Neuroscience

Synaptic Connectivity of Sensorimotor Circuits for Vocal Imitation in the Songbird

1. Massimo Trusel
2. Ziran Zhao
3. Danyal H. Alam
4. Ethan S. Marks
5. Maaya Z. Ikeda
6. Todd F. Roberts

• Curated by eLife

  eLife Assessment

  The songbird vocal motor nucleus HVC contains cells that project to the basal ganglia, the auditory system, or downstream vocal motor structures. In this fundamental study, the authors conduct optogenetic circuit mapping to clarify how four distinct inputs to HVC act on these distinct HVC cell types. They provide compelling evidence that all long-range projections engage inhibitory circuits in HVC and can also exhibit cell-type specific preferences in monosynaptic input strength. Understanding the HVC microcircuit at this microcircuit level is critical for informing models of song learning and production.

Reviewed by eLife

Stimulus representation in human frontal cortex supports flexible control in working memory

1. Zhujun Shao
2. Mengya Zhang
3. Qing Yu

• Curated by eLife

  eLife Assessment

  This work presents important findings that the human frontal cortex is involved in a flexible, dual role in both maintaining information in short-term memory, and controlling this memory content to guide adaptive behavior and decisions. The evidence supporting the conclusions is compelling, with a well-designed task, best-practice decoding methods, and careful control analyses. The work will be of broad interest to cognitive neuroscience researchers working on working memory and cognitive control.

Reviewed by eLife

Plasma Membrane Remodelling in GM2 Gangliosidoses Drives Synaptic Dysfunction

1. Alex S. Nicholson
2. David A. Priestman
3. Robin Antrobus
4. James C. Williamson
5. Reuben Bush
6. Henry G. Barrow
7. Emily Smith
8. Kostantin Dobrenis
9. Nicholas A. Bright
10. Frances M. Platt
11. Janet E. Deane

Reviewed by Review Commons

Reproducibility of in vivo electrophysiological measurements in mice

1. International Brain Laboratory
2. Kush Banga
3. Julius Benson
4. Jai Bhagat
5. Dan Biderman
6. Daniel Birman
7. Niccolò Bonacchi
8. Sebastian A Bruijns
9. Kelly Buchanan
10. Robert AA Campbell
11. Matteo Carandini
12. Gaëlle A Chapuis
13. Anne K Churchland
14. M Felicia Davatolhagh
15. Hyun Dong Lee
16. Mayo Faulkner
17. Berk Gerçek
18. Fei Hu
19. Julia Huntenburg
20. Cole Hurwitz
21. Anup Khanal
22. Christopher Krasniak
23. Christopher Langfield
24. Petrina Lau
25. Nancy Mackenzie
26. Guido T Meijer
27. Nathaniel J Miska
28. Zeinab Mohammadi
29. Jean-Paul Noel
30. Liam Paninski
31. Alejandro Pan-Vazquez
32. Cyrille Rossant
33. Noam Roth
34. Michael Schartner
35. Karolina Socha
36. Nicholas A Steinmetz
37. Karel Svoboda
38. Marsa Taheri
39. Anne E Urai
40. Shuqi Wang
41. Miles Wells
42. Steven J West
43. Matthew R Whiteway
44. Olivier Winter
45. Ilana B Witten
46. Yizi Zhang

• Curated by eLife

  eLife Assessment

  This paper represents an important contribution to the field. Summarizing results from neural recording experiments in mice across ten labs, the work provides compelling evidence that basic electrophysiology features, single-neuron functional properties, and population-level decoding are fairly reproducible across labs with proper preprocessing. The results and suggestions regarding preprocessing and quality metrics may be of significant interest to investigators carrying out such experiments in their own labs.

Reviewed by eLife

Sequence action representations contextualize during early skill learning

1. Debadatta Dash
2. Fumiaki Iwane
3. William Hayward
4. Roberto Salamanca-Giron
5. Marlene Bonstrup
6. Ethan R. Buch
7. Leonardo G. Cohen

• Curated by eLife

  eLife Assessment

  This valuable study investigates how the neural representation of individual finger movements changes during the early period of sequence learning. By combining a new method for extracting features from human magnetoencephalography data and decoding analyses, the authors provide incomplete evidence of an early, swift change in the brain regions correlated with sequence learning, including a set of previously unreported frontal cortical regions. The addition of more control analyses to rule out that head movement artefacts influence the findings, and to further explain the proposal of offline contextualization during short rest periods as the basis for improvement performance would strengthen the manuscript.

Reviewed by eLife

Serotonin modulates infraslow oscillation in the dentate gyrus during non-REM sleep

1. Gergely F Turi
2. Sasa Teng
3. Xinyue Chen
4. Emily CY Lim
5. Carla Dias
6. Ruining Hu
7. Ruizhi Wang
8. Fenghua Zhen
9. Yueqing Peng

• Curated by eLife

  eLife Assessment

  This important study shows that a very slow (infraslow) oscillation occurs in voltage recordings from the dentate gyrus of the adult mouse. The authors suggest that it is related to sleep stage and serotonin acting at one type of serotonin receptor in the dentate gyrus. The results are significant because they suggest new insight into how a slow oscillation affects memory through serotonin receptors in the dentate gyrus. Convincing data are provided to support the claims.

Reviewed by eLife

A toolbox for ablating excitatory and inhibitory synapses

1. Aida Bareghamyan
2. Changfeng Deng
3. Sarah Daoudi
4. Shubash C Yadav
5. Xiaocen Lu
6. Wei Zhang
7. Robert E Campbell
8. Richard H Kramer
9. David M Chenoweth
10. Don B Arnold

• Curated by eLife

  eLife Assessment

  This compelling study introduces a set of novel genetically encoded tools for the selective and reversible ablation of excitatory and inhibitory synapses. These new tools enable selective and efficient ablation of excitatory synapses, and photoactivatable and chemically inducible methods for inhibitory synapse ablation in specific cell types, providing valuable methods for disrupting neural circuits. This approach holds broad potential for investigating the roles of specific synaptic input onto genetically determined cells.

Reviewed by eLife

Inference technique for the synaptic conductances in rhythmically active networks and application to respiratory central pattern generation circuits

1. Yaroslav I Molkov
2. Anke Borgmann
3. Hidehiko Koizumi
4. Noriyuki Hama
5. Ruli Zhang
6. Jeffrey C Smith

• Curated by eLife

  eLife Assessment

  The paper describes a novel approach for inferring features of synaptic networks from recordings of individual cells within the network. The paper will be a valuable contribution to those studying central pattern generators, including those involved in respiration. However, the theoretical approach to drawing inferences regarding the underlying synaptic currents is incomplete as it relies on unsupported simplifying assumptions.

Reviewed by eLife

Altered visual cortex excitatory/inhibitory ratio following transient congenital visual deprivation in humans

1. Rashi Pant
2. Kabilan Pitchaimuthu
3. José Ossandón
4. Idris Shareef
5. Sunitha Lingareddy
6. Jürgen Finsterbusch
7. Ramesh Kekunnaya
8. Brigitte Röder

• Curated by eLife

  eLife Assessment

  This neuroimaging and electrophysiology study in a small cohort of congenital cataract patients with sight recovery aims to characterize the effects of early visual deprivation on excitatory and inhibitory balance in visual cortex. While contrasting sight-recovery with visually intact controls suggested the existence of persistent alterations in Glx/GABA ratio and aperiodic EEG signals, it provided incomplete evidence supporting claims about the effects of early deprivation itself. The reported data were considered valuable, given the rare study population. However, methodological limitations will likely restrict usefulness to scientists working in this particular subfield.

Reviewed by eLife

Convolutional networks can model the functional modulation of the MEG responses associated with feed-forward processes during visual word recognition

1. Marijn van Vliet
2. Oona Rinkinen
3. Takao Shimizu
4. Anni-Mari Niskanen
5. Barry Devereux
6. Riitta Salmelin

• Curated by eLife

  eLife Assessment

  van Vliet and colleagues show a useful correlation between internal states of a convolutional neural network (CNN) trained on visual word stimuli with three specific components of evoked MEG potentials during reading in humans. The findings are solid, though quantitative evidence that model can produce any of the phenomena that the human visual system is known to have (e.g., feedback connections, sensitivity to word frequency), or that it has comparable performance to human behaviour (i.e., similar task accuracy with a comparable pattern of mistakes) would make the conclusions much stronger.

Reviewed by eLife