Neuroscience

  9. Machine Learning Based Modelling of Human and Insect Olfaction Screens Millions of compounds to Identify Pleasant Smelling Insect Repellents

    1. Joel Kowalewski
    2. Sean M Boyle
    3. Ryan Arvidson
    4. Jadrian Ejercito
    5. Anandasankar Ray

    • Curated by eLife

      eLife Assessment

      This useful study uses a chemoinformatics pipeline to identify a list of candidate mosquito repellants that may be pleasant to smell and safe for humans. The strength of evidence and in particular the computational methodology are incomplete because it is insufficiently benchmarked against other leading models. At the high concentrations tested, there may also be off-target effects of the repellents on the mosquitoes that are not considered.

    Reviewed by eLife

    9 evaluationsAppears in 1 listLatest version Latest activity

  10. Understanding neural circuit principles for representation learning through joint-embedding predictive architectures

    1. Ashena Gorgan Mohammadi
    2. Manu Srinath Halvagal
    3. Friedemann Zenke

    • Curated by eLife

      eLife Assessment

      This manuscript proposes a valuable idea on how cortical networks may learn a helpful representation of sensory stimuli. The model implementing this idea is tested in multiple experimental paradigms. However, the evidence remains incomplete as to whether the method supports both invariance and equivariance and whether it can estimate the dynamics of the moving object.

    Reviewed by eLife

    5 evaluationsAppears in 1 listLatest version Latest activity
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