Individual differences in sequential decision-making

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2025, Номер unknown

Опубликована: Апрель 5, 2025

1People differ widely in how they make decisions uncertain environments. While many studies leverage this variability to measure differences specific cognitive processes and parameters, the key dimension(s) of individual decision-making tasks has not been identified. Here, we analyzed behavioral data from 1001 participants performing a restless three-armed bandit task, where reward probabilities fluctuated unpredictably over time. Using novel analytical approach that controlled for stochasticity tasks, identified dominant nonlinear axis variability. We found primary was strongly selectively correlated with probability exploration, as inferred by latent state modeling. This suggests major factor shaping task performance is tendency explore (versus exploit), rather than personality characteristics, reinforcement learning model or low-level strategies. Certain demographic characteristics also predicted variance along principle axis: at exploratory end tended be younger exploitative end, self-identified men were overrepresented both extremes. Together, these findings offer principled framework understanding behavior while highlighting factors shape under uncertainty.

Язык: Английский

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Reinforcement learning increasingly relates to memory specificity from childhood to adulthood

Nature Communications, Год журнала: 2025, Номер 16(1)

Опубликована: Апрель 30, 2025

Язык: Английский

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Compulsivity is linked to maladaptive choice variability but unaltered reinforcement learning under uncertainty

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2023, Номер unknown

Опубликована: Янв. 5, 2023

Compulsivity has been associated with variable behavior under uncertainty. However, previous work not distinguished between two main sources of behavioral variability: the stochastic selection choice options that do maximize expected reward (choice variability), and random noise in reinforcement learning process updates option values from outcomes (learning variability). Here we studied relation dimensional compulsivity variability, using a computational model which dissociates its sources. We found is more frequent switches options, triggered by increased variability but no change variability. This effect on ‘trait’ component observed even conditions where this source yields cognitive benefits. These findings indicate compulsive individuals make maladaptive choices uncertainty, hold degraded representations values.

Язык: Английский

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The metacontrol hypothesis as diagnostic framework of OCD and ADHD: A dimensional approach based on shared neurobiological vulnerability

Neuroscience & Biobehavioral Reviews, Год журнала: 2022, Номер 137, С. 104677 - 104677

Опубликована: Апрель 21, 2022

Язык: Английский

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Controlling morpho-electrophysiological variability of neurons with detailed biophysical models

iScience, Год журнала: 2023, Номер 26(11), С. 108222 - 108222

Опубликована: Окт. 17, 2023

Variability, which is known to be a universal feature among biological units such as neuronal cells, holds significant importance, as, for example, it enables robust encoding of high volume information in circuits and prevents hypersynchronizations. While most computational studies on electrophysiological variability were done with single-compartment neuron models, we instead focus the detailed biophysical models multi-compartmental morphologies. We leverage Markov chain Monte Carlo method generate populations electrical reproducing experimental recordings while being compatible set morphologies faithfully represent specifi morpho-electrical type. demonstrate our approach layer 5 pyramidal cells study particular, find that morphological alone insufficient reproduce variability. Overall, this provides strong statistical basis create neurons controlled

Язык: Английский

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