Nonsynaptic encoding of behavior by neuropeptides
A basic tenet of neuroscience is that animal behavior is generated by neural circuits that operate through synaptic transmission. On top of this synaptic ‘chassis’ of nervous systems, neuropeptides and hormones have traditionally been considered as slow neuromodulatory signals that fine-tune synapti...
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| Main Authors: | , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
23 October 2024
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| In: |
Current Opinion in Behavioral Sciences
Year: 2024, Volume: 60, Pages: 1-13 |
| ISSN: | 2352-1554 |
| DOI: | 10.1016/j.cobeha.2024.101456 |
| Online Access: | Verlag, kostenfrei, Volltext: https://doi.org/10.1016/j.cobeha.2024.101456 Verlag, kostenfrei, Volltext: https://www.sciencedirect.com/science/article/pii/S2352154624001074 
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| Author Notes: | Gáspár Jékely and Rafael Yuste |
| Summary: | A basic tenet of neuroscience is that animal behavior is generated by neural circuits that operate through synaptic transmission. On top of this synaptic ‘chassis’ of nervous systems, neuropeptides and hormones have traditionally been considered as slow neuromodulatory signals that fine-tune synaptic circuits. However, neuropeptides can generate many behaviors, including quite complex ones, from cnidarians to humans. Moreover, neuropeptide actions span larger temporal scales than fast synaptic transmission and are thus better matched to behavioral time courses than synaptic circuits. Furthermore, in some metazoans, the effects of neuropeptides are independent of synaptic connectivity, and in many species, the systemic application of neuropeptides can trigger selective behaviors. Based on this, we argue that nonsynaptic neuropeptide signaling via chemical networks - forming a ‘chemical’ connectome - represents the ancestral mechanism to encode behavioral sequences, whereas synaptic networks co-evolved as a specialization complementing chemical networks in the control of behaviors and computational functions. |
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| Item Description: | Gesehen am 10.04.2025 |
| Physical Description: | Online Resource |
| ISSN: | 2352-1554 |
| DOI: | 10.1016/j.cobeha.2024.101456 |