Biology subjects

Rutledge, R.

Publications and source records attributed to Rutledge, R..

5 recordsLinked to original sources

bioRxiv2025

Depression symptoms enhance goal-directed behavior underuncertainty

A core premise in decision-making research is that beliefs about uncertain outcomes shape value-based choice: pessimistic expectations should reduce goal pursuit, whereas optimistic expectations should promote it. Depression provides a critical test of this assumption, as motivational symptoms such as apathy and anhedonia are linked to diminished expectations of success. Yet whether such biases actually impair goal-directed behavior, particularly when risk must be learned from experience, remains unknown. We developed a multi-step planning task in which participants (n = 384) learned the structure and risks of maze-like environments across two days, then chose between certain rewards and risky goals varying in reward magnitude and distance, with greater distance entailing higher compounding risk. Using transdiagnostic symptom factors, we observed a dissociation: individuals with elevated apathy-anhedonia reported lower subjective expectations of goal success, yet showed no reduction in risky goal pursuit. Instead, higher apathy-anhedonia was associated with enhanced performance, including stronger discrimination of goal values, increased model-based flexibility, and faster goal navigation. These effects were specific to apathy-anhedonia; other symptom factors, including worry and impulsivity, were unrelated to expectations or goal-directed behavior. Together, these findings demonstrate that pessimistic beliefs and goal-directed competence are dissociable, revealing that motivational symptoms can coexist with sharpened value-based planning when risk is learned from experience.

neuroscience↗

bioRxiv2024

Mood impacts confidence through biased learning of reward likelihood

Mood disturbances are accompanied by marked and apparently non-rational changes in self-efficacy and goal-directed behaviour, yet the mechanisms linking affective states to these fluctuations remain unclear. Here we tested whether mood biases confidence in reward-based decision-making and whether this is amplified by trait instability in mood and self-efficacy. By formalising both confidence and mood within a computational model of reward learning, we adjudicated between two accounts of these clinically relevant effects: mood imposing a direct, evidence-independent shift in confidence, or mood distorting the accumulation of reward learning signals from which confidence is then rationally inferred. Across two independent studies--a laboratory experiment (n = 35) and a preregistered online replication (n = 106)--participants completed a reinforcement-learning task with mood manipulation and repeated confidence ratings. Mood systematically biased confidence without affecting objective accuracy. Critically, this effect accumulated gradually across learning rather than emerging immediately after mood induction, even as mood itself returned toward baseline. These dynamics were captured by a computational model in which mood biases the accumulation of reward probability estimates. A single mood-bias parameter accounted for shifts in confidence, biased valuation of stimuli learned under different mood states, and amplification of these effects in individuals with elevated hypomanic traits. These findings suggest that disturbances in confidence arise from mood-biased learning signals, providing a mechanistic account linking these distortions to disrupted goal pursuit and self-efficacy in mood disorders.

neuroscience↗

bioRxiv2023

The role of serotonin and of perceived social differences in infering the motivation of others

Attributing motives to others is a crucial aspect of mentalizing, can be biased by prejudice, and also is affected by common psychiatric disorders. It is therefore important to understand in depth the mechanisms underpinning it. Toward improving models of mentalizing motives, we hypothesized that people quickly infer whether others motives are likely beneficial or detrimental, then refine their judgment ( Classify-refine). To test this, we used a modified Dictator game, a game theoretic task, where participants judged the likelihood of intent to harm vs. self-interest in economic decisions. Toward testing the role of serotonin in judgments of intent to harm, we delivered the task in a week-long, placebo vs. Citalopram study. Computational model comparison provided clear evidence for the superiority of Classify-refine models over traditional ones, strongly supporting the central hypothesis. Further, while Citalopram helped refine attributions about motives through learning, it did not induce more positive initial inferences about others motives. Finally, model comparison indicated a minimal role for racial bias within economic decisions for the large majority of our sample. Overall, these results support a proposal that classify-refine social cognition is adaptive, although relevant mechanisms of Serotonergic antidepressant action will need to be studied over longer time spans.

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bioRxiv2019

Timing matters: primacy effects of experience on mood revealed using a novel Mood-Machine-Interface

Humans refer to their own mood state regularly in day-to-day as well as in clinical interactions. Theoretical accounts suggest that when reporting on our mood we integrate over the history of our experiences; yet, the temporal structure of this integration remains unexamined. Here we use a computational approach to quantitatively answer this question and show that early events exert a stronger influence on the reported mood compared to recent events. We show that a Primacy model accounts better for mood reports compared to a range of alternative temporal representations, and replicate this result across random, consistent or dynamic structures of reward environments, age groups and both healthy and depressed participants. Moreover, we find evidence for neural encoding of the Primacy, but not the Recency, model in frontal brain regions related to mood regulation. These findings hold implications for the timing of events in experimental or clinical settings and suggest new directions for individualized mood interventions. SignificanceHow we rate our own mood at any given moment is shaped by our experiences; but are the most recent experiences the most influential, as assumed by current theories? Using several sources of experimental data and mathematical modeling, we show that earlier experiences within a context are more influential than recent events, and replicate this finding across task environments, age groups, and in healthy and depressed participants. Additionally, we present neural evidence supporting this primacy model. Our findings show that delineating a temporal structure is crucial in modeling mood and this has key implications for its measurement and definition in both clinical and everyday settings.

neuroscience↗

bioRxiv2017

Age-dependent Pavlovian biases influence motor decision-making

Healthy ageing is associated with decreased risk taking in motor1 and economic2-4 decision-making. However, it is unknown whether a single underlying mechanism explains these changes. Age-related changes in economic risk taking are explained by reduced Pavlovian biases that promote action toward reward2, 5, 6. Although Pavlovian biases also promote inaction in the face of punishment, the role such Pavlovian biases play in motor decision-making, which additionally depends on estimating the probability of successfully executing an action7-10, is unknown. To address this, we developed a novel app-based motor decision-making task to measure sensitivity to reward and punishment when subjects (n=26,532) made a go/no-go motor gamble based on the perceived ability to execut ...

neuroscience↗