Neuroscience

Molecular and spatial transcriptomic classification of midbrain dopamine neurons and their alterations in a LRRK2G2019S model of Parkinson’s disease

1. Zachary Gaertner
2. Cameron Oram
3. Amanda Schneeweis
4. Elan Schonfeld
5. Cyril Bolduc
6. Chuyu Chen
7. Daniel Dombeck
8. Loukia Parisiadou
9. Jean-Francois Poulin
10. Rajeshwar Awatramani

• Curated by eLife

  eLife Assessment

  This important study combines single nucleus transcriptional profiling with spatial transcriptomics to identify and map heterogeneity among dopamine neurons in the mouse ventral midbrain. The compelling results separate dopamine neurons into three broad families that have unique (yet overlapping) spatial distribution within the ventral tegmental area and substantia nigra, and also identify population-specific changes in a LRRK2 mouse model of Parkinson's Disease. The creation of a public-facing app where the snRNA-seq data can be investigated by anyone is a major strength.

Reviewed by eLife

Layer 6 corticocortical neurons are a major route for intra- and interhemispheric feedback

1. Simon Weiler
2. Manuel Teichert
3. Troy W Margrie

• Curated by eLife

  eLife Assessment

  This important study compares the cortical projections to primary motor and sensory areas originating from the ipsilateral and contralateral hemispheres. Results show that, while there is substantial symmetry between the two hemispheres regarding the areas sending projections to these primary cortical areas, contra-hemispheric projections had more inputs from layer 6 neurons than ipsi-projecting ones. The evidence is compelling and the conclusions are supported by rigorous analyses.

Reviewed by eLife

The asymmetric transfers of visual perceptual learning determined by the stability of geometrical invariants

1. Yan Yang
2. Yan Zhuo
3. Zhentao Zuo
4. Tiangang Zhuo
5. Lin Chen

• Curated by eLife

  eLife Assessment

  This important and unique study proposes a framework to understand and predict generalization in visual perceptual learning in humans based on form invariants. Using behavioral experiments in humans and by training deep networks, the authors offer evidence that the presence of stable invariants in a task leads to faster learning. However, this interpretation is promising but counter-intuitive and incomplete, since there could be possible other confounds such as differing attentional demands that lead to differing patterns of generalization. It can be strengthened through additional experiments and by rejecting alternate explanations.

Reviewed by eLife

Efficient coding explains neural response homeostasis and stimulus-specific adaptation

1. Edward James Young
2. Yashar Ahmadian

• Curated by eLife

  eLife Assessment

  This work derives a valuable general theory unifying theories of efficient information transmission in the brain with population homeostasis. The general theory provides an explanation for firing rate homeostasis at the level of neural clusters with firing rate heterogeneity within clusters. Applying this theory to the primary visual cortex, the authors present solid evidence that accounts for stimulus-specific and neuron-specific adaptation.

Reviewed by eLife

Modulation of habenula axon terminals supports action-outcome associations in larval zebrafish

1. Emanuele Paoli
2. Virginia Palieri
3. Amey Shenoy
4. Ruben Portugues

Reviewed by preLights

Distinct representational properties of cues and contexts shape fear learning and extinction

1. Antoine Bouyeure
2. Daniel Pacheco
3. Marie-Christin Fellner
4. George Jacob
5. Malte Kobelt
6. Jonas Rose
7. Nikolai Axmacher

• Curated by eLife

  eLife Assessment

  This is an important study with solid evidence that multi-voxel fMRI activity patterns for threat-conditioned stimuli are altered by learning CS-US contingencies. The analyses are dense but mostly rigorous. The protocol is quite nuanced and complex, but the authors have done a fair job of explaining and presenting the results, and the results could be further improved by adjustment for multiple comparisons. The readability could be improved for an audience without highly-specialised knowledge of the field and the fMRI analytical approach.

Reviewed by eLife

Preclinical systematic review of CCR5 antagonists as cerebroprotective and stroke recovery enhancing agents

1. Ayni Sharif
2. Matthew S Jeffers
3. Dean A Fergusson
4. Raj Bapuji
5. Stuart G Nicholls
6. John Humphrey
7. Warren Johnston
8. Ed Mitchell
9. Mary-Ann Speirs
10. Laura Stronghill
11. Michele Vuckovic
12. Susan Wulf
13. Risa Shorr
14. Dar Dowlatshahi
15. Dale Corbett
16. Manoj M Lalu

• Curated by eLife

  eLife Assessment

  This study is important, and the findings add substantially to the evidence base regarding CCR5 antagonist drugs for neuroprotection and stroke management. The authors adhered to the expected systematic review and meta-analysis standards, and the presented evidence is convincing.

Reviewed by eLife

Insights into the foraging Gene’s Influence on Mating Investments of Male Drosophila

1. Wengjing Li
2. Yongwen Huang
3. Woo Jae Kim

Reviewed by Review Commons

Cell type-specific driver lines targeting the Drosophila central complex and their use to investigate neuropeptide expression and sleep regulation

1. Tanya Wolff
2. Mark Eddison
3. Nan Chen
4. Aljoscha Nern
5. Preeti Sundaramurthi
6. Divya Sitaraman
7. Gerald M Rubin

• Curated by eLife

  eLife Assessment

  This is a fundamental body of work reporting anatomical, molecular, and functional mapping of the central complex in Drosophila. There were a few concerns of a minor nature, and all were addressed by the authors. The tools generated and the findings, which include characterization of neuromodulators used by different cells, will undoubtedly serve as a foundation for future studies of this brain region. The data are compelling and likely to have a major impact.

Reviewed by eLife

The neural correlates of novelty and variability in human decision-making under an active inference framework

1. Shuo Zhang
2. Yan Tian
3. Quanying Liu
4. Haiyan Wu

• Curated by eLife

  eLife Assessment

  This valuable study addresses a central question in systems neuroscience (validation of active inference models of exploration) using a combination of behaviour, neuroimaging, and modelling. The data provided offers solid evidence that humans do perceive, choose and learn in a manner consistent with the essential ingredients of active inference, and that quantities that correlate with relevant parameters of this active inference scheme are encoded in different regions of the brain.

Reviewed by eLife