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Local Design Principles at Hippocampal Synapses Revealed by an Energy-Information Trade-Off

Overview
Journal eNeuro
Specialty Neurology
Date 2020 Aug 28
PMID 32847867
Citations 1
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Abstract

Synapses across different brain regions display distinct structure-function relationships. We investigated the interplay of fundamental design constraints that shape the transmission properties of the excitatory CA3-CA1 pyramidal cell connection, a prototypic synapse for studying the mechanisms of learning in the mammalian hippocampus. This small synapse is characterized by probabilistic release of transmitter, which is markedly facilitated in response to naturally occurring trains of action potentials. Based on a physiologically motivated computational model of the rat CA3 presynaptic terminal, we show how unreliability and short-term dynamics of vesicular release work together to regulate the trade-off of information transfer versus energy use. We propose that individual CA3-CA1 synapses are designed to operate near the maximum possible capacity of information transmission in an efficient manner. Experimental measurements reveal a wide range of vesicular release probabilities at hippocampal synapses, which may be a necessary consequence of long-term plasticity and homeostatic mechanisms that manifest as presynaptic modifications of the release probability. We show that the timescales and magnitude of short-term plasticity (STP) render synaptic information transfer nearly independent of differences in release probability. Thus, individual synapses transmit optimally while maintaining a heterogeneous distribution of presynaptic strengths indicative of synaptically-encoded memory representations. Our results support the view that organizing principles that are evident on higher scales of neural organization percolate down to the design of an individual synapse.

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Jedlicka P, Bird A, Cuntz H Open Biol. 2022; 12(7):220073.

PMID: 35857898 PMC: 9277232. DOI: 10.1098/rsob.220073.

References
1.
Pfister J, Dayan P, Lengyel M . Synapses with short-term plasticity are optimal estimators of presynaptic membrane potentials. Nat Neurosci. 2010; 13(10):1271-5. PMC: 3558743. DOI: 10.1038/nn.2640. View

2.
Levy W, Baxter R . Energy-efficient neuronal computation via quantal synaptic failures. J Neurosci. 2002; 22(11):4746-55. PMC: 6758790. DOI: 20026456. View

3.
Aoki Y, Igata H, Ikegaya Y, Sasaki T . The Integration of Goal-Directed Signals onto Spatial Maps of Hippocampal Place Cells. Cell Rep. 2019; 27(5):1516-1527.e5. DOI: 10.1016/j.celrep.2019.04.002. View

4.
Shapiro M, Tanila H, Eichenbaum H . Cues that hippocampal place cells encode: dynamic and hierarchical representation of local and distal stimuli. Hippocampus. 1997; 7(6):624-42. DOI: 10.1002/(SICI)1098-1063(1997)7:6<624::AID-HIPO5>3.0.CO;2-E. View

5.
Kandaswamy U, Deng P, Stevens C, Klyachko V . The role of presynaptic dynamics in processing of natural spike trains in hippocampal synapses. J Neurosci. 2010; 30(47):15904-14. PMC: 6633767. DOI: 10.1523/JNEUROSCI.4050-10.2010. View