Decision articles within Nature Communications

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  • Article
    | Open Access

    In uncertain conditions, people make accurate decisions by considering multiple pieces of information. Here, the authors show that pharmacological n-methyl-d-aspartate (NMDA) receptor hypofunction is associated with elevated uncertainty and premature decisions based on unreliable evidence.

    • Alexandre Salvador
    • , Luc H. Arnal
    •  & Valentin Wyart

  • Article
    | Open Access

    While evidence is constantly changing during real-world decisions, little is known about how the brain deals with such changes. Here, the authors show that the brain strategically suppresses motor output via the frontal eye fields in response to stimulus changes.

    • Maxwell Shinn
    • , Daeyeol Lee
    •  & Hyojung Seo

  • Article
    | Open Access

    The authors show that metacognitive awareness of choice certainty is closely linked to endogenous attentional states that guide decision behaviour.

    • Jeroen Brus
    • , Helena Aebersold
    •  & Rafael Polania

  • Article
    | Open Access

    Models of perceptual decision making typically take into account either reactive responses to external stimuli or proactive aspects to decision making. Here the authors found that rat perceptual responses are generated by a combination of the standard evidence accumulation process with a fixed decision boundary, and a separate stochastic boundary collapse triggered by a parallel proactive process.

    • Lluís Hernández-Navarro
    • , Ainhoa Hermoso-Mendizabal
    •  & Alexandre Hyafil

  • Article
    | Open Access

    Information-seeking is important for learning, social behaviour and decision making. Here the authors investigate factors that associate with individual differences in information-seeking behaviour.

    • Christopher. A. Kelly
    •  & Tali Sharot

  • Article
    | Open Access

    Human learning depends on opposing effects of two noise factors: volatility and stochasticity. Here the authors present a model of learning that shows how and why joint estimation of these factors is important for understanding healthy and pathological learning.

    • Payam Piray
    •  & Nathaniel D. Daw

  • Article
    | Open Access

    How visual social information informs movement is unclear. Here, the authors characterise the algorithm zebrafish use to transform visual inputs from neighbours into movement decisions during collective swimming behavior. The authors can also predict the neural circuits involved in transforming the visual input into movement decisions.

    • Roy Harpaz
    • , Minh Nguyet Nguyen
    •  & Florian Engert

  • Article
    | Open Access

    Animals distribute their choices between alternative options according to relative reinforcement they receive from those options (matching law). Here, the authors propose metrics based on information theory that can predict this global behavioral rule based on local response to reward feedback.

    • Ethan Trepka
    • , Mehran Spitmaan
    •  & Alireza Soltani

  • Article
    | Open Access

    A crucial component of voluntary behaviour is deciding that it is worth doing something rather than nothing. Here the authors show the brain network that encodes this decision, which includes the habenula and anterior insula.

    • Nima Khalighinejad
    • , Neil Garrett
    •  & Matthew F. S. Rushworth

  • Article
    | Open Access

    Langevin dynamics describe transient behavior of many complex systems, however, inferring Langevin equations from noisy data is challenging. The authors present an inference framework for non-stationary latent Langevin dynamics and test it on models of spiking neural activity during decision making.

    • Mikhail Genkin
    • , Owen Hughes
    •  & Tatiana A. Engel

  • Article
    | Open Access

    A Bayesian framework based on partially observable Markov decision processes (POMDPs) not only predicts subjects’ confidence in a perceptual decision making task but also explains well-known discrepancies between confidence and choice accuracy as arising from incomplete knowledge of the environment.

    • Koosha Khalvati
    • , Roozbeh Kiani
    •  & Rajesh P. N. Rao

  • Article
    | Open Access

    Models of decision making have so far been unable to account for how humans’ choices can be flexible yet efficient. Here the authors present a linear reinforcement learning model which explains both flexibility, and rare limitations such as habits, as arising from efficient approximate computation

    • Payam Piray
    •  & Nathaniel D. Daw

  • Article
    | Open Access

    Making a decision requires one to differentiate between choice options, committing to one and leaving the other behind. Here, the authors show that decision-making paradoxically binds options together, such that the outcome of the choice ends up changing the value of both the chosen and the unchosen options, in opposite directions.

    • Natalie Biderman
    •  & Daphna Shohamy

  • Article
    | Open Access

    Feedback modulates visual neurons, thought to help achieve flexible task performance. Here, the authors show decision-related feedback is not only relayed to task-relevant neurons, suggesting a broader mechanism and supporting a previously hypothesized link to feature-based attention.

    • Katrina R. Quinn
    • , Lenka Seillier
    •  & Hendrikje Nienborg

  • Article
    | Open Access

    People can infer unobserved causes of perceptual data (e.g. the contents of a box from the sound made by shaking it). Here the authors show that children compare what they hear with what they would have heard given other causes, and explore longer when the heard and imagined sounds are hard to discriminate.

    • Max H. Siegel
    • , Rachel W. Magid
    •  & Laura E. Schulz

  • Article
    | Open Access

    Value-based decision making involves choosing from multiple options with different values. The authors identify a neural mechanism that directly transforms absolute values to categorical choices within the superior colliculus and which supports value-based decision making critical for real-world economic behaviours.

    • Beizhen Zhang
    • , Janis Ying Ying Kan
    •  & Michael Christopher Dorris

  • Article
    | Open Access

    How is neural processing adjusted when people experience uncertainty about the relevance of a stimulus feature? Here, the authors provide evidence suggesting that heightened uncertainty shifts cortical networks from a rhythmic to an asynchronous (“excited”) state and that the thalamus is central for such uncertainty-related shifts.

    • Julian Q. Kosciessa
    • , Ulman Lindenberger
    •  & Douglas D. Garrett

  • Article
    | Open Access

    In this study, the authors distinguish between changes of mind about perceptual vs. intentional decisions. A Hierarchical Attractor Network Model is proposed in which human voluntary actions emerge from continuous and dynamic integration of higher-order intentions with sensory evidence and motor costs.

    • Anne Löffler
    • , Anastasia Sylaidi
    •  & Patrick Haggard

  • Article
    | Open Access

    Decisions under uncertainty involve a balance between exploiting familiar valuable options and exploring unfamiliar ones. Here, the authors study hippocampal responses using fMRI during a reinforcement learning task, and show the differential involvement of the anterior-posterior regions in the explore-exploit aspects of the task.

    • Alexandre Y. Dombrovski
    • , Beatriz Luna
    •  & Michael N. Hallquist

  • Article
    | Open Access

    Even decisions based on simple sensory stimuli result from an interplay between many brain regions. Here, the authors track the dynamics of information about sensory input and behavioral choice across the human cerebral cortex, uncovering feedback of decision signals to early sensory cortex.

    • Niklas Wilming
    • , Peter R. Murphy
    •  & Tobias H. Donner

  • Article
    | Open Access

    Motor neurons are generally considered to be passive receivers of commands from other neurons. However, this study shows that motor neurons may shape locomotor behaviour by regulating premotor neurons, and that premotor neurons serve to integrate information from sensory neurons and motor neurons.

    • Ping Liu
    • , Bojun Chen
    •  & Zhao-Wen Wang

  • Article
    | Open Access

    Humans are able to exploit patterns or schemas when performing new tasks, but the mechanism for this ability is still unknown. Using graph-learning tasks, we show that humans are able to transfer abstract structural knowledge and suggest a computational mechanism by which such transfer can occur.

    • Shirley Mark
    • , Rani Moran
    •  & Timothy E. J. Behrens

  • Article
    | Open Access

    Humans can unconsciously learn to gamble on rewarding options, but can they do so when it comes to their own mental states? Here, the authors show that participants can learn to use unconscious representations in their own brains to earn rewards, and that metacognition correlates with their learning processes.

    • Aurelio Cortese
    • , Hakwan Lau
    •  & Mitsuo Kawato

  • Article
    | Open Access

    This study shows that cerebellar molecular layer interneurons (MLIs) develop responses encoding for identity of the stimulus in an associative learning task. Chemogenetic inhibition of MLIs decreased the ability of mice to discriminate stimuli suggesting that MLIs encode for stimulus valence.

    • Ming Ma
    • , Gregory L. Futia
    •  & Diego Restrepo

  • Article
    | Open Access

    Fatigue influences our choices to engage in physical activity. Here, the authors investigate the underlying cognitive and neuronal mechanisms by which fatigue influences decisions to exert, and show that information about motor cortical state modulates decisions to engage in physical activity.

    • Patrick S. Hogan
    • , Steven X. Chen
    •  & Vikram S. Chib

  • Article
    | Open Access

    What sensory information is available for decision making? Here, using multi-alternative decisions, the authors show that a substantial amount of information from sensory representations is lost during the transformation to a decision-level representation.

    • Jiwon Yeon
    •  & Dobromir Rahnev

  • Article
    | Open Access

    Wittmann and colleagues show that not only single outcome events but also the global reward state (GRS) impact learning in macaques; low GRS drives explorative choices. Analyses of macaque BOLD signal reveals that GRS impacts activity in the anterior insula as well as the dorsal raphe nucleus.

    • Marco K. Wittmann
    • , Elsa Fouragnan
    •  & Matthew F. S. Rushworth

  • Article
    | Open Access

    In value-based decision-making, single prefrontal neurons represent multiple variables at different times in the decision process. Here, the authors show these representations to be separable and stable at the population level, allowing read out of specific variables at behaviorally relevant times.

    • Daniel L. Kimmel
    • , Gamaleldin F. Elsayed
    •  & William T. Newsome

  • Article
    | Open Access

    In some types of decision-making, people must accept or forego an option without knowing what prospects might later be available. Here, the authors reveal how a key bias– asymmetric learning from negative versus positive outcomes – emerges in this type of decision.

    • Neil Garrett
    •  & Nathaniel D. Daw

  • Article
    | Open Access

    Decision-making is traditionally thought to be guided by memories of option values. Here, the authors challenge this view by showing that merely making a choice – even without experiencing any outcomes – alters neural representations of stimulus-reward associations and biases future decisions.

    • Lennart Luettgau
    • , Claus Tempelmann
    •  & Gerhard Jocham

  • Article
    | Open Access

    The thalamus provides sensory input to the cortex, but many aspects of thalamocortical signaling remain unknown. Here, the authors reveal parallel non-overlapping thalamic pathways with distinct representations of tactile and decision-related information during a goal-directed sensorimotor task.

    • Sami El-Boustani
    • , B. Semihcan Sermet
    •  & Carl C. H. Petersen

  • Article
    | Open Access

    Habitat complexity influences the sensory ecology of predator-prey interactions. Here, the authors show that habitat complexity also affects the use of different decision-making paradigms, namely habit- and plan-based action selection. Simulations across habitat types show that only savanna-like terrestrial habitats favor planning during visually-guided predator evasion, while aquatic and simple terrestrial habitats do not.

    • Ugurcan Mugan
    •  & Malcolm A. MacIver

  • Article
    | Open Access

    People often ignore evidence that disconfirms their prior beliefs. Here, the authors investigate the underlying cognitive, computational and neuronal mechanisms of such confirmation bias, and show that high confidence induces a selective neural processing of choice-consistent information.

    • Max Rollwage
    • , Alisa Loosen
    •  & Stephen M. Fleming

  • Article
    | Open Access

    Goal directed behavior requires the sequential retrieval and evaluation of the multiple choices for action and their deterministic outcomes. Here, the authors report sequential, decodable probabilistic outcome representations in magnetoencephalography (MEG) signals during a risky foraging task.

    • Giuseppe Castegnetti
    • , Athina Tzovara
    •  & Dominik R. Bach

  • Article
    | Open Access

    The cognitive computational mechanisms underlying the antidepressant treatment response of SSRIs is not well understood. Here the authors show that SSRI treatment in healthy subjects for a week manifests as an amplification of the perception of positive outcomes when learning occurs in a positive mood setting.

    • Jochen Michely
    • , Eran Eldar
    •  & Raymond J. Dolan

  • Article
    | Open Access

    Conventional theory suggests that people’s confidence about a decision reflects their subjective probability that the decision was correct. By studying decisions with multiple alternatives, the authors show that confidence reports instead reflect the difference in probabilities between the chosen and the next-best alternative.

    • Hsin-Hung Li
    •  & Wei Ji Ma

  • Article
    | Open Access

    The authors use a combination of perceptual decision making in rats and computational modeling to explore the interplay of priors and sensory cues. They find that rats can learn to either alternate or repeat their actions based on reward likelihood and the influence of bias on their actions disappears after making an error.

    • Ainhoa Hermoso-Mendizabal
    • , Alexandre Hyafil
    •  & Jaime de la Rocha

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