to edit and comment
a collaborative knowledge base characterizing the state of current thought in Cognitive Science.
Pavlovian bias (also called motivational bias) denotes that phenomenon that - reward-related cues (eliciting reward anticipation) invigorate action (lead to more active "Go" responses and speed up these Go responses) - punishment-related cues (eliciting punishment anticipation) suppress action (lead to less "Go" / more "NoGo" responses and slow down Go responses). This phenomenon is often believed to arise based on asymmetric nature of the direct ("Go") and indirect ("NoGo") pathway in the basal ganglia (Frank, 2005, Collins & Frank, 2014). The direct pathway is assumed to "gate" / release actions, while the indirect pathway is believed to suppress/inhibit actions. The direct pathway features more dopamine D1 receptors (activated by high dopamine levels as in positive prediction errors elicited by rewards), while the indirect pathway features more dopamine D2/D3 receptors (activated by low dopamine levels as in negative prediction errors elicited by punishments). Hence, rewards should make the direct pathway more sensitive to input and thus facilitate action release, while punishments should make the indirect pathway more sensitive to input and thus facilitate action suppression. Pavlovian biases are typically measured with the motivational go/nogo learning task. fMRI studies featuring this task having typically not found BOLD signal from the striatum/ basal ganglia to reflect reward vs. punishment anticipation (as predicted by the above basal ganglia model), but instead to reflect the executed response (Go vs. NoGo) (Guitart-Masip et al., 2011; Guitart-Masip, Huys et al., 2012; Guitart-Masip, Chowdhury et al., 2012; Moutoussis et al., 2018; Algermissen et al., 2021). Instead, cue valence (Win vs. Avoid) has been found to be encoded in vmPFC BOLD (positively) and ACC BOLD (negatively). Pavlovian bias in behavior could arise from a response bias (i.e. reward/ punishment prospects biasing response selection), but also from biased action-outcome learning: A learning bias such that learning of Go responses after reward feedback is enhanced, while unlearning of NoGo responses after punishment feedback is attenuated, will also give rise to motivational biases (Swart et al., 2017, 2018; de Boer et al., 2019). Pavlovian bias has been suggested as a response strategy in face of little control over the environment (Csifcsák et al., 2019; Dorfman & Gershman, 2019; Gershman et al., 2021).

Definition contributed by JAlgermissen

Asserted relationships to other concepts

Pavlovian bias
is a kind of

  • response bias
  • Pavlovian bias
    is a part of

  • economic value processing
  • are a kind of
    Pavlovian bias

    No associations
    are a part of
    Pavlovian bias

  • appetitive motivation
  • Tasks that are asserted to measure Pavlovian bias

    Task Contrast Measure

    motivational go/no-go learning task
    • Action


    Intermittent Absence of Control during Reinforcement Learning Interferes with Pavlovian Bias in Action Selection
    Gábor Csifcsák, Eirik Melsæter and Matthias Mittner
    Journal of Cognitive Neuroscience

    Controllability governs the balance between Pavlovian and instrumental action selection
    Hayley M. Dorfman and Samuel J. Gershman
    Nature Communications

    Dorsal striatal dopamine D1 receptor availability predicts an instrumental bias in action learning
    Lieke de Boer, Jan Axelsson, Rumana Chowdhury, Katrine Riklund, Raymond J. Dolan, Lars Nyberg, Lars Bäckman and Marc Guitart-Masip
    Proceedings of the National Academy of Sciences

    The misbehavior of value and the discipline of the will
    Peter Dayan, Yael Niv, Ben Seymour and Nathaniel D. Daw
    Neural Networks

    Frontal network dynamics reflect neurocomputational mechanisms for reducing maladaptive biases in motivated action
    Jennifer C. Swart, Michael J. Frank, Jessica I. Määttä, Ole Jensen, Roshan Cools, Hanneke E. M. den Ouden and Marios Philiastides
    PLOS Biology

    Catecholaminergic challenge uncovers distinct Pavlovian and instrumental mechanisms of motivated (in)action
    Jennifer C Swart, Monja I Froböse, Jennifer L Cook, Dirk EM Geurts, Michael J Frank, Roshan Cools and Hanneke EM den Ouden

    Effects of dopamine on reinforcement learning in Parkinson’s disease depend on motor phenotype
    Annelies J van Nuland, Rick C Helmich, Michiel F Dirkx, Heidemarie Zach, Ivan Toni, Roshan Cools and Hanneke E M den Ouden

    Neural activity and fundamental learning, motivated by monetary loss and reward, are intact in mild to moderate major depressive disorder
    Michael Moutoussis, Robb B. Rutledge, Gita Prabhu, Louise Hrynkiewicz, Jordan Lam, Olga-Therese Ousdal, Marc Guitart-Masip, Peter Fonagy, Raymond J. Dolan and Jean Daunizeau

    Change, stability, and instability in the Pavlovian guidance of behaviour from adolescence to young adulthood
    Michael Moutoussis, Edward T. Bullmore, Ian M. Goodyer, Peter Fonagy, Peter B. Jones, Raymond J. Dolan, Peter Dayan and Samuel J. Gershman
    PLOS Computational Biology

    Go and no-go learning in reward and punishment: Interactions between affect and effect
    Marc Guitart-Masip, Quentin J.M. Huys, Lluis Fuentemilla, Peter Dayan, Emrah Duzel and Raymond J. Dolan

    Action Dominates Valence in Anticipatory Representations in the Human Striatum and Dopaminergic Midbrain
    M. Guitart-Masip, L. Fuentemilla, D. R. Bach, Q. J. M. Huys, P. Dayan, R. J. Dolan and E. Duzel
    Journal of Neuroscience

    Differential, but not opponent, effects of l-DOPA and citalopram on action learning with reward and punishment
    Marc Guitart-Masip, Marcos Economides, Quentin J. M. Huys, Michael J. Frank, Rumana Chowdhury, Emrah Duzel, Peter Dayan and Raymond J. Dolan

    Action controls dopaminergic enhancement of reward representations
    M. Guitart-Masip, R. Chowdhury, T. Sharot, P. Dayan, E. Duzel and R. J. Dolan
    Proceedings of the National Academy of Sciences

    Action versus valence in decision making
    Marc Guitart-Masip, Emrah Duzel, Ray Dolan and Peter Dayan
    Trends in Cognitive Sciences