Characterizing habit learning in the human brain at the individual and group levels: A multi-modal MRI study

Gera, Rani; Or, Maya Bar; Tavor, Ido; Roll, Dana; Cockburn, Jeffrey; Barak, Segev; Tricomi, Elizabeth; O’Doherty, John P.; Schönberg, Tom

doi:10.1016/j.neuroimage.2023.120002

Cited by 4 publications

(3 citation statements)

References 131 publications

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“…The finding that the behavior of only a subgroup of participants was best explained by the repetition bias model seems consistent with previous studies where only subsets of participants were found to show habitual behaviour ( Pool et al, 2022; Gera et al, 2023 ). One reason might be a strong motivation to perform well in experimental tasks ( Cerasoli et al, 2014 ).…”

Section: Discussionsupporting

confidence: 91%

Cognitive Computational Model Reveals Repetition Bias in a Sequential Decision-Making Task

Legler,

Rivera,

Schwöbel

et al. 2024

Preprint

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Humans tend to repeat past actions due to rewarding outcomes. Recent computational models propose that the probability of selecting a specific action is also, in part, based on how often this action was selected before, independent of previous outcomes or reward. However, these new models so far lack empirical support. Here, we present evidence of a repetition bias using a novel sequential decision-making task and computational modeling to reveal the influence of choice frequency on human value-based choices. Specifically, we find that value-based decisions can be best explained by concurrent influence of both goal-directed reward seeking and a repetition bias. We also show that participants differ substantially in their repetition bias strength, and relate these measures to task performance. The new task enables a novel way to measure the influence of choice repetition on decision-making. These findings can serve as a basis for further experimental studies on the interplay between rewards and choice history in human decision-making.

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Section: Discussionsupporting

confidence: 91%

Cognitive Computational Model Reveals Repetition Bias in a Sequential Decision-Making Task

Legler,

Rivera,

Schwöbel

et al. 2024

Preprint

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“…Importantly, this does, of course, not exclude the possibility that other neural indices might be associated with behavioral indices of habit formation. For example, previous research found that training-related brain activity changes in angular gyrus 13 and head of caudate 53 were associated with habit strength. Connectivity-wise, from our previous research, we found that the functional connectivity changes involving the sensorimotor and the CON contributed most prominently to habit strength prediction 14 .…”

Section: Discussionmentioning

confidence: 99%

The dynamics of functional brain network segregation in feedback-driven learning

Wang,

Zwosta,

Hennig

et al. 2024

Commun Biol

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Prior evidence suggests that increasingly efficient task performance in human learning is associated with large scale brain network dynamics. However, the specific nature of this general relationship has remained unclear. Here, we characterize performance improvement during feedback-driven stimulus-response (S-R) learning by learning rate as well as S-R habit strength and test whether and how these two behavioral measures are associated with a functional brain state transition from a more integrated to a more segregated brain state across learning. Capitalizing on two separate fMRI studies using similar but not identical experimental designs, we demonstrate for both studies that a higher learning rate is associated with a more rapid brain network segregation. By contrast, S-R habit strength is not reliably related to changes in brain network segregation. Overall, our current study results highlight the utility of dynamic functional brain state analysis. From a broader perspective taking into account previous study results, our findings align with a framework that conceptualizes brain network segregation as a general feature of processing efficiency not only in feedback-driven learning as in the present study but also in other types of learning and in other task domains.

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“…A noteworthy difference between these replication attempts and the original study is that the replications were conducted outside an fMRI scanner. Yet a recently reported direct replication attempt also failed to replicate the findings, suggesting that the potential contribution of the use of a scanner to the original findings can be ruled out [42]. It is worth noting that some habit effects in animals [43] after overtraining have also failed to replicate [44][45][46].…”

Section: General Habit Effectsmentioning

confidence: 92%

Poor Reliability and Validity of Habit Effects in Substance Use and Novel Insights from a Goal-Directed Perspective

Buabang

Köster²,

Hogarth³

et al. 2023

Preprint

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The habit theory is an influential explanation for problematic substance use. We review the main assumptions of the habit theory and emphasize concerns regarding the reliability and validity of the supporting experimental evidence. We also highlight the challenge for the habit theory to explain observational data regarding the complexity of substance use, specifically, the diversity of risk factors and intervention strategies. To address these issues, we elaborate and apply the goal-directed model of Moors et al. (2017) to explain substance use. Based on this application, we identify several factors that may contribute to substance use. We argue that this goal-directed model provides a more compelling synthesis of the experimental evidence and the observational data on substance use. In addition to providing a more nuanced understanding of substance use, we believe it also allows for a better explanation of its complexity and individual variations. The proposed shift in explanations for substance use from habit to goal-directed theory also has implications for intervention.

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Characterizing habit learning in the human brain at the individual and group levels: A multi-modal MRI study

Cited by 4 publications

References 131 publications

Cognitive Computational Model Reveals Repetition Bias in a Sequential Decision-Making Task

Cognitive Computational Model Reveals Repetition Bias in a Sequential Decision-Making Task

The dynamics of functional brain network segregation in feedback-driven learning

Poor Reliability and Validity of Habit Effects in Substance Use and Novel Insights from a Goal-Directed Perspective

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