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\begin{document}

\title{Central and Peripheral Physiological Responses to Decision Making in
Hoarding Disorder}



\author[1]{Hannah Levy}%
\author[2]{Adam Naples}%
\author[1]{Sarah Collett}%
\author[3]{James McPartland}%
\author[4]{David Tolin}%
\affil[1]{Hartford Hospital}%
\affil[2]{Yale University}%
\affil[3]{Yale}%
\affil[4]{Hartford Hospital Institute of Living}%


\vspace{-1em}



  
  \date{May 21, 2024}


\begingroup
\let\center\flushleft
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\endgroup





\selectlanguage{english}
\begin{abstract}
Individuals with hoarding disorder (HD) have difficulty parting with
personal possessions, which leads to the accumulation of excessive
clutter. According to a proposed biphasic neurobiological model, HD is
characterized by blunted central and peripheral nervous system activity
at rest and during neutral (non-discarding) decisions, and exaggerated
activity during decision-making about discarding personal possessions.
Here, we compared the error-related negativity (ERN) and
psychophysiological responses (skin conductance, heart rate and heart
rate variability, and end tidal CO2) during neutral and
discarding-related decisions in 26 individuals with HD, 37 control
participants with anxiety disorders, and 28 healthy control participants
without psychiatric diagnoses. We also compared alpha asymmetry between
the HD and control groups during a baseline resting phase. Participants
completed a series of Go/No Go decision-making tasks, one involving
choosing certain shapes (neutral task) and the other involving choosing
images of newspapers to imaginally ``discard'' (discarding task).
Contrary to hypotheses, there were no group differences in the ERN or
any psychophysiological measures. Alpha asymmetry at rest did not differ
between groups. The findings suggest that the ERN and
psychophysiological responses may not differ in individuals with HD
during simulated discarding decisions relative to control participants,
although the null results may be explained by methodological challenges
in using Go/No Go tasks as discarding tasks. Future replication and
extension of these results will be needed using ecologically valid
discarding tasks.%
\end{abstract}%



\sloppy


Central and Peripheral Physiological Responses to Decision Making in
Hoarding Disorder

Hannah C. Levy\textsuperscript{1}

Adam J. Naples\textsuperscript{2, 3}

Sarah Collett\textsuperscript{1}

James C. McPartland\textsuperscript{2, 3}

David F. Tolin\textsuperscript{1, 4}

\textsuperscript{1}Anxiety Disorders Center, Institute of Living,
Hartford, CT, USA

\textsuperscript{2}Yale Child Study Center, Yale School of Medicine, New
Haven, CT, USA

\textsuperscript{3}Center for Brain and Mind Health, Yale School of
Medicine, New Haven, CT, USA

\textsuperscript{4}Yale University School of Medicine

Author Note

Correspondence concerning this article should be addressed to Hannah
Levy, Anxiety Disorders Center, Institute of Living/Hartford Hospital,
200 Retreat Avenue, Hartford, CT 06106. Tel.: 860-545-7847. Fax:
860-545-7105. Email: hannah.levy@hhchealth.org.

Author email addresses: Adam Naples, adam.naples@yale.edu; Sarah
Collett, sarah.collett@hhchealth.org; James McPartland,
james.mcpartland@yale.edu; David Tolin, david.tolin@hhchealth.org

Abstract

Individuals with hoarding disorder (HD) have difficulty parting with
personal possessions, which leads to the accumulation of excessive
clutter. According to a proposed biphasic neurobiological model, HD is
characterized by blunted central and peripheral nervous system activity
at rest and during neutral (non-discarding) decisions, and exaggerated
activity during decision-making about discarding personal possessions.
Here, we compared the error-related negativity (ERN) and
psychophysiological responses (skin conductance, heart rate and heart
rate variability, and end tidal CO\textsubscript{2}) during neutral and
discarding-related decisions in 26 individuals with HD, 37 control
participants with anxiety disorders, and 28 healthy control participants
without psychiatric diagnoses. We also compared alpha asymmetry between
the HD and control groups during a baseline resting phase. Participants
completed a series of Go/No Go decision-making tasks, one involving
choosing certain shapes (neutral task) and the other involving choosing
images of newspapers to imaginally ``discard'' (discarding task).
Contrary to hypotheses, there were no group differences in the ERN or
any psychophysiological measures. Alpha asymmetry at rest did not differ
between groups. The findings suggest that the ERN and
psychophysiological responses may not differ in individuals with HD
during simulated discarding decisions relative to control participants,
although the null results may be explained by methodological challenges
in using Go/No Go tasks as discarding tasks. Future replication and
extension of these results will be needed using ecologically valid
discarding tasks.

\emph{Keywords} : hoarding disorder; error-related negativity;
psychophysiological responses; discarding

Central and Peripheral Physiological Responses to Decision Making in
Hoarding Disorder

Hoarding disorder (HD) is characterized by difficulty discarding
personal possessions, which leads to the accumulation of excessive
clutter (American Psychiatric Association, 2013). HD is associated with
significant functional impairment. Compared to patients with related
mental health problems such as obsessive-compulsive disorder (OCD),
patients with HD report significantly worse overall functioning and
quality of life (Saxena et al., 2011). A systematic review similarly
concluded that individuals with HD experience greater impairment in
various domains of functioning relative to control groups (Ong et al.,
2015).

Unfortunately, treatment options for HD are limited.
Cognitive-behavioral therapy (CBT) is efficacious for HD (Steketee et
al., 2010; Tolin et al., 2019), but results are modest. Meta-analytic
research suggests that only 35\% of patients with HD who receive CBT
achieve clinically significant change (a measure of remission status)
(Tolin et al., 2015). To address this problem, research has focused on
identifying neurobiological mechanisms of HD that may inform novel
treatment development. A proposed biphasic neurobiological model of HD
(Tolin, 2023) posits that HD is characterized by blunted central nervous
system (CNS) and peripheral nervous system (PNS) activity at rest or
during neutral (non-discarding) tasks, and exaggerated CNS and PNS
activity during decision-making about discarding personal possessions.

Some evidence points to a baseline under-engagement of CNS processes in
individuals with HD. An early positron emission tomography (PET) study,
which predates the DSM-5 diagnosis of HD, found that OCD patients with
prominent hoarding symptoms exhibited significantly lower activity in
posterior cingulate gyrus and cuneus relative to healthy control
participants during a task-free resting state (Saxena et al., 2004). A
more recent functional magnetic resonance imaging (fMRI) study (Sunol et
al., 2019) found that individuals with HD demonstrated decreased
activity in dorsolateral prefrontal cortex (dlPFC), dorsomedial
prefrontal cortex (dmPFC), and precentral gyrus during error processing
in a Go/No Go task relative to individuals with OCD and healthy control
participants, though orbitofrontal cortex (OFC) activity was enhanced.
Other fMRI research has similarly shown attenuated activity in frontal
regions, including the anterior cingulate cortex (ACC) and insula,
during emotionally-neutral decision-making in HD participants relative
to clinical and nonclinical control groups (Stevens et al., 2020; Tolin
et al., 2012). In contrast to these results, it should be noted that
Hough et al. (2016) reported greater activation of frontal regions (ACC
and dlPFC) during an emotionally neutral (non-discarding) Go/No Go task
in participants with HD, compared to healthy controls and individuals
with OCD.

Conversely, when making emotionally salient decisions about discarding
personal possessions during fMRI, relative to healthy control
participants and those with OCD, individuals with HD demonstrate
excessive activity in the ACC and insula (Stevens et al., 2020; Tolin et
al., 2012). Further evidence of exaggerated responding comes from
studies of PNS response. When making personally relevant decisions about
discarding their own possessions vs. when deciding whether to discard
matched control items (``experimenter owned'' possessions, which were
items donated by study staff), participants with HD demonstrated greater
heart rate, greater skin conductance, and increased hyperventilation as
indicated by lower end tidal CO\textsubscript{2} (ETCO\textsubscript{2})
(Levy, Nett, \& Tolin, 2019).

The present study aimed to expand on these prior studies, which
collectively suggest a biphasic abnormality, by measuring CNS and PNS
activity during a neutral task and during a simulated decision-making
task about possessions. For CNS measurement, we used
electroencephalography (EEG) because it captures ongoing neural activity
with a temporal resolution that is superior to fMRI, thus allowing us to
examine moment-to-moment changes in brain activity that may be specific
to discarding decisions. We focused first on error-related negativity
(ERN), a negative event-related potential that is generated by the ACC
when an individual detects that they have made an error, or when an
error is likely. Consistent with prior studies of CNS responses (Stevens
et al., 2020; Sunol et al., 2019; Tolin et al., 2012), during
non-discarding-related tasks, the ERN is significantly lower in
individuals with HD relative to individuals with OCD and healthy control
participants (Baldwin et al., 2019; Mathews et al., 2016). In a sample
of undergraduate student participants, hoarding symptoms predicted
greater ERN amplitudes for discarding-related decisions but not
emotionally neutral decisions (Baldwin, Whitford, \& Grisham, 2016). We
predicted that individuals with HD would demonstrate greater ERN during
discarding decisions, and lower ERN during emotionally neutral
decisions, compared to anxious and healthy control groups, and that the
ERN during simulated discarding decisions would predict the severity of
HD symptoms.

We also assessed resting state alpha asymmetry, or the difference
between left and right alpha wave activity in the frontal regions of the
brain. Relatively greater left vs. right alpha activity is commonly
associated with approach motivation (Harmon-Jones, Peterson, \& Harris,
2009; Harmon-Jones et al., 2004), whereas relatively greater right vs.
left alpha is thought to reflect withdrawal/avoidance motivation (Coan,
Allen, \& Harmon-Jones, 2001). Consistent with these results, greater
right alpha is associated with psychiatric conditions that are
characterized by withdrawal and avoidance, such as depression {[}for a
review, see Coan and Allen (2004){]}. We are not aware of any prior
research assessing alpha asymmetry in patients with HD; however, based
on evidence from related psychiatric conditions such as depression, we
predicted that the HD group would demonstrate greater right vs. left
alpha asymmetry during the baseline resting period.

For PNS activity, we compared psychophysiological responses among HD
participants and the control groups. Specifically, we measured
ETCO\textsubscript{2}, heart rate (HR) and heart rate variability (HRV),
and skin conductance. Thus, this study expands the findings of Levy,
Nett and Tolin (2019) who did not use a control group. We predicted that
the HD group would demonstrate greater psychophysiological activation
for simulated discarding decisions, and lower psychophysiological
activity during emotionally neutral decisions, relative to the control
groups.

\textbf{Method}

\textbf{Participants}

Participants were 26 adults with a primary diagnosis of HD, 37 adults
with a primary diagnosis of a DSM-5 (American Psychiatric Association,
2013) anxiety disorder (ANX), and 28 adult healthy control participants
without psychiatric disorders (HC). Participants were recruited from the
regular patient flow at an anxiety disorders specialty clinic, through a
registry of individuals who had previously consented to be contacted
about research opportunities at the clinic, and through media
advertisements and flyers posted throughout the surrounding community.

All participants were required to be fluent in English, be right-handed,
and have no history of anoxic or traumatic brain injury with loss of
consciousness greater than five minutes and no history of neurocognitive
disorder that may interfere with the ability to understand the study
tasks and provide informed consent. Any history of psychotic disorder or
bipolar disorder, current substance use disorder, and serious suicide
risk were also exclusionary.

Inclusion criteria for the HD group were a primary diagnosis of HD of at
least moderate severity as indicated by a Clinical Global Impression
(CGI) (Guy, 1976) rating of 4 or greater. Inclusion criteria for the ANX
group were a primary diagnosis of a DSM-5 anxiety disorder of at least
moderate severity as indicated by a CGI rating of 4 or greater. For both
clinical groups, comorbid conditions were permitted as long as they were
secondary to the primary diagnosis. Antidepressants, stimulants, and
benzodiazepines were permitted at stable dosages for a minimum of eight
weeks. All other psychiatric medications were excluded. For participants
taking benzodiazepines and stimulants, a 24-hour ``washout'' of these
medications was required prior to the study with the prescriber's
approval. Inclusion criteria for the HC group were no past or current
psychiatric disorders or mental health treatment.

As shown in Table 1, although we attempted to match the control groups
to the HD group for age and sex assigned at birth, we had significant
age differences. As such, we controlled for age in all study analyses.
We note that we assessed sex assigned at birth and not gender identity
to be consistent with the National Institute of Mental Health National
Data Archive (NDA), in order to facilitate data transfer to the NDA (a
requirement of the grant). As expected, the HD group scored
significantly higher than did the control groups on the \emph{Saving
Inventory-Revised} (SI-R), a measure of hoarding severity.

Table 1\selectlanguage{english}
\begin{longtable}[]{@{}llllll@{}}
\toprule
\begin{minipage}[b]{0.16\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[b]{0.16\columnwidth}\raggedright\strut
Total Sample, \% (\emph{N})\strut
\end{minipage} & \begin{minipage}[b]{0.16\columnwidth}\raggedright\strut
HD Group, \% (\emph{n})\strut
\end{minipage} & \begin{minipage}[b]{0.16\columnwidth}\raggedright\strut
ANX Group, \% (\emph{n})\strut
\end{minipage} & \begin{minipage}[b]{0.16\columnwidth}\raggedright\strut
HC Group, \% (\emph{n})\strut
\end{minipage} & \begin{minipage}[b]{0.16\columnwidth}\raggedright\strut
Group Comparison, \selectlanguage{greek}χ\selectlanguage{english}\textsuperscript{2} or \emph{F}, \emph{p}\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Age, \emph{M} (\emph{SD})\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
48.36 (13.03)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
56.08 (7.76)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
43.16 (13.68)*\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
48.07 (12.88)*\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
8.82, \textless{}.001\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Female sex assigned at birth\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
72.5 (66)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
84.6 (22)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
67.6 (25)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
67.9 (19)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
2.67, .263\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
Race Black/African-American Asian White American Indian/Alaska Native
More than one race Unknown/not reported Other\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
4.4 (4) 1.1 (1) 90.1 (82) 1.1 (1) (1) (1) 1.1 (1)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
3.8 (1) 0 (0) 92.3 (24) 0 (0) 0 (0) 3.8 (1) 0 (0)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
0 (0) 2.7 (1) 91.9 (34) 0 (0) 2.7 (1) 0 (0) 2.7 (1)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
10.7 (3) 0 (0) 85.7 (24) 4.2 (1) 0 (0) 0 (0) 0 (0)\strut
\end{minipage} & \begin{minipage}[t]{0.16\columnwidth}\raggedright\strut
13.40, .340\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Hispanic/Latinx\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
9.9 (9)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
0 (0)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
8.1 (3)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
21.4 (6)*\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
7.17, .028\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
SI-R, \emph{M} (\emph{SD}) Total Clutter Saving Acquiring\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
25.71 (22.05) 10.16 (10.42) 8.44 (7.20) 7.11 (5.76)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
56.46 (11.65) 24.27 (6.07) 18.23 (4.00) 13.96 (4.67)\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
16.73 (10.25)* 6.11 (5.57)* 5.57 (3.83)* 5.05 (3.84)*\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
9.04 (6.77)* 2.43 (3.17)* 3.14 (2.34)* 3.46 (2.46)*\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
184.83, \textless{}.001 142.19, \textless{}.001 146.38, \textless{}.001
62.17, \textless{}.001\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

\emph{Demographic and Clinical Characteristics and Comparisons Between
Groups}

\emph{Note} . HD = Hoarding disorder. ANX = Anxious control. HC =
Healthy control. SI-R = Saving Inventory-Revised.

*significantly different from the HD group, \emph{p} \textless{} .05

\textbf{Measures}

\textbf{Diagnostic assessment.} Diagnoses were determined using
the\emph{Diagnostic Interview for Anxiety, Mood, and
Obsessive-Compulsive and Related Disorders} (DIAMOND) (Tolin et al.,
2018), a structured diagnostic interview based on the DSM-5 (American
Psychiatric Association, 2013) that has demonstrated good reliability
and validity estimates for anxiety disorders and HD (e.g., adequate
inter-rater reliability for anxiety disorders {[}\selectlanguage{greek}κ \selectlanguage{english}= 0.73{]} and HD {[}\selectlanguage{greek}κ
\selectlanguage{english}= 0.86{]}) (Tolin et al., 2018). Interviewers completed a comprehensive
training program in administration and scoring of the DIAMOND
(www.diamondinterview.org), and were trained to criterion (\selectlanguage{greek}κ \selectlanguage{english}= 0.80
against an expert rater) prior to administering the interview.
Interviewers were licensed psychologists or Bachelor's-level clinical
research assistants supervised by licensed psychologists. After
administering the DIAMOND, the clinician rated overall global illness
severity using the CGI, a 7-point clinician-administered rating of
overall symptom severity (\emph{1} =\emph{Normal} ; \emph{7} =
\emph{Extreme} ).

\textbf{Self-report measures.} Self-reported HD severity was assessed
using the 23-item \emph{Saving-Inventory-Revised} (SI-R) (Frost,
Steketee, \& Grisham, 2004), which has demonstrated adequate reliability
as well as strong convergent and discriminant validity. Items are scored
on a 5-point Likert scale (\emph{0} = \emph{None} ; \emph{4}
=\emph{Almost All/Complete} ), with higher scores indicating more severe
hoarding symptoms. The SI-R yields a total score as well as three
subscales (clutter, difficulty discarding, and acquiring).

\textbf{Psychophysiological Assessment}

We used the BIOPAC MP150 system (BIOPAC System, Inc., Goleta, CA), a
modular data acquisition and analysis system that is widely used in
psychophysiological research, to assess psychophysiological activation,
alpha asymmetry, and the ERN. We used AcqKnowledge software to filter
and extract data.

\textbf{Psychophysiological activation.} The following measures were
assessed during a 5-minute baseline resting phase and throughout the
discarding and neutral tasks. We assessed skin conductance level (SCL)
through a constant voltage of 0.5 V across two electrodes placed on the
first and second fingers of the left hand. The total number of skin
conductance responses (SCRs), which reflect the peaks in the SCL
waveform, were extracted along with mean SCL. Heart rate variability
(HRV) and heart rate (HR) data were collected via electrocardiogram
(ECG) leads attached to both the left and right wrists, as well as the
left ankle. ETCO\textsubscript{2} was collected through nasal cannula
and was measured in real time using the AcqKnowledge software rate
calculation function. This function allowed for breath-by-breath
measurement of ETCO\textsubscript{2} percentage which then we
statistically transformed to mmHg.

\textbf{ERN} . EEG data was recorded at 2000hz from six electrodes
{[}`Fz','O1', `F3', `O2', `F4', `Pz'{]} with a linked mastoid reference.
All EEG post processing was conducted using the MNE software package
(Gramfort et al., 2013). Data were bandpass filtered from 1 to 17Hz and
EEG was segmented from 500ms before to 350ms after the commission of a
response and baseline corrected from mean activity in the -500 to -100ms
pre-response. Epochs with activity greater than 125mv were excluded for
artifact. The ERN was measured as the difference between incorrect and
correct responses at electrodes F3, Fz, \& F4 50 to 150ms post response
in line with prior literature (Gehring et al., 2018; Larson et al.,
2010; Meyer, 2016; Meyer et al., 2020; Riesel, 2019) and confirmed with
visual inspection of grand averaged waveforms.

\textbf{Resting state alpha asymmetry} . Alpha asymmetry was assessed
during the baseline resting phase. Baseline EEG was segmented into 1-sec
epochs. Artifact detection was the same as for ERN analyses.
Artifact-free segments were decomposed into the frequency domain using
multitaper fast fourier transform (FFT) implemented in the MNE software
package. Frontal asymmetry indices were calculated by subtracting the
natural log of the power of the left hemisphere electrode from that of
the homologous right hemisphere electrode (In{[}right (F4){]} -- {[}left
(F3){]}).

\textbf{Quality control} . To minimize artifacts, participants were
asked not to move during the study other than to press the appropriate
button on the Go/No Go tasks (see below). They were closely observed by
a research assistant throughout the study. Any movements that occurred
were recorded on a testing form with the specific time that they
occurred. If artifacts appeared in the waveform at those times, the
sections of the waveform that included the artifact were excluded from
the analyses. To ensure reliable data for the EDA analyses, prior to
starting the tasks, we asked participants to hold their breath for a few
seconds to verify that the signal responded to the breath-holding (EDA
waveform should increase with breath-holding). Prior to starting the
tasks, we visually inspected the ECG waveform to ensure that QRS peaks
were being recorded properly. Additionally, during application of the
EEG cap, each electrode was abraded (via a Q-tip) and re-jelled with
abrasive electrolyte-gel up to three times, or until impedances as
determined by an electrode impedance checker were less than 5 k\selectlanguage{greek}Ω. \selectlanguage{english}The
testing room in which the study took place was regulated at a
temperature ranging between 71\selectlanguage{ngerman}°F-73°F in order to ensure quality data
collection.

For HRV, we applied a band pass filter (low frequency cutoff = 1 Hz;
high frequency cutoff = 35 Hz; QRS peak threshold = 0.5 mV, which was
adjusted as needed depending on the height of individual participants'
QRS peaks). For EDA, we first applied a low pass filter (1 Hz). The SCR
threshold level was set at 0.02 microsiemens.

\textbf{Tasks}

\textbf{Discarding task} . We modeled the discarding task from prior
research (Baldwin, Whitford, \& Grisham, 2016) in which participants
were asked to imagine that pictures of newspapers displayed on the
screen belonged to them. They were told: ``Newspapers can contain
important information, but it's also important to declutter your home.
Therefore, we want you to get rid of some of your newspapers.'' Pictures
of various newspapers were presented (see Figure 1), and participants
were asked to select only the newspapers containing text (vs. pictures
and text, the No Go distractor) to discard (the Go target) via button
press.

The targets and distractors were counterbalanced across participants.
Trials began with (a) a central fixation crosshair presented for
800-1000ms followed by (b) either a target or a distractor image
presented for 112ms followed by (c) a 2000ms response period.
Participants were instructed to respond as quickly as possible while
remaining accurate in their responses. EEG was segmented to the onset of
participant responses. Go and No Go trials were presented at a ratio of
75:25, respectively. After the first 20 trials of only No Go stimuli, Go
and No Go pictures were presented at random in blocks of 300 trials each
(75 No Go trials), lasting approximately three minutes per block. Prior
research has established that the ERN can be reliably measured with only
14 trials and similar published tasks (Baldwin, Whitford, \& Grisham,
2016) reported error rates \textgreater{} 70\%.

It should be noted that we modified the visual appearance of the
newspapers from the Baldwin, Whitford and Grisham (2016) task in order
to make the task more challenging. In the original Baldwin study, red
(Go target) and blue (No Go distractor) newspapers were used. In our
study, we used only blue newspapers, some of which had text only (Go
target) vs. pictures and text (No Go distractor).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

\textbf{Emotionally neutral task.} As in the Baldwin, Whitford and
Grisham (2016) study, we used colored shapes for the neutral
(non-discarding) task. Participants were asked to choose blue shapes
containing lighter colors (Go target) vs. darker colors (No Go
distractor; see Figure 2). These shapes were matched in overall color
composition and luminance to those in the discarding task. The trial
structure was identical to the discarding task (see above) and
participants were encouraged to respond as quickly and accurately as
possible.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image5/image5}

\end{center}
\end{figure}

\textbf{Procedure}

All study procedures were approved by the hospital's Institutional
Review Board. Prior to completing any study procedures, participants
provided written informed consent. They then completed a series of
questionnaires and the DIAMOND. BIOPAC system sensors were then placed,
and participants completed the baseline resting period followed by the
two tasks in counterbalanced order. Participants received \$50 for their
participation.

\textbf{Statistical Analyses}

As explained above, we controlled for age in the analyses. To test the
prediction that the HD group would demonstrate greater ERN during
simulated discarding decisions relative to emotionally neutral decisions
as compared to the control groups, we used a 3 (group) x 2 (task: ERN
during the discarding task vs. neutral task) mixed analysis of
covariance (ANCOVA), controlling for age. To test the prediction that
the HD group would demonstrate greater right vs. left alpha asymmetry,
we used 1-way ANCOVA, controlling for age. For our prediction that the
HD group would demonstrate greater psychophysiological activity during
the simulated discarding task relative to the neutral task compared to
the control groups, we used 3 (group) x 2 (task: ETCO\textsubscript{2},
SCL, HRV, and HR during the discarding task vs. neutral task) mixed
ANCOVAs, controlling for age. Finally, we used hierarchical multiple
regression to test the prediction that the ERN during discarding
decisions would predict SI-R scores, controlling for age.

\textbf{Power Analysis}

We conducted an \emph{a priori} power analysis using G*Power 3 (Faul et
al., 2007) to determine adequate sample size. At \selectlanguage{greek}α \selectlanguage{english}= .05 and 80\% power,
a total sample size of 42 would be needed to detect a medium effect
(\emph{f} = 0.25) for the between-groups comparisons of ERN,
ETCO\textsubscript{2}, SCL, HRV, and HR.

\textbf{Results}

\textbf{Group Comparisons}

\textbf{ERN.} There were no main effects of group, \emph{F} (2, 75) =
0.29, \emph{p} = .751, \selectlanguage{greek}η\selectlanguage{english}\textsuperscript{2}\textsubscript{p} = 0.01 or
task, \emph{F} (1, 75) = 0.09, \emph{p} = .769,
\selectlanguage{greek}η\selectlanguage{english}\textsuperscript{2}\textsubscript{p} = 0.00 for the ERN. There was no
significant group x time interaction, \emph{F} (2, 75) = 0.66, \emph{p}
= .519, \selectlanguage{greek}η\selectlanguage{english}\textsuperscript{2}\textsubscript{p} = 0.02. Contrary to
hypotheses, these results indicated no differences in the ERN between
the simulated discarding and neutral tasks, and no differences between
the HD and control groups. See Table 2 for group means and standard
deviations and Figure 3 for grand average waveforms depicting ERN
difference waves (error -- correct) waveforms for the neutral and
discarding tasks. See Table S1 in the Supplement for estimated marginal
means controlling for age and 95\% confidence intervals.

Table 2

\emph{Means and Standard Deviations ofPsychophysiological Measures}\selectlanguage{english}
\begin{longtable}[]{@{}lllllll@{}}
\toprule
\begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
Measure\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
HD group\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
HD group\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
ANX group\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
ANX group\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
HC group\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
HC group\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Discarding, \emph{M} (\emph{SD})\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Neutral, \emph{M} (\emph{SD})\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Discarding, \emph{M} (\emph{SD})\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Neutral, \emph{M} (\emph{SD})\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Discarding, \emph{M} (\emph{SD})\strut
\end{minipage} & \begin{minipage}[t]{0.14\columnwidth}\raggedright\strut
Neutral, \emph{M} (\emph{SD})\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
ERN\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
-1.54 (3.38)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
-2.14 (3.96)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
-1.56 (2.34)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
-2.31 (2.92)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
-1.59 (2.11)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
-2.92 (2.94)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
Alpha asymmetry (baseline only)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
-0.01 (0.02)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
---\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
-0.01 (0.03)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
---\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
-0.02 (0.03)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
---\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
ETCO\textsubscript{2}\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
35.80 (17.76)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
35.43 (17.62)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
39.40 (16.17)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
40.18 (17.20)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
32.51 (17.95)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
32.48 (18.09)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
HRV\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
26.04 (12.47)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
23.91 (13.34)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
31.84 (19.34)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
30.00 (16.71)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
33.38 (25.08)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
35.79 (35.81)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
Heart rate\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
72.34 (10.45)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
72.81 (10.90)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
73.66 (11.89)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
73.41 (11.51)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
68.89 (8.50)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
68.82 (8.48)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
SCL\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
1.75 (1.56)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
1.94 (1.54)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
2.60 (1.80)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
2.82 (1.94)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
2.28 (1.87)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
2.34 (1.81)\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
SCR\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
11.27 (8.78)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
13.41 (9.48)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
15.55 (9.88)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
16.90 (11.48)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
12.32 (7.83)\strut
\end{minipage} & \begin{minipage}[t]{0.12\columnwidth}\raggedright\strut
13.05 (8.47)\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

\emph{Note} . HD = Hoarding disorder. ANX = Anxious control. HC =
Healthy control. ERN = Error-related negativity. ETCO\textsubscript{2} =
end-tidal

CO\textsubscript{2}. HRV = Heart rate variability. SCL = Skin
conductance level. SCR = Skin conductance response\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image9/image9}

\end{center}
\end{figure}

Figure 3. Grand average waveforms depicting ERN difference waves (error
-- correct) waveforms for neutral and discarding tasks. The left
waveform depicts the neutral task, and the right waveform depicts the
discarding task. The temporal region (50-150ms) where the mean ERN is
measured is demarcated by the grey rectangle.

\textbf{Alpha asymmetry.} There were no significant group differences in
alpha asymmetry, \emph{F} (2, 81) = 2.43, \emph{p} = .094,
\selectlanguage{greek}η\selectlanguage{english}\textsuperscript{2}\textsubscript{p} = 0.06 (see Table 2).

\textbf{Psychophysiological activity.} It should be noted that we had
missing data for ETCO\textsubscript{2} (\emph{n} = 23; 7 HD, 5 ANX, 11
HC) due to equipment failure. For ETCO\textsubscript{2}, there were no
main effects of group, \emph{F} (2, 64) = 1.47, \emph{p} = .237,
\selectlanguage{greek}η\selectlanguage{english}\textsuperscript{2}\textsubscript{p} = 0.04 or task, \emph{F} (1, 64) =
1.62, \emph{p} = .208, \selectlanguage{greek}η\selectlanguage{english}\textsuperscript{2}\textsubscript{p} = 0.03 and
no interaction, \emph{F} (2, 64) = 1.56, \emph{p} = .219,
\selectlanguage{greek}η\selectlanguage{english}\textsuperscript{2}\textsubscript{p} = 0.05. For HRV, there were no
main effects of group, \emph{F} (2, 82) = 1.15, \emph{p} = .320,
\selectlanguage{greek}η\selectlanguage{english}\textsuperscript{2}\textsubscript{p} = 0.03 or task, \emph{F} (1, 82) =
0.24, \emph{p} = .625, \selectlanguage{greek}η\selectlanguage{english}\textsuperscript{2}\textsubscript{p} = 0.00 and
no interaction, \emph{F} (2, 82) = 0.57, \emph{p} = .566,
\selectlanguage{greek}η\selectlanguage{english}\textsuperscript{2}\textsubscript{p} = 0.01. For HR, there were no main
effects of group, \emph{F} (2, 82) = 1.61, \emph{p} = .206,
\selectlanguage{greek}η\selectlanguage{english}\textsuperscript{2}\textsubscript{p} = 0.04 or task, \emph{F} (1, 82) =
1.26, \emph{p} = .265, \selectlanguage{greek}η\selectlanguage{english}\textsuperscript{2}\textsubscript{p} = 0.02 and
no interaction, \emph{F} (2, 82) = 0.15, \emph{p} = .863,
\selectlanguage{greek}η\selectlanguage{english}\textsuperscript{2}\textsubscript{p} = 0.00.

We also had missing EDA data for 18 participants (4 HD, 8 ANX, 6 HC) due
to quality control issues. For SCL, there were no main effects of
group,\emph{F} (2, 69) = 1.06, \emph{p} = .351,
\selectlanguage{greek}η\selectlanguage{english}\textsuperscript{2}\textsubscript{p} = 0.03 or task, \emph{F} (1, 69) =
2.19, \emph{p} = .143, \selectlanguage{greek}η\selectlanguage{english}\textsuperscript{2}\textsubscript{p} = 0.03 and
no interaction, \emph{F} (2, 69) = 0.58, \emph{p} = .562,
\selectlanguage{greek}η\selectlanguage{english}\textsuperscript{2}\textsubscript{p} = 0.02. Finally, for SCRs, there
were no main effects of group, \emph{F} (2, 69) = 1.44, \emph{p} = .244,
\selectlanguage{greek}η\selectlanguage{english}\textsuperscript{2}\textsubscript{p} = 0.04 or task, \emph{F} (1, 69) =
1.62, \emph{p} = .207, \selectlanguage{greek}η\selectlanguage{english}\textsuperscript{2}\textsubscript{p} = 0.02 and
no interaction, \emph{F} (2, 69) = 0.43, \emph{p} = .650,
\selectlanguage{greek}η\selectlanguage{english}\textsuperscript{2}\textsubscript{p} = 0.01.

Contrary to hypotheses, these findings indicate no differences in
psychophysiological activity among the groups or between the two tasks.
See Table 2 for means and standard deviations across groups.

\textbf{Prediction of Hoarding Severity}

The ERN during the simulated discarding task did not predict SI-R total
(\selectlanguage{greek}β \selectlanguage{english}= -0.07, \emph{p} = .559) or subscale (Clutter: \selectlanguage{greek}β \selectlanguage{english}= -0.06, \emph{p} =
.573; Difficulty Discarding, \selectlanguage{greek}β \selectlanguage{english}= -0.03, \emph{p} = .794; Acquiring, \selectlanguage{greek}β \selectlanguage{english}=
-0.10, \emph{p} = .379) scores, controlling for age.

\textbf{Discussion}

The aim of this study was to compare CNS activity, measured with ERN and
alpha asymmetry, and PNS activity, measured by HRV, HR,
ETCO\textsubscript{2}, SCL, and SCR, during simulated discarding
decisions and emotionally neutral decisions in individuals with HD,
anxious control participants, and healthy control participants. Contrary
to hypotheses, there were no significant group differences on any CNS or
PNS measures for neutral or discarding decisions. The ERN during the
simulated discarding task was not associated with hoarding symptoms. We
offer some potential explanations for these null findings below.

As described above, we had initially intended to use a simulated
discarding task that had been used in prior research on the ERN
(Baldwin, Whitford, \& Grisham, 2016). However, we had to modify the
original task to increase its difficulty and obtain more errors to
reliably measure the ERN, and we may have unintentionally ended up with
more of a visual detection task (participants had to distinguish between
newspapers that did and did not have pictures on them) rather than a
discarding-related decision-making task. Prior studies that have found
exaggerated activity in frontal brain regions and excessive
psychophysiological activation during discarding decisions have used
more ecologically valid tasks that likely were more emotionally salient
for those with HD, including sorting and discarding personal possessions
or imagined personal possessions (Levy, Nett, \& Tolin, 2019; Stevens et
al., 2020; Tolin et al., 2012). On the other hand, the task itself would
not explain why the neutral (non-discarding) task also showed no group
differences for CNS or PNS activity. Prior studies have found decreased
activity in frontal regions during neutral (non-discarding) error
processing tasks (Mathews et al., 2016; Sunol et al., 2019) and during
tasks involving discarding others' possessions (Tolin et al., 2012). By
contrast, Hough et al. (2016) reported greater activity in frontal
regions during error processing, making it challenging to draw
conclusions about CNS processes during decision-making in HD.

Alternatively, it is possible that our use of EEG hampered our ability
to detect HD-related abnormalities. As described above, the most
reliable evidence of exaggerated CNS activity during discarding
decisions comes from fMRI research (Stevens et al., 2020; Tolin et al.,
2012). The major advantage of EEG relative to fMRI is the ability to
assess moment-to-moment changes in brain activity, which is not possible
in fMRI due to the delayed BOLD signal. However, the ERN occurs at a
very specific time following commission of an error {[}approximately 50
milliseconds after the error; for a review, see Olvet and Hajcak
(2008){]}, so the tasks must be timed exactly to capture the effect.
Discarding tasks involving real possessions, by nature, cannot be timed
this precisely, making it challenging to design an ecologically valid
discarding task that is also accurate for measuring the ERN.

We also did not find evidence of greater right vs. left alpha asymmetry
during a baseline resting period in HD relative to the anxious and
healthy control groups. To our knowledge, this study is the first to
assess alpha asymmetry in individuals with HD. Prior research has shown
that depression, which is commonly comorbid with HD, is characterized by
right lateralized alpha asymmetry (Coan \& Allen, 2004; Kemp et al.,
2010), although it should be noted that a meta-analysis did not find
alpha asymmetry differences between patients with major depressive
disorder and healthy controls (van der Vinne et al., 2017). We were
surprised by this finding, particularly because patients with HD
commonly engage in avoidance behaviors (particularly discarding their
possessions) and they experience social impairment often characterized
by withdrawal from significant others. Alpha asymmetry has previously
been linked to avoidance/withdrawal motivation (Coan, Allen, \&
Harmon-Jones, 2001). On the other hand, other mental health disorders
characterized by avoidance that are often comorbid with HD, including
anxiety-related disorders, have not consistently shown significantly
right lateralized alpha asymmetry (Harrewijn, Van der Molen, \&
Westenberg, 2016; Kemp et al., 2010; Smith, Zambrano-Vazquez, \& Allen,
2016). Based on the results of the current study, alpha asymmetry may
not be a fruitful biomarker for future study in HD.

Future investigations of CNS and PNS responses to decision-making in HD
may require more ecologically valid discarding tasks. Although this may
be challenging due to the barriers we described above, a potential
avenue for future research is the use of virtual reality technology,
which was tested and showed promise in terms of treatment acceptability
and enhancing motivation for change in reducing clutter (Chasson et al.,
2020). In this work, participants were immersed in a virtual reality
environment that depicted rooms in their own homes. It is possible that
a virtual reality environment would preserve the ecological validity of
a discarding task but also allow the individual discarding decisions to
be timed accurately enough to measure the ERN.

In addition to the methodological challenges described above, the
current study had other limitations. First, the study was conducted
during the COVID-19 pandemic, when recruitment for in-laboratory studies
was particularly difficult. Because we were attempting to recruit
individuals with HD, who are typically older, we suspect that many
prospective participants declined the study due to discomfort about
attending an in-person appointment. We also faced unexpected data loss
due to equipment malfunctions, which further reduced our sample size and
statistical power. It should be noted that the effect sizes we obtained
in the current study were so small (ranging from
\selectlanguage{greek}η\selectlanguage{english}\textsuperscript{2}\textsubscript{p} = 0.00-0.06) that it would have
taken very large samples to detect these effects; we thus do not have
reason to suspect that a larger sample would have greatly changed the
results of the current study. Furthermore, our \emph{a priori} power
analysis indicated that our sample was large enough to detect at least a
medium effect (see above). Our sample was also limited in terms of
racial diversity. Second, despite our efforts to match the control
groups to the HD group for age and sex, we ended up with age differences
and had to control for age in the study analyses. To ensure that
covarying age did not undermine our statistical power, we re-ran the
study analyses excluding the covariate and found similar results for the
ERN and psychophysiological activity. Nevertheless, matching for age
across comparison groups is an important consideration for EEG research,
given normative changes in neural activity that are associated with
aging (Daselaar et al., 2015; Meyer, 2017; Raz et al., 2005; Rodrigue \&
Raz, 2004; Walhovd et al., 2011).

Further clarification of the neurobiology of HD is hoped to point to
novel biological mechanisms that could be targeted in intervention
development. As an example, a recent study in undergraduate students
found that a single-session cognitive-behavioral intervention focused on
reducing error sensitivity decreased the ERN, particularly for those
with the highest baseline ERN (Meyer et al., 2020). It will also be
important to further test the proposed neurobiological model of HD
(Tolin, 2023). One particular area that remains to be studied pertains
to the hypoactivity observed at rest (Saxena et al., 2004) and in
neutral (non-discarding) tasks (Mathews et al., 2016; Sunol et al.,
2019) among individuals with HD. It is unclear whether this hypoactivity
is a critical or causal mechanism of HD or simply a side effect of HD
symptoms. We look forward to future work that addresses these questions.

\textbf{Acknowledgements}

The authors wish to thank Rachel Goldblum, Kate Everhardt, Cassandra
Franke, Margaret Azu, Sophie Cramer-Benjamin, and Diogo Goncalves-Fortes
for their assistance with data collection and analysis.

Study funded by NIMH R21MH122182 (Co-PIs: Tolin and McPartland).

The datasets analyzed during the current study are available in the NIMH
Data Archive, NIMH Data Archive Digital Object Identifier (DOI):
10.15154/w5re-z011.

This manuscript reflects the views of the authors and may not reflect
the opinions or views of the NIH or of the Submitters submitting
original data to NDA.

\textbf{Conflict-of-Interest Statement}

Dr. Levy has received grant funding from Hartford Hospital Medical Staff
and the American Psychological Foundation.

James C. McPartland consults with Customer Value Partners, Bridgebio,
Determined Health, and BlackThorn Therapeutics, has received research
funding from Janssen Research and Development, serves on the Scientific
Advisory Boards of Pastorus and Modern Clinics, and receives royalties
from Guilford Press, Lambert, Oxford, and Springer.

Dr. Tolin has received grant funding from Hartford Hospital Medical
Staff; grant funding, material support, and consultant fees from Oui
Therapeutics; consultant fees from Mindyra LLC; and royalties from
Guilford Press, Oxford University Press, Cambridge University Press,
John Wiley and Sons, Springer Publications, and New Harbinger
Publications.

Dr. Naples and Sarah Collett have no conflicts to declare.

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