Biology subjects

Eldar, E.

Publications and source records attributed to Eldar, E..

7 recordsLinked to original sources

bioRxiv2025

Prefrontal and Subcortical Value Representation during Explore-Exploit Decision-Making and Suicide Attempts

BackgroundThis study aims to understand learning and decision-making in suicidal behavior by investigating temporal dynamics of reward value encoding in individuals with late-life depression and a history of suicide attempts. MethodsIn a retrospective case-control study, 134 older adults (33 with depression and history of suicide attempts, 29 with depression and suicidal ideation but no past attempts, 32 with depression and no suicidal ideation/past attempts, and 40 psychiatrically healthy controls) completed an explore-exploit decision-making task during functional MRI (fMRI). Multilevel models of deconvolved fMRI time series, time-locked to trial events, interrogated whether temporal patterns of reward value encoding was associated with suicidal behavior. ResultsSuicidal behavior in general was associated with blunted ventral PFC (vPFC) value signals, but profiles varied as a function of attempt lethality. Specifically, low-lethality suicide attempts and excessive behavioral shifts were associated with abolished phasic responses to value updates in the default network vPFC and its connected regions, including the striatum, amygdala, and hippocampus. Additionally, an unexpected pattern of sustained negative value responses was observed in vPFC and striatal control subregions, and hippocampus of high-lethality suicide attempters. ConclusionsDiverging patterns of decision-related responses may reflect different paths toward suicidal behavior. Impaired value updating in individuals with low-lethality suicide attempts suggests a failure to integrate recent outcomes alongside prior experience, potentially relating to over-reactivity to stressors and a lower threshold for suicide attempts. In contrast, increased control network responses to difficult choices in high-lethality attempters may underlie cognitive constriction and consideration of a narrow set of potential solutions.

neuroscience↗

bioRxiv2024

The resource elasticity of control

The ability to determine how much the environment can be controlled through our actions has long been viewed as fundamental to adaptive behavior. While traditional accounts treat controllability as a fixed property of the environment, we argue that real-world controllability often depends on the effort, time and money we are able and willing to invest. In such cases, controllability can be said to be elastic to invested resources. Here we propose that inferring this elasticity is essential for efficient resource allocation, and thus, elasticity misestimations result in maladaptive behavior. To test this hypothesis, we developed a novel treasure hunt game where participants encountered environments with varying degrees of controllability and elasticity. Across two pre-registered studies (N=514), we first demonstrate that people infer elasticity and adapt their resource allocation accordingly. We then present a computational model that explains how people make this inference, and identify individual elasticity biases that lead to suboptimal resource allocation. Finally, we show that overestimation of elasticity is associated with elevated psychopathology involving an impaired sense of control. These findings establish the elasticity of control as a distinct cognitive construct guiding adaptive behavior, and a computational marker for control-related maladaptive behavior.

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↗

bioRxiv2021

Optimism and Pessimism in Optimised Replay

The replay of task-relevant trajectories is known to contribute to memory consolidation and improved task performance. A wide variety of experimental data show that the content of replayed sequences is highly specific and can be modulated by reward as well as other prominent task variables. However, the rules governing the choice of sequences to be replayed still remain poorly understood. One recent theoretical suggestion is that the prioritization of replay experiences in decision-making problems is based on their effect on the choice of action. We show that this implies that subjects should replay sub-optimal actions that they dysfunctionally choose rather than optimal ones, when, by being forgetful, they experience large amounts of uncertainty in their internal models of the world. We use this to account for recent experimental data demonstrating exactly pessimal replay, fitting model parameters to the individual subjects choices.

neuroscience↗

bioRxiv2020

SSRIs modulate asymmetric learning from reward and punishment

Human instrumental learning is driven by a history of outcome success and failure. We demonstrate that week-long treatment with a serotonergic antidepressant modulates a valence-dependent asymmetry in learning from reinforcement. In particular, we show that prolonged boosting of central serotonin reduces reward learning, and enhances punishment learning. This treatment induced learning asymmetry can result in lowered positive and enhanced negative expectations. A consequential effect is more rewarding, and less disappointing, experiences and this may, in part, explain the slow temporal evolution of serotonins well-established antidepressant effects.

neuroscience↗

bioRxiv2020

The roles of online and offline replay in planning

Animals and humans replay neural patterns encoding trajectories through their environment, both whilst they solve decision-making tasks and during rest. Both on-task and off-task replay are believed to contribute to flexible decision making, though how their relative contributions differ remains unclear. We investigated this question by using magnetoencephalography to study human subjects while they performed a decision-making task that was designed to reveal the decision algorithms employed. We characterized subjects in terms of how flexibly each adjusted their choices to changes in temporal, spatial and reward structure. The more flexible a subject, the more they replayed trajectories during task performance, and this replay was coupled with re-planning of the encoded trajectories. The less flexible a subject, the more they replayed previously and subsequently preferred trajectories during rest periods between task epochs. The data suggest that online and offline replay both participate in planning but support distinct decision strategies.

neuroscience↗

bioRxiv2018

A pupillary index of susceptibility to decision biases

Under what conditions do humans systematically deviate from rational decision making? Here we show that pupillary indices of low neural gain are associated with strong and consistent biases across six different extensively-studied decision making tasks, whereas indices of high gain are associated with weak or absent biases. Lower susceptibility to biases, however, comes at the cost of indecisiveness, or alternatively, prolonged deliberation time. We explain the association between low gain and strong biases as reflecting a broader information integration process that gives greater weight to weak biasing influences. The findings underscore the role of pupil-linked brain states in the generation of decision making biases.\n\nSignificance\"Framing effects\" are demonstrations that peoples decisions can be biased by the way a decision problem is presented, and consequently, people can make decisions that violate the principles of rationality. Using a set of classic decision-making tasks, we show that pupil dilation, previously linked to levels of the neuromodulator norepinephrine and to a tradeoff between narrowly focused and broadly integrative modes of information processing, distinguishes between people who are consistently biased and people who are relatively immune to these effects. Our findings suggest that norepinephrine may drive these individual differences, and that a narrowly focused mode of information processing confers relative immunity to these decision making biases, whereas the integration of a wider range of information results in greater susceptibility.

neuroscience↗