeweg et al., 2006, 2004, Garrido et al., 2009a, 2009b; Haenschel et al., 2005). When this prediction is violated by the appearance of a deviant stimulus, negativity is evident in the deviant ERP that is hypothesized to signal a prediction error. Importantly, the negativity evoked by the deviant stimulus increases as the number of standards preceding it increases, such that violations of stronger predictions evoke larger prediction error signals (Baldeweg et al., 2004; Baldeweg and Hirsch, 2015; Haenschel et al., 2005; Todd et al., 2013) Although this deviant-evoked negativity has traditionally been identified as the MMN, it has more recently been referred to as the “deviant negativity” (DN) (Baldeweg et al., 2006) to distinguish it from the MMN difference wave, which is now recognized to comprise two constituent parts: 1) the RP, reflecting the strength the memory trace for the standard stimulus and the associated prediction that it will recur, and 2) the DN, reflecting the strength of the prediction error signal (Garrido et al., 2009b; Heilbron and Chait, 2017). Elucidation of predictive coding features of the MMN and its constituent RP and DN components can be optimized using “roving standard” MMN paradigms (Baldeweg et al., 2004; Baldeweg, 2007; Cowan et al., 1993; Haenschel et al., 2005; Winkler et al., 1996).

In a roving standard MMN paradigm, a series of standards is presented, followed by a deviant, as in a typical oddball paradigm. However, after the first appearance of the deviant stimulus, it is repeated over successive trials, becoming the new standard. This new standard series is subsequently interrupted by a new deviant, and the process repeats. Relative to a traditional oddball sequence, the changing physical properties of each successive train of standard stimuli permits examination of the build-up of the memory trace for a new standard. By binning the standards according to their sequential position and generating standard ERPs for early (e.g., position 2), intermediate (e.g., position 6), and late (e.g., position 36) standards, a “memory trace effect” is evident in the RP component of the standard ERPs, with late standards showing a more positive RP than early standards (e.g.,(Baldeweg, 2007)). Similarly, a memory trace effect is evident in the DN, with deviants preceded by a longer train of repeating standards showing a more negative DN than those preceded by a shorter train (Baldeweg et al., 2004; Baldeweg and Hirsch, 2015; Haenschel et al., 2005; Todd et al., 2013). Finally, by calculating difference waves between the corresponding deviant and standard ERPs, a memory trace effect is also evident in the MMN (Baldeweg et al., 2004; Baldeweg and Hirsch, 2015; Haenschel et al., 2005; Todd et al., 2013), reflecting contributions from both RP and DN (Baldeweg, 2007).

Attenuation of the MMN memory trace effect, reflected by a flatter slope of MMN amplitude change across deviants preceded by shorter vs. longer trains of standards, has previously been reported in SZ compared with healthy controls (Baldeweg et al., 2004; Baldeweg and Hirsch, 2015). Moreover, greater attenuation of the MMN memory trace effect was associated with greater deficits in working memory and episodic memory (Baldeweg et al., 2004; Baldeweg and Hirsch, 2015). Beyond reporting an overall reduction in RP and DN amplitudes in SZ, one study (Baldeweg et al., 2004) found the memory trace effect to be attenuated for RP but normal for DN, suggesting that stimulus repetition failed to strengthen the predictive code but nonetheless modulated the strength of the prediction error signal.

The aim of this study was to develop and test a roving standard MMN paradigm to optimize evaluation of predictive coding in people with SZ. We hypothesized that SZ patients, relative to HC participants, would show: 1) overall MMN amplitude reduction when ERPs were derived by traditional averaging of all standards and deviants, 2) reduced amplitudes and attenuated memory trace effects for RP, DN, and MMN associated with short, intermediate, and long trains of standard stimulus repetitions and their immediately subsequent deviants. Additional study aims were to examine cognitive and clinical correlates of the roving standard MMN indices, and to assess the test-retest reliability of the indices over a two-week interval.

Method

Participants

Clinical, cognitive, and EEG assessments were obtained from 43 SZ and 30 HC participants at baseline (Time 1). Of these participants, 43 SZ and 29 HC returned for a two-week follow-up (Time 2). After excluding participants with unusable EEG data, 40 SZ and 30 HC had useable Time 1 data, 38 SZ and 27 HC had usable Time 2 data. In total 43 SZ and 30 HC contributed usable data to at least one timepoint, and 35 SZ and 27 HC contributed usable data to both timepoints. SZ patients were recruited from local clinics and residences, and HC participants were recruited via internet advertisements. Inclusion criteria for patients were: 1) DSM-IV (American Psychiatric Association, 1994) diagnosis of schizophrenia based on SCID-I/P interview (First and Gibbon, 2004), 2) age 18–60 years, and 3) stable outpatient status and no antipsychotic medication changes in the month prior to testing. For HC participants, inclusion criteria were: 1) no history of a DSM-IV diagnosis of recurrent major depressive disorder, bipolar disorder, or schizophrenia-spectrum disorder (including schizoid, schizotypal, paranoid, and avoidant personality disorder) based on SCID-I/P and SCID-II interview (Benjamin, 1994; First et al., 2014), 2) no history of a schizophrenia-spectrum disorder among first-degree relatives, and 3) age 18–60 years. Exclusion criteria for all participants were: 1) history of a neurological disorder or head injury resulting in loss of consciousness, and 2) alcohol or substance abuse or dependence in the three months prior to testing, and 3) benzodiazepine or sedative use in the 12 hours before testing. Urine toxicology screenings were performed at each study visit. Sample characteristics are presented in Table 1.

Table 1.

Clinical and demographic information by group

SZ
(n=43)
n (%)		 HC
(n=30)
n (%)		 χ2 (df), p
Gender 29 male (67.4%) 18 male (60.0%) χ2(1)=0.43, p=0.51
Hispanic ethnicity 5 (11.6%) 6 (20.0%) χ2(1)=0.97, p=0.33
Race χ2(3)=5.65, p=0.13
 Caucasian 20 (46.5%) 19 (63.3%)
 African American 19 (44.2%) 6 (20.0%)
 Asian 2 (4.7%) 4 (13.3%)
 Other 2 (4.7%) 1 (3.3%)
Mean (s.d.) Mean (s.d.) t (df), p
Age (years) 47.81 (10.04) 46.40 (8.50) t(71)=0.63, p=0.53
Personal education (years) 12.53 (1.98) 14.87 (1.55) t(71)=−5.40, p<0.01
Parental education (years) 13.23 (4.25) 15.03 (2.76) t(68)=−2.03, p=0.05
MCCB Overall Composite Score 36.79 (13.00) 46.97 (12.90) t(71)=−3.30, p<0.01
MCCB Speed of Processing 43.95 (13.42) 47.47 (11.42) t(71)=−1.17, p=0.25
MCCB Attention/Vigilance 40.44 (12.63) 49.07 (14.36) t(71)=−2.71, p=0.01
MCCB Working Memory 39.91 (11.69) 48.33 (12.53) t(71)=−2.94, p<0.01
MCCB Verbal Learning 42.84 (12.41) 51.40 (12.37) t(71)=−2.91, p=0.01
MCCB Visual Learning 43.09 (10.61) 48.87 (10.66) t(71)=−2.28, p=0.03
MCCB Reasoning and Problem Solving 51.79 (9.17) 48.27 (11.14) t(71)=1.48, p=0.14
MCCB Social Cognition 31.95 (10.41) 44.97 (11.08) t(71)=−5.12, p<0.01
RFS Work 2.56 (1.65) --
RFS Independent Living 4.72 (1.49) --
RFS Family 5.37 (1.43) --
RFS Social 4.60 (1.79) --
BPRS total 41.51 (9.90) --
 Positive symptoms factor 2.09 (0.96) --
 Negative symptoms factor 2.10 (1.12) --
 Agitation/Mania symptoms factor 1.28 (0.35) --
 Depressive/Anxious symptoms factor 1.65 (0.56) --
CAINS Motivation and Pleasure scale 14.53 (5.70) --
CAINS Expression scale 4.63 (4.13) --
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Note: SZ, schizophrenia group; HC, healthy control group; MCCB, MATRICS Consensus Cognitive Battery; RFS, Role Functioning Scale; BPRS, Brief Psychiatric Rating Scale; CAINS, Clinical Assessment Interview for Negative Symptoms.

Symptom severity and community functioning were rated by trained raters using the 24-item Brief Psychiatric Rating Scale (BPRS) (Lukoff et al., 1986) and the Clinical Assessment Interview for Negative Symptoms (CAINS) (Kring et al., 2013), and the Role Functioning Scale (RFS) (Goodman et al., 1993). Each rater achieved a median intraclass correlation coefficient (ICC) of 0.80 or higher across all BPRS, CAINS, and RFS. For the SCID, clinical raters demonstrated an overall kappa coefficient, kappa sensitivity, and kappa specificity > 0.75, and a diagnostic accuracy kappa > 0.85. The MATRICS Consensus Cognitive Battery (MCCB) (Nuechterlein and Green, 2006) was administered at Time 1 to assess cognition using age- and gender-corrected domain and overall composite scores.

Procedures

Roving Standard Mismatch Negativity Paradigm:

Prior work has shown that MMNs elicited by different types of auditory deviance (e.g., pitch versus duration) are subserved by different neural generators (Alho, 1995; Csépe, 1995; Deouell et al., 1998; Giard et al., 1990; Molholm et al., 2004; Paavilainen et al., 1991). Further, there is variability in relative sensitivity of pitch vs. duration MMN to SZ across the illness course (Avissar et al., 2017; Bodatsch et al., 2011; Erickson et al., 2016; Haigh et al., 2017; Michie et al., 2000; Näätänen and Kähkönen, 2009; Nagai et al., 2013; Perez et al., 2014; Todd et al., 2008; Umbricht and Krljes, 2005) in that paradigms that produce larger MMNs tend to show larger MMN deficits in SZ (Avissar et al., 2017; Javitt et al., 1998). Also, MMN amplitude is enhanced when multiple types of deviance are combined in a single stimulus (Levanen et al., 1993; Paavilainen et al., 2001; Schroger, 1995; Takegata et al., 1999; Wolff and Schröger, 2001). Hence, the paradigm tested here used pitch+duration “double deviants”, similar to our prior studies (Hay et al., 2015; Perez et al., 2014).

Participants completed the roving standard MMN at Time 1 and Time 2. The paradigm comprised five blocks (block duration: 317s), each separated by a 30s break, during which tones of 50 ms or 100 ms duration, varying in pitch between 700Hz - 1250Hz, were presented binaurally (80 dB, 5ms rise/fall time, 400ms SOA) through insert earphones (ER-2, Etymotic Research, Inc., Elk Grove Village, IL). The stimulus sequence comprised short (3), intermediate (8), and long (33) trains of identical standard tones followed by a deviant tone differing from the standard in both pitch (minimum change 100 Hz, maximum change 300 Hz) and duration (± 50 ms). The deviant tone then repeated, effectively becoming the new standard, with a train of 3, 8, or 33 standard repetitions preceding the next deviant (see Figure 1). A randomly permuted sequence of short, intermediate, and long trains of identical standard repetitions was generated for each block, with all 5 blocks comprising 90 occurrences of each train length. Participants were instructed to ignore the tones while they performed a tactile oddball distractor task and maintained visual fixation on a central cross on a computer screen. In the tactile oddball task, participants held a game controller with both hands that transmitted a pseudorandom sequence of three distinct vibration patterns: a frequent (p=0.8) standard (right side), an infrequent (p=0.10) target (right side), and an infrequent (p=0.10) foil (left side). Participants responded with a button press to targets only.

Figure 1.

Figure 1.

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Roving standard MMN task design. For the roving standard MMN paradigm, an identical standard tone is repeated 3, 8, or 33 times within each stimulus train. For each change to a new stimulus train, the first stimulus constitutes a deviant tone, differing from the preceding train of standards in both pitch and duration. The deviant tone then becomes the new standard, repeating 3, 8, or 33 times until the next deviant appears, Note: S, standard stimulus; D, deviant stimulus.

Specific standard and deviant trials were averaged to generate ERP waveforms and corresponding deviant-standard difference waves, and all components (RP, DN, MMN) were measured by calculating the mean amplitude between 100–200ms at electrode Fz from their respective ERPs. RPs were assessed in ERPs derived from standard trials in sequence positions 3, 8, or 33 within local trains of standard repetitions, resulting in 270 trials for the 3rd standard (RP3), 180 trials for the 8th standard (RP8), and 90 trials for the 33rd standard (RP33). Likewise, DNs were assessed in ERPs derived from deviant trials occurring after 3 (DN3), 8 (DN8), or 33 (DN33) standard repetitions, with each ERP comprising 90 trials. MMNs associated with different numbers of standard repetitions preceding the deviant stimulus (MMN3, MMN8, MMN33) were assessed in corresponding deviant-standard difference waves (e.g., MMN3=DN3-RP3). “Memory trace” indices for RP, DN and MMN, were calculated as the amplitude difference between components associated with long versus short trains of standard repetitions (e.g., DNMT=DN33-DN3) for use in correlational analyses. In addition, overall mean RP, DN, and MMN were measured from ERP averages of all standards, all deviants, and their corresponding difference waves. Additional information about the EEG procedures are in Supplementary Materials.

Data analysis plan

The groups were compared on demographic, clinical, and cognitive variables using χ2 and independent sample t-tests. MMN, RP, and DN amplitudes were analyzed separately using 2 (Group; SZ, HC) x 3 (Standard Repetition; 3, 8, 33) x 2 (Time; Time 1, Time 2) mixed models. In these models, memory trace effects were assessed using two a priori orthogonal reverse Helmert contrasts for standard repetitions: 1) intermediate (8) vs. short (3), and 2) long (33) vs. mean of intermediate and short (8,3). Overall MMN amplitude was assessed using a 2 (Group; SZ, HC) x 2 (Time; Time 1, Time 2) mixed model. Using hierarchical linear regression models, MCCB cognitive measures were each regressed on a MMN index (MMNMT, RPMT, DNMT, overall MMN amplitude), Group, and the MMN index x Group interaction to test for significant regression line slope differences between the groups. Significant slope differences were followed up with bivariate correlations within each group. When the MMN index x Group interaction was not significant, it was dropped from the model, and the common slope was then tested for significance. Relationships of clinical and functioning measures with MMN indices were assessed in the SZ group with bivariate correlations. For each family of regression or correlation analyses (cognitive, clinical, functioning), correction for multiple tests were imposed using Bonferroni correction (family wise-corrected alpha set to p<0.05). Finally, ICC (3,1) coefficients (Shrout and Fleiss, 1979) were calculated to assess test-retest reliability of the roving standard indices.

Results

Demographic, clinical, cognitive, and functioning data are presented in Table 1. The groups were well matched on age, gender, race, and ethnicity. The level of personal education was significantly lower, and the level of parental education was marginally lower, in SZ compared to HC.

Means of the roving standard MMN indices are presented by group in Table 2. The number of trials included in ERP averages after artifact rejection are presented in Supplementary Materials. Grand average waveforms for RP, DN, and MMN and topographic maps across the three standard repetition train lengths for each group are presented in Figures 2 and 3. Average amplitudes for the MMN, RP, and DN associated with short, intermediate, and long trains of standard repetitions for each group are plotted in Figure 4. Descriptive data and mixed models results are presented in Tables 2 and 3.

Table 2.

Descriptive statistics for roving standard MMN indices and mixed model analyses

Roving Standard MMN indices SZ Time 1
n=40
Mean (S.D.)		 SZ Time 2
n=38
Mean (S.D.)		 HC Time 1
n=30
Mean (S.D.)		 HC Time 2
n=27
Mean (S.D.)
MMN3 −0.19 (1.19) 0.02 (1.54) −0.49 (1.25) −0.93 (1.00)
MMN8 −0.64 (2.03) −0.51 (1.63) −0.67 (1.40) −0.60 (1.59)
MMN33 −1.64 (2.06) −1.21 (2.15) −1.99 (1.88) −2.61 (2.16)
RP3 −0.17 (0.98) −0.49 (1.02) −0.36 (0.87) −0.36 (0.93)
RP8 0.04 (0.94) −0.09 (1.10) −0.11 (1.03) −0.29 (0.96)
RP33 0.53 (1.22) 0.41 (1.44) 0.43 (1.01) 0.52 (1.09)
DN3 −0.36 (1.42) −0.47 (1.46) −0.86 (1.34) −1.29 (1.28)
DN8 −0.59 (1.78) −0.60 (1.88) −0.96 (1.42) −0.89 (1.25)
DN33 −1.12 (1.66) −0.80 (1.74) −1.72 (1.65) −2.09 (1.80)
Overall MMN amplitude −0.74 (1.12) −0.57 (1.16) −1.08 (1.14) −1.38 (1.06)
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Note: SZ, schizophrenia group; HC, healthy control group; RP, repetition positivity; DN, deviant negativity.

Figure 2.

Figure 2.

Figure 2.

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a) MMN averaged waveforms (electrode Fz), and b) MMN topographic maps, collapsed across Time 1 and Time 2. Note: HC, healthy control group; SZ, schizophrenia group; MMN, mismatch negativity. Shaded box denotes 100–200ms time window.

Figure 3.

Figure 3.

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RP and DN averaged waveforms (electrode Fz) collapsed across Time 1 and Time 2 Note: HC, healthy control group; SZ, schizophrenia group; RP, repetition positivity; DN, deviant negativity. Shaded box denotes 100–200ms time window.

Figure 4.

Figure 4.

Figure 4.

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Average amplitude for a) MMN and b) RP to standards and DN to deviants associated with different numbers of standard repetitions in SZ and HC. Note: MMN, mismatch negativity; RP, repetition positivity; DN, deviant negativity; HC, healthy control group; SZ, schizophrenia group.

Table 3.

Mixed model analyses

Roving Standard MMN indices Contrast F/t (df), p
MMN3,8,33 Effect of Group: F(1,66.62)=4.14, p=0.05
Effect of Standard Repetition: F(2,327.00)=37.44, p<0.001
Effect of Time: F(1,347.64)=0.03, p=0.87
Group × Time: F(1,347.64)=4.82, p=0.03
Reverse Helmert Contrasts
MMN3 vs MMN8 t(327.00)=−1.13, p=0.26
MMN3 vs. MMN8 × Group: t(327.00)=1.54, p=0.12
MMN3 vs. MMN8 × Time: t(327.00)=0.59, p=0.56
MMN3 vs. MMN8 × Group × Time: t(327.00)=−0.82, p=0.42
MMN3,8 vs. MMN33: t(327.00)=−8.58, p<0.001
MMN3,8 vs. MMN33 × Group: t(327.00)=−1.67, p=0.10
MMN3,8 vs. MMN33 × Time: t(327.00)=−0.27, p=0.79
MMN3,8 vs. MMN33 × Group × Time: t(327.00)=1.10, p=0.27
RP3,8,33 Effect of Group: F(1,73.12)=0.06, p=0.81
Effect of Standard Repetition: F(2,332.88)=35.27, p<0.001
Effect of Time: F(1,346.82)=2.00, p=0.16
Group × Time: F(1,346.82)=1.75, p=0.19
Reverse Helmert Contrasts
RP3 vs. RP8: t(332.88)=2.34, p=0.02
RP3 vs. RP8 × Group: t(332.88)=−0.72, p=0.47
RP3 vs. RP8 × Time: t(332.88)=−0.01, p=0.99
RP3 vs. RP8 × Group × Time: t(332.88)=0.93, p=0.36
RP3,8 vs. RP33: t(332.88)=8.07, p<0.001
RP3,8 vs. RP33 × Group: t(332.88)=0.62, p=0.54
RP3,8 vs. RP33 × Time: t(332.88)=0.84, p=0.40
RP3,8 vs. RP33 × Group × Time: t(332.88)=−0.19, p=0.85
DN3,8,33 Effect of Group: F(1,70.86)=4.39, p=0.04
Effect of Standard Repetition: F(2,330.38)=15.13, p<0.001
Effect of Time: F(1,342.79)=0.38, p=0.51
Group × Time: F(1,342.79)=2.28, p=0.13
Reverse Helmert Contrasts
DN3 vs. DN8: t(330.38)=−0.12, p=0.91
DN3 vs. DN8 × Group: t(330.38)=1.17, p=0.24
DN3 vs. DN8 × Time: t(330.38)=1.06, p=0.29
DN3 vs. DN8 × Group × Time: t(330.38)=−0.70, p=0.48
DN3,8 vs. DN33: t(330.38)=−5.50, p<0.001
DN3,8 vs. DN33 × Group: t(330.38)=−1.84, p=0.07
DN3,8 vs. DN33 × Time: t(330.38)=0.37, p=0.71
DN3,8 vs. DN33 × Group × Time: t(330.38)=1.14, p=0.25
Overall MMN amplitude Effect of Group: F(1,68.51)=4.49, p=0.04
Effect of Time: F(1,61,21)=0.10, p=0.75
Group × Time: F(1,61.21)=4.60, p=0.04
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Note: SZ, schizophrenia group; HC, healthy control group; RP, repetition positivity; DN, deviant negativity.

Mixed model analyses of roving standard ERP indices.

The mixed model analysis of MMN amplitudes revealed a significant main effect of Group, with SZ patients showing smaller (i.e., less negative) MMN than HC participants. This effect interacted significantly with Time, with the MMN amplitude deficit in SZ patients, relative to HC, being larger at Time 2 than at Time 1. Despite this, neither the increase in MMN amplitude over time in HC [F(1,147.25)=2.81, p=0.10], nor the decrease in MMN amplitude over time in SZ [F(1,203.29)=2.20, p=0.14], were significant. Two reverse Helmert contrasts among levels of the Standard Repetition factor were used to assess the MMN memory trace effect. The MMN3 vs MMN8 contrast was not significant, nor did it significantly interact with Group, Time, or with Group x Time. However, the MMN3,8 vs. MMN33 contrast was highly significant (p<0.001) reflecting a marked increase in MMN amplitude (i.e., increased negativity) when deviants were preceded by long trains of standard repetitions, relative to the average MMN associated with short and intermediate trains of standard repetitions. While this MMN memory trace effect appeared to be larger in the HC than in the SZ group (see Figure 3a), the difference was not significant (p=0.10). Furthermore, the MMN3,8 vs. MMN33 contrast effect did not significantly interact with Time or with Group x Time. No other main effects or interactions were significant.

Next, RP and DN across the three Standard Repetition train lengths and two Time points in SZ and HC were tested in two separate mixed model analyses. For RP, memory trace effects were significant for both reverse Helmert contrasts, indicating that RP amplitude modestly (p=0.02) increased in positivity for the 8th standard relative to the 3rd standard in repeating standard stimulus trains, and strongly (p<0.001) increased for the 33rd standard relative to the mean of the 3rd and 8th standards. These memory trace effects on the RP did not significantly interact with Group, Time, or Group x Time.

For DN, there was a significant main effect of Group (p=0.04), with HC exhibiting a larger (i.e., more negative) DN amplitude than SZ. This effect did not significantly interact with Time, nor was the main effect of Time significant. Memory trace effects on DN were not significant for the DN3 vs. DN8 contrast, nor did this contrast significantly interact with Group, Time, or Group x Time. However, when the mean of DN3 and DN8 were contrasted with DN33, a strong memory trace effect was evident (p<0.001). This significant memory trace effect on DN showed a trend interaction with Group (p=0.07), with the increase in amplitude (i.e., increased negativity) of DN33, relative to DN3,8, being larger in HC [t(141.54)=−4.87, p<0.001] than in SZ [t(189.67)=−2.80, p=0.06].

For overall MMN amplitude (i.e., based on ERPs derived from all deviants and standards), there was a significant main effect of Group (p=0.04), with HC exhibiting larger (i.e., more negative) MMN amplitude compared to SZ. In addition, a significant Group x Time interaction (p=0.04) was present, indicating that the SZ deficit in overall MMN amplitude relative to HC was greater at Time 2 than at Time 1. Despite this interaction, neither the slight increase in MMN amplitude in HC over time [F(1,27.98)=2.89, p=0.10], nor the slight decrease in MMN amplitude in SZ over time [F(1,33.61)=1.89, p=0.19], was significant.

Cognitive, clinical, and functioning relationships with roving standard MMN indices.

The regression analyses and correlation matrices are presented in Supplementary Materials. Although a few differential associations between the memory trace indices and MCCB variables were found in SZ and HC, none survived correction for multiple tests. Similarly, correlations of clinical or community functioning with MMN indices in the SZ group were not significant after correction for multiple tests.

Test-retest reliability of roving standard ERP indices.

Test-retest reliability coefficients (ICCs) for the roving standard ERP indices are presented in Table 4. In brief, the ICCs indicated good to moderate reliabilities for overall MMN, DN and RP. However, when looking at the values for the separate short, intermediate, and long standard trains, the reliabilities were moderate to poor. Finally, the reliabilities were poor for memory trace effects.

Table 4.

Test-retest reliability coefficients for roving standard MMN indices.

ICC
Roving standard MMN Measure SZ
n=35		 HC
n=27
MMN3 0.00 0.01
MMN8 0.35* 0.34*
MMN33 0.30* 0.56**
RP3 0.59** 0.53**
RP8 0.58** 0.59**
RP33 0.20 0.56**
DN3 0.30* 0.37*
DN8 0.48** 0.07
DN33 0.57** 0.59**
MMNMT 0.04 0.37*
RPMT 0.05 0.30
DNMT 0.14 0.22
Overall MMN 0.55** 0.64**
Overall RP 0.74** 0.86**
Overall DN 0.72** 0.67**
Open in a new tab

Note:

*

p<0.05,

**

p<0.01;

ICC, intra-class correlation, using two-way mixed single measures consistency formula (ICC 3, 1 from Shrout and Fleiss, 1979); SZ, schizophrenia group; HC, healthy control group; MMN, mismatch negativity; RP, repetition positivity; DN, deviant negativity. MT, memory trace effect, defined for each component by subtracting value associated with repeated standard 3 from value associated with repeated standard 33. Overall MMN, RP, and DN measures are based on ERP averages of all standards, all deviants, and the resulting ERP deviant-standard difference waves.

Discussion

Using a roving standard MMN paradigm, with trains of 3, 8, or 33 standards before a deviant that heralded the onset of a new standard train, a significant memory trace effect was evident for MMN in both HC and SZ groups, with MMN amplitude being substantially larger (i.e., more negative) when deviants were preceded by 33 versus 3 or 8 standards. This memory trace effect is thought to reflect the build-up of a stronger memory trace for the standard, and a stronger prediction that it will recur, as the number of standard repetitions increase, and a correspondingly larger prediction error signal to deviants preceded by longer trains of standards. Although this memory trace effect tended to be smaller in the SZ patients than in the HC controls, this difference was not significant. Moreover, MMN did not show a significant memory trace effect in either group when deviants were preceded by 8 standards relative to 3 standards.

An advantage of the roving standard MMN paradigm is its ability to disentangle the two processes that contribute to MMN: 1) the build-up of the memory trace for the standard and the development of the prior expectation that it will recur, reflected by the RP response to repeated standard sounds, and 2) the prediction error signal elicited by stimuli that violate prior expectations, reflected by the DN response to infrequent deviant sounds. A corresponding limitation of the roving standard paradigm is that it does not equate the number of trials for the various repetition sequence lengths for RP. Our results showed the predicted memory trace effect on the RP, with its amplitude modestly but significantly increasing to the 8th repeated standard relative to the 3rd, and a more prominent increase to the 33rd standard. These effects were equally evident in both groups. While the standard repetition train lengths used in this study (i.e., 3, 8, and 33) were similar to those used in prior roving standard MMN paradigms (e.g., (Baldeweg et al., 2004)), a memory trace effect on the DN and the MMN was not evident in either group when comparing deviants preceded by 3 versus 8 standards. However, a memory trace effect was seen in increased negativity for deviants preceded by 33 standards relative to 8 or 3 standards, and this effect was attenuated at a trend level in SZ relative to HC participants.

In addition to these memory trace effects, our results replicated the expected reduction in overall MMN amplitude in SZ patients, relative to HC, both in the overall MMN measured from ERP averages of all standards and deviants, and in the standard repetition analysis. Based on the separate analyses of MMN’s constituents (i.e., DN and RP), the SZ patient MMN deficit can be attributed to a significant overall reduction in DN, but not RP, amplitude. Overall, our findings support the idea that SZ patients show aberrant prediction error signaling, and they show a trend toward reduced strengthening of this prediction error signal with more standard repetitions. Furthermore, our findings with RP suggest that SZ patients do not have deficits in forming memory traces of, or establishing and building expectations for, recurring auditory stimuli. The overall reduction in amplitude of the DN and MMN in this SZ sample are congruent with the findings of Baldeweg et al. (2004). However, the studies differ in that Baldeweg et al. (2004) found that the memory trace was diminished for RP and relatively intact for DN in SZ, whereas we found the opposite pattern. The roving standard paradigm used by Baldeweg et al. (2004) differed from the one used in the current study with regard to the type of deviant and the number of repetitions of the standard, which may contribute to the different pattern of findings. It is also possible that the poor reliability of the roving standard indices may contribute to the different findings across studies.

Previous studies have reported significant relationships between MMN and symptoms, cognitive performance, and functional outcome in schizophrenia (Baldeweg et al., 2004; Baldeweg and Hirsch, 2015; Friedman et al., 2012; Hamilton et al., 2017; Kiang et al., 2007; Light et al., 2015; Light and Braff, 2005; Wynn et al., 2010). We expected to find similar correlations with the predictive coding indices derived from this roving standard paradigm. However, while we found some moderately-sized associations within groups, none of the correlations survived correction for multiple tests. One could speculate that predictive coding-related measures from the roving standard MMN paradigm might be more relevant to shorter term mechanisms of neural plasticity that support new learning, rather than stable cognitive abilities that may be learned over a lifetime and may be more closely related to daily functioning.

MMN from traditional (i.e., non-roving) paradigms have previously been shown to have moderate to good test-retest reliability in SZ (Biagianti et al., 2017; Hall et al., 2006; Lew et al., 2007; Light et al., 2012; Light and Braff, 2005). The ICCs for the overall MMN derived in our study is comparable to some of these estimates. This paper represents the first report of test-retest reliability of MMN, RP, and DN components, as well as the corresponding memory trace effects, derived from a roving standard MMN paradigm in SZ and HC. Within the two groups, the roving ERP indices for RP, DN, and MMN at each of the three repetition sequences showed poor to moderate test-retest reliability. Notably, there was a general tendency for reliability to improve as the number of standard presentations in a sequence increased, and correspondingly, as the amplitudes of the components increased. The memory trace effects, i.e., the difference in ERP amplitude between the longest and shortest repetition sequences for MMN, RP, and DN, showed particularly poor reliability. Possibly, the memory trace effects are more susceptible to state-related influences and noise than the component amplitudes from which they are derived.

Even though the paradigm included more trials of the short sequences (i.e. 3 and 8), even this might not have been enough to establish high levels of reliability because shorter sequences would be expected to have more noise than longer sequences. This potential benefit of increasing trial numbers is consistent with the observation that the overall MMN, RP, and DN, derived from all available standard and deviant trials, achieved moderate to strong reliability. However, the potential impact on testing session length and subject burden does present a limitation for the number of long sequence trials that can be included in a testing session. Moreover, it is not possible to equate the number of trials presented to the subject for the various repetition sequence lengths for RP. It is also possible that the tactile distractor task used in this study may have impacted the reliability estimates of the MMN indices, as MMN latency and amplitude can be influenced by distractor task attentional demands and modality (Rissling et al., 2013). Further study of the impact of altering task parameters, including the number of standard repetitions in the sequence, the type of deviants, and the type of distractor task, on psychometric properties is warranted.

In conclusion, our results demonstrate the potential utility of roving standard MMN paradigms and applications of the predictive coding framework to the study of SZ. These data demonstrate that MMN deficits in SZ patients can be understood to reflect deficient prediction error signaling, rather than reduced memory trace formation for the standard. The reliability analyses suggest that further refinements to roving standard paradigms will be needed to yield adequate reliability for roving standard ERP indices if they are to be used in longitudinal studies or clinical trials.

Supplementary Material

Supplemental Materials

Acknowledgement

We thank the research subjects for participating in this study. We gratefully acknowledge Ana Cecilia Myers, M.S. for coordinating the study, Michelle Dolinsky, B.A. for subject recruitment efforts, Courtney Fazli, B.S., Gabrielle Pascual, B.S., and Nora Polon, B.A. for their assistance with data collection.

Financial Support

This study was supported by funding from FORUM Pharmaceuticals, Inc. (PIs: Green & Marder), the Veterans Administration VISN 22 Mental Illness Research, Education, and Clinical Center (MIRECC), the Veterans Administration Research Enhancement Award Program (REAP) on Enhancing Community Integration for Homeless Veterans. Dr. McCleery is currently supported by a career development award from NIH (K23MH108829), and previously by an NIH institutional training fellowship (T32MH096682).

Footnotes

Conflict of Interest

Dr. McCleery has received compensation from MedAvante-Prophase, Inc. for clinical assessment services. Dr. Mathalon serves as a consultant for Boehringer Ingelheim and Takeda. Dr. Marder has been a consultant for FORUM, Allergan, Lundbeck, Roche, Otsuka, Merck, Teva, Takeda, and Newron. He has received research support from FORUM and Neurocrine. Dr. Green has been a consultant to AiCure, Lundbeck, and Takeda, and he is on the scientific board of Cadent. He has received research funds from FORUM. Dr. Wynn, Dr. Hellemann, and Mr. Roach report no disclosures.

Ethical Standards

The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008.

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