Editing Dendrite (section)

==Electrical properties==
The structure and branching of a neuron's dendrites, as well as the availability and variation of [[voltage-gated ion channel|voltage-gated ion conductance]], strongly influences how the neuron integrates the input from other neurons. This integration is both temporal, involving the summation of stimuli that arrive in rapid succession, as well as spatial, entailing the aggregation of excitatory and inhibitory inputs from separate branches.<ref>{{cite book| vauthors = Kandel ER |title=Principles of neural science.|date=2003|publisher=McGraw Hill|location=Cambridge|isbn=0-8385-7701-6|edition=4th|url-access=registration|url=https://archive.org/details/isbn_9780838577011}}</ref>

Dendrites were once thought to merely convey electrical stimulation passively. This passive transmission means that [[voltage]] changes measured at the cell body are the result of activation of distal synapses propagating the electric signal towards the cell body without the aid of [[voltage-gated ion channels]]. [[Cable theory|Passive cable theory]] describes how voltage changes at a particular location on a dendrite transmit this electrical signal through a system of converging dendrite segments of different diameters, lengths, and electrical properties. Based on passive cable theory one can track how changes in a neuron's dendritic morphology impact the membrane voltage at the cell body, and thus how variation in dendrite architectures affects the overall output characteristics of the neuron. Dendrite radius has notable effects on resistance to electrical current, which in turn affects conduction time and speed. Dendrite branching optimizes of energy efficiency while maintaining functional connectivity by minimizing power and emphasizing effective signal transmission, supporting their roles in signal integration over longer times. This behavior seen in dendrites differs from that in axons, which give more priority to conduction time (and speed). Such tradeoffs influence overall neuronal structures, leading to a scaling relationship between conduction time and body size. <ref name="Koch 1999">{{cite book| vauthors = Koch C |title=Biophysics of computation : information processing in single neurons|date=1999|publisher=Oxford Univ. Press|location=New York [u.a.]|isbn=0-19-510491-9}}</ref><ref name="Häusser 2008">{{cite book| vauthors = Häusser M |title=Dendrites|date=2008|publisher=Oxford University Press|location=Oxford|isbn=978-0-19-856656-4|edition=2nd}}</ref><ref>{{Cite journal |last1=Desai-Chowdhry |first1=Paheli |last2=Brummer |first2=Alexander B. |last3=Savage |first3=Van M. |date=2022-12-02 |title=How axon and dendrite branching are guided by time, energy, and spatial constraints |journal=Scientific Reports |language=en |volume=12 |issue=1 |pages=20810 |doi=10.1038/s41598-022-24813-2 |issn=2045-2322 |pmc=9718790 |pmid=36460669|bibcode=2022NatSR..1220810D }}</ref>

Action potentials initiated at the [[axon hillock]] propagate back into the dendritic arbor. These [[Neural backpropagation|back-propagating]] action potentials depolarize the dendritic membrane and provide a crucial signal for synapse modulation and [[long-term potentiation]]. Back-propagation is not completely passive, but modulated by the presence of dendritic [[Voltage-gated potassium channel|voltage-gated potassium channels]]. Furthermore, in certain types of neurons, a train of back-propagating action potentials can induce a calcium action potential (a [[dendritic spike]]) at dendritic initiation zones.<ref>{{Cite journal |last1=Gidon |first1=Albert |last2=Zolnik |first2=Timothy Adam |last3=Fidzinski |first3=Pawel |last4=Bolduan |first4=Felix |last5=Papoutsi |first5=Athanasia |last6=Poirazi |first6=Panayiota |last7=Holtkamp |first7=Martin |last8=Vida |first8=Imre |last9=Larkum |first9=Matthew Evan |date=2020-01-03 |title=Dendritic action potentials and computation in human layer 2/3 cortical neurons |journal=Science |language=en |volume=367 |issue=6473 |pages=83–87 |doi=10.1126/science.aax6239 |pmid=31896716 |issn=0036-8075|doi-access=free |bibcode=2020Sci...367...83G }}</ref><ref>{{Cite journal |last1=Larkum |first1=Matthew E. |last2=Wu |first2=Jiameng |last3=Duverdin |first3=Sarah A. |last4=Gidon |first4=Albert |date=2022 |title=The Guide to Dendritic Spikes of the Mammalian Cortex In Vitro and In Vivo |journal=Neuroscience |language=en |volume=489 |pages=15–33 |doi=10.1016/j.neuroscience.2022.02.009|pmid=35182699 |doi-access=free }}</ref>