1. Neuroscience
Download icon

Recurrent processes support a cascade of hierarchical decisions

  1. Laura Gwilliams  Is a corresponding author
  2. Jean-Remi King
  1. New York University, United States
  2. École normale supérieure, PSL University, CNRS, France
Research Article
  • Cited 1
  • Views 1,729
  • Annotations
Cite this article as: eLife 2020;9:e56603 doi: 10.7554/eLife.56603


Perception depends on a complex interplay between feedforward and recurrent processing. Yet, while the former has been extensively characterized, the computational organization of the latter remains largely unknown. Here, we use magneto-encephalography to localize, track and decode the feedforward and recurrent processes of reading, as elicited by letters and digits whose level of ambiguity was parametrically manipulated. We first confirm that a feedforward response propagates through the ventral and dorsal pathways within the first 200 ms. The subsequent activity is distributed across temporal, parietal and prefrontal cortices, which sequentially generate five levels of representations culminating in action-specific motor signals. Our decoding analyses reveal that both the content and the timing of these brain responses are best explained by a hierarchy of recurrent neural assemblies, which both maintain and broadcast increasingly rich representations. Together, these results show how recurrent processes generate, over extended time periods, a cascade of decisions that ultimately accounts for subjects' perceptual reports and reaction times.

Data availability

Anonymised source data for figures have been uploaded to Dryad: https://datadryad.org/stash/share/Brtqvoy74YhoHxvaBZMsCeL5JOvWdI_Yuaui5fyIJPA

The following data sets were generated

Article and author information

Author details

  1. Laura Gwilliams

    Psychology, New York University, New York, United States
    For correspondence
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9213-588X
  2. Jean-Remi King

    Departement d'Etudes Cognitives, École normale supérieure, PSL University, CNRS, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2121-170X


William Orr Dingwall Dissertation Fellowship (Dissertation Fellowship)

  • Laura Gwilliams

Abu Dhabi Institute Grant (G1001)

  • Laura Gwilliams

Horizon 2020 Framework Programme (660086)

  • Jean-Remi King

Bettencourt-Schueller Foundation (Bettencourt-Schueller Foundation)

  • Jean-Remi King

Fondation Roger de Spoelberch (Fondation Roger de Spoelberch)

  • Jean-Remi King

Philippe Foundation (Philippe Foundation)

  • Jean-Remi King

National Institutes of Health (R01DC05660)

  • Laura Gwilliams

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.


Human subjects: This study was ethically approved by the comité de protection des personnes (CPP) IDF 7 under the reference CPP 08 021. All subjects gave written informed consent to participate in this study, which was approved by the local Ethics Committee, in accordance with the Declaration of Helsinki. Participants were compensated for their participation.

Reviewing Editor

  1. Thomas Serre, Brown University, United States

Publication history

  1. Received: March 3, 2020
  2. Accepted: August 30, 2020
  3. Accepted Manuscript published: September 1, 2020 (version 1)
  4. Version of Record published: September 18, 2020 (version 2)


© 2020, Gwilliams & King

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.


  • 1,729
    Page views
  • 232
  • 1

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)

Further reading

    1. Computational and Systems Biology
    2. Neuroscience
    Douglas G Lee, Jean Daunizeau
    Research Article Updated

    Why do we sometimes opt for actions or items that we do not value the most? Under current neurocomputational theories, such preference reversals are typically interpreted in terms of errors that arise from the unreliable signaling of value to brain decision systems. But, an alternative explanation is that people may change their mind because they are reassessing the value of alternative options while pondering the decision. So, why do we carefully ponder some decisions, but not others? In this work, we derive a computational model of the metacognitive control of decisions or MCD. In brief, we assume that fast and automatic processes first provide initial (and largely uncertain) representations of options' values, yielding prior estimates of decision difficulty. These uncertain value representations are then refined by deploying cognitive (e.g., attentional, mnesic) resources, the allocation of which is controlled by an effort-confidence tradeoff. Importantly, the anticipated benefit of allocating resources varies in a decision-by-decision manner according to the prior estimate of decision difficulty. The ensuing MCD model predicts response time, subjective feeling of effort, choice confidence, changes of mind, as well as choice-induced preference change and certainty gain. We test these predictions in a systematic manner, using a dedicated behavioral paradigm. Our results provide a quantitative link between mental effort, choice confidence, and preference reversals, which could inform interpretations of related neuroimaging findings.

    1. Neuroscience
    Rundong Jiang et al.
    Research Article

    The ventral visual pathway is crucially involved in integrating low-level visual features into complex representations for objects and scenes. At an intermediate stage of the ventral visual pathway, V4 plays a crucial role in supporting this transformation. Many V4 neurons are selective for shape segments like curves and corners, however it remains unclear whether these neurons are organized into clustered functional domains, a structural motif common across other visual cortices. Using two-photon calcium imaging in awake macaques, we confirmed and localized cortical domains selective for curves or corners in V4. Single-cell resolution imaging confirmed that curve or corner selective neurons were spatially clustered into such domains. When tested with hexagonal-segment stimuli, we find that stimulus smoothness is the cardinal difference between curve and corner selectivity in V4. Combining cortical population responses with single neuron analysis, our results reveal that curves and corners are encoded by neurons clustered into functional domains in V4. This functionally-specific population architecture bridges the gap between the early and late cortices of the ventral pathway and may serve to facilitate complex object recognition.