Error monitoring and response inhibition in adolescents with bipolar disorders: An ERP study.

Error Monitoring and Response Inhibition in Adolescents with Bipolar Disorders: An ERP Study - PMC Skip to main content An official website of the United States government Here's how you know Here's how you know Search Log in Primary site navigation Search Log in Search PMC Full-Text Archive Search in PMC Journal List User Guide As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health. Learn more: PMC Disclaimer | PMC Copyright Notice Cogn Affect Behav Neurosci . Author manuscript; available in PMC: 2026 Jun 1. Published in final edited form as: Cogn Affect Behav Neurosci. 2024 Dec 19;25(3):852–867. doi: 10.3758/s13415-024-01253-1 Error Monitoring and Response Inhibition in Adolescents with Bipolar Disorders: An ERP Study Kasey Stack 1, 2 , Joshua J Stim 3, 4 , Scott R Sponheim 1, 3, 5 , Paul Collins 3 , Monica Luciana 5 , Snežana Urošević 1, 3 Author information Article notes Copyright and License information 1 Minneapolis VA Health Care System, Minneapolis, Minnesota; 2 Department of Neurology,Georgetown University Medical Center; 3 Department of Psychiatry and Behavioral Sciences, University of Minnesota, Twin Cities; 4 Department of Biostatistics, Johns Hopkins University; 5 Department of Psychology, University of Minnesota, Twin Cities. Authors’ contributions: Kasey Stack: First draft and editing of the manuscript, preprocessed the EEG data, ran statistical analyses. Joshua J Stim: Contributed to the data preprocessing and analysis and edited the manuscript. Scott R Sponheim: Contributed to the data analysis and edited the manuscript. Paul Collins: Contributed to study design, data preprocessing and edited the manuscript. Monica Luciana: Contributed to study design and edited the manuscript. Snežana Urošević: Senior author, procured study funding, designed the study, directed data collection and data analysis, and edited the manuscript. ✉ Corresponding author: Snežana Urošević, Ph.D., Minneapolis VA Health Care System, Psychology Services #116B, One Veterans Drive, Minneapolis, Minnesota 55417; snezana.urosevic@gmail.com , snezana.urosevic@va.gov Issue date 2025 Jun. PMC Copyright notice PMCID: PMC12129687  NIHMSID: NIHMS2076987  PMID: 39702729 The publisher's version of this article is available at Cogn Affect Behav Neurosci Abstract Cognitive control develops throughout adolescence, a high-risk period for bipolar disorders (BD) onset. Despite neurobehavioral abnormalities in adults with BD, there is minimal research investigating deviations in cognitive control in adolescents with BD. Cognitive control involves numerous processes and identifying the specific neural abnormalities in adolescent BD could provide precise targets for novel interventions that improve illness outcomes. The present study administered a Go/No-Go (GNG) task to 98 adolescents (44 BD; 54 controls) to activate response inhibition and error processes and recorded EEG for event-related potentials (ERPs) analysis. Stimulus-locked N2 and P3 (response inhibition) and response-locked error-related negativity (ERN; early error detection) and error positivity (Pe; conscious error detection) were analyzed. Adolescents with BD had attenuated Pe mean amplitudes following failed inhibition trials. There were no group differences in other ERP amplitudes, including N2, P3, and ERN. The pattern of findings implicates conscious error detection impairment in adolescents with BD, without support for deficits in more automatic, earlier error detection. Impaired conscious error detection in adolescents with BD may be an early expression of BD pathophysiology and a possible intervention target for cognitive rehabilitation. Further studies are needed to examine Pe in BD across the lifetime. Keywords: bipolar disorder, adolescence, response inhibition, error detection, event-related potentials Deficits in cognitive control appear to be transdiagnostic and underlie multiple psychiatric disorders ( McTeague et al., 2016 , Yan et al., 2022 ). These impairments are particularly pronounced in bipolar disorders (BD), as adults with BD exhibit more severe deficits in cognitive control than those with many other psychiatric disorders (i.e., larger effect sizes, more cross-domain deficits, decreased gray matter in relevant brain regions; McTeague et al., 2016 ; Gildengers et al., 2013). Cognitive control is a set of higher order cognitive processes that adjust behavioral responses to varying environmental demands with the fundamental goal of successfully executing goal-oriented behavior ( Miller & Cohen, 2001 ; Menon & D’Esposito, 2022 ) and lending efficiency to related brain functions ( Mackie et al., 2013 ). In addition, adolescence is thought to be a unique time in the development of cognitive control, during which neural processes start to gain the flexibility that is evident during adulthood ( Luna et al., 2010 ). Despite adolescence being a period of neurodevelopment for cognitive control and a high-risk period for BD onset, cognitive control processes in adolescents with BD have not been fully examined. Understanding deviations in subdomains of cognitive control (i.e., response inhibition and error monitoring) among adolescents with BD could provide specific neural targets for interventions that prevent poor outcomes in youth with BD. To address this gap in research, the present study is the first to date to examine neural processes during response inhibition and error monitoring in adolescents with BD using event-related potentials (ERPs). Impulsivity is a hallmark of BD, manifesting in both mania and depression in different ways, and may be conceptualized as a failure of cognitive control processes ( Swann et al., 2010 ). Research of healthy adults and adolescents supports this view of impulsivity, finding that individuals scoring higher on impulsivity measures exhibit smaller ERN amplitudes during flanker tasks, which could be a result of reduced error salience or decreased motivation for error monitoring ( Potts et al., 2006 , Heffer & Willoughby, 2021 ; Pailing et al., 2002 ; Taylor et al., 2018 ). In people with BD, increased impulsivity during mania may contribute to classic manic symptoms such as risk-taking behaviors, aggression, and disregard for consequences ( Najt et al., 2007 ; Strakowski et al., 2010 ; Swann et al, 2009 ; Perroud et al., 2011 ). In depression, levels of non-planning impulsivity are higher, ( Patton et al., 1995 ; Swann et al., 2008 ), which may be why impulsivity has been linked to increased suicidality in individuals with BD ( Swann et al., 2005 , Dramilaraki et al., 2021 ). Even when euthymic, adults with BD have higher levels of impulsivity than healthy adults ( Newman & Meyer, 2014 ; Saddichha & Schuetz., 2014 ; Najt et al., 2007 ; Saunders et al., 2016 ). Among young adults with Bipolar II Disorder, high impulsivity predicts a greater likelihood of progression to Bipolar I Disorder, or worsening BD illness course ( Alloy et al., 2012 ). In adults, self-reported impulsivity is a significant predictor of longitudinal illness severity ( Rote et al., 2018 ). Thus, several lines of research support the link between higher impulsivity, or cognitive control difficulties, and poor illness outcomes in BD. Adults with BD also exhibit deficits in several more direct behavioral measures of cognitive control. A meta-analysis documented that people with BD make more commission and omission errors than people without mental disorders in Go/No-Go (GNG) tasks, which require cue-dependent response inhibition ( Wright et al., 2014 ). Additional studies demonstrate that adults with BD perform worse than healthy adults on other tests of cognitive control, such as Stroop tasks or the Immediate Memory Task ( Strawkowsi et al., 2005 ; Swann et al., 2009 ). Frangou et al. (2005) found that response inhibition further deteriorates with illness duration, suggesting a neuroprogressive process may be in play in BD. While less extensive than in adults, behavioral studies of adolescents with BD find similar deficits in executive function, attention, and memory (e.g., Pavuluri et al., 2009 ). However, behavioral studies are blind to the temporal dynamics of neural processes that underlie cognitive control deficits in BD. Thus, when neural aberrations in cognitive control occur in response to a stimulus and whether response inhibition or error detection are affected in adolescents with BD are largely unknown. Existing studies in adolescents with BD have primarily used functional magnetic resonance imaging (fMRI; e.g. Diler et al., 2014 ; Passarotti et al., 2010 ; Diler et al., 2013 ; Pavuluri et al., 2010 ) and show abnormal activations in the caudate, anterior cingulate, and ventrolateral prefrontal cortex. The use of electroencephalography (EEG), with its higher temporal resolution, are needed for a more fine-grained examination of cognitive control processes, such as response inhibition and error monitoring, to fully characterize the primary neural deficits in adolescent BD. Several ERPs are key to investigate response inhibition and error monitoring processes. Related to response inhibition, tasks that include standard and rare stimuli, such GNG or Oddball tasks, elicit the N2, a relatively early medial-frontal negative component ( Patel & Azzam, 2005 ). The N2 is thought to be a marker of pre-motor response inhibition of a primed response ( Falkenstein et al., 1999 ; Jodo & Kayama, 1991). Previous research has established that N2 amplitude is generally larger in correct No-Go trials (when response inhibition is successful) compared to the more frequently occurring Go trials. (e.g., Falkstein et al., 1999 ; Jonkman et al., 2003 ; Folstein & Van Petten, 2008 ). The P3 is thought to be a marker of response inhibition when attending to task relevant stimuli ( Picton et al., 1992 ). Larger P3 amplitudes are elicited by novel or target stimuli which often occur less frequently than non-targets. In the GNG task, the No-Go trials, which occur less frequently than Go trials, are the novel stimuli that elicit P3 (e.g., Smith et al., 2008 ; Bruin & Wijers, 2002 ; Bokura et al., 2001 ). Two response-locked ERPs, error-related negativity (ERN) and error positivity (Pe), are frequently examined in relation to error monitoring. The ERN is an early post-response negative component immediately following erroneous responses thought to reflect the activation of an early error detection system ( Scheffer et. al, 1996 ; Gehring et al., 1993 ; Nieuwenhuis et al., 2001 ; Falkenstein et al., 1999 ). Less frequently studied, the Pe is a later positive component thought to be a marker of conscious awareness and detection of one’s mistakes, and is larger for error trials, such as failed inhibition ( Nieuwenhuis et al., 2001 ; Falkenstein et al., 2000 ). Despite well-established behavioral deficits in GNG task performance in studies of adults with BD, there has been less research into the specific neural processes that may be affected during the GNG task. The available ERP studies assessing response inhibition and error monitoring during a GNG task in adults with BD consistently report attenuated No-Go N2 amplitudes in BD ( Michelini et al., 2016 ; Morsel et al., 2017 ; Chun, 2010 ). The relationship between P3 and BD is less clear, as studies have found that P3 amplitudes were attenuated, equal to, or even greater in those with BD compared to controls ( Michelini et al., 2016 ; Van Voorhis et al., 2019 ; Chun et al., 2013 ; Chun 2010 ). To date no studies have examined ERN or Pe in adults or adolescents with BD using a standard visual GNG task. The limited understanding of cognitive control processes in adolescents with BD is a critical gap in literature given that early-onset BD is linked to worse illness outcomes. Early-onset BD has been associated with increased psychiatric comorbidities, episode frequency, and suicidality ( Perlis et al., 2004 ; Holtzman et al., 2015 ; Cirone et al., 2021 ; Schuroff et al., 2000 ). In addition to being a marker of poor prognosis, onset of BD symptoms in childhood or adolescence is common, as studies with large samples have shown that mean age at first BD episode is younger than 20 ( Perlis et al., 2004 ; Beesdo et al., 2009 Post et al., 2010 ). It is possible that part of the reason for a link between an early onset of BD and poor prognosis is due to the disruption of the neurodevelopment of cognitive control that occurs during adolescence (e.g., Lebel & Beaulieu, 2011 ; Luna, 2009 ; Luciana et al., 2012 ). To address this gap in literature, the present study is the first to examine ERP indices of cognitive control processes during a GNG task in adolescents with BD. This approach will allow us to determine first, if neural abnormalities in cognitive control processes are present in adolescents with BD, and second, if these abnormalities are in response inhibition, recognition of novel stimuli, early preconscious error detection, or later conscious error detection processes. Given evidence of increased impulsivity in adults with BD, we hypothesize generally attenuated neural resources in cognitive control processes in adolescents with BD compared to typically developing adolescents. In other words, adolescents with BD will have lower mean amplitudes than controls in both response inhibition and error monitoring ERPs, such as lower N2 and P3 amplitudes to No-Go trials, and lower Pe and ERN amplitudes to error trials. However, given the paucity of current ERP research in adolescent BD and mixed findings in certain ERP studies of adult BD, it is also possible that adolescents with BD will have attenuation only for a singular cognitive control domain and its associated ERP. Methods Participants The sample consisted of 107 adolescents ages 13–19 part of a larger longitudinal study who were recruited through university-affiliated clinics, a community research database, and community flyers. Adolescents with BD (n = 49), met criteria for a DSM-5 diagnosis ( American Psychiatric Association, 2013 ) of Bipolar I (BD-I), Bipolar II (BD-II), or Other Specified Bipolar Disorder (BD-OS). Those with BD-OS had major depressive episodes and short duration hypomania, but are included in this study due prior research indicating that BD-OS is both a risk factor for progression to BD-I or BD-II ( Alloy et al., 2012 ) and on the same spectrum as BD-I ( Hafeman et al., 2013 ). The healthy control group (HC) did not meet any criteria for any DSM-5 mental disorders and had no family history of BD or psychosis. The Kiddie Schedule for Affective Disorders and Schizophrenia-Present and Lifetime Version 2009 ( K-SADS-PL, Axelson et. al, 2009 ) was administered to all participants, as well as their parents, if the participant was a minor (age < 18 years). Inter-rater reliability for the K-SADS-PL-rated symptoms was excellent (weighted- kappa = 0.87) and additional consensus procedures were used to establish diagnostic validity and reliability (see Urosevic et al., 2016 ). The K-SADS Depression Rating Scale (KDRS) and K-SADS Mania Rating Scale (KMRS; Axelson et. al, 2003 ), which assess past week depressive and manic symptoms, were administered to the BD group to determine current clinical state. Participants were required to meet the following inclusion criteria: absence of neurological disorders or severe head injury; no major/chronic physical conditions; absence of fMRI contraindications; IQ ≥ 70; absence of learning disabilities/developmental problems; normal/corrected-to-normal vision and hearing; native English speaker or bilingual since age 5; and right handedness. Nine participants (5 BD, 4 HC) were excluded from all analyses due to technical difficulties during EEG recording/preprocessing or deviations in task administration protocol (e.g., suspected coaching by parent). The final sample included 98 participants (44 BD, 54 HC). Table 1 provides additional demographic and clinical characteristics. Table 1. Demographic and Clinical Characteristics of Study Participants Measure BD (n = 44) HC (n = 54) p Age, M (SD) 16.08 (1.73) 15.72 (1.76) .321 Female, n (%) 24 (55%) 24 (44%) .320 Race, n (%) .323 African-American 4 (9%) 2 (4%) Asian/Pacific Islander 1 (2%) 2 (4%) Caucasian 31 (71%) 43 (80%) Native American 0 (0%) 2 (4%) Other 8 (18%) 5 (9%) Hispanic, n (%) 1 (2%) 1 (2%) .883 IQ, M (SD) 106.70 (12.54) 115.13 (10.76) <.001 ISS-Activation, M (SD) 152.50 (106.42) 71.67 (64.42) <.001 ISS-Depression, M (SD) 35.23 (38.79) 5.74 (11.26) <.001 MPQ-BF Control, M (SD) 5.82 (2.76) 8.06 (2.73) <.001 Current psychopharmacology, n (%) 39 (89%) -- BD I Dx, n (%) 17 (39%) -- BD II Dx, n (%) 15 (34%) -- BD NOS Dx, n (%) 12 (27%) -- BD age of onset, M (SD) 8.95 (3.19) Number of lifetime comorbid diagnoses, M (SD) 2.57 (1.80) -- ADHD, n (%) 18 (41%) -- Any Anxiety Dx, n (%) 30 (68%) -- Any Eating Dx, n (%) 11 (25%) -- Enuresis, n (%) 7 (16%) -- ODD/CD Dx, n (%) 6 (14%) -- Any Substance Use Dx, n (%) 12 (27%) -- Open in a new tab Note . ADHD = Attention-Deficit Hyperactivity Disorder; BD NOS = Bipolar Disorder Not Otherwise Specified; ISS = Internal State Scale; MPQ-BF = Multidimensional Personality Questionnaire-Brief Form; ODD/CD = Oppositional Defiant Disorder/Conduct Disorder. Procedures Participants and their parents/legal guardians provided informed assent/consent before data collection. The larger study was divided into two visits, the first of which included an informed assent/consent, a diagnostic interview, self-report questionnaires, and an intelligence assessment. The second visit involved behavioral task testing, EEG data collection, and fMRI. Although some of the larger study’s findings have been previously reported (e.g., Urosevic et al., 2016 ), the present set of analyses is novel and uses participant age, current symptom assessments, intelligence, self-report of impulsivity, and ERP and behavioral data from the GNG task. Measures The Internal State Scale (ISS; Bauer et al., 1991 ; 2000 ). The ISS is a self-report measure of four bipolar symptom dimensions (Activation, Depression, Perceived Conflict, and Well-being) in the 24 hours before testing. ISS-Activation and Depression scores correlate strongly with interview-based ratings of mania and depression, respectively ( Bauer et al., 1991 ). The Multidimensional Personality Questionnaire-Brief Form (MPQ-BF; Patrick et al., 2002 ). The MPQ-BF is a self-report personality assessment composed of 11 primary trait scales that make up three higher order temperament factors. The Control primary scale is a measure of impulsivity mainly related to response inhibition and lack of premeditation ( Whiteside & Lynam, 2001 ; Sach et al., 2018 ) and has been used as a measure of impulsivity in previous GNG studies of normative populations (e.g., Sach et al., 2018 ). 91 participants (39 BD, 52 HC) had valid MPQ-BF data available (based on the MPQ validity scales scores; Patrick et al., 2002 ). Wechsler’s Abbreviated Scale of Intelligence-Second Edition (WASI-II; Wechsler, 2011 ). The Vocabulary and Matrix Reasoning subsets of the WASI-II were administered as a measure of intellectual ability. The Go/No-Go (GNG) Task ( Hooper et al., 2004 ). This modified version of the GNG task included a standard GNG in which participants were instructed to press button 3 on a 5-point button box when any letter besides X appeared on the screen, and to refrain from pressing the button when an X appeared on the screen. The other conditions included target detection (button push only for the letter X), and response shift (press one button for X and press another button for all other letters). Participants were instructed to answer as quickly as they could, while minimizing errors. Only the standard GNG condition is analyzed here for ease of interpretation in the context of adult BD and broader GNG literature. Participants completed two blocks of the standard GNG for a total of 228 trials. About 24% of trials were No-Go (“X”) trials. Trials had a maximum presentation duration of 2000 ms, with a randomly selected intertrial interval of 800 ms, 1000ms, or 1200 ms. Because Go trials are more frequent than No-Go trials, there is a primed tendency to respond on all trials. Participants must inhibit this response when an X appears. d’ (the z-score transformation of hit rate minus the z-score transformation of failed inhibition rate, with an adjustment for perfect performance; Stanislaw & Todorow, 1999 ) was used as a primary measure of participants’ overall accuracy. Table 2 provides additional task performance behavioral measures. Table 2. Group Means and Differences in Go/No-Go Behavioral Data Behavioral Measure, M (SD) BD (n = 44) HC (n = 54) p # Incorrect Go trials 22.91 (24.37) 10.52 (13.01) .002 # Incorrect No-Go trials 25.77 (8.33) 24.35 (8.39) .203 Hit rate .868 (.140) .940 (.075) .003 Successful inhibition rate .621 (.229) .760 (.178) .001 Overall accuracy rate .786 (.123) .847 (.077) .006 d’ 1.36 (0.86) 1.84 (0.80) .005 Post-error accuracy change −0.11 (0.14) −0.47 (0.07) .009 Hit RT (ms) 288.92 (40.34) 282.98 (40.72) .473 Failed inhibition RT (ms) 259.53 (36.50) 244.69 (23.15) .022 Open in a new tab Note . Failed inhibition = Incorrect No-Go trial; Hit = Correct Go trial; Overall accuracy rate = Proportion of correct Go and No-Go trials to all trials. RT = Reaction time; Successful inhibition = Correct No-Go trial. EEG Recording and Preprocessing. EEG data were collected with a 128-electrode Geodesic sensor net (GSN128; Electrical Geodesics Inc., Eugene, OR). Electrode impedances were kept below 100KΩ. The data were band-pass filtered between 0.5 Hz and 80 Hz. The sample rate at the time of recording was 250 Hz; we did not resample the data. Epochs were extracted from −200–950 ms relative to stimulus onset, and −450–500 ms relative to response. A custom-built EEG preprocessing pipeline with Independent Component Analysis (ICA) was used to remove artifacts from the EEG ( Kang et. al., 2019 ). Prior to ICA decomposition, epochs containing atypical signal artifacts, such as those produced by body or electrode movements, were manually removed from the data. Following ICA decomposition, independent components (ICs) were identified based on visual inspection of the IC topography, time series, and power spectrum. ICs that constituted signal artifacts were removed from the EEG data. The artifact-free data were then re-referenced to the average of all scalp electrodes. No participant had > 20% of their epochs excluded during preprocessing. ERP Analysis. Using ERPLab ( Lopez-Calderon & Luck, 2014 ), stimulus-locked ERPs were baseline-corrected using a window of −200 to 0 ms pre-stimulus ( Burwell et al., 2016 ; Shen et al., 2020 ). The N2 mean amplitude was derived across the 225–350 ms post-stimulus time-window at frontocentral sites (FCz and its 6 nearest sites, averaging across all 7 electrodes), and P3 mean amplitude was derived across the 270–550 ms post-stimulus time-window at parietal sites (Pz and its 6 nearest sites, averaging across all 7 electrodes). Response-locked ERPs were baseline-corrected using a window of −450 to −250 ms pre-response ( Burwell et al., 2016 ). The ERN mean amplitude was derived across the 0–150 ms post-response time-window at the same frontocentral sites (averaging across all 7 electrodes), and Pe mean amplitude was derived across the 150–400 ms post-response time-window at the same parietal sites (averaging across all 7 electrodes). Previous research and visual inspection were used to establish ERP time windows ( Burwell et al., 2016 ; Johnstone et al., 2005 ; Wiersema et al., 2007 ; Heffer & Willoughby, 2021 ). Statistical Analysis. For the stimulus-locked ERPs (N2 and P3) only correct trials were included, consistent with past studies of GNG. We refer to correct Go trials as dominant response and correct Go trials as successful inhibition . For response-locked ERPs (ERN and Pe), correct Go trials and incorrect No-Go trials were analyzed and are referred to as hits and failed inhibitions , respectively. Since the response-locked ERN and Pe require a behavioral response, incorrect Go trials (absence of dominant response, i.e., a button press) and correct No-Go trials (successful inhibition of a button press) were not included in these analyses. For failed inhibition analyses only, data from 3 participants (0 BD, 3 HC) were excluded due to having less than 6 failed inhibition epochs ( M = 18.1 for those included; Olvet & Hajcak, 2009 ; Heffer & Willoughby, 2021 ; Lamm et al., 2006 ). For stimulus-locked analyses, all 98 participants had at least 7 correct trials for each condition ( M = 79.3 trials). For group differences in demographic and behavioral performance measures analyses, t-tests were used. Hierarchical linear modeling (HLM) was used for all other analyses, specifically the lme4 R package ( Bates et al., 2015 ), and p-values were obtained using lmerTest package (Kuznetsova, et al., 2017). Satterthwaite’s method was used to estimate degrees of freedom. Unstandardized beta values ( B ) are reported as effect sizes. Four separate models, each with a different ERP component as its dependent variable, were created. In addition, two models were fit for behavioral data. Fixed effects for all models included group (BD, HC), trial type (correct dominant response/hit, successful inhibition, failed inhibition), age (mean-centered, continuous), and all interactions between these variables. To reduce type I errors, all main effects and interaction terms were entered simultaneously. Continuous variables were mean-centered and categorical variables were coded using effects coding to aid interpretability. To account for repeated measures, intercepts were allowed to vary by participant. Results Behavioral Data There were no group differences in demographic characteristics ( ps ≥ .320; see Table 1 ). The BD group had greater current hypomanic and depression symptoms than HC, as measured by the ISS Activation and Depression scales respectively ( p < .001 for both), while the HC group had higher MPQ-BF Control scores than BD group ( p < .001). The BD group also had lower estimated IQs than controls ( p < .001). Inclusion of ISS Activation, ISS Depression, and IQ as covariates in our statistical models did not significantly alter the pattern of findings (see Supplemental Materials ). For the sake of model simplicity, we present findings without covariates. Response time for correct dominant response in Go trials did not differ between the two groups ( ps = .473). For failed inhibition trials, adolescents with BD responded slower than controls ( p = .022). Those with BD had lower accuracy rates for both Go and No-Go trials compared to controls ( p = .003 and p = .001, respectively), with an overall lower d’ than controls ( p = .005), suggesting a decreased ability to adjust responses overall to changing demands of the GNG task. See Table 2 for further behavioral data details. EEG Data Figure 1 depicts all grand average ERP waveforms and topographies. Correlations between ERP measures are reported in Supplemental Table 1 . Figure 1. Open in a new tab Scalp Activation Maps and Grand Average ERPs Collapsed Across Groups Note . Stimulus-locked ERPs consisted of the N2 (a.) and P3 (b.). Response locked ERPs consisted of the ERN (c.) and Pe (d.). Scalp activation maps depict mean amplitudes for the ERP’s respective time window of measurement, separately for relevant task conditions. Each ERP’s relevant electrodes are green. The gray shaded section of each graph represents the ERP time window, and the shaded ribbon around each waveform represents the standard error. Stimulus-Locked ERPs N2 Mean Amplitude. There were no significant main or interaction effects of group, condition, or age on N2 ( ps ≥ .184). P3 Mean Amplitude. There were significant main effects of condition (hit > successful inhibition, B = 1.87, SE = 0.15, t (94) = 12.93, p < .001) and age (smaller amplitude with older age, B = −0.55, SE = 0.19, t (94) = −2.90, p = .005) on P3, which were qualified by a condition-by-age interaction ( F (94)= 4.12, p = .045). In post-hoc analyses, older age was associated with lower P3s for successful inhibition trials ( B = −0.70, SE = 0.20, t (121.00) = −3.43, p < .001), with similar but weaker association for hit trials ( B = −0.40, SE = 0.20, t (121.00) = −1.98, p =. 0499). There were no significant group effects on P3 ( ps ≥ .075). Response-Locked ERPs ERN Mean Amplitude. There was a significant main effect of condition on ERN, with more negative (larger) ERNs for failed inhibition trials than for hit trials ( B = −0.91, SE = 0.20, t (91.28) = −4.49, p < .001). There were no significant group or age effects on ERN ( ps ≥ .147). Pe Mean Amplitude. There were significant main effects of both group (BD < HC, B = −1.06, SE = 0.33, t (92.44) = −3.24, p = .002) and condition (failed inhibition > hit trials, B = 2.88, SE = 0.24, t (91.46) = 12.25, p < .001) on Pe, which were qualified by a group-by-condition interaction ( F (91.46) = 14.46, p <. 001). Further analysis showed that adolescents with BD had smaller Pe amplitudes than HC in failed inhibition trials ( B = −1.95, SE = 0.41, t (169.22) = −4.82, p < .001), but not in correct hit trials ( ps = .684; see Figure 2 ). Finally, there was a significant condition-by-age interaction effect on Pe ( F (90.56) = 4.99, p = .028). In post-hoc analyses, older age was associated with smaller Pe amplitudes for failed inhibition trials ( B = −0.56, SE = 0.20, t (168.02) = −2.78, p = .006), but not in hit trials ( ps = .857). Figure 2. Open in a new tab Group-by-Condition Interaction on Response-Locked Pe Mean Amplitude: Scalp Activation Maps and Average ERPs Note . Scalp activation maps depict mean amplitudes for Pe (150–400 ms post-response) separately for hit (top left) and failed inhibition trials (bottom left) . Pe’s relevant electrodes are green. There was no clear Pe for adolescents with BD or HCs following hit trials ( top right ). Adolescents with BD had lower Pe mean amplitudes than HCs following failed inhibition trials ( bottom right ). The gray shaded section of each graph represents the ERP time window, and the shaded ribbon around each waveform represents the standard error. The response-locked ERPs reported above were baseline-corrected using a window of −450 to −250 ms pre-response. Because baseline window selection for response-locked analyses varies across studies (e.g., Ruchsow et al., 2005 ), we conducted a post-hoc analysis of ERN and Pe using a correction window of −250 to −50 ms pre-response. All observed effects remained, and effect sizes were very similar to the original findings, if not larger (see Supplemental Materials ). Finally, ERN was calculated using participant specific local peak calculations with ±50 ms time windows for mean amplitudes and still yielded the same pattern of findings (see Supplemental Materials ). Post-Hoc Analyses of Pe and ERN Associations with Behavioral, Self-Report, and Other Measures To more fully understand the finding that Pe was smaller in BD than in the HC group for failed inhibition/error trials, exploratory analyses of associations with task behavioral performance measures were run. Pe amplitudes during failed inhibition trials were positively associated with behavioral accuracy on the task, i.e., d’ ( r (93) = .204, p = .047). We also examined post-error accuracy changes, defined as the hit rate for Go trials following an error response to a No-Go trial (i.e., failed inhibition) minus the hit rate for Go trials following a correct response to a Go trial ( Wu et al., 2021 ). Adolescents with BD had a significantly greater decrease in hit rate after failed inhibition trials than did healthy controls ( t (63.07) = −2.87, p = .009). However, across all participants and within the BD group only, post-error accuracy change was not associated with Pe amplitudes for failed inhibition trials ( ps ≥.321). We also conducted several post-hoc analyses to investigate previously established factors that could potentially impact ERN and/or Pe amplitudes in adolescents with BD. MPQ-BF Control scores had a significant positive association with Pe amplitudes for failed inhibition trials ( r (86) = .246, p = .021), but were not related to any other ERPs examined ( ps ≥ .248). In other words, adolescents with greater self-reported premeditation before acting also exhibited greater Pe amplitudes, which is associated with conscious error detection. Additional analyses were conducted to explore confounding contributions of specific psychotropic medications and comorbid psychiatric conditions to observed Pe and ERN findings. For both hit and failed inhibition trials, there were no significant differences in Pe or ERN mean amplitudes between adolescents with BD currently prescribed antipsychotic medication and adolescents with BD not currently prescribed antipsychotics ( ps ≥ .203). Similarly, for both hit and failed inhibition trials, adolescents with BD and a comorbid anxiety diagnosis did not significantly differ in Pe and ERN mean amplitudes compared to adolescents with BD and no comorbid anxiety diagnosis ( ps ≥ .156). Adding anxiety diagnosis or antipsychotic medication prescription to the response-locked HLMs did not significantly alter the pattern of findings. Discussion The present study presents novel findings using ERP indices of response inhibition and error detection during a GNG task in adolescents with BD. Following errors in inhibition, adolescents with BD had attenuated Pe mean amplitudes compared to their peers. However, adolescents with BD and their neurotypically developing peers had similar mean amplitudes of stimulus-locked ERPs and the response-locked ERN. These results suggest that adolescents with BD’s cognitive control deficits are not broad, but rather are restricted to a late and deliberative conscious error monitoring, as indexed by Pe. The functional significance of Pe has been discussed for years, with numerous theories emerging ( Overbeek et al., 2005 ). Several studies have suggested that Pe is a neurophysiological marker of conscious error detection given that Pe is significantly larger for errors that a participant recognizes rather than those that are unrecognized ( Falkenstein et al., 2000 ; Shalgi et al., 2009 ; Wessel et al., 2011 ; Hughes & Yeung, 2011 ; Wang et al., 2020 ; Murphy et al., 2012 ). Evidence that Pe is larger for conscious errors lends credence to the idea that Pe reflects the salience of an error; consciously perceived errors should have more salience than unperceived errors to correct erroneous behaviors in the future. Pe amplitudes are also larger for genuine errors than for experimentally manipulated errors, such as forced or incorrectly classified errors ( Stemmer et al., 2001 ; Ehlis et al., 2005 ), suggesting that Pe is related to the cognitive or affective salience of true errors, and not just poor task outcomes. Steinhauser and Yeung (2010) , proposed that Pe reflects accumulated evidence regarding whether an error has occurred since Pe is higher in a task condition instructing participants to report all trial errors (or minimize missed error signaling) than in a task condition where participants were instructed to avoid falsely signaling errors. Despite some differences in nuances of Pe function, overall, these studies support Pe as an index of conscious error monitoring process, while GNG studies of ERN amplitudes suggest preconscious error detection processes (Endrass et al., 2006, O’Connell et al., 2007 ). Consistently, the present findings indicate that only the conscious detection of errors in adolescents with BD is impaired. Our exploratory findings suggest that reduced conscious detection of errors may be related to aspects of heightened impulsivity observed in adolescents with BD. Adolescents with BD exhibited lower MPQ-BF Control scores compared to their typically developing peers, which are thought to reflect decreased premeditation prior to acting, or heightened impulsivity, in adolescents with BD. Higher self-reported MPQ-BF Control subscale scores were uniquely related to larger Pe mean amplitudes for failed inhibition trials. Since the MPQ-BF Control subscale is an inverse index of impulsivity and indicates lack of premeditation ( Whiteside & Lynam, 2001 ), it is possible that these non-planning/non-premeditation aspects of impulsivity may be driving deficits in conscious error detection observed in adolescents with BD. Future studies, particularly those examining Pe, are needed to fully understand the role of impulsivity, both at clinical and nonclinical levels, in conscious and preconscious error monitoring. On the behavioral performance level, Pe amplitudes during failed inhibition had a small but significant positive association with greater behavioral accuracy on the task. Consistently, adolescents with BD exhibited lower behavioral accuracy (d’) than their typically developing peers. However, this association between Pe amplitudes during failed inhibition and behavioral accuracy was not significant when examining adolescents with BD only ( ps = .284). Thus, it is unclear whether adolescents with BD are dedicating less effortful attention to the task, which would both increase errors and decrease Pe amplitude. Adolescents with BD also had greater decreases in post-error accuracy than their peers. In healthy adults, post-error accuracy improvements are only present after errors the participant was aware of ( Klein et al., 2007 ; although not consistently, see Danielmeier & Ullsperger, 2011 ). Despite the possibility that post-error accuracy could be worse in adolescents with BD due to reduced error awareness as indexed by Pe, post-error accuracy was not associated with Pe amplitude. In addition, the GNG task did not include feedback on behavioral performance or self-reporting of errors. Thus, it is unknown whether adolescents with BD have attenuated Pe amplitudes due to issues with error perception, reduced salience of errors, or lower motivation to avoid erroneous actions in the future. Regardless of contributing causes for attenuated Pe in adolescent BD, these deficits in conscious error detection could lead adolescents with BD to repeat impulsive behaviors, i.e., fail to inhibit a behavioral response that may lead to negative consequences in their daily lives, as is often seen in patients with BD (e.g., Newman & Meyer, 2014 ). Future studies with more nuanced behavioral paradigms are needed to fully examine factors contributing to attenuated Pe (e.g., error perception, reduced salience of errors, low motivation to correct errors) in adolescent BD and to determine whether these factors are malleable through neuromodulation or cognitive training. For example, in a study of healthy adults, Masina et al. (2019) showed that Pe amplitudes during a GNG task are malleable through repetitive transcranial magnetic stimulation to the left dorsolateral prefrontal cortex before the task performance. Future neuromodulation studies in adolescents with BD could attempt to increase their Pe mean amplitudes, and correspondingly, their conscious error awareness. Alternatively, existing studies suggest that behavioral therapies focused on promoting mindfulness, growth mindset, and cognitive flexibility, may impact Pe amplitudes as well ( Moser et al., 2011 ; Lin et al., 2019 ; Olfers & Band, 2017). Bolstering confidence in the validity of the present pattern of findings, expected GNG task condition effects were observed for P3, ERN, and Pe. Reflecting previous research ( Smith et al., 2008 ; Nieuwenhuis et al., 2001 ; Falkenstein et al., 2000 ), P3 was larger for No-Go trials, ERN was more negative for error trials, and Pe was larger for error trials. This increases confidence that the GNG task elicited the desired neural processes. For N2, there were no condition effects observed, which is consistent with at least two previous studies of adolescents without psychopathology ( Connell et al., 2019 , Lewis et al., 2006). Moreover, condition effects on N2 amplitudes in the GNG task appear inconsistent in adult and adolescent literature, with some studies reporting greater N2 amplitudes for No-Go trials than for Go trials (e.g., Falkstein et al., 1999 ; Jonkman et al., 2003 ; Folstein & Van Petten, 2008 , Shen et al., 2020 ) and other studies reporting N2 mean amplitudes for Go trials were greater than or equivalent to No-Go trials ( Johnstone et al., 2005 ; Barry et al., 2014 ). However, it is possible that using mean amplitude, rather than peak amplitude, for N2 is masking condition effects (see Figure 1 ). Figure 1 also indicates that across groups the sample distribution of ERN peak latency may be somewhat bimodal, indicative of individual differences in ERN latency. In a post-hoc analysis, we recalculated the ERN using mean amplitude surrounding the individual participant’s local ERN peak, but our findings remained consistent (see Supplemental Materials ). Given that mean amplitudes of ERPs are generally considered less noisy, more reliable, and more robust than peak amplitudes ( Clayson et al., 2013 ; Luck, 2014 ), present study analyses focused on mean amplitudes rather than peak amplitude. Regardless of possible waveform differences, the GNG condition effects for all examined ERPs, including N2 and ERN, have precedent in prior literature. In the present study, the GNG task was selected to probe whether fundamental response inhibition and error monitoring processes under emotionally neutral conditions are intact in adolescents with BD. This complicates comparisons of our findings to those studies using more complex cognitive control tasks, such as the flanker task ( Eriksen & Eriksen, 1974 ), that also involves spatial attention and processing, i.e., additional cognitive processes on which people with BD perform poorly ( Frantom et al., 2008 ; Lera-Miguel et al., 2010; Najt et al., 2013 ; Dias et al., 2008 ). Still, in a study using a modified flanker task, acutely depressed adults with BD had similar pattern of findings to the present study: attenuated Pe amplitudes for both error and correct trials and similar ERN amplitudes for errors compared to adults without psychopathology ( Kopf et al., 2015 ). A subset of patients were tested again when euthymic and continued to exhibit attenuated Pe amplitudes following error trials, suggesting that conscious error detection deficits may be trait-like and independent of clinical state in adults with BD. Consistently, in the present study, there were no significant associations of current bipolar symptoms with Pe for error trials ( ps ≥ .166). Additional longitudinal studies examining both electrophysiological changes and mental health outcomes in people with BD across the lifespan would provide a more complete picture of abnormalities in conscious error detection, and other cognitive control processes. Additionally, once emotional context is introduced to a GNG task, both emotional processing and cognitive control are needed, meaning that two neural systems are involved. Studies have found that people with BD have difficulty recognizing facial emotions and have irregular brain activation in emotional attention tasks ( Addington & Addington 1998 ; Getz et al., 2003 ; Malhi et al., 2007 ; Malhi et al., 2005 ; Rich et al., 2006 ). For populations with deficits in multiple areas of cognitive function, isolating systems of interest may be necessary to understand function at its most basic level. Future studies with additional processes and emotional contexts are necessary to test generalizability of the present findings related to conscious error monitoring. Future studies are also needed to examine whether the same deficits in conscious error detection are present in adults with BD, as there are no studies examining ERN or Pe in adults with BD using a GNG task, emotional or otherwise. Finally, the observed older age associations with reduced amplitudes of both Pe for error trials and P3 for successful inhibition trials extend prior studies of visual tasks that also show age-related decreases in P3 amplitude (e.g., Katsanis et al., 1996 ; Carlson & Iacono, 2006 ; Brumback et al., 2012 ; Santopetro et al., 2023 ). Developmental cortical thinning and increased efficiency are posited as possible explanations for this maturation effect on Pe and P3 amplitudes (Lu et al., 2007). Other studies of GNG are mixed in their support for age-related P3 and Pe decreases, but these other studies vary widely in age ranges included (e.g,. restricted age and/or no adolescent group; Johnstone et al., 2005 ; Wiersma et al., 2007 ; Burwell et al., 2016 ; Gorday & Meyer, 2018 ), making direct comparison difficult. A recent meta-analysis by Boen et al. (2022) found age-related attenuation in Pe amplitudes were restricted specifically to adolescence, consistent with this study’s findings. Limitations and Future Directions The present study has several limitations. Although the current study’s sample size is greater than other GNG studies in adults with BD (e.g., Degabriele et al., 2011 ; Chun et al., 2013 ) and comparable to studies of adolescents (e.g., Burwell et al., 2016 ), the present sample is insufficient for subgroup analyses within adolescents with BD based on current clinical state or specific bipolar diagnostic categories. For ethical reasons, participants were not asked to stop medication use during the study, nor were we able to use medication as a covariate in our analyses, given its near ubiquity with the BD group. While 89% of participants in the BD group were on psychotropic medications, past research suggests that medications do not always affect brain functions of interest in adult BD ( Hafeman et al., 2012 ) and thus, medication use is unlikely to fully explain the group differences observed. Consistently, given the dopaminergic system’s role in error processing ( Holroyd & Coles, 2002 ), and that antipsychotic medications commonly impact dopamine, we compared and found no differences in ERN and Pe mean amplitudes of adolescents with BD prescribed antipsychotic medications versus those without prescribed antipsychotics. Still, a larger sample is needed to fully examine cognitive control differences between subgroups in BD based on the classes of prescribed psychotropic medications. Without comparison groups with other mental disorders, the present study is unable to determine BD-specificity of observed findings in adolescent psychopathology or to fully address influence of comorbid psychiatric conditions on the present findings. For example, since youth with anxiety disorders exhibit larger ERN amplitudes than those observed in typically developing youth (e.g., Meyer et al., 2017 ), it’s possible that comorbid anxiety disorders could be obscuring a group difference in ERN after failed inhibition trials. However, we did not find any significant differences in ERN amplitudes among adolescents with BD based on the presence versus absence of comorbid anxiety disorder. Finally, the cross-sectional nature prohibits the determination of the exact age that error monitoring deviates from typical development in adolescents with BD. Longitudinal studies with larger sample sizes are needed to address these limitations. Conclusion Adolescents with BD exhibit impaired conscious error monitoring, without evidence for early error monitoring or response inhibition deficits, in the present study. This is the first study examining the GNG task using ERPs in adolescents with BD. Additional longitudinal research is necessary to replicate these findings and delve further into when error monitoring begins to deviate from neurotypical development. Future research could further hone in on identifying causal factors contributing to adolescents with BD’s impaired conscious error detection, examining conscious error detection under emotional contexts, and exploration of real-world impacts on psychosocial functioning of adolescents with BD. The present study suggests a link between impulsivity, or lack of premeditation specifically, and conscious error detection deficits in adolescent BD that require additional examination. These findings can provide a more detailed road map for future neuromodulation studies aiming to improve outcomes for adolescents with BD. Supplementary Material Supplementary Materials NIHMS2076987-supplement-Supplementary_Materials.docx (369.6KB, docx) Acknowledgments Drs. Urošević’s and Sponheim’s efforts were also partially supported with resources and the use of facilities at the Minneapolis VA Health Care System. The contents do not represent the views of the U.S. Department of Veterans Affairs or the United States Government. This article was written without the use of generative AI technologies. Finally, the authors would like to thank the research staff that contributed to data collection and especially the research participants and their families for their participation in this study. Funding: Research was supported by National Institute of Mental Health Grant K01 MH093621 to Snežana Urošević, PhD and by the University of Minnesota’s Center for Neurobehavioral Development. Drs. Urošević’s and Sponheim’s efforts were also partially supported with resources and the use of facilities at the Minneapolis VA Health Care System. Footnotes Conflicts of interest/competing interests: The authors declare no conflicts of interest with respect to their authorship or the publication of this article. Ethics approval: All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the University of Minnesota’s Institutional Review Board. Consent to participate: Informed consent was obtained from individual participants included in the study. If individual participants were under the age of 18, informed consent was obtained from their legal guardians and minors provided written assent. Code availability: Data analyses were conducted using the freely available software applications ERPLab and R. Open practices statement: Study data and materials are available from Snežana Urošević upon request. 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