Neuroscience

An anatomical and physiological basis for flexible coincidence detection in the auditory system

1. Lauren J Kreeger
2. Suraj Honnuraiah
3. Sydney Maeker
4. Siobhan Shea
5. Gordon Fishell
6. Lisa Goodrich

• Curated by eLife

  eLife Assessment

  Kreeger et al. convincingly demonstrate that octopus cells in the mouse cochlear nucleus, previously thought to rely primarily on excitatory inputs for coincidence detection, also receive glycinergic inhibitory synaptic inputs that influence their synaptic integration. Using advanced techniques, including genetic mouse models, optogenetics, microscopy, slice physiology, and computational modeling, this important study reveals that inhibition can shunt synaptic currents and alter the timing of dendritic EPSPs, both of which are significant for auditory processing. This research broadens the understanding of octopus cells' roles in sensory processing, highlighting the importance of inhibitory inputs in shaping fast, high-frequency neural response capabilities.

Reviewed by eLife

Movies reveal the fine-grained organization of infant visual cortex

1. Cameron T Ellis
2. Tristan S Yates
3. Michael J Arcaro
4. Nicholas Turk-Browne

• Curated by eLife

  eLife Assessment

  This study presents valuable evidence concerning the potential for naturalistic movie-viewing fMRI experiments to reveal some features that are correlated with the functional and topographical organization of the developing visual system in awake infants and toddlers. The data are compelling given the difficulty of studying this population, the methodology is original and validated, and the evidence supporting the conclusions is convincing and in line with prior research using resting-state and awake task-based fMRI. This study will be of interest to cognitive neuroscientists and developmental psychologists, and in particular those interested in using fMRI to investigate brain organisation in pediatric and clinical populations with limited tolerance to fMRI.

Reviewed by eLife

Control of innate olfactory valence by segregated cortical amygdala circuits

1. James R Howe
2. Chung-Lung Chan
3. Donghyung Lee
4. Marlon Blanquart
5. James H Lee
6. Haylie K Romero
7. Abigail N Zadina
8. Mackenzie E Lemieux
9. Fergil Mills
10. Paula A Desplats
11. Kay M Tye
12. Cory M Root

• Curated by eLife

  eLife Assessment

  This study provides important insights into how a specific brain region controls innate responses to odors, showing that different parts of this region govern behaviors related to attraction and aversion. The findings are convincing and supported by a combination of well-executed experimental approaches, including genetic manipulations and neural activity mapping, though the evidence could be strengthened by addressing certain methodological concerns, such as clarifying the rationale for specific experimental choices and exploring alternative techniques.

Reviewed by eLife

CaBLAM! A high-contrast bioluminescent Ca ²⁺ indicator derived from an engineered Oplophorus gracilirostris luciferase

1. Gerard G. Lambert
2. Emmanuel L. Crespo
3. Jeremy Murphy
4. Daniela Boassa
5. Selena Luong
6. Dmitrijs Celinskis
7. Stephanie Venn
8. Daniel K. Nguyen
9. Junru Hu
10. Brittany Sprecher
11. Maya O. Tree
12. Richard Orcutt
13. Daniel Heydari
14. Aidan B. Bell
15. Albertina Torreblanca-Zanca
16. Ali Hakimi
17. Diane Lipscombe
18. Christopher I. Moore
19. Ute Hochgeschwender
20. Nathan C. Shaner

Reviewed by Arcadia Science

Cholinergic waves have a modest influence on the transcriptome of retinal ganglion cells

1. Rachana Deven Somaiya
2. Matthew A. Po
3. Marla B. Feller
4. Karthik Shekhar

Reviewed by Arcadia Science

A split-GAL4 driver line resource for Drosophila neuron types

1. Geoffrey W Meissner
2. Allison Vannan
3. Jennifer Jeter
4. Kari Close
5. Gina M DePasquale
6. Zachary Dorman
7. Kaitlyn Forster
8. Jaye Anne Beringer
9. Theresa Gibney
10. Joanna H Hausenfluck
11. Yisheng He
12. Kristin Henderson
13. Lauren Johnson
14. Rebecca M Johnston
15. Gudrun Ihrke
16. Nirmala A Iyer
17. Rachel Lazarus
18. Kelley Lee
19. Hsing-Hsi Li
20. Hua-Peng Liaw
21. Brian Melton
22. Scott Miller
23. Reeham Motaher
24. Alexandra Novak
25. Omotara Ogundeyi
26. Alyson Petruncio
27. Jacquelyn Price
28. Sophia Protopapas
29. Susana Tae
30. Jennifer Taylor
31. Rebecca Vorimo
32. Brianna Yarbrough
33. Kevin Xiankun Zeng
34. Christopher T Zugates
35. Heather Dionne
36. Claire Angstadt
37. Kelly Ashley
38. Amanda Cavallaro
39. Tam Dang
40. Guillermo A Gonzalez
41. Karen L Hibbard
42. Cuizhen Huang
43. Jui-Chun Kao
44. Todd Laverty
45. Monti Mercer
46. Brenda Perez
47. Scarlett Rose Pitts
48. Danielle Ruiz
49. Viruthika Vallanadu
50. Grace Zhiyu Zheng
51. Cristian Goina
52. Hideo Otsuna
53. Konrad Rokicki
54. Robert R Svirskas
55. Han SJ Cheong
56. Michael-John Dolan
57. Erica Ehrhardt
58. Kai Feng
59. Basel EI Galfi
60. Jens Goldammer
61. Stephen J Huston
62. Nan Hu
63. Masayoshi Ito
64. Claire McKellar
65. Ryo Minegishi
66. Shigehiro Namiki
67. Aljoscha Nern
68. Catherine E Schretter
69. Gabriella R Sterne
70. Lalanti Venkatasubramanian
71. Kaiyu Wang
72. Tanya Wolff
73. Ming Wu
74. Reed George
75. Oz Malkesman
76. Yoshinori Aso
77. Gwyneth M Card
78. Barry J Dickson
79. Wyatt Korff
80. Kei Ito
81. James W Truman
82. Marta Zlatic
83. Gerald M Rubin
84. FlyLight Project Team

• Curated by eLife

  eLife Assessment

  This valuable study presents a resource for researchers using Drosophila to study neural circuits, in the form of a collection of split-Gal4 lines with an online search engine, which will facilitate the mapping of neuronal circuits. The evidence is convincing to demonstrate the utility of these new tools, and of the search engine, for understanding expression patterns in adults and larvae, and differences between the sexes. These resources will be of broad interest to Drosophila researchers in the field of neurobiology.

Reviewed by eLife

Driver lines for studying associative learning in Drosophila

1. Yichun Shuai
2. Megan Sammons
3. Gabriella R Sterne
4. Karen L Hibbard
5. He Yang
6. Ching-Po Yang
7. Claire Managan
8. Igor Siwanowicz
9. Tzumin Lee
10. Gerald M Rubin
11. Glenn C Turner
12. Yoshinori Aso

• Curated by eLife

  eLife Assessment

  This important collection of over 800 new cell type-specific driver lines will be an invaluable resource for researchers studying associative learning in Drosophila. Thoroughly characterized and well documented, this collection will permit researchers to selectively target neurons that deliver information to, or receive it from, the memory center of the fly brain called the Mushroom Body. Given the wealth of new drivers and the genetic access they provide to over 300 cell types, this compelling work will be of interest not only to researchers studying the mechanisms of associative learning but more generally to those dissecting sensorimotor circuits in the fly nervous system.

Reviewed by eLife

Tripartite organization of brain state dynamics underlying spoken narrative comprehension

1. Lanfang Liu
2. Jiahao Jiang
3. Hehui Li
4. Guosheng Ding

• Curated by eLife

  eLife Assessment

  This study provides important insights into the brain activity and connectivity underlying speech comprehension, revealing three brain states. The authors present compelling evidence by leveraging hidden Markov modeling of fMRI data to link brain state dynamics to comprehension scores, though the functional role of these states remains under-explored. These findings advance our understanding of how brain state transitions in narrative comprehension relate to stimulus-specific features.

Reviewed by eLife

Learned response dynamics reflect stimulus timing and encode temporal expectation violations in superficial layers of mouse V1

1. Scott G Knudstrup
2. Catalina Martinez
3. Jeffrey P Gavornik

• Curated by eLife

  eLife Assessment

  This paper presents useful results that extend our understanding of how the visual cortex encodes temporal structure, providing new information about sequence representations in the upper layers of the visual cortex. The evidence for prediction errors is solid, however, support for other claims regarding sparsification and simplification of activity following training is incomplete. The main concerns pertain to the confounds associated with restricted ordering within blocks that does not allow for separate plasticity mechanisms operating on different time scales.

Reviewed by eLife

Using normative models pre-trained on cross-sectional data to evaluate intra-individual longitudinal changes in neuroimaging data

1. Barbora Rehak Buckova
2. Charlotte Fraza
3. Rastislav Rehák
4. Marián Kolenič
5. Christian F Beckmann
6. Filip Španiel
7. Andre F Marquand
8. Jaroslav Hlinka

• Curated by eLife

  eLife Assessment

  This paper addresses an important topic (normative trajectory modelling), seeking to provide a method aiming to accurately reflect the individual deviation of longitudinal/temporal change compared to the normal temporal change characterized based on a pre-trained population normative model. The evidence provided for the new methods is solid.

Reviewed by eLife