Introduction
The electroencephalogram (EEG) shows promising clinical utility in being
non-invasive, easy to record and cost-effective compared to other
neuroimaging methods (Hajcak et al., 2019). Event-related potentials
(ERPs) on the EEG are indexes of task-related brain activity time-locked
to stimuli or other events and potential biomarkers of mental disorders
(Hajcak et al., 2019). Several ERPs have been associated with diagnostic
categories and severity of diagnosis-specific symptoms (Luck &
Kappenman, 2011). However, for the emotional disorders, one of the main
causes of suffering worldwide, ERP findings remain inconsistent
(González-Robles et al., 2018; Watson et al., 2022; Widiger & Oltmanns,
2017). While differences between ERP studies in paradigm design and
preprocessing and analysis methods limit comparison of some results,
discrepancies also stem from issues inherent in categorical taxonomies
and which are especially abundant in the emotional disorders (Michelini
et al., 2021). Recent evidence indicate that at least some ERPs are more
closely related to transdiagnostic measures of psychopathology than to
diagnostic categories (Donaldson et al., 2020; Macedo et al., 2021;
Pasion & Barbosa, 2019; Riesel et al., 2022). Given this, a
comprehensive investigation of the associations between classic ERPs, of
which some were discovered in the 1960’s, and transdiagnostic measures
of psychopathology is called for (Latzman & DeYoung, 2020; Polich,
2020). In this study, we aim to do so by assessing a mixed sample for
correlations between ERPs and transdiagnostic measures of
psychopathology while accounting for the effects of medication and
psychotherapy treatment.
Biomarkers in psychiatry could greatly improve clinical practice in
providing objective measures of psychopathology and treatment outcome
(Singh & Rose, 2009). The discovery of such markers requires a sound
psychopathology framework from which to derive biobehavioral targets to
examine (Latzman & DeYoung, 2020; Michelini et al., 2021). ERP studies
have traditionally evaluated differences in ERP measures such as peak or
average amplitude or latency between diagnostic groups based on
categorical taxonomies ICD and DSM (DSM-IV-TR., 2000; WHO, 2004). These
taxonomies posit that mental disorders are discrete entities with
specific symptoms and clear-cut boundaries between healthy and ill and
between diagnoses (Clark et al., 2017). However, clinical reality shows
that comorbidity among the emotional disorders is in the range of 40 to
80% and that symptom profiles of patients with the same diagnosis
varies greatly (González-Robles et al., 2018). This suggests that
categorical taxonomies do not capture the true nature of psychopathology
(Clark et al., 2017; González-Robles et al., 2018). There being no
straightforward way to account for comorbidity in case-control designs,
most ERP studies merely report concurrent diagnoses and rely on the
primary diagnosis as a sufficient classification of the sample
(Petrolini & Vicente, 2022; Zald & Lahey, 2017). To see why this can
be problematic, consider the error-related negativity (ERN) which is
robustly enhanced (increased amplitude) in some anxiety disorders such
as obsessive-compulsive disorder (OCD) compared to healthy comparison
subjects (Macedo et al., 2021). Somewhat inconsistent results indicate
that ERN is attenuated (decreased amplitude) in depression (Klawohn et
al., 2020). It is clear to see how a study examining ERN in depression
while not accounting for anxiety-related comorbidity might end up with
null results. Heterogeneity within disorders and arbitrary boundaries
between healthy and ill pose similar loss-of-information problems in
studies based on categorical taxonomies (Michelini et al., 2021). In
fact, with the notable exception of ERN in OCD, decades of research has
revealed no robust deviations in ERPs or other EEG measures in any of
the emotional disorders as defined in the categorical taxonomies, e.g.,
depression or major depressive disorder (MDD) (de Aguiar Neto & Rosa,
2019), generalized anxiety disorder (GAD) (Maron & Nutt, 2022), panic
disorder (PD) (Howe et al., 2014) and social anxiety disorder (SAD)
(Al-Ezzi et al., 2020).
Alternative frameworks of psychopathology transcends arbitrary
diagnostic boundaries in considering transdiagnostic symptoms which are
shared among disorders as the basic building blocks of mental disorders
(Clark et al., 2017). The Hierarchical Taxonomy of Psychopathology
(HiTOP) is an empirical and data-driven attempt to describe the full
range of psychopathology (Kotov et al., 2017). In the HiTOP,
transdiagnostic symptoms and maladaptive traits at the lowest level of
the hierarchy are clustered based on shared features into subfactors
roughly corresponding to categorical diagnoses, which in turn are joined
into higher-level spectra such as the Internalizing and Thought disorder
spectra. Accordingly, the emotional disorders share core symptoms and
traits but are further up in the hierarchy allocated to the Fearand Distress subfactors, the latter containing depression and
GAD. The HiTOP comes with several advantages for neuroimaging research
(Conway et al., 2022; Corr & Mobbs, 2023; Kotov et al., 2022; Latzman
& DeYoung, 2020; Michelini et al., 2021; Perkins et al., 2019). By
design, the HiTOP deals with comorbidity, symptom heterogeneity within
disorders and arbitrary boundaries between healthy and ill. In contrast
to categorical taxonomies, the HiTOP encourages studies of mixed samples
characterized at different levels of the hierarchy capturing the full
range of psychopathology (Conway et al., 2022; Latzman & DeYoung,
2020). In other words, subjects included in a study based on the HiTOP
do not need to fulfill some diagnostic criteria or score above some
threshold, but are fully characterized in terms of homogeneous
dimensional constructs. A given ERP measure can thereby be investigated
in terms of being a marker of a transdiagnostic symptom or trait, of a
subfactor or of a whole spectrum. Relying on the HiTOP is also
advantageous when selecting biobehavioral targets with which
associations to ERPs are sought. For transdiagnostic measures, rather
than using sub scales of rating scales developed in categorical setting,
measures consistent with the HiTOP would directly place results in the
context of a comprehensive empirical model of mental disorders (Perkins
et al., 2019).
Ample evidence support that biological measures align more closely to
transdiagnostic constructs than to diagnostic categories (Kotov et al.,
2020; Waszczuk et al., 2020; Watson et al., 2022). The Research Domain
Criteria (RDoC) was launched to encourage research into such
biobehavioral constructs cutting across diagnostic boundaries (Cuthbert
& Insel, 2010). In line with this, several ERPs have recently been
recast as markers of transdiagnostic psychopathology. ERN and its
counter-part, the correct-related negativity (CRN), previously solely
associated with OCD, are now conceived as markers of specific
transdiagnostic measures of anxiety and negative affect in the
Internalizing spectrum (Macedo et al., 2021; Pasion & Barbosa, 2019;
Riesel et al., 2022). Mismatch negativity (MMN) and some other ERP
components in auditory oddball paradigms do not seem to be uniquely
related to a chronic diagnosis of schizophrenia but to symptoms shared
by a range of psychotic disorders (Donaldson et al., 2020; Parker et
al., 2021). These developments being very recent, only the ERN, CRN, and
to a lesser extent the late-positive potential, have thus far been cast
in the light of transdiagnostic psychopathology in the emotional
disorders (Granros, 2021). A comprehensive investigation of the
associations between other classic ERPs and transdiagnostic markers of
psychopathology in the emotional disorders is lacking. Conversely,
further validation of the HiTOP with biological measures is called for
(Perkins et al., 2019).
The aim of the present study was to examine the associations between a
set of transdiagnostic measures of psychopathology and a range of ERPs
elicited by thee classic paradigms (the Eriksen Flanker, the auditory
Attended Oddball and the auditory Unattended Oddball) (Luck &
Kappenman, 2011). Measures of transdiagnostic psychopathology were
assessed with validated self-report measures covering symptoms and
traits consistent with the HiTOP Internalizing spectra. We included 50
patients with emotional disorders undergoing 14 weeks of UP
transdiagnostic group cognitive behavioral psychotherapy and 37 healthy
comparison subjects (HC) matched in age and sex (Barlow et al., 2017;
Reinholt et al., 2021). Patients were assessed with EEG and self-report
questionnaires three times: before, 10 weeks into, and within one week
after treatment. The majority of HCs were assessed once but some a
second time after at least two months in order to account for normal
variation in the models.
To evaluate the associations between ERPs and measures of
transdiagnostic psychopathology, we conducted robust mass univariate
linear regression based on single-trial ERP analysis as implemented in
the EEGLAB toolbox LIMO EEG (Delorme & Makeig, 2004; C. R. Pernet et
al., 2011). LIMO EEG is based on statistical parametric mapping (SPM),
as in the analysis of fMRI data, and provides a complete workflow from
preprocessed EEG data to the evaluation of single-trial subject-level
ERPs at group level with a range of robust statistical measures (Kiebel
& Friston, 2004; C. R. Pernet et al., 2021). Employing a hierarchical
generalized linear model (GLM) approach, the method makes redundant
several choices required in traditional ERP methods known to inflate
false positives and influence group level statistics (Feuerriegel &
Bode, 2022; Luck & Gaspelin, 2017). Instead of requiring the á
priori selection of channel and time window regions of interest, as
well as methods for peak or average amplitude extraction, LIMO EEG
models the subject-level single-trial GLM across all channels and time
points concurrently. False positives are controlled through bootstrap
methods and threshold-free cluster enhancement (TFCE) (Maris &
Oostenveld, 2007; Mensen & Khatami, 2013; C. R. Pernet, 2015).
Consequently, the investigate scope is vastly expanded without loss of
statistical power and can reveal effects at other channels and time
periods than what is traditionally investigated (Fields & Kuperberg,
2020). Recognizing current issues in the preprocessing of ERP data, we
relied on a novel cleaning pipeline based on an empirical evaluation of
other well-established pipelines, the Reduction of
Electroencephalographic Artifacts (RELAX) Bailey et al. (2022); Bailey
et al. (2023). Given evidence that robust single-trial methods allows
for less aggressive cleaning of ERP data, thereby preserving more brain
activity, we applied a less strict than default cleaning of artifacts
and noise (Alday & van Paridon, 2021; Delorme, 2022).
Establishing associations between measures of transdiagnostic
psychopathology and ERPs, many of which are related to specific neural
functioning, would be an important step toward biomarkers in psychiatry
and would increase our understanding of the neural basis of mental
disorders (Hajcak et al., 2019; Lavoie et al., 2019).
Given the exploratory nature of
the study, we refrain from making specific hypotheses. However, as found
in two recent studies, we expected the ERN to be related to one or more
measures in the Internalizing spectrum (Macedo et al., 2021; Riesel et
al., 2022).