Biology subjects

Tarlow, M.

Publications and source records attributed to Tarlow, M..

3 recordsLinked to original sources

bioRxiv2025

Reward and punishment promote distinct computational effort profiles for adaptive cognitive control

Human motivation is fundamentally shaped by ones expectations of the reward they could earn for good performance or the punishment they would receive for poor performance. However, the extent to which distinct brain regions are selectively associated with specific incentives and/or their corresponding influence on control strategy remains unclear. Using model-based fMRI and a novel multi-incentive control task, we observed distinct neural patterns by incentive valence, with ventral striatum and caudal subregion of dorsal anterior cingulate cortex showing greater sensitivity to rewards whereas inferior frontal gyrus and rostral subregion of dorsal anterior cingulate cortex showing greater sensitivity to penalties. Reward-sensitive regions were associated with increased efficiency (e.g., faster responding with moderate decreases in accuracy) whereas penalty-sensitive regions were associated with increased caution (e.g., slower responding with increased accuracy). We disentangled the global and selective influences of motivation on control processes and subjective experience, providing novel insight into the neurocomputational mechanisms of how effort is determined by expected reward and punishment. TeaserDistinct dACC sub-networks guide dissociable control strategies, revealing how dissociable mental effort profiles are determined by reward and punishment.

neuroscience↗

bioRxiv2025

A Novel Approach-Avoidance Task to Study Decision Making Under Outcome Uncertainty

To behave adaptively, people need to integrate information about probabilistic outcomes and balance drives to approach positive outcomes and avoid negative outcomes. However, questions remain about how uncertainty in positive and negative outcomes influence approach-avoid decision-making dynamics. To fill this gap, we developed a novel Probabilistic Approach Avoidance Task (PAAT) and characterized behavior in this task using sequential sampling models In this task, participants (Study 1: blinded mixed clinical sample N=34; Study 2: online nonpsychiatric sample N = 58) made a series of choices between pairs of options, each consisting of variable probabilities of reaching a positive outcome (monetary reward) and of reaching a negative outcome (aversive image). Participants tended to choose options that maximized the likelihood of reward and minimized the likelihood of aversive outcomes. Moreover, the weights they placed on each of these differed for choices where these likelihoods were in opposition (i.e., the riskier option was also more rewarding; incongruent trials) relative to when these were aligned (congruent trials). Computational modeling revealed that the relative influence of rewarding and aversive outcomes on choice was captured by differences in the rate of decision-relevant information accumulation. These modeling results were validated with a series of model comparisons and posterior predictive checks, demonstrating that our sequential sampling models reliably captured our behavioral data. Together, these findings improve our understanding of the influence of motivational conflict, outcome type, and levels of uncertainty on approach-avoid decision-making.

neuroscience↗

bioRxiv2023

Motivational context determines the impact of aversive outcomes on mental effort allocation

It is well known that people will exert effort on a task if sufficiently motivated, but how they distribute these efforts across different strategies (e.g., efficiency vs. caution) remains uncertain. Past work has shown that people invest effort differently for potential positive outcomes (rewards) versus potential negative outcomes (penalties). However, this research failed to account for differences in the context in which negative outcomes motivate someone - either as punishment or reinforcement. It is therefore unclear whether effort profiles differ as a function of outcome valence, motivational context, or both. Using computational modeling and our novel Multi-Incentive Control Task, we show that the influence of aversive outcomes on ones effort profile is entirely determined by their motivational context. Participants (N:91) favored increased caution in response to larger penalties for incorrect responses, and favored increased efficiency in response to larger reinforcement for correct responses, whether positively or negatively incentivized. Statement of RelevancePeople have to constantly decide how to allocate their mental effort, and in doing so can be motivated by both the positive outcomes that effort accrues and the negative outcomes that effort avoids. For example, someone might persist on a project for work in the hopes of being promoted or to avoid being reprimanded or even fired. Understanding how people weigh these different types of incentives is critical for understanding variability in human achievement as well as sources of motivational impairments (e.g., in major depression). We show that people not only consider both potential positive and negative outcomes when allocating mental effort, but that the profile of effort they engage under negative incentives differs depending on whether that outcome is contingent on sustaining good performance (negative reinforcement) or avoiding bad performance (punishment). Clarifying the motivational factors that determine effort exertion is an important step for understanding motivational impairments in psychopathology.

neuroscience↗