Discussion
In this study, we utilized linear regression models based on robust
single-trial ERP analysis as implemented in the EEGLAB toolbox LIMO EEG
to test for correlations between a range of well-studied ERPs and
symptom and trait measures of psychopathology compatible with the
transdiagnostic framework the HiTOP. Recruiting a mixed sample of 50
patients with emotional disorders undergoing 14 weeks of transdiagnostic
psychotherapy as well as 37 healthy comparison subjects matched in age
and sex, we assessed longitudinal correlations across the full
psychopathology spectrum. In the following, we pragmatically follow a
top-down discourse in that we first treat results covering the HiTOP
spectrum and subfactor levels. After this, we look at ERPs which only
correlated with a single or a few sub scales and therefore are of
relevance to the lowest symptom and maladaptive trait level.
The most consistent result in this study was that a reduced P3b elicited
to Target stimuli in the AO paradigm correlated with worse
symptomatology. In fact, significant correlations between higher scores
and reduced P3b was found in all psychopathology measures with
two exceptions: MEDI Positive temperament - where, as expected, we found
the opposite pattern - and PID36 Psychoticism. These findings were
corroborated by results from the Correct response stimulus-locked
Flanker ERPs elicited to Congruent stimuli. Although not significant at
the corrected level, at 5% a reduced stimulus-locked Flanker P3b
correlated with higher scores in several of the psychopathology
measures, including MEDI total score11Note that because the P3b
in the Flanker paradigm falls immediately before button press, it
cannot be as reliably analysed as the P3b from the AO paradigm due to
some trials overlapping.. The P3b is thought to be an index of
cognitive processes such as context updating and memory processing (Luck
& Kappenman, 2011; Polich, 2007). While P3b is consistently reduced in
chronic schizophrenia and less consistently reduced in depression, we
are not aware of studies relating P3b to specific symptoms in any of the
emotional disorders included in this study (Klawohn et al., 2020;
Onitsuka et al., 2013). In schizophrenia, some studies have reported
associations between a reduced P3b and increased symptoms of cognitive
deficits (Giordano et al., 2021; Kruiper et al., 2019). Our results are
in line with these findings and support that cognitive impairment is a
mainstay also of the emotional disorders. In the HiTOP, our results
suggest that a reduced P3b is a marker not of subfactor or lower symptom
and trait levels but of the Internalizing spectrum as a whole. Given the
above as well as evidence of reductions also in Externalizing disorders,
it can be speculated that a reduced P3b is a marker not only of the
Internalizing, but also of the Externalizing and Thought disorder
spectra in the HiTOP (Pasion & Barbosa, 2019; Patrick et al., 2006).
Indeed, cognitive impairment is a symptom of most, if not all,
psychiatric disorders (Etkin et al., 2013). As such, a reduced P3b could
be a marker of the general p-factor sometimes included at the top of the
HiTOP hierarchy (Levin-Aspenson et al., 2021). However, there is some
evidence of an increased P3b in OCD (Gohle et al., 2008; Mavrogiorgou et
al., 2002). This highlights the unique features of OCD in a
transdiagnostic framework (see below) (Faure & Forbes, 2021). Finally,
it should be noted that cognitive impairment is not only a core symptom
of psychiatric disorders, but also a known side effect to treatment with
psychotropic medication (Cowen & Sherwood, 2013; Paterniti et al.,
1999). Even though we accounted for medication status in our analysis,
86% of the patient population was treated with at least one psychiatric
medication. Given this high proportion, we can’t be certain that
cognitive impairment, as indexed by a reduced P3b, were due to disorder
or psychotropic medication. However, a separate analysis with a model
excluding medication status did not yield stronger P3b regional effects,
suggesting that medication status did not contribute to the results.
Indeed, evidence indicate that the P3b is not altered by SSRI treatment,
which was the most prevalent psychotropic medication in our sample
(d’Ardhuy et al., 1999; Oranje et al., 2008-06-31; however, see Wienberg
et al., 2010).
After the P3b, the second most consistent findings involved the
response-locked Flanker ERPs, indexing conflict or performance
monitoring (Larson et al., 2014). Starting with the ERN, elicited to
errors, we had hypothesized than an increased ERN would correlate with
higher scores, especially in the psychopathology measures indexing
different forms of anxiety and symptoms related to OCD. This was based
on findings of correlations between increases in the ERN and
transdiagnostic dimensions related to OCD and anxiety, especially
Fear-based anxiety, within the Internalizing spectrum (Gorka et al.,
2017; Pasion & Barbosa, 2019; Riesel et al., 2022). Contrary to this
hypothesis, however, we found consistent and strong correlations between
a reduced ERN and the majority of symptom dimensions in MEDI, as
well as the Anankastia, Detachment and Negative Affect maladaptive
traits in PID36. This apparent discrepancy with the literature invites
to several interpretations. First, a few studies have indeed found
correlations between a reduced ERN and Internalizing psychopathology.
Tanovic et al. (2017) found associations between a reduced ERN and
symptoms of ruminations, but only when controlling for effects of
anxiety. Olvet et al. (2010) found associations between depression
severity and both an increased CRN and a reduced dERN, the difference
wave between ERN and CRN. Our results therefore corroborate these
results in finding correlations with increased scores in MEDI Intrusive
Cognitions and MEDI Depression, the latter for which we also found
correlations with an increased CRN as in Olvet et al. (2010) (see
below). Second, owing to the nature of linear regression models as
utilized in this study, regional effects can either indicate a reduced
or an increased ERN, but not both simultaneously. Consequently, if the
‘ground truth’ is that both types of ERN deviations correlate with
higher scores, the dominant feature ‘wins’, or, alternatively, the
effects cancel out and the correlation is not significant. Perhaps this
is why Seow et al. (2020) failed to find associations between the ERN
and transdiagnostic measures in a community sample. In Riesel et al.
(2022), correlations between increases in the ERN and an anxious-misery
dimension was in a mixed sample across the OCD spectrum. In that study,
the patient group had a significantly increased ERN compared to the
healthy comparison group. For our present sample, we have recently shown
that a sub sample based on the HiTOP subfactor Distress - containing the
ICD-10 diagnoses of Depression and GAD - had a reduced ERN at
baseline compared to healthy comparison subjects (Randau et al., 2023).
In that study, the ERN of the Fear subfactor - containing agoraphobia,
OCD, PD and SAD - was not significantly different to either the Distress
or HC group. As such, our sample characteristics differs from Riesel et
al. (2022) in that the group contributing the most to the
psychopathology variance is not defined by an increased ERN, but rather
by a decreased one. Third, it is established that the ERN is sensitive
to not only manipulations of experimental factors, but also to
preprocessing and analysis methods (Clayson, 2020; Clayson et al., 2021;
Feuerriegel & Bode, 2022). In all paradigm-related aspects, our study
closely followed established conventions in the literature. However, we
cannot rule out that a desensitizing effect across sessions took place
for the patient group, essentially decreasing the perceived threat of
errors and thereby the ERN. That being said, patients showed a reduced
ERN compared to HC already at baseline and the ERN has been shown to be
stable across sessions (Olvet & Hajcak, 2009a; Randau et al., 2023).
Neither can we rule out a fatigue effect from the rather long paradigm,
even though such an effect has not been demonstrated (Olvet & Hajcak,
2009b). In addition, our paradigm was not longer in duration than the
one used in Riesel et al. (2022) and divided into 10 rather than 6
blocks. Taken together, we do not find it likely that our divergent
effects were paradigm- or study design-related. While we believe that
the robust single-trial analysis method utilized in this study
constitutes an improvement, we did not conduct a formal analysis
comparing our methods against traditional methods. However, we can
report that applying traditional baseline subtraction methods at
intervals commonly reported in the literature (-500 to -300 and -200 to
0 ms pre-stimulus, respectively) did not noticeably alter the group-wise
grand average ERN waveforms in terms of maximum peak amplitude or
latency. In Gorka et al. (2017) on a transdiagnostic sample, OCD was an
exclusion criteria and yet higher scores in a derived Fear dimension -
but not in a Distress dimension - correlated with increases in a
residual ERN-measure, 22Defined as the ERN activity when the CRN
is ’regressed out (Gorka et al., 2017).. In our study, even though
the ERN beta coefficient represents residual activity when effects of
the CRN beta coefficient (and the adjusted mean) are accounted for, we
also informally tested an explicit ERN-CRN difference contrast. However,
results for this dERN was in the same direction as the ERN. Therefore,
we must conclude that when it comes to the ERN, ‘all roads lead to Rome’
in the sense that both decreases and increases can be observed in
clinical populations and that both types of deviations are associated
with worse symptomatology. In this regard, it must be noted that past
studies have utilized rating scales based on a categorical understanding
of psychopathology and converted these into transdiagnostic dimensions
through factor analysis conducted on the study sample or from weights
derived from previous studies. Needless to say, into what latent
dimension a given rating scale is allocated will affect the direction of
correlations, if any. While neither MEDI nor PID36 are directly derived
from the HiTOP, both measures are validated in large populations and
index distinct transdiagnostic dimensions consistent with the HiTOP
framework. In terms of the HiTOP, then, as we saw for the P3b, a reduced
ERN seems to be associated with worse symptomatology across the whole
Internalizing spectrum. In addition to ruminations and depressive
symptoms, reductions in the ERN have been associated with symptoms and
traits belonging to the Externalizing spectrum (Hall et al.,
2007; Lutz et al., 2021; Pasion & Barbosa, 2019). However, we found no
significant correlations between the ERN and the two Externalizing
traits in PID36 (Disinhibition and Antagonism). Then again, our sample
did not include Externalizing disorders. Indeed, scores for Antagonism
were comparably low and did not differ between the two groups. Finally,
in the HiTOP, the placement of OCD within the Internalizing spectrum is
not fully established, with results indicating that symptoms cross-load
on the Fear subfactor within the Internalizing spectrum but also on the
Thought-disorder spectrum (Faure & Forbes, 2021). As such, we can raise
the possibility that a reduced ERN is specific to the
Internalizing and the Externalizing spectra, as conceptualized in the
HiTOP, while an increased ERN is a specific marker of some other
construct encompassing both anxiety symptoms contained in the Fear
subfactor as well as symptoms related to the Thought disorder spectrum.
The uniqueness of OCD in terms of ERP abnormalities is also supported by
associations with an increased P3b discussed above (Gohle et al., 2008).
We can conclude that more studies are needed to understand the
associations between the ERN and psychopathology, especially studies
looking to discern divergent effects in different patient populations
and using validated transdiagnostic measures.
Results for the CRN, elicited to correct responses, were somewhat more
specific and in the expected direction. Firstly, we can corroborate
results from Riesel et al. (2022) in finding correlations between an
increased CRN and PID36 Anankastia. PID36 Anankastia must be considered
to capture much of the same psychopathology as the dimensions
Compulsiveness and Personal standards examined in Riesel et al. (2022).
In addition, we can corroborate results from Olvet et al. (2010) in
finding correlations between an increased CRN and depressive symptoms as
indexed by MEDI Depression. Indeed, we find that increased CRN
correlates strongly with transdiagnostic dimensions which can be
considered to load unto the HiTOP Distress subfactor (MEDI Depression
and PID36 Negative Affect, but also PID36 Detachment33We note
that Detachment is in itself a spectrum in the HiTOP.), whereas it
correlates more weakly or not at all with Fear subfactor dimensions,
e.g., MEDI Autonomic Arousal, Neurotic Temperament, Social
Anxiety44Here, correlations were present but considerably weaker
than for MEDI Depression and PID36 Negative Affect., Somatic Anxiety
and PID36 Avoidance. As such, we find some evidence of an increased CRN
as a marker of symptoms and traits in the HiTOP Distress subfactor. At
first sight, this contradicts the results from our above-mentioned
study, where the Distress subfactor - containing patients with a primary
ICD-10 diagnosis of depression and GAD - had a significantlyreduced CRN compared to healthy comparison subjects (Randau et
al., 2023). However, group-level differences between HiTOP subfactors
based on primary ICD-10 diagnosis do not necessarily translate to
correlations with transdiagnostic symptomatology. While the
above-mentioned Distress dimensions must be considered to be a core part
of both ICD-10 Depression and GAD, both HCs as well as patients with
disorders which would be allocated to the Fear subfactor contributed to
the correlations. Therefore, it is not a contradiction to state that
categorical diagnoses associated with Distress show a reduced CRN
compared to healthy comparison subjects, but when considering the full
spectrum of psychopathology, an increased CRN correlates with
dimensions which primarily load unto the Distress subfactor. It is
likely that other factors which are common to Distress disorders and not
captured by our psychopathology measures, such as cognitive impairment,
influence to reduce the CRN. Some evidence of a negative (reduced)
effect of cognitive impairment on the response-locked Flanker ERPs exist
(Eppinger et al., 2008; Simó et al., 2018; Swainston et al., 2021).
ERN and CRN are followed by the Pe and Pc, which are believed to index
the conscious awareness of correct and error responses, respectively
(Overbeek et al., 2005; Wessel, 2012). In the main analysis, only
correlations between a reduced Pe and MEDI total survived the corrected
level of 0.1%. Post-hoc , a reduced Pe correlated strongly with
increased scores in MEDI Avoidance and Social Anxiety and more weakly
with Autonomic Arousal, Intrusive Cognitions and Somatic Anxiety. Even
though PID36 total scores did not survive the main analysis, a look at
the sub scales reveals significant but considerably weaker correlations
with Anankastia, Disinhibition, Negative Affect and Psychoticism. Given
this, and the absence of strong correlations with Distress subfactor
dimensions and traits, it is possible that a reduced Pe is a marker of
the HiTOP Fear subfactor rather than of the whole Internalizing
spectrum. Again, OCD would not fit well into Fear in having an increased
Pe compared to healthy comparison subjects (Bellato et al., 2021). As
for Pc, correlations with MEDI and PID36 total scores were not
significant in the main analysis. Post-hoc , we find quite
specifically that a reduced Pe correlates only with increased scores in
PID36 Negative Affect. This speaks for the specificity of the Correct
response-locked Flanker ERPs in that both CRN and Pc correlate with
Distress symptoms, the latter perhaps at the lowest symptom and trait
level.
Having discussed the major results spanning HiTOP spectra and subfactor
levels, we now turn to more specific sub scale results representing
effects at the symptom and maladaptive trait level. It should be noted
that the following results were not tested at the main analysis
corrected level of 0.1% but at the more conventional 5%. Speaking for
their specificity, neither of the MMN measures (with the exception of
cMMN with LPFS) nor the Novelty P300 elicited to Distractor stimuli in
the AO paradigm or the stimulus-locked Flanker N2 yielded significant,
strong correlations with any of the four major psychopathology measures
(K10, LPFS, MEDI and PID36) at either level.
The Novelty P300 is rightfully distinguished from the more typical P3a
elicited to deviant stimuli in the Unattended oddball paradigm (Polich,
2007). Perhaps due to some confusion in the literature, we are not aware
of studies examining correlations between the Novelty P300 and measures
of psychopathology. We find, quite specifically, that a reduced Novelty
P300 at Fz, FCz and Cz correlates with increased scores in PID36
Negative Affect. For MEDI Depression, a reduced Novelty P300 correlates
with higher scores, but weaker and more posterior at CPz and Pz. We note
that this effect of central versus posterior effects might to some
extent be due to correlations with latency in addition to amplitude.
Nevertheless, PID36 Negative Affect and MEDI Depression can be
considered to index roughly similar symptom and trait level dimensions.
As such, given the absence of other correlations, we can postulate that
a reduced Novelty P300 is a marker of a negative affect dimension at the
lowest level of the HiTOP hierarchy, or alternatively, of the Distress
subfactor.
For LPFS at the main analysis level, increases in the latter part of the
cMMN as well as in the following combined deviant dP3a correlated with
higher scores. This curiously indicates an association between MMN/dP3a
and measures of personality functioning or maladaptive traits. MMN is an
index of pre-attentive auditory processing and is reduced in chronic
schizophrenia. However, studies examining the role of MMN in personality
disorders and associated symptoms are, to our knowledge, rare or
inconclusive. Increases in MMN have been associated with schizotypal and
antisocial personality disorders as well as with treatment-resistant
depression when controlling for comorbid borderline personality disorder
(He et al., 2010; Liu et al., 2007). Given this potential connection
between MMN and the personality disorders, it is interesting to have a
look at the PID36 sub scales. Here, increased MMN correlated with
Detachment, Disinhibition and more weakly with Psychoticism and
Anankastia. Decreased MMN correlated with Antagonism and Negative
Affect, the latter consistent with reduced MMN in depression (Tseng et
al., 2021). These results stand in an interesting contrast to results
for the MEDI sub scales, where the only significant correlation was
between increased MMN and Social Anxiety. Taken together, we find
compelling evidence of MMN being a quite specific marker of maladaptive
personality traits loading unto the Internalizing (Detachment, Negative
Affect), Externalizing (Antagonism, Disinhibition) and Thought-disorder
(Psychoticism) spectra in the HiTOP. Such a specificity was not seen in
the following dP3a, which, even though an increased dP3a correlated with
LPFS, was equally related to both MEDI and PID36 sub scales. Curiously,
dP3a was most strongly associated with with MEDI Avoidance and PID36
Antagonism where a decreased dP3a correlated with higher scores.
However, we believe it is beyond the scope of this paper to discuss
similarities between these two measures.
The last ERPs we consider in this discussion are the stimulus-locked
Flanker N2s elicited to correct response to congruent and incongruent
stimuli, respectively. Like the CRN and the ERN, the Flanker N2 is an
index of conflict monitoring and cognitive control (Larson et al.,
2014). First, we note that only the Flanker N2 elicited to congruent
stimuli yielded strong correlations. Second, while both the CRN and the
ERN correlated with maladaptive traits as indexed by LPFS and PID36, as
well as with symptom dimensions as indexed by K10 and MEDI total score,
the Flanker N2 correlated only with a few sub scales in MEDI.
Specifically, a reduced Flanker N2 correlated with higher scores in
Intrusive Cognitions and Traumatic Re-experiencing. Even though the
dimensions in MEDI are distinct and validated, these two sub scales must
be considered to capture closely related psychopathology. As such, we
can postulate that a reduced Flanker N2 to congruent stimuli is a marker
of a single or a few specific symptom dimensions at the lowest level of
the HiTOP hierarchy. However, it is unclear to us to what extent
Intrusive Cognitions and Traumatic Re-experiencing loads unto the
Internalizing and Thought-disorder spectra (Kotov et al., 2020). We also
saw that an increased Flanker N2 to congruent stimuli correlated with
increased scores in MEDI Neurotic Temperament, a core part of the
Internalizing spectrum (Watson et al., 2022).
Our study has several limitations. First, our setup did not allow us to
infer to what extent treatment and group influenced the correlations. As
such, we cannot rule out that our results are driven by correlations
which are the strongest in, e.g., patients at baseline. Second, while we
believe that we controlled for false positives with the conservative
level in the main analysis, we did not define how large a significant
region shall be for it to be considered a true correlation. Add to this
that we found several significant effects at regions not corresponding
to traditional ERP evaluation windows and channels. Rather than
considering only the strongest correlations clearly corresponding to
traditional ERPs, we opted to describe all significant regions above
some arbitrary visual threshold and to quantify these correlations in
terms of strong or weak. It is likely that with more data, some of these
regions would either become larger or vanish.
To our knowledge, this is the first comprehensive examination of the
associations between ERPs and transdiagnostic psychopathology. The ERPs
included in the study are easily measured in a clinical setting and
index pre-attentive auditory processing, cognition and performance
monitoring. Some ERPs, e.g., the MMN, appear to be exclusively related
to maladaptive personality traits at the lowest level of the hierarchy,
whereas others, e.g., the P3b, cut across and are related to entire
spectra or even the general p-factor. The ERN remains elusive in that we
found solid evidence of a reduced ERN correlating with higher scores at
the spectrum level. Conversely, increases in the CRN correlated with
worse symptomatology at the subfactor level, results which are in line
with the literature. In showing that abnormalities in such basic brain
processes are associated with transdiagnostic symptoms and traits at
several levels of the HiTOP hierarchy we have taken yet another small
step toward biomarkers in psychiatry. We have also shown the advantages
of utilizing a consistent framework such as the HiTOP, which allowed us
to pinpoint associations between ERPs and diagnostic measures to
specific levels in the hierarchy. While we did not directly compare our
results against traditional ERP methods, we can state that robust
single-trial ERP analysis as implemented in LIMO EEG is an excellent
tool for a pragmatic analysis of ERP features across channels and time
frames. In future steps, after replication, machine learning and related
advanced method would be obvious candidates in translating ERP features
into transdiagnostic symptom profiles at the subject level (Nielsen et
al., 2020).