eLife

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1. We couldn't get details of this article at this time:
   10.1101/2024.11.12.623302

2. Combined transcriptomic, connectivity, and activity profiling of the medial amygdala using highly amplified multiplexed in situ hybridization (hamFISH)

   This article has 15 authors:

   1. Mathew D Edwards
   2. Ziwei Yin
   3. Risa Sueda
   4. Alina Gubanova
   5. Chang S Xu
   6. Virág Lakner
   7. Megan Murchie
   8. Chi-Yu Lee
   9. Kristal Ng
   10. Karolina Farrell
   11. Rupert Faraway
   12. Subham Ganguly
   13. Elina Jacobs
   14. Bogdan Bintu
   15. Yoh Isogai

   This article has been curated by 1 group:

   • Curated by eLife

     eLife Assessment

     The study presents important findings that are highly relevant for research aiming to combine transcriptomics, connectivity studies, and activity profiling in the rodent brain and the revisions improve the study. The evidence overall remains convincing as the authors use appropriate and validated methodology in line with current state-of-the-art.

   Reviewed by eLife

3. We couldn't get details of this article at this time:
   10.1101/2024.10.28.620613

4. We couldn't get details of this article at this time:
   10.1101/2024.06.10.598182

5. We couldn't get details of this article at this time:
   10.1101/2024.09.11.24313489

6. We couldn't get details of this article at this time:
   10.1101/2023.10.05.561025

7. We couldn't get details of this article at this time:
   10.21203/rs.3.rs-3191814/v5

8. Fluidity and Predictability of Epistasis on an Intragenic Fitness Landscape

   This article has 3 authors:

   1. Sarvesh Baheti
   2. Namratha Raj
   3. Supreet Saini

   This article has been curated by 1 group:

   • Curated by eLife

     eLife Assessment

     This paper addresses the significant question of quantifying epistasis patterns, which affect the predictability of evolution, by reanalyzing a recently published combinatorial deep mutational scan experiment. The findings are useful, showing that epistasis is fluid, i.e. strongly background dependent, but that fitness effects of mutations are statistically predictable based on the background fitness. While the general approach appears solid, some claims remain incompletely supported by the analysis, as arbitrary cutoffs are used and the description of methods lacks specifics. This analysis should be of interest to the community working on fitness landscapes.

   Reviewed by eLife

9. How relevant is the prior? Bayesian causal inference for dynamic perception in volatile environments

   This article has 3 authors:

   1. David Meijer
   2. Roberto Barumerli
   3. Robert Baumgartner

   This article has been curated by 1 group:

   • Curated by eLife

     eLife Assessment

     This study makes a valuable contribution to understanding Bayesian inference in dynamic environments by demonstrating how humans integrate prior beliefs with sensory evidence, revealing an overestimation of environmental volatility while accurately tracking noise. The evidence is solid, supported by robust model fitting and principled factorial model set analyses, though limitations in sample size and inconclusive findings on memory capacity tradeoffs reduce the overall impact. Future work should expand validation across datasets, enhance model comparisons, and explore the generalizability of reduced Bayesian frameworks to strengthen the conclusions and broader relevance of the study.

   Reviewed by eLife

10. We couldn't get details of this article at this time:
    10.1101/2024.09.05.610266