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  2. Inverted Assembly of the Lens Within Ocular Organoids Reveals Alternate Paths to Ocular Morphogenesis

    1. Elin Stahl
    2. Miguel Angel Delgado-Toscano
    3. Ishwariya Saravanan
    4. Anastasija Paneva
    5. Joachim Wittbrodt
    6. Lucie Zilova

    • Curated by eLife

      eLife Assessment

      This important study demonstrates that ocular organoids can generate both retina and lens through a non-canonical, "inside-out" morphogenetic route. The work is supported by convincing data, with well-designed experiments combining imaging, molecular analysis, and transcriptomics to establish that lens formation in organoids follows conserved molecular programs despite an alternative morphogenesis. These findings expand our understanding of self-organization and developmental plasticity, and will be of broad interest to researchers working on eye development, organoids, and tissue engineering.

      [Editors' note: this paper was reviewed by Review Commons.]

    Reviewed by eLife, Review Commons

    14 evaluationsAppears in 2 listsLatest version Latest activity

  3. Neural Representation of Associative Threat Learning in Pulvinar Divisions, Lateral Geniculate Nucleus, and Mediodorsal Thalamus in Humans

    1. Muhammad Badarnee
    2. Zhenfu Wen
    3. B Isabel Moallem
    4. Stephen Maren
    5. Mohammed R Milad

    • Curated by eLife

      eLife Assessment

      This study provides valuable insights into the role of thalamic nuclei in associative threat and extinction learning, underpinned by a large dataset and rigorous, multipronged analyses. The evidence provided is solid, supporting the main conclusions. Minor analytical refinements notwithstanding, the manuscript will be of broad interest to researchers in learning and memory, fear, thalamic circuitry, and related mental health conditions.

    Reviewed by eLife

    10 evaluationsAppears in 1 listLatest version Latest activity

  6. Spontaneous fluctuations in global connectivity reflect transitions between states of high and low prediction error

    1. Paul C Bogdan
    2. Shenyang Huang
    3. Lifu Deng
    4. Simon W Davis
    5. Roberto Cabeza

    • Curated by eLife

      eLife Assessment

      This study uses a valuable combination of functional magnetic resonance imaging and electroencephalography (EEG) to study brain activity related to prediction errors in relation to both sensorimotor and more complex cognitive functions. It provides incomplete evidence to suggest that prediction error minimisation drives brain activity across both types of processing and that elevated inter-regional functional coupling along a superior-inferior axis is associated with high prediction error, whereas coupling along a posterior-anterior axis is associated with low prediction error. The manuscript will be of interest to neuroscientists working on predictive coding and decision-making, but would benefit from more precise localisation of EEG sources and more rigorous statistical controls.

    Reviewed by eLife

    9 evaluationsAppears in 1 listLatest version Latest activity

  7. Spyglass: a framework for reproducible and shareable neuroscience research

    1. Kyu Hyun Lee
    2. Eric L Denovellis
    3. Ryan Ly
    4. Jeremy Magland
    5. Jeff Soules
    6. Alison E Comrie
    7. Daniel P Gramling
    8. Jennifer A Guidera
    9. Rhino Nevers
    10. Philip Adenekan
    11. Chris Brozdowski
    12. Samuel R Bray
    13. Emily Monroe
    14. Ji Hyun Bak
    15. Michael E Coulter
    16. Xulu Sun
    17. Emrey Broyles
    18. Donghoon Shin
    19. Sharon Chiang
    20. Cristofer Holobetz
    21. Andrew Tritt
    22. Oliver Rübel
    23. Thinh Nguyen
    24. Dimitri Yatsenko
    25. Joshua Chu
    26. Caleb Kemere
    27. Samuel Garcia
    28. Alessio Buccino
    29. Loren M Frank

    • Curated by eLife

      eLife Assessment

      This valuable study presents a framework for a shareable data analysis pipeline aimed at improving reproducibility in neuroscience. The evidence for robustness and inter-laboratory operability is convincing. Overall, this work will be of interest to neuroscientists engaged in the analysis of large-scale neuronal recordings.

    Reviewed by eLife

    7 evaluationsAppears in 1 listLatest version Latest activity
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