New light on cortical neuropeptides and synaptic network plasticity
Open accessAbstract
Neuropeptides, members of a large and evolutionarily ancient family of proteinaceous cell-cell signaling molecules, are widely recognized as extremely potent regulators of brain function and behavior. At the cellular level, neuropeptides are known to act mainly via modulation of ion channel and synapse function, but functional impacts emerging at the level of complex cortical synaptic networks have resisted mechanistic analysis. New findings from single-cell RNA-seq transcriptomics now illuminate intricate patterns of cortical neuropeptide signaling gene expression and new tools now offer powerful molecular access to cortical neuropeptide signaling. Here we highlight some of these new findings and tools, focusing especially on prospects for experimental and theoretical exploration of peptidergic and synaptic networks interactions underlying cortical function and plasticity.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Neuropeptides are major agents for intercellular communications in the brain.
“Neuropeptides are also major agents for intercellular communications in the brain58,59.”
From A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain (2023) · cites this paper as [58]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 97 · Cited by 26
Research works printed but not linked: 5
- Meriney SD, Fanselow EE: Ch. 19 Neuropeptide transmitters. In Synaptic Transmission. Edited by Meriney SD, Fanselow EE. Academic Press; 2019:421-434.
- Huh D, Sejnowski TJ: Gradient descent for spiking neural networks. Advances in Neural Information Processing Systems. 2018:1433-1443.
- Bellec G, Scherr F, Subramoney A, Hajek E, Salaj D, Legenstein R, Maass W: A solution to the learning dilemma for recurrent networks of spiking neurons. bioRxiv 2019:738385.
- Miconi T, Rawal A, Clune J, Stanley KO: Backpropamine: training self-modifying neural networks with differentiable neuromodulated plasticity. 7th International Conference on Learning Representations, {ICLR} 2019; New Orleans, LA, USA, May 6-9, 2019: 2019. Edited by. This machine learning paper demonstrates improvements in a bench- mark language modeling task by including neuromodulatory effects (dopamine) in non-spiking artificial neural networks. More generally, the authors argue that the concept of lifetime meta-learning ('learning to learn') can significantly improve the field of machine learning.
- Bellec G, Salaj D, Subramoney A, Legenstein R, Maass W: Long short-term memory and learning-to-learn in networks of spiking neurons. Advances in Neural Information Processing Systems. 2018:787-797:. Edited by.
- Authors
- Smith, S. J., Hawrylycz, M., Rossier, J., & Sümbül, U.
- Affiliations
- Allen Institute for Brain Science (US)
- Sorbonne Université (FR)
- Corresponding author
- Smith, Stephen J
- Venue
- Current Opinion in Neurobiology
- Publisher
- Elsevier BV
- Published
- 2020-08
- Volume
- 63
- Pages
- 176-188
- ISSN
- 0959-4388 (ISSN-L)
- OpenAlex
- W3017357251
- Cited by
- 26
- References
- 97
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 2 · 2023: 9 · 2022: 6 · 2021: 4
- FWCI
- 0.65
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Current Opinion in Neurobiology (publishedVersion, cc-by)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- Allen Institute founder
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuropeptides and Animal Physiology
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Social Sciences › Psychology › Social Psychology › Neuroendocrine regulation and behavior
- Keywords
- neuropeptides, synaptic plasticity, peptidergic signaling, single-cell RNA sequencing, neuropeptide gene expression, ion channel modulation, synaptic function, cortical networks
- MeSH terms
- Neuronal Plasticity, Neuropeptides, Synapses, Signal Transduction
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
