Bipolar disorder rarely announces itself with a clean onset. Instead, it tends to emerge from a murky period of subtle emotional and cognitive shifts that clinicians struggle to interpret, particularly in adolescents whose brains and personalities are still under construction. A new study published in BMC Psychiatry by Serap Akpınar of the University of Health Sciences Ankara Etlik City Hospital and colleagues, including Emre Bora of Dokuz Eylul University and the Melbourne Neuropsychiatry Centre, set out to map this murky terrain with unusual precision. The researchers asked a deceptively simple question: can specific, measurable patterns of thinking and behaving — reward sensitivity, risk-taking, impulsivity, and the ability to resolve emotional conflict — serve as candidate vulnerability markers that distinguish adolescents at different stages of bipolar risk from healthy peers?
The design of the study is what gives it its power. Rather than comparing a single patient group with controls, the team recruited 111 adolescents spanning a gradient of risk: 25 with a diagnosis of bipolar I disorder who were currently euthymic, meaning their mood was stable at the time of testing; 32 classified as high-risk, typically because of a family history of the illness; 24 deemed ultra-high risk, showing attenuated or subclinical manic symptoms identified through instruments such as the Bipolar Prodrome Symptom Scale-Prospective; and 30 healthy controls. This four-tier structure allowed the investigators to ask whether neurocognitive alterations deepen as one moves along the continuum from familial risk toward full-threshold illness — a question that cross-sectional comparisons of patients and controls alone cannot answer.
Each participant completed a battery of behavioral tasks and questionnaires targeting four cognitive-affective domains. Risk-taking was probed with the Modified Balloon Analog Risk Task, in which participants inflate virtual balloons for points while weighing the danger of an explosion, and with the Iowa Gambling Task, a classic decision-making paradigm that requires learning, often without conscious awareness, which of several card decks yields long-term gains. Impulsivity was measured behaviorally with a Go/No-Go Task, which tests the ability to suppress a prepotent motor response, and subjectively with the Barratt Impulsivity Scale-11, a widely used self-report instrument that decomposes impulsivity into attentional, motor, and non-planning facets. Reward sensitivity was assessed with the Behavioral Inhibition/Behavioral Activation Scale, which quantifies the strength of approach and avoidance motivational systems. Finally, emotional conflict resolution was tested with an Emotional Stroop Task, in which participants must name the color of words while ignoring their emotional content, forcing the brain to resolve interference between affective salience and task demands.
The statistical approach was deliberately conservative. Group comparisons used the Kruskal-Wallis test, appropriate for non-normally distributed data, with Benjamini-Hochberg false discovery rate correction to control for multiple comparisons, and the most robust findings were further checked against the stricter Bonferroni threshold. Multinomial logistic regression, adjusted for age and sex, then tested which measures best classified adolescents into the four groups, and receiver operating characteristic analysis quantified diagnostic discrimination. This layered pipeline matters because the field of psychiatric biomarkers is littered with findings that evaporate under multiple-comparison scrutiny; here, the authors explicitly flagged which results survived which level of correction.
The standout result was accuracy on the Emotional Stroop Task. Conflict accuracy — the ability to correctly respond despite emotional interference — was the most consistent discriminator in the entire study. It separated the high-risk, ultra-high-risk, and bipolar groups from healthy controls, and, crucially, it also distinguished the bipolar group from both risk groups. In other words, deficits in resolving emotional conflict appear not merely as a consequence of the illness but as a feature that intensifies across the risk continuum, making it one of the most promising candidate markers identified. The regression analysis underscored this: emotional conflict accuracy discriminated the combined ultra-high-risk and bipolar groups from the combined healthy and high-risk groups with an area under the curve of 0.923, a level of discrimination that, if replicated, would be remarkable for a single behavioral measure in psychiatry. The authors are careful to note, however, that this cut-off is exploratory and derived from a modest sample.
Decision-making under risk also told a coherent story. Lower net scores on the Iowa Gambling Task differentiated all three clinical groups — bipolar, high-risk, and ultra-high-risk — from healthy controls, suggesting that impaired affective decision-making is a broad vulnerability feature present even before illness onset. On the Modified Balloon Analog Risk Task, a higher average number of pumps — a direct behavioral index of risk-taking — differentiated the ultra-high-risk and bipolar groups from controls in the adjusted models. Notably, this elevated risk-taking in the ultra-high-risk group correlated with concurrent subclinical manic symptoms, hinting that the balloon-pumping behavior may capture something phenomenologically close to the emerging hypomanic temperament. Group differences on the Emotional Stroop, Iowa Gambling Task, Barratt Impulsivity Scale, and Go/No-Go task survived both false discovery rate and Bonferroni correction, whereas the balloon task differences survived false discovery rate correction only.
Perhaps the most clinically useful aspect of the findings is the differential pattern across impulsivity subdomains. Non-planning impulsivity, reward sensitivity, and emotional conflict resolution deficits distinguished all three clinical groups from healthy controls, positioning them as potential trait markers of vulnerability that are present from the earliest identifiable risk stage. By contrast, motor and attentional impulsivity, fun-seeking, and response inhibition deficits were more specific to the ultra-high-risk and bipolar groups, appearing only as adolescents move closer to or into full-threshold illness. This dissociation suggests a staged model of neurocognitive deterioration: a baseline vulnerability layer shared across the risk spectrum, overlaid by a later-emerging layer of inhibitory and attentional dyscontrol that may signal imminent transition. If longitudinal studies confirm this architecture, clinicians could in principle use the profile of deficits — not just their presence — to estimate where along the risk pathway a given adolescent sits.
The theoretical implications reach into long-standing models of bipolar disorder. Heightened reward sensitivity and approach motivation have been central to psychological theories of mania, and the present findings align with the idea that a hyperactive behavioral activation system, combined with impaired top-down regulation of emotional interference, creates a cognitive environment in which mood dysregulation can escalate. The anterior cingulate cortex, a region heavily implicated in conflict monitoring and error processing, is a plausible neural substrate for the Emotional Stroop deficits observed, and its dysfunction could plausibly link the affective and cognitive disturbances that characterize the bipolar prodrome. The authors themselves frame these alterations as candidate markers rather than established ones, a distinction that reflects both the strength and the limits of the evidence.
Those limits deserve emphasis. The study is cross-sectional, meaning it captures a snapshot rather than a trajectory; it cannot prove that the observed deficits predict who will convert from risk to illness, only that they covary with risk stage at a single point in time. The sample, while thoughtfully stratified, is modest — 111 adolescents across four groups — and the ultra-high-risk subgroup in particular is small. The authors also note that the striking area under the curve of 0.923 for emotional conflict accuracy should be treated as a hypothesis-generating estimate, since classification metrics derived from the same dataset used for discovery are prone to optimism. Longitudinal follow-up of high-risk and ultra-high-risk cohorts, ideally with neuroimaging and repeated cognitive assessment, will be needed to determine whether these candidate markers genuinely forecast onset and whether early intervention targeting emotional regulation could alter the course of the illness.
Even with those caveats, the study represents a meaningful step toward a long-sought goal in child and adolescent psychiatry: identifying measurable, task-based signals that stratify bipolar risk before the first full manic episode. Bipolar disorder in young people is frequently misdiagnosed, often as unipolar depression or attention deficit hyperactivity disorder, and treatment delays carry substantial costs in academic, social, and neurobiological terms. A validated cognitive profile — impaired emotional conflict resolution, compromised affective decision-making, and stage-specific impulsivity changes — could eventually complement clinical interviews and family history to sharpen risk assessment. For now, the message from Ankara and Izmir is one of cautious optimism: the cognitive fingerprints of bipolar vulnerability appear to be detectable in adolescence, arranged along a gradient that mirrors the illness itself, and waiting to be tested against the passage of time.
Subject of Research: Neurocognitive vulnerability markers across bipolar disorder risk stages in adolescents
Article Title: Neurocognitive candidate markers across bipolar disorder risk stages in adolescents
Article References: Akpınar, S., Kafali, H. Y., Kabasakal, İ., Kaya, H., Akman, A. Ö., Bora, E., & Dinç, G. Ş. (2026). Neurocognitive candidate markers across bipolar disorder risk stages in adolescents. BMC Psychiatry. https://doi.org/10.1186/s12888-026-08732-4
Image Credits: AI Generated
DOI: 10.1186/s12888-026-08732-4
Keywords: bipolar disorder, adolescents, ultra-high risk, emotional conflict, reward sensitivity, impulsivity, risk-taking, Iowa Gambling Task, Emotional Stroop Task, neuropsychology, prodrome, predictive markers
Cite Scienmag News
Glenn Wilkins. (October 7, 2026). Adolescent Brain Clues: How Emotional Conflict May Signal Bipolar Risk. Scienmag. https://scienmag.com/adolescent-brain-clues-how-emotional-conflict-may-signal-bipolar-risk/
Glenn Wilkins. "Adolescent Brain Clues: How Emotional Conflict May Signal Bipolar Risk." Scienmag, 7 October 2026, https://scienmag.com/adolescent-brain-clues-how-emotional-conflict-may-signal-bipolar-risk/. Accessed 7 October 2026.
Glenn Wilkins. "Adolescent Brain Clues: How Emotional Conflict May Signal Bipolar Risk." Scienmag. October 7, 2026. https://scienmag.com/adolescent-brain-clues-how-emotional-conflict-may-signal-bipolar-risk/

