A dendrite is a dendrite is a dendrite?: dendritic signal integration beyond the “antenna” model
Neurons in central nervous systems receive multiple synaptic inputs andtransform them into a largely standardized output to their target cells—the actionpotential. A simplified model posits that synaptic signals are integrated by linearsummation and passive propagation towards the axon initial segme...
Gespeichert in:
| Hauptverfasser: | , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
2025
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| In: |
Pflügers Archiv
Year: 2025, Jahrgang: 477, Pages: 9-16 |
| ISSN: | 1432-2013 |
| DOI: | 10.1007/s00424-024-03004-0 |
| Online-Zugang: | Verlag, kostenfrei, Volltext: https://doi.org/10.1007/s00424-024-03004-0
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| Verfasserangaben: | Moritz Stingl, Andreas Draguhn, Martin Both |
MARC
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| 245 | 1 | 2 | |a A dendrite is a dendrite is a dendrite? |b dendritic signal integration beyond the “antenna” model |c Moritz Stingl, Andreas Draguhn, Martin Both |
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| 520 | |a Neurons in central nervous systems receive multiple synaptic inputs andtransform them into a largely standardized output to their target cells—the actionpotential. A simplified model posits that synaptic signals are integrated by linearsummation and passive propagation towards the axon initial segment, where thethreshold for spike generation is either crossed or not. However, multiple lines ofresearch during past decades have shown that signal integration in individualneurons is much more complex, with important functional consequences at thecellular, network, and behavioral-cognitive level. The interplay between concomitantexcitatory and inhibitory postsynaptic potentials depends strongly on the relativetiming and localization of the respective synapses. In addition, dendrites containmultiple voltage-dependent conductances, which allow scaling of postsynapticpotentials, non-linear input processing, and compartmentalization of signals.Together, these features enable a rich variety of single-neuron computations,including non-linear operations and synaptic plasticity. Hence, we have to reviseover-simplified messages from textbooks and use simplified computational models likeintegrate-and-fire neurons with some caution. This concept article summarizes themost important mechanisms of dendritic integration and highlights some recentdevelopments in the field. | ||
| 650 | 4 | |a Action potential generation | |
| 650 | 4 | |a Axon and dendritic guidance | |
| 650 | 4 | |a Dendrimers | |
| 650 | 4 | |a Dendritic cells | |
| 650 | 4 | |a Dendritic excitability | |
| 650 | 4 | |a Dendritic integration | |
| 650 | 4 | |a Input-output relation | |
| 650 | 4 | |a Neuronal physiology | |
| 650 | 4 | |a Neurons | |
| 650 | 4 | |a Review | |
| 650 | 4 | |a Single-cell computations | |
| 650 | 4 | |a Synaptic Transmission | |
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