Neuroscience

Transcriptomics-informed large-scale cortical model captures topography of pharmacological neuroimaging effects of LSD

1. Joshua B Burt
2. Katrin H Preller
3. Murat Demirtas
4. Jie Lisa Ji
5. John H Krystal
6. Franz X Vollenweider
7. Alan Anticevic
8. John D Murray

• Curated by eLife

  Evaluation Summary:

  This paper will be of interest to scientists working on computational modelling of neuroimaging data, and on the neural effects of psychedelic drugs and other pharmacological interventions. The study is well-motivated. The statistical and data analytic methodologies are rigorous and advanced. The with conclusions are well-supported by the presented data. The modelling methodology includes technical innovations that are potentially of broad utility and importance.

  (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 and Reviewer #2 agreed to share their names with the authors.)

Reviewed by eLife

A transient postnatal quiescent period precedes emergence of mature cortical dynamics

1. Soledad Domínguez
2. Liang Ma
3. Han Yu
4. Gabrielle Pouchelon
5. Christian Mayer
6. George D Spyropoulos
7. Claudia Cea
8. György Buzsáki
9. Gordon Fishell
10. Dion Khodagholy
11. Jennifer N Gelinas

• Curated by eLife

  Evaluation Summary:

  The authors use dense electrode recordings in young mice and EEG recordings in human infants to quantitatively describe the transition from immature patterns of brain activity in sleep to more mature patterns. Interestingly, they find an intervening period when overall activity declines in both species. This study is interesting because it enriches our relatively impoverished view of how mature activity patterns emerge during development. However, reviewers expressed concerns that further work was need to rule out potential artifacts of the surgical and recording techniques used in the animal experiments.

  (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 and Reviewer #3 agreed to share their names with the authors.)

Reviewed by eLife

Closed-loop auditory stimulation method to modulate sleep slow waves and motor learning performance in rats

1. Carlos G Moreira
2. Christian R Baumann
3. Maurizio Scandella
4. Sergio I Nemirovsky
5. Sven Leach
6. Reto Huber
7. Daniela Noain

• Curated by eLife

  Evaluation Summary:

  This manuscript describes their phase-targeted closed-loop auditory stimulation protocol to alter slow wave oscillations in rodents. This manuscript provides a set of proof-of-concept data for a rodent model of closed-loop auditory stimulation during sleep as a method for augmenting NREM sleep thalamocortical oscillations and its behavioral effect on a motor task. The strongest contribution of this study to the field is that it provides a technical basis for future studies to be carried out which actually explore the neurobiological underpinnings of CLAS in detail. Applying this tool to rodent research in future studies may allow for bridging some of the putative mechanisms underlying memory consolidation (e.g., replay during NREM sleep) and behavioral changes observed with sleep (e.g., improved hippocampus-dependent memory). It's also nice to have a non-invasive way to manipulate sleep, particularly to translate rodent research to clinical work.

  (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)

Reviewed by eLife

A unified platform to manage, share, and archive morphological and functional data in insect neuroscience

1. Stanley Heinze
2. Basil el Jundi
3. Bente G Berg
4. Uwe Homberg
5. Randolf Menzel
6. Keram Pfeiffer
7. Ronja Hensgen
8. Frederick Zittrell
9. Marie Dacke
10. Eric Warrant
11. Gerit Pfuhl
12. Jürgen Rybak
13. Kevin Tedore

• Curated by eLife

  Evaluation Summary:

  This manuscript will be of interest to insect neuroscientists and broadly to the neuroanatomy community. It presents a new web resource that collects and displays neuron, brain region and species data in user-friendly ways. If taken up by the community, it has the potential to become an important data hub.

  (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 agreed to share their name with the authors.)

Reviewed by eLife, preLights

Non-neuronal expression of SARS-CoV-2 entry genes in the olfactory system suggests mechanisms underlying COVID-19-associated anosmia

1. David H. Brann
2. Tatsuya Tsukahara
3. Caleb Weinreb
4. Marcela Lipovsek
5. Koen Van den Berge
6. Boying Gong
7. Rebecca Chance
8. Iain C. Macaulay
9. Hsin-Jung Chou
10. Russell B. Fletcher
11. Diya Das
12. Kelly Street
13. Hector Roux de Bezieux
14. Yoon-Gi Choi
15. Davide Risso
16. Sandrine Dudoit
17. Elizabeth Purdom
18. Jonathan Mill
19. Ralph Abi Hachem
20. Hiroaki Matsunami
21. Darren W. Logan
22. Bradley J. Goldstein
23. Matthew S. Grubb
24. John Ngai
25. Sandeep Robert Datta

Reviewed by ScreenIT, preLights

An oscillating computational model can track pseudo-rhythmic speech by using linguistic predictions

1. Sanne ten Oever
2. Andrea E Martin

• Curated by eLife

  Evaluation Summary:

  The topic is highly interesting and provides new insights to the ongoing debate about the role of oscillations and predictability in speech recognition. The manuscript is of broad interest to readers in the field of speech recognition and neuronal oscillations. Particularly, the authors provide a computational model which additionally to feedforward acoustic input incorporates linguistic predictions as feedback, allowing a fixed oscillator to process non-isochronous speech. The model is tested extensively by applying it to a linguistic corpus, EEG and behavioral data. It explains variations in speech duration based on linguistic predictability, and recently reported phase-dependency of speech perception, supporting the authors claims. The reviewers agreed that this study provides new insights in the current debate about the role of neural oscillations and top-down predictability in speech recognition, and that it represents an important contribution to the field of language neurobiology. Although they thought that the results support the authors' conclusions, the reviewers each raised a number of questions about the modelling and stated that greater clarity is needed in describing this.

  (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1, Reviewer #2 and Reviewer #3 agreed to share their names with the authors.)

Reviewed by eLife

Slow oscillation–spindle coupling strength predicts real-life gross-motor learning in adolescents and adults

1. Michael A Hahn
2. Kathrin Bothe
3. Dominik Heib
4. Manuel Schabus
5. Randolph F Helfrich
6. Kerstin Hoedlmoser

Reviewed by eLife

Decoding the brain state-dependent relationship between pupil dynamics and resting state fMRI signal fluctuation

1. Filip Sobczak
2. Patricia Pais-Roldán
3. Kengo Takahashi
4. Xin Yu

• Curated by eLife

  Evaluation Summary:

  Pupil diameter is used as an index of the brain's arousal system, and has traditionally thought to be a non-invasive index of specific neuromodulatory activity. It is therefore been heavily used as a measure in neuroscience. More recent data suggests a more complex picture whereby a pupil dilation might track cocktail of different neuromodulators. This paper provides firm data supporting this view, and introduces the new view that the make-up of this cocktail changes significantly over time. Pupil dynamics are linked with different neuromodulatory centers over different intervals of time. This is clearly important data across a broad range of human and animal systems neuroscience.

  (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 agreed to share their name with the authors.)

Reviewed by eLife

Motor planning under uncertainty

1. Laith Alhussein
2. Maurice A Smith

• Curated by eLife

  Evaluation Summary:

  This study addresses an important debate in the field of motor control: Can motor commands generated under uncertain conditions be better explained as an average of different candidate motor programs, or by a single motor plan that minimizes the expected costs? The paper provides evidence for the latter hypothesis. Previous studies have provided clear evidence against the motor averaging hypothesis, however the present study provides the most elegant and conclusive examination of these two ideas to date. While some of the interpretation, especially of Experiment 2, requires more nuanced consideration, overall we thought the evidence presented supported the key conclusion.

  (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 agreed to share their name with the authors.)

Reviewed by eLife

Multiphasic value biases in fast-paced decisions

1. Elaine A Corbett
2. L Alexandra Martinez-Rodriguez
3. Cian Judd
4. Redmond G O'Connell
5. Simon P Kelly

• Curated by eLife

  Evaluation Summary:

  Corbett and colleagues developed a novel experimental framework to account for value biases in fast-paced decisions. For this purpose, they developed detailed computational models of how value biases can alter the decision-making process and used EEG data to constrain the estimation of model parameters and their comparison. In contrast to existing accounts which describe value biases using a single bias mechanism, they found that a more complex and dynamic pattern of mechanisms best explains the EEG and behavioral data.

  (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 agreed to share their name with the authors.)

Reviewed by eLife