Error-related negativity

Error-related negativity (ERN), also referred to as the error negativity (Ne), is a component of the event-related brain potential (ERP) observed in electroencephalography (EEG) studies, characterized by a sharp negative deflection in scalp-recorded voltage that peaks approximately 50–100 ms after the commission of an error during speeded-response cognitive tasks.^[1] This component is maximal at fronto-central electrode sites, such as FCz or Cz, and reflects rapid neural processes involved in error detection and performance monitoring.^[2] The ERN was independently identified in the early 1990s by two research groups: Falkenstein et al. reported a fronto-central negativity (Ne) in 1991 during choice reaction tasks under divided attention conditions, where error trials elicited a distinct negative waveform compared to correct responses.^[3] Shortly thereafter, Gehring et al. in 1993 described the ERN as part of a broader neural system for error detection and compensation, demonstrating its enhancement when participants emphasized accuracy over speed and its association with post-error behavioral adjustments.^[1] Neuroimaging and source localization studies have pinpointed the anterior cingulate cortex (ACC) as the primary generator of the ERN, with contributions from adjacent regions like the supplementary motor area and dopaminergic pathways in the basal ganglia.^[4] Functionally, the ERN is implicated in conflict monitoring and reinforcement learning, where it signals discrepancies between expected and actual outcomes to facilitate adaptive cognitive control.^[5]^[6] Theoretical models, such as the conflict monitoring hypothesis, propose that the ERN arises from the detection of response conflicts,^[6] while the reinforcement learning theory links it to midbrain dopamine bursts evaluating error salience for future learning.^[5] In psychopathology, the ERN serves as a potential endophenotype for disorders involving aberrant error processing: it is typically enlarged (more negative) in anxiety disorders and obsessive-compulsive disorder (OCD), reflecting heightened sensitivity to errors, whereas it is reduced in attention-deficit/hyperactivity disorder (ADHD), depression, and substance use disorders, indicating deficits in monitoring and adjustment.^[4]^[7] Developmental research further shows that ERN amplitude increases with age during childhood and adolescence, paralleling maturation of executive functions, and exhibits moderate heritability (around 47%).^[2] These findings underscore the ERN's utility as a biomarker for studying cognitive control across healthy and clinical populations.

Introduction and Characteristics

Definition and Overview

Error-related negativity (ERN), also known as the error negativity (Ne), is a component of the event-related brain potential (ERP) characterized by a sharp negative deflection in the electroencephalogram (EEG) that occurs following the commission of an error.^[4] This potential is elicited in speeded choice reaction tasks, peaking approximately 50-100 ms after an erroneous response, primarily at frontocentral scalp electrodes.^[4] As part of the broader ERP framework, which involves averaging EEG signals time-locked to specific events to isolate brain responses, the ERN reflects rapid neural processing without requiring conscious reflection.^[8] The ERN has been observed in both humans and non-human primates, such as macaques, where analogous error signals are recorded from the anterior cingulate cortex (ACC) during tasks involving motor errors or performance deviations.^[9] In these contexts, it indexes an automatic mechanism for detecting discrepancies between intended and actual actions, contributing to cognitive control processes that monitor and adjust ongoing behavior.^[10] This automaticity underscores the ERN's role in performance monitoring, enabling the brain to signal errors even when they are not overtly recognized. Typically, the ERN exhibits greater negativity on error trials compared to correct ones, though this varies with factors like task demands. Importantly, the ERN is distinct from conscious error awareness, as it emerges regardless of whether the individual subjectively detects the mistake; subsequent components like the error positivity (Pe) are more closely tied to awareness.^[8] This dissociation highlights the ERN's function as an early, preconscious indicator within the performance monitoring system.^[11]

Electrophysiological Properties

The error-related negativity (ERN) is characterized by a sharp negative deflection in the event-related potential (ERP) waveform, typically peaking between 50 and 100 ms following the commission of an erroneous response in speeded choice reaction tasks.^[12] This negativity is often followed by a subsequent positive deflection known as the error positivity (Pe), which emerges around 200-400 ms post-response, though the Pe may partially overlap with the ERN in some recordings.^[13] The ERN is response-locked, meaning it is time-aligned to the onset of the incorrect action (e.g., button press or EMG onset), distinguishing it from stimulus-locked components.^[14] A related correct-response negativity (CRN) can be observed following correct responses, exhibiting similar timing but reduced amplitude compared to the ERN.^[12] The scalp topography of the ERN is maximal over fronto-central midline electrodes, such as Cz and FCz in the 10-20 international system, with a symmetric distribution centered over the medial frontal cortex.^[13] This frontocentral focus is evident in difference waveforms (error minus correct trials) and remains consistent across various speeded-response paradigms, reflecting its robustness as an error-monitoring signal.^[12] Quantification of the ERN typically involves measuring its peak amplitude or mean amplitude within a 50-100 ms post-response window, corrected against a pre-response baseline such as -200 to 0 ms relative to the response onset.^[15] The amplitude is calculated as:

\text{ERN amplitude} = V_{\text{peak}} - V_{\text{baseline}}

where V_{\text{peak}} is the voltage at the negative peak on error trials and V_{\text{baseline}} is the average voltage in the baseline interval.^[12] To reduce noise and isolate error-specific activity, a difference score is commonly used:

\Delta \text{ERN} = \text{ERN amplitude} - \text{CRN amplitude}

This peak-to-peak or base-to-peak approach enhances reliability by subtracting the CRN from the ERN.^[13] The morphology of the ERN is influenced by response modality and task demands. For instance, ERN amplitude varies across output types, with reliable elicitation observed in manual (e.g., button press), vocal (e.g., picture naming), foot, and oculomotor responses, though the precise amplitude differences depend on the specific setup.^[12] Task factors such as emphasis on speed versus accuracy also modulate the ERN; speed-stressed conditions tend to yield smaller amplitudes, while accuracy-focused or high-conflict tasks produce larger ERNs.

Historical Background

Discovery

The initial observation of what is now recognized as the error-related negativity (ERN) occurred in 1968 during studies of voluntary movements in humans, where Natalia Bekhtereva and colleagues identified a brain response specifically associated with errors in task performance, termed the "error detector."^[16] This finding emerged within the broader tradition of Soviet electrophysiology, which paralleled Western research on slow cortical potentials.^[17] The ERN's origins can be traced to investigations of anticipatory brain activity, including the contingent negative variation (CNV)—a slow negative potential preceding expected stimuli or responses, first described by Grey Walter and colleagues in 1964—and the readiness potential, a motor preparatory negativity identified by Kornhuber and Deecke in 1965.^[18] These components provided the electrophysiological framework for detecting error-specific deflections, as Bekhtereva's work built on similar paradigms to explore mental activity and performance monitoring in healthy adults.^[17] The component was independently rediscovered in 1990 through parallel studies in Western laboratories. Michael Falkenstein and colleagues observed a negativity, labeled "Ne," peaking around 100-150 ms after incorrect responses in choice reaction tasks, distinguishing it from correct-trial potentials under focused and divided attention conditions. Concurrently, William Gehring and team reported a similar error-accompanying negativity, termed ERN, in event-related potentials during speeded-response tasks, presented at the Society for Psychophysiological Research meeting. These early descriptions appeared in key publications, including Falkenstein et al.'s 1990 chapter in an EEG supplement detailing error-specific negativity in healthy adults' ERPs, and a follow-up 1991 paper in Electroencephalography and Clinical Neurophysiology further characterizing the Ne's properties. Gehring's findings were elaborated in a 1993 journal article, solidifying the ERN as a distinct post-error component.

Key Milestones

In the 1990s, research on error-related negativity (ERN) advanced through its integration with computational models of cognitive control, particularly the conflict monitoring theory, which posited that the anterior cingulate cortex (ACC) detects response conflicts to adjust behavior, building on early ERN observations from speeded choice tasks.^[19] This framework, formalized in Botvinick et al. (2001), explained the ERN as a signal of conflict detection rather than mere error awareness, using 1990s ERP data to support simulations of ACC activation during incompatible responses.^[19] Concurrently, dipole source modeling established the dorsal ACC as the primary neural generator of the ERN, with studies localizing a frontocentral dipole to this region based on high-density EEG recordings during error commission tasks. For instance, Miltner et al. (1997) applied equivalent dipole analysis to time-estimation errors, confirming ACC involvement in a generic error detection system. During the 2000s, ERN research expanded to clinical populations, revealing heightened amplitudes in obsessive-compulsive disorder (OCD), which suggested overactive performance monitoring as a core feature. A seminal 2000 study by Gehring et al. demonstrated larger ERN responses in OCD patients relative to controls during a response competition task, linking this enhancement to symptom severity and supporting its role as a potential endophenotype.^[20] Additionally, the development of the feedback-related negativity (FRN), a variant elicited by external feedback rather than self-generated errors, broadened ERN applications to reinforcement learning contexts. Holroyd and Coles (2002) proposed a reinforcement learning account, where FRN amplitude reflects dopamine-modulated reward prediction errors, evidenced by midfrontal negativities to negative outcomes in gambling tasks. The 2010s saw meta-analyses affirming the ERN's reliability as a biomarker for anxiety, with enhanced amplitudes correlating specifically with worry-related traits across diverse samples. Moser et al. (2013) conducted a meta-analysis of 63 studies, finding a moderate effect size (r = -0.20) for the anxiety-ERN link, strongest for anxious apprehension subtypes, and emphasizing its predictive utility for internalizing disorders. ERN research also incorporated developmental perspectives, tracking its emergence from early childhood and relation to anxiety trajectories. Meyer et al. (2015) longitudinally examined children aged 6 years, showing that larger ERN at baseline predicted anxiety onset by age 9, highlighting maturation of ACC-prefrontal circuits in performance monitoring.^[21] Post-2020 developments have focused on validating ERN's behavioral correlates and exploring familial patterns. Clayson et al. (2023) reviewed psychometric evidence, confirming moderate convergent validity (r ≈ 0.50) between ERN and post-error slowing across tasks like flanker and Stroop, while noting task-specific variability in reliability.^[22] Recent studies have uncovered intergenerational transmission of ERN patterns, with maternal ERN amplitudes predicting adolescent offspring's responses in at-risk families, potentially conferring vulnerability to internalizing symptoms via shared genetic or environmental factors. Furthermore, investigations into sex differences have shown that the ERN-anxiety association is stronger in females.

Experimental Methods

Primary Paradigms

The primary paradigms for eliciting error-related negativity (ERN) involve speeded choice reaction time tasks that reliably generate errors through cognitive conflict or response inhibition demands, allowing for the extraction of this frontocentral ERP component peaking 50-100 ms after incorrect responses via EEG recording. These paradigms emphasize rapid decision-making, typically with response deadlines under 500 ms, to promote error rates of 5-20%, ensuring a minimum of 20-50 error trials per participant for robust averaging and signal-to-noise ratio in ERP analysis. Common setups include 500-1500 trials overall, with performance feedback sometimes provided to maintain engagement without directly influencing the response-locked ERN.^[4] The Eriksen flanker task, a cornerstone paradigm for ERN research, requires participants to indicate the direction of a central target arrow (e.g., →) via button press, while ignoring flanking arrows that are either congruent (e.g., →→→→→) or incongruent (e.g., →←→←→). Incongruent flankers induce response conflict, increasing error probability on speeded trials and eliciting a pronounced ERN following mistakes. This design highlights compatibility judgments under distraction, with error rates controlled by stimulus proportion (e.g., 20% incongruent) to optimize ERN amplitude without excessive fatigue.^[4] In the Go/NoGo task, participants respond quickly to frequent "Go" stimuli (e.g., a specific letter or shape) but withhold responses to rare "NoGo" stimuli (e.g., 20-30% probability), fostering errors of commission on NoGo trials that trigger the ERN. This inhibition-focused paradigm probes action monitoring, with the ERN reflecting rapid detection of failed suppression, as evidenced in early ERP investigations of response errors. Optimal error induction relies on low NoGo frequency to build habitual responding, yielding 5-15% error rates suitable for averaging across 300-600 trials.^[23]^[4] The color-word Stroop task presents words denoting colors (e.g., "red") printed in congruent or incongruent ink colors (e.g., "red" in green ink), requiring participants to name the ink color while ignoring the word meaning under time pressure. Semantic interference from incongruent trials elevates error rates, particularly on speeded responses, producing an ERN that indexes conflict resolution failures, consistent with conflict-monitoring theories supported by ERP data from interference paradigms. Typically comprising 400-800 trials with 25% incongruent stimuli, this task maintains error rates around 10% to facilitate reliable ERN measurement.^[4]

Measurement Techniques

Error-related negativity (ERN) is typically recorded using electroencephalography (EEG) with multi-channel setups ranging from 32 to 128 electrodes positioned according to the international 10-20 or 10-10 systems, allowing for adequate spatial resolution over frontocentral scalp regions where the ERN is maximal.^[24] Sampling rates of 500 to 1000 Hz are standard to capture the rapid temporal dynamics of event-related potentials (ERPs), with bandpass filters applied online or offline at 0.1-30 Hz to isolate relevant frequency bands while attenuating noise.^[25]^[26] Referencing is commonly to linked mastoids or a common average reference to minimize distortion from peripheral artifacts, with electrode impedances maintained below 10 kΩ for signal quality.^[24]^[26] Preprocessing begins with bandpass filtering to remove low-frequency drifts and high-frequency noise, followed by artifact rejection to address ocular, muscular, and other non-neural contaminants. Independent component analysis (ICA) is widely employed to identify and subtract components corresponding to eye blinks and movements, often using algorithms like Infomax or AMICA, with manual inspection to confirm classifications.^[24]^[25]^[26] Remaining epochs exceeding amplitude thresholds (e.g., ±50-100 μV) are rejected to exclude trials with excessive muscular activity or drifts. Data are then segmented into response-locked epochs, typically from -200 ms to 500 ms relative to the erroneous response, to align with the ERN's post-error onset.^[26] Baseline correction subtracts the mean voltage from -200 to 0 ms pre-response to normalize epochs and highlight deviation-based deflections.^[25]^[26] Analysis involves grand averaging of clean error-locked epochs separately from correct-response epochs to isolate the ERN from the correct-response negativity (CRN), with the ERN quantified as peak or mean amplitude in the 0-100 ms window post-response at frontocentral sites like FCz or Cz.^[27] Paired t-tests compare ERN and CRN amplitudes across conditions, with effect sizes such as Cohen's d reported to assess magnitude (e.g., d > 0.8 indicating robust error-specific effects in healthy adults).^[27] For low error rates, which can reduce signal-to-noise ratio, reliability is enhanced by including at least 20-30 error trials per participant or using simulations to model stability, ensuring detectable ERN components.^[28] Test-retest reliability of ERN amplitude is generally high, with intraclass correlation coefficients (ICCs) exceeding 0.7 over intervals of weeks to months when sufficient trials are averaged, supporting its use as a stable individual difference measure.^[29]^[28]

Neural Mechanisms and Theories

Brain Sources

The primary generator of the error-related negativity (ERN) is the dorsal anterior cingulate cortex (dACC), localized at approximate Talairach coordinates x=0, y=20, z=30 mm. This localization aligns with the fronto-central scalp distribution observed in EEG recordings, consistent with the dACC's role in conflict monitoring.^[30] Dipole modeling studies, beginning in the mid-1990s, have consistently identified the ACC as the main source.^[30] Concurrent electroencephalography and functional magnetic resonance imaging (EEG-fMRI) further supports this, revealing that trial-by-trial variations in ERN amplitude positively correlate with blood-oxygen-level-dependent (BOLD) signal increases in the ACC during error processing tasks.^[31] Subcortical inputs from the basal ganglia and insula modulate dACC activity, providing reinforcement learning signals that influence ERN generation. Dopaminergic projections from the basal ganglia to the ACC encode prediction errors, enhancing error detection in probabilistic learning contexts, while insular signals integrate aversive or salient error feedback to amplify ACC responses.^[4] Recent source localization efforts using advanced multimodal imaging confirm a multi-generator model for the ERN, incorporating the ACC alongside contributions from the supplementary motor area (SMA). These 2023 analyses indicate that overlapping dipoles from medial frontal regions, including the SMA, contribute to the composite ERN signal, with radial and tangential orientations allowing summation at fronto-central electrodes. The ERN is also closely associated with midline frontal theta (4-7 Hz) oscillations, which may underlie its scalp-recorded negativity.^[32]^[33]

Theoretical Explanations

One prominent theoretical framework for the error-related negativity (ERN) is the conflict monitoring theory, which posits that the ERN arises from the detection of response conflict within the dorsal anterior cingulate cortex (dACC). According to this model, conflict is computed through Hebbian learning mechanisms where co-activation of incompatible response units generates a signal that the ERN reflects, thereby triggering subsequent cognitive control adjustments to resolve the interference. An alternative explanation is provided by the reinforcement learning model, which interprets the ERN as a phasic dip in dopaminergic activity signaling a negative reward prediction error in the midcingulate cortex when an action outcome is worse than expected. This error signal, denoted as \delta, updates value functions to guide future behavior via the temporal difference learning rule:

\delta = r + \gamma V(s') - V(s)

where r is the received reward, \gamma is the discount factor, V(s) is the value of the current state, and V(s') is the value of the next state; this \delta drives the dopaminergic response that modulates the ERN amplitude. The motivational account complements these cognitive models by emphasizing that the ERN is amplified when errors carry high personal significance or are committed under incentivized conditions, reflecting an affective response akin to defensive motivation and distress. For instance, larger ERN amplitudes occur in contexts where errors elicit stronger negative affect, such as when they impact self-evaluation or social evaluation, linking the component to motivational systems beyond pure conflict or learning signals. Recent integrative efforts have sought to reconcile these perspectives, positing that the ERN emerges from the interaction of mismatch in expected outcomes and response competition, offering explanatory power for transdiagnostic patterns in error processing across disorders. These models highlight the ERN's role in adaptive, context-dependent control, drawing on both Hebbian and temporal difference mechanisms for a unified framework. The feedback-related negativity (FRN), also denoted as feedback ERN (fERN), is an event-related potential component manifesting as a negative deflection in the electroencephalogram, peaking approximately 200-300 ms following the presentation of negative feedback signals, such as monetary losses or indicators of incorrect performance.^[34]^[35] This component reflects neural processing of unfavorable outcomes in stimulus-locked paradigms, distinguishing it from the core error-related negativity (ERN) associated with self-generated response errors.^[36] The FRN is typically elicited in probabilistic gambling tasks, including the doors task, where participants select among multiple options (e.g., doors) that yield gains or losses based on hidden probabilities, with feedback provided after each choice.^[37] Amplitudes are amplified for unexpected negative feedback relative to expected losses, underscoring the role of prediction error in its generation, consistent with reinforcement learning theory.^[38]^[39] In contrast to the action ERN, which emerges 50-100 ms post-response with a pronounced frontocentral scalp distribution and sensitivity to error commission, the FRN exhibits a later peak latency due to its feedback-locked timing and responds primarily to the valence of external outcomes rather than internal monitoring.^[40]^[34] While both components share an anterior cingulate cortex source, the FRN often shows a slightly more posterior or parietal-influenced topography in some paradigms.^[41]

Error Positivity

The error positivity (Pe) is a positive deflection in the event-related brain potential that emerges approximately 200–400 ms following the commission of an error, typically peaking with maximal amplitude at parietal electrode sites such as Pz.^[42] This component follows the earlier error-related negativity (ERN) and is elicited during tasks involving speeded responses, such as flanker or Stroop paradigms, where participants detect and respond to errors in their actions.^[43] Functionally, the Pe indexes conscious awareness of errors and their motivational salience, reflecting a later stage of error processing that involves explicit evaluation and significance attribution.^[44] Unlike unaware errors, where Pe amplitude is markedly reduced or absent, the component is prominently elicited when errors are subjectively felt, underscoring its sensitivity to perceptual detection rather than mere response conflict.^[11] This distinction highlights the Pe's role in bridging automatic error detection with deliberate cognitive control. Pe amplitude is larger for errors that participants consciously recognize compared to those they do not, with effect sizes indicating a strong modulation by subjective experience. Furthermore, greater Pe amplitude correlates with adaptive post-error behavioral adjustments, such as improved accuracy on subsequent trials, suggesting it contributes to performance optimization through heightened error significance.^[45] This analysis emphasized the Pe's posterior neural origins and its reliance on evidence accumulation for awareness, distinct from the anterior cingulate cortex-dominated ERN.^[46]

Pre-Movement Positivity

Pre-movement positivity (PMP) refers to a positive deflection in the event-related potential (ERP) observed approximately 0–100 ms prior to correct motor responses, peaking around 110 ms pre-response in response-locked analyses.^[47] This component manifests as a positive-going peak originating in the posterior medial frontal cortex, reflecting preparatory processes for action execution.^[47] In relation to the error-related negativity (ERN), the PMP is prominent on correct trials but absent or reduced on error trials, thereby contributing to the relative enhancement of negativity in error waveforms.^[47] This differential presence is particularly evident in correct-minus-error difference waves, where the PMP appears as a positivity specific to correct responses, increasing the contrast that defines the ERN.^[47] Functionally, the PMP is interpreted as a "go-ahead" signal for motor preparation, facilitating condition-action mapping and movement initiation.^[47] Source localization studies attribute its generation primarily to the supplementary motor area (SMA) and pre-SMA, with contributions from the mid-cingulate cortex (approximately 39% of activity) and SMA (21%).^[47] This aligns with earlier foundational work on movement-related cortical potentials, which identified the PMP as a late component of pre-movement activity in voluntary actions.^[48] Early 2000s research demonstrated that the PMP can overlap with the ERN time window, and subtracting or regressing out PMP effects improves ERN isolation by correcting baseline shifts in response-locked ERPs.^[49] Subsequent studies have shown reduced PMP amplitudes preceding errors, particularly in conditions like attention-deficit/hyperactivity disorder, though updates remain limited beyond methodological refinements such as regression-ERPs for disentangling these components.^[47]

Functional and Clinical Significance

Behavioral and Cognitive Functions

The error-related negativity (ERN) plays a key role in performance monitoring by predicting post-error slowing (PES), a behavioral adaptation where reaction times on subsequent trials increase following an error, often by 50-100 ms, to promote caution and reduce future inaccuracies. This slowing reflects an adaptive strategy to enhance accuracy after mistakes, as evidenced in tasks like the Flanker paradigm. Seminal single-trial analyses have shown that larger ERN amplitudes directly correlate with greater PES magnitude, indicating that heightened neural error signals drive these behavioral adjustments, though recent reviews note mixed evidence on this link.^[45]^[22] ERN amplitude also scales with error rates and supports learning through reinforcement mechanisms, where more pronounced negativity facilitates behavioral adjustments to minimize errors over time. In probabilistic learning tasks, unexpected errors elicit larger ERNs, which correlate with improved adaptation and reduced error rates in subsequent trials, underscoring its role in updating action-outcome associations. Additionally, ERN responds to working memory demands, with higher cognitive load modulating its amplitude and linking it to resource allocation during error detection.^[50] Motivational factors further influence ERN, with enhanced amplitudes observed under incentives or when accuracy is emphasized, reflecting heightened error salience in goal-directed contexts. This sensitivity aligns with personality traits, as larger ERN amplitudes are associated with higher conscientiousness, suggesting a trait-level basis for vigilant monitoring. Recent research indicates mixed evidence on the translation of amplified ERN to behavioral changes like PES in high-anxiety individuals, suggesting distinct neural and adaptive roles in error processing.^[51]

Applications in Psychopathology

Error-related negativity (ERN) has emerged as a key biomarker in anxiety disorders, characterized by enhanced amplitudes that reflect heightened error monitoring and emotional sensitivity to mistakes. Individuals with anxiety disorders exhibit ERN amplitudes that are typically approximately 1-2 μV more negative than those in healthy controls, serving as a transdiagnostic marker across conditions such as generalized anxiety disorder and social anxiety.^[52]^[53] A 2023 longitudinal study confirms that larger baseline ERN amplitudes predict increases in social anxiety over a two-year follow-up, underscoring its role in vulnerability to internalizing symptoms.^[54] In obsessive-compulsive disorder (OCD), increased ERN amplitudes indicate error hypervigilance, with meta-analytic evidence showing moderate effect sizes (Hedges' g ≈ 0.54-0.55) compared to controls, consistent with overactive anterior cingulate cortex involvement in threat detection.^[55] Conversely, attention-deficit/hyperactivity disorder (ADHD) is associated with blunted ERN responses, signaling impaired performance monitoring, with meta-analyses reporting effect sizes in the moderate range (g ≈ 0.44-0.65) that correlate with inattention and impulsivity symptoms.^[56]^[57] Developmental research highlights larger ERN amplitudes as a predictor of anxiety onset in childhood, with longitudinal studies showing that enhanced error-related activity at ages 6-9 forecasts new disorder emergence by early adolescence, independent of baseline symptoms.^[58] Recent investigations also reveal sex differences, wherein females exhibit a stronger link between ERN amplitude and anxiety severity than males, potentially due to greater motivational sensitivity to errors.^[59] Intergenerational transmission studies further support ERN's heritability, with maternal ERN amplitudes correlating with offspring measures and predicting child anxiety risk beyond parenting behaviors.^[60] Therapeutically, ERN serves as an endophenotype for predicting cognitive-behavioral therapy (CBT) outcomes in anxiety and OCD, where pretreatment enhanced amplitudes moderate symptom reduction, with non-responders showing persistently larger ERN post-treatment.^[61] Post-2020 data extend this to personality traits, revealing that ERN moderates the association between neuroticism and irritability, such that high neuroticism predicts elevated irritability only in those with blunted ERN, informing targeted interventions for transdiagnostic irritability in internalizing disorders.^[62]^[63]