Evaluated articles

A list by eLife

Articles that have been evaluated by eLife.

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  3. Whole human organ clearing and multimodal mapping

    1. Héloïse Policet-Bétend
    2. Tomàs Jordà-Siquier
    3. Geraldine Cuenu
    4. Maeva Badré
    5. Sami Schranz
    6. Julien Da Costa
    7. Céline Brockmann
    8. Pascal Senn
    9. Daniel Huber
    10. Christophe M Lamy

    • Curated by eLife

      eLife Assessment

      This important paper introduces a generalisable tissue-clearing method to study human anatomy and the organisation of complex tissues and organs. The evidence for its broad applicability is compelling, based on results from 15 diverse human tissues, including highly heterogeneous specimens, with successful labelling using five antibodies and five fluorescent dyes. The method has broad potential applications across multiple disciplines.

    Reviewed by eLife

    3 evaluationsAppears in 1 listLatest version Latest activity

  6. Spatiotemporal Dissociation of Human Amygdala Response to Negative Affect

    1. Ke Bo
    2. Martin A. Lindquist
    3. Peter J. Gianaros
    4. Tor D. Wager

    • Curated by eLife

      eLife Assessment

      This study provides valuable new insights into the functional differentiation of human amygdala subnuclei during the observation of negative images and emotional reappraisal. The evidence is convincing, particularly regarding differences in the time course of evoked responses and their partial correspondence with broad anatomical subdivisions. The work will be of interest to researchers studying the amygdala, emotional processing, and emotion regulation.

    Reviewed by eLife

    3 evaluationsAppears in 1 listLatest version Latest activity

  19. Reinforcement learning for closed-loop optimisation of spatiotemporal stimulation in patterned neuronal networks

    1. Benedikt Maurer
    2. Vaiva Vasiliauskaitė
    3. Julian Hengsteler
    4. Gino Cathomen
    5. Tobias Ruff
    6. Cedric Schmid
    7. János Vörös
    8. Stephan J. Ihle

    • Curated by eLife

      eLife Assessment

      This study presents an open-source reinforcement learning framework for the real-time, closed-loop optimization of spatiotemporal electrical stimulation in engineered neuronal networks. Using single-spike-resolution activity as continuous feedback, the authors provide solid evidence that their platform can identify stimulation patterns that drive specific activity motifs within a structurally constrained four-node circuit. While this reproducible system offers a valuable and accessible tool for interacting with biological neural networks in an adaptive manner, further validation is needed to determine how well these stimulation strategies generalize to larger, unstructured, or more conventional network architectures.

    Reviewed by eLife

    5 evaluationsAppears in 1 listLatest version Latest activity
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