Neuroscience

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. Reviewers have provided additional suggestions for improving the readability of the manuscript, as well as discussing previous results on adapting coding as well as those aspects of experimental data that are not fully explained by the present theory.

Reviewed by eLife

Type-I nNOS neurons orchestrate cortical neural activity and vasomotion

1. Kevin Turner
2. Dakota Brockway
3. Md Shakhawat Hossain
4. Keith Griffith
5. Denver Greenawalt
6. Qingguang Zhang
7. Kyle Gheres
8. Nicole Crowley
9. Patrick J Drew

• Curated by eLife

  eLife Assessment

  This important study provides solid evidence for new insights into the role of Type-1 nNOS interneurons in driving neuronal network activity and controlling vascular network dynamics in awake, head-fixed mice. The authors use an original strategy based on the ablation of Type-1 nNOS interneurons with local injection of saporin conjugated to a substance P analogue into the somatosensory cortex. They show that ablation of type I nNOS neurons has surprisingly little effect on neurovascular coupling, although it alters neural activity and vascular dynamics.

Reviewed by eLife

Complex opioid-driven modulation of glutamatergic and cholinergic neurotransmission in a GABAergic brain nucleus associated with emotion, reward, and addiction

1. Ramesh Chittajallu
2. Anna Vlachos
3. Adam P Caccavano
4. Xiaoqing Yuan
5. Steven Hunt
6. Daniel Abebe
7. Edra London
8. Kenneth A Pelkey
9. Chris J McBain

• Curated by eLife

  eLife Assessment

  This study presents important information about the role of mu opioid receptors in neurotransmission between the medial habenula and the interpeduncular nucleus. The authors provide convincing evidence that mu opioid receptor activation has differential effects on transmission from substance P neurons and cholinergic neurons, and that blockade of potassium channels can unmask a nicotinic cholinergic synaptic response. This work will be of high interest to those studying this brain region, and potentially to the larger neuroscience community studying motivated behavior.

Reviewed by eLife

Differential destinations, dynamics, and functions of high- and low-order features in the feedback signal during object processing

1. Wenhao Hou
2. Sheng He
3. Jiedong Zhang

• Curated by eLife

  eLife Assessment

  This study reports important findings about the nature of feedback to primary visual cortex (V1) during object recognition. The state-of-the-art functional MRI evidence for the main claims is solid, and the combination of high-resolution fMRI with MEG yields significant insight into neural mechanisms. The findings presented here are relevant to a number of scientific fields such as object recognition, categorisation and predictive coding.

Reviewed by eLife

Oxytocin neurons signal state-dependent transitions from rest to thermogenesis and behavioral arousal in social and non-social settings

1. Morgane Vandendoren
2. Jason G Landen
3. Joseph F Rogers
4. Samantha Killmer
5. Baizar Alamiri
6. Celeste Pohlman
7. Glenn J Tattersall
8. Nicole L Bedford
9. Adam C Nelson

• Curated by eLife

  eLife Assessment

  This study presents a valuable finding regarding the role of oxytocin neurons in thermogenesis and behavioral thermoregulation. The use of numerous converging methods, including behavior, fiber photometry, optogenetics, thermal recordings, metabolic analyses, and more, produces a multi-dimensional dataset delivering findings that provide solid support for the conclusions. Conclusions would be strengthened with validation of the approaches, inclusion of a loss of function experiment, and further investigation of the social nature of the behavior. The maternal findings are, at present, somewhat disconnected from the conclusions. The findings are novel and open new doors for understanding the role of the PVT and oxytocin in thermoregulation work; the work will be of strong interest to the thermoregulation, social behavior, and oxytocin signaling communities.

Reviewed by eLife

Deep Neural Networks to Register and Annotate Cells in Moving and Deforming Nervous Systems

1. Adam A Atanas
2. Alicia Kun-Yang Lu
3. Brian Goodell
4. Jungsoo Kim
5. Saba Baskoylu
6. Di Kang
7. Talya S Kramer
8. Eric Bueno
9. Flossie K Wan
10. Karen L Cunningham
11. Brandon Weissbourd
12. Steven W Flavell

• Curated by eLife

  eLife Assessment

  Whole-brain imaging of neuronal activity in freely behaving animals holds great promise for neuroscience, but numerous technical challenges limit its use. In this important study, the authors describe a new set of deep learning-based tools to track and identify the activity of head neurons in freely moving nematodes (C. elegans) and jellyfish (Clytia hemisphaerica). While the tools convincingly enable high tracking speed and accuracy in the settings in which the authors have evaluated them, the claim that these tools should be easily generalizable to a wide variety of datasets is incompletely supported.

Reviewed by eLife

Adaptive behavior is guided by integrated representations of controlled and non-controlled information

1. Bingfang Huang
2. Harrison Ritz
3. Jiefeng Jiang

• Curated by eLife

  eLife Assessment

  This useful study uses creative scalp EEG decoding methods to attempt to demonstrate that two forms of learned associations in a Stroop task are dissociable, despite sharing similar temporal dynamics. However, the evidence supporting the conclusions is incomplete due to concerns with the experimental design and methodology. This paper would be of interest to researchers studying cognitive control and adaptive behavior, if the concerns raised in the reviews can be addressed satisfactorily.

Reviewed by eLife

Heterochronic transcription factor expression drives cone-dominant retina development in 13-lined ground squirrels

1. Kurt Weir
2. Pin Lyu
3. Sangeetha Kandoi
4. Roujin An
5. Nicole Pannullo
6. Isabella Palazzo
7. Jared A Tangeman
8. Jun Shi
9. Steven H DeVries
10. Dana K Merriman
11. Jiang Qian
12. Seth Blackshaw

• Curated by eLife

  eLife Assessment

  This important study investigates why the 13-lined ground squirrel (13LGS) retina is unusually rich in cone photoreceptors, the cells responsible for color and daylight vision. The authors perform deep transcriptomic and epigenetic comparisons between the mouse and the 13-lined ground squirrel (13LGS) to provide convincing evidence that identifies mechanisms that drive rod vs cone-rich retina development. Overall, this key question is investigated using an impressive collection of new data, cross-species analysis, and subsequent in vivo experiments. However, the functional analysis showing the sufficiency and necessity of Zic3 and Mef2C remains incomplete, and further analyses are needed to support the claim that these enhancers are newly evolved in 13LGS.

Reviewed by eLife

Two time scales of adaptation in human learning rates

1. Jonas Simoens
2. Senne Braem
3. Pieter Verbeke
4. Haopeng Chen
5. Stefania Mattioni
6. Mengqiao Chai
7. Nicolas W Schuck
8. Tom Verguts

• Curated by eLife

  eLife Assessment

  This study makes a valuable contribution by separating two timescales of adaptation: rapid, within block reductions in learning rate, and slower, location specific, meta-learned adjustments. Behavioural data and computational modeling converge to support both processes. The evidence is solid with neuroimaging results suggesting that meta-learned learning rates are encoded in the orbitofrontal cortex, while prediction errors are represented in a distributed network including the ventral striatum and are modulated by expected error magnitude, though the specificity of these effects requires further contextualization. The manuscript is timely and clearly written; its main limitation is the weak linkage between neural signals and behavior, leaving uncertainty over whether the reported signals play a mechanistic role in learning.

Reviewed by eLife

Combinatorial protein barcodes enable self-correcting neuron tracing with nanoscale molecular context

1. Sung Yun Park
2. Arlo Sheridan
3. Bobae An
4. Erin Jarvis
5. Julia Lyudchik
6. William Patton
7. Jun Y. Axup
8. Stephanie W. Chan
9. Hugo G.J. Damstra
10. Daniel Leible
11. Kylie S. Leung
12. Clarence A. Magno
13. Aashir Meeran
14. Julia M. Michalska
15. Franz Rieger
16. Claire Wang
17. Michelle Wu
18. George M. Church
19. Jan Funke
20. Todd Huffman
21. Kathleen G.C. Leeper
22. Sven Truckenbrodt
23. Johan Winnubst
24. Joergen M.R. Kornfeld
25. Edward S. Boyden
26. Samuel G. Rodriques
27. Andrew C. Payne

Reviewed by Arcadia Science