Neuroscience

Increased reluctant vesicles underlie synaptic depression by GPR55 in axon terminals of cerebellar Purkinje cells

1. Takuma Inoshita
2. Shin-ya Kawaguchi

• Curated by eLife

  eLife Assessment

  This is an important study reporting that activation of the presynaptic GPR55 receptor suppresses synaptic transmission by modulating GABA release through the reduction of the readily releasable pool without affecting the presynaptic AP waveform and calcium influx. The evidence supporting this claim is compelling and based on an impressive array of techniques including patch-clamp recordings from the axon terminals of cerebellar Purkinje cells and fluorescent imaging of vesicular exocytosis. However, a few technical issues leave some questions open, these include uncertainty regarding the specificity of pharmacological agents and the nature of the endogenous process that would activate this pathway in vivo. In the current form, the evidence indicating that synaptic vesicles become insensitive to VGCC activation in the presence of GPR55 is weak and would need to be supported with additional experimental data.

Reviewed by eLife

Visually-guided compensation of deafening-induced song deterioration

1. Manon Rolland
2. Anja T. Zai
3. Richard H. R. Hahnloser
4. Catherine Del Negro
5. Nicolas Giret

Reviewed by preLights

Modeling and simulation of neocortical micro- and mesocircuitry (Part II, Physiology and experimentation)

1. James B Isbister
2. András Ecker
3. Christoph Pokorny
4. Sirio Bolaños-Puchet
5. Daniela Egas Santander
6. Alexis Arnaudon
7. Omar Awile
8. Barros-Zulaica Natali
9. Jorge Blanco Alonso
10. Elvis Boci
11. Giuseppe Chindemi
12. Jean-Denis Courcol
13. Tanguy Damart
14. Thomas Delemontex
15. Alexander Dietz
16. Gianluca Ficarelli
17. Mike Gevaert
18. Joni Herttuainen
19. Genrich Ivaska
20. Weina Ji
21. Daniel Keller
22. James King
23. Pramod Kumbhar
24. Samuel Lapere
25. Polina Litvak
26. Darshan Mandge
27. Eilif B Muller
28. Fernando Pereira
29. Judit Planas
30. Rajnish Ranjan
31. Maria Reva
32. Armando Romani
33. Christian Rössert
34. Felix Schürmann
35. Vishal Sood
36. Aleksandra Teska
37. Anil Tuncel
38. Werner Van Geit
39. Matthias Wolf
40. Henry Markram
41. Srikanth Ramaswamy
42. Michael W Reimann

• Curated by eLife

  eLife Assessment

  This study reports a model of 8 somatosensory areas of the rat cortex consisting of 4.2 million morphologically and electrically detailed neurons. The authors carry out simulation experiments aimed at understanding how multiscale organization of the cortical network shapes neural activity. While the reviewers found the results to be solid, they note that they could have likely been obtained using a much smaller portion of the model. Nonetheless, the release of the modeling platform represents a significant contribution to the field by providing a valuable resource for the scientific community.

Reviewed by eLife

Robust variability of grid cell properties within individual grid modules enhances encoding of local space

1. William T Redman
2. Santiago Acosta-Mendoza
3. Xue-Xin Wei
4. Michael J Goard

• Curated by eLife

  eLife Assessment

  This valuable study examines the variability in spacing and direction of entorhinal grid cells, providing convincing evidence that such variability helps disambiguate locations within an environment. This study will be of interest to neuroscientists working on spatial navigation and, more broadly, on neural coding.

Reviewed by eLife

Chronic RNA G-quadruplex accumulation in aging and Alzheimer’s disease

1. Lena Kallweit
2. Eric Daniel Hamlett
3. Hannah Saternos
4. Anah Gilmore
5. Ann-Charlotte Granholm
6. Scott Horowitz

• Curated by eLife

  eLife Assessment

  The current human tissue-based study provides compelling evidence correlating hippocampal expressions of RNA guanine-rich G-quadruplexes with aging and with Alzheimer's Disease presence and severity. The results are fundamental and will rejuvenate our understanding of aging and AD's pathogenesis.

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

Reviewed by eLife, Review Commons

Rate of brain aging associates with future executive function in Asian children and older adults

1. Susan F Cheng
2. Wan Lin Yue
3. Kwun Kei Ng
4. Xing Qian
5. Siwei Liu
6. Trevor WK Tan
7. Kim-Ngan Nguyen
8. Ruth LF Leong
9. Saima Hilal
10. Ching-Yu Cheng
11. Ai Peng Tan
12. Evelyn C Law
13. Peter D Gluckman
14. Christopher Li-Hsian Chen
15. Yap Seng Chong
16. Michael J Meaney
17. Michael WL Chee
18. BT Thomas Yeo
19. Juan Helen Zhou

• Curated by eLife

  eLife Assessment

  This valuable study marks a significant advancement in brain aging research by centering on Asian populations (Chinese, Malay, and Indian Singaporeans), a group frequently underrepresented in such studies. It unveils solid evidence for anatomical differences in brain aging predictors between the young and old age groups. Overall, this study broadens our understanding of brain aging across diverse ethnicities.

Reviewed by eLife

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

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

• 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

Biophysically inspired mean-field model of neuronal populations driven by ion exchange mechanisms

1. Giovanni Rabuffo
2. Abhirup Bandyopadhyay
3. Carmela Calabrese
4. Kashyap Gudibanda
5. Damien Depannemaecker
6. Lavinia Mitiko Takarabe
7. Maria Luisa Saggio
8. Mathieu Desroches
9. Anton Ivanov
10. Marja-Leena Linne
11. Christophe Bernard
12. Spase Petkoski
13. Viktor K Jirsa

• Curated by eLife

  eLife Assessment

  This manuscript presents a useful mean-field model for a network of Hodgkin-Huxley neurons retaining the equations for ion exchange between the intracellular and extracellular space. The mean-field model derived in this work relies on approximations and heuristic arguments that, on the one hand, allow a closed-form derivation of the mean-field equations, but also raise questions about their justifications and the degree to which the results agree with experiments as well as direct numerical simulations. Therefore, the evidence for the utility of this approach is at present incomplete.

Reviewed by eLife

Mapping the topographic organization of the human zona incerta using diffusion MRI

1. Roy AM Haast
2. Jason Kai
3. Alaa Taha
4. Violet Liu
5. Greydon Gilmore
6. Maxime Guye
7. Ali R Khan
8. Jonathan C Lau

• Curated by eLife

  eLife Assessment

  This important study uses diffusion magnetic resonance imaging to non-invasively map the white matter fibres connecting the zona incerta and cortex in humans. The authors present convincing evidence to indicate that these connections are organized along a rostro-caudal axis. The findings will be of interest to researchers interested in neuroanatomy and cortico-subcortical connectivity.

Reviewed by eLife

Adaptive chunking improves effective working memory capacity in a prefrontal cortex and basal ganglia circuit

1. Aneri Soni
2. Michael J Frank

• Curated by eLife

  eLife Assessment

  This important work proposes a neural network model of interactions between the prefrontal cortex and basal ganglia to implement adaptive resource allocation in working memory, where the gating strategies for storage are adjusted by reinforcement learning. Numerical simulations provide convincing evidence for the superiority of the model in improving effective capacity, optimizing resource management, and reducing error rates, as well as for its human-like performance. This work will be of broad interest to computational and cognitive neuroscientists, and may also interest machine-learning researchers who seek to develop brain-inspired machine-learning algorithms for memory.

Reviewed by eLife