Neuroscience

A toolbox for genetic targeting of the claustrum

1. Joël Tuberosa
2. Madlaina Boillat
3. Julien Dal Col
4. Leonardo Marconi
5. Julien Codourey
6. Loris Mannino
7. Elena Georgiou
8. Marc Menoud
9. Alan Carleton
10. Ivan Rodriguez

• Curated by eLife

  eLife assessment

  This valuable research identifies Smim32 as a new genetic marker for the claustrum and generates transgenic mouse lines aimed at enhancing specificity when studying this brain region. However, the evidence supporting the increased specificity of this marker and its associated transgenic lines is inadequate, as Smim32's specificity to the claustrum is limited. Nevertheless, this work will be of interest to researchers studying the molecular organization of the claustrum.

Reviewed by eLife

Direct observation of the neural computations underlying a single decision

1. Natalie Steinemann
2. Gabriel M Stine
3. Eric Trautmann
4. Ariel Zylberberg
5. Daniel M Wolpert
6. Michael N Shadlen

• Curated by eLife

  eLife assessment

  This fundamental work quantifies the stochastic dynamics of neural population activity in the lateral intraparietal area (LIP) of the macaque monkey brain during single perceptual decisions. These single-trial dynamics have been subject to intense debate in neuroscience, and they have significant implications for modelling decision-making in various fields including neuroscience and psychology. Through a combination of state-of-the-art recordings from many LIP neurons and theory-driven data analyses, the authors provide convincing evidence for the notion that single-trial neural population dynamics in LIP encode the decision variable postulated by the drift-diffusion model of decision-making.

Reviewed by eLife

Sequential temporal anticipation characterized by neural power modulation and in recurrent neural networks

1. Xiangbin Teng
2. Ru-Yuan Zhang

• Curated by eLife

  eLife assessment

  This valuable study provides insights into how the brain learns to better detect a target by predicting when the target may appear. Overall, solid evidence is provided that the power fluctuations of alpha- and beta-band oscillations can reflect the predicted occurrence time of the target, but some conclusions, especially ones related to the neural-network model and temporal gain control account, need further consideration. The study highlights an advanced EEG analysis approach as well as a close combination of human EEG analysis and computational modeling using recurrent neural networks.

Reviewed by eLife

Sexually dimorphic role of diet and stress on behavior, energy metabolism, and the ventromedial hypothalamus

1. Sanutha Shetty
2. Samuel J. Duesman
3. Sanil Patel
4. Pacific Huyhn
5. Sanjana Shroff
6. Anika Das
7. Disha Chowhan
8. Robert Sebra
9. Kristin Beaumont
10. Cameron S. McAlpine
11. Prashant Rajbhandari
12. Abha K. Rajbhandari

Reviewed by preLights

Probing PAC1 receptor activation across species with an engineered sensor

1. Reto B Cola
2. Salome N Niethammer
3. Preethi Rajamannar
4. Andrea Gresch
5. Musadiq A Bhat
6. Kevin Assoumou
7. Elyse T Williams
8. Patrick Hauck
9. Nina Hartrampf
10. Dietmar Benke
11. Miriam Stoeber
12. Gil Levkowitz
13. Sarah Melzer
14. Tommaso Patriarchi

• Curated by eLife

  eLife assessment

  This fundamental paper reports a new biosensor to study G protein-coupled receptor activation by the pituitary adenylyl cyclase-activating polypeptide (PACAP) in cell culture, ex vivo (mouse brain slices), and in vivo (zebrafish, mouse). Convincing data are presented that show the new sensor works with high affinity in vitro, while requiring very high (non-physiological) concentrations of exogenous PACAP when applied to intact tissues. The sensor has not yet been used to detect endogenously released PACAP, raising questions about whether the sensor can be used for its intended purpose. While further work must be pursued to achieve broad in vivo applications under physiological conditions, the new tool will be of interest to cell biologists, especially those studying the large and significant GPCR family.

Reviewed by eLife

Combining array tomography with electron tomography provides insights into leakiness of the blood-brain barrier in mouse cortex

1. Georg Kislinger
2. Gunar Fabig
3. Antonia Wehn
4. Lucia Rodriguez
5. Hanyi Jiang
6. Cornelia Niemann
7. Andrey S Klymchenko
8. Nikolaus Plesnila
9. Thomas Misgeld
10. Thomas Müller-Reichert
11. Igor Khalin
12. Martina Schifferer

• Curated by eLife

  eLife assessment

  The present paper describes an important methodological development that combines light (confocal) microscopy with scanning and transmission EM and EM tomography. The method expands the level of structural detail accessible to large-volume EM studies and thus represents an approach to integrate analyses of cellular and sub-cellular structures in biological samples. The study, which provides a compelling proof-of-principle, will be of particular value to cell biologists interested in the in-depth interpretation of high-resolution ultrastructural information from sparsely distributed targets - at multiple scales and in diverse biological structures.

Reviewed by eLife

Sex-peptide targets distinct higher order processing neurons in the brain to induce the female post-mating response

1. Mohanakarthik P Nallasivan
2. Deepanshu ND Singh
3. Mohammed Syahir RS Saleh
4. Matthias Soller

• Curated by eLife

  eLife assessment

  This valuable study provides new insights into the neural circuits involved in post-mating responses in Drosophila females. It presents convincing evidence that the circuits for mating receptivity and egg-laying are distinct. A more thorough discussion regarding the integration of the new findings into the current understanding of post-mating behavior as well as clarification of some experimental details would further improve the manuscript.

Reviewed by eLife

Systematic annotation of a complete adult male Drosophila nerve cord connectome reveals principles of functional organisation

1. Elizabeth C Marin
2. Billy J Morris
3. Tomke Stürner
4. Andrew S Champion
5. Dominik Krzeminski
6. Griffin Badalamente
7. Marina Gkantia
8. Christopher R Dunne
9. Katharina Eichler
10. Shin-ya Takemura
11. Imaan FM Tamimi
12. Siqi Fang
13. Sung Soo Moon
14. Han SJ Cheong
15. Feng Li
16. Philipp Schlegel
17. Sebastian E Ahnert
18. Stuart Berg
19. Janelia FlyEM Project Team
20. Gwyneth M Card
21. Marta Costa
22. David Shepherd
23. Gregory SXE Jefferis

• Curated by eLife

  eLife assessment

  This fundamental study provides a near-comprehensive anatomical description and annotation of neurons in a male Drosophila ventral nerve cord, based on large-scale circuit reconstruction from electron microscopy. This connectome resource will be of substantial interest to neuroscientists interested in sensorimotor control, neural development, and analysis of brain connectivity. However, although the evidence is extensive and compelling, the presentation of results in this very large manuscript lacks clarity and concision.

Reviewed by eLife

Human adherent cortical organoids in a multiwell format

1. Mark van der Kroeg
2. Sakshi Bansal
3. Maurits Unkel
4. Hilde Smeenk
5. Steven A Kushner
6. Femke MS de Vrij

• Curated by eLife

  eLife assessment

  This paper describes an important advance in an in vitro neural culture system to generate mature, functional, diverse, and geometrically consistent cultures, in a 384-well format with defined dimensions and the absence of the necrotic core, which persists for up to 300 days. The well-based format and conserved geometry make it a promising tool for arrayed screening studies. Some of the evidence is incomplete and could benefit from a more direct head-to-head comparison with more standard culture methods and standardization of cell seeding density as well as further data on reproducibility in each well and for each cell line.

Reviewed by eLife

Revealing unexpected complex encoding but simple decoding mechanisms in motor cortex via separating behaviorally relevant neural signals

1. Yangang Li
2. Xinyun Zhu
3. Yu Qi
4. Yueming Wang

• Curated by eLife

  eLife assessment

  This study presents a useful method for the extraction of behaviour-related activity from neural population recordings based on a specific deep learning architecture, a variational autoencoder. Although the authors performed thorough benchmarking of their method in the context of decoding behavioural variables, the evidence supporting claims about encoding is incomplete as the results may stem, in part, from the properties of the method itself.

Reviewed by eLife