Intrinsic spine dynamics are critical for recurrent network learning in models with and without autism spectrum disorder

Abstract

It is often assumed that Hebbian synaptic plasticity forms a cell assembly, a mutually interacting group of neurons that encodes memory. However, in recurrently connected networks with pure Hebbian plasticity, cell assemblies typically diverge or fade under ongoing changes of synaptic strength. Previously assumed mechanisms that stabilize cell assemblies do not robustly reproduce the experimentally reported unimodal and long-tailed distribution of synaptic strengths. Here, we show that augmenting Hebbian plasticity with experimentally observed intrinsic spine dynamics can stabilize cell assemblies and reproduce the distribution of synaptic strengths. Moreover, we posit that strong intrinsic spine dynamics impair learning performance. Our theory explains how excessively strong spine dynamics, experimentally observed in several animal models of autism spectrum disorder, impair learning associations in the brain.

Activity Dependent and Independent Determinants of Synaptic Size Diversity

“…A second explanation class attributes these distributions to intrinsic size fluctuations that contain multiplicative (and additive) components (Yasumatsu et al, 2008;Loewenstein et al, 2011;Kaufman et al, 2012;Statman et al, 2014;Rubinski and Ziv, 2015;Ishii et al, 2018, Humble et al, 2019Ziv and Brenner, 2018). Most of such explanations are based on descriptive models in which size fluctuations are treated statistically without addressing their sources.…”

“…Intrinsic size fluctuations are sufficient to produce differently sized synapses at appropriate proportions As mentioned in the Introduction, prior studies suggest that synaptic sizes are affected by intrinsic size fluctuations, as are the shape and scale of synaptic size distributions (Yasumatsu et al, 2008;Loewenstein et al, 2011;Kaufman et al, 2012;Statman et al, 2014;Rubinski and Ziv, 2015;Ishii et al, 2018;Ziv and Brenner, 2018;Humble et al, 2019). Yet, as characteristics of intrinsic size fluctuations in neurons with no prior history of network activity were not measured to date, it remained unknown whether such intrinsic fluctuations are sufficient to pro-duce the extensive diversity and broad, skewed distributions of synaptic sizes observed in chronically silenced networks.…”

“…Such distributions are not only broad but also rightward skewed and heavy-tailed, and are often described as log-normal (Murthy et al, 1997;Song et al, 2005;Arellano et al, 2007;Lefort et al, 2009;Minerbi et al, 2009;Loewenstein et al, 2011;Ikegaya et al, 2013;Keck et al, 2013;Statman et al, 2014;Cossell et al, 2015;Zhang et al, 2015;Hobbiss et al, 2018;Ishii et al, 2018;Masch et al, 2018;Sakamoto et al, 2018;Sammons et al, 2018;Wegner et al, 2018;Santuy et al, 2018; for review, see Barbour et al, 2007;Buzsáki and Mizuseki, 2014;Scheler, 2017). Such distributions, reflecting of a majority of weak/small synapses and a diminishing tail of increasingly stronger/larger synapses, were suggested to optimize storage capacity, neuronal firing rates and long-distance information transfer and thus impart important properties to neuronal networks (Song et al, 2005;Barbour et al, 2007;Lefort et al, 2009;Ikegaya et al, 2013;Buzsáki and Mizuseki, 2014;Scheler, 2017;Humble et al, 2019).…”

“…Importantly, such fluctuations persist following abrupt suppressions of network activity or synaptic transmission (Yasumatsu et al, 2008;Minerbi et al, 2009;Dvorkin and Ziv, 2016). These intrinsic fluctuations, probably driven by the innate dynamics of synaptic molecules-binding, unbinding, and turnover (Kasai et al, 2010;Ziv and Fisher-Lavie, 2014;Shomar et al, 2017;Triesch et al, 2018)-were suggested to drive synaptic size diversification and determine the shape and scale of size distributions (Yasumatsu et al, 2008;Minerbi et al, 2009;Kasai et al, 2010, Loewenstein et al, 2011Kaufman et al, 2012;Statman et al, 2014;Shomar et al, 2017;Ishii et al, 2018;Ziv and Brenner, 2018;Humble et al, 2019). It remains unclear, however, whether intrinsic size fluctuations are indeed sufficient to give rise to a full repertoire of synaptic sizes and at the right proportions.…”

Homeostatic mechanisms regulate distinct aspects of cortical circuit dynamics

“…Other modeling studies have investigated the interaction between Hebbian and homeostatic plasticity for the stable formation and maintenance of Hebbian assemblies in the context of memory storage and recall ( 43 – 45 ), which are different from the sensory deprivation paradigm studied here. Interestingly, a recent modeling framework for the homeostatic recovery from visual deprivation proposed that the disinhibitory effect of inhibitory plasticity, rather than synaptic scaling, can drive the recovery of firing rates and correlations in specific subnetworks of excitatory neurons ( 46 ), based on experimental results ( 40 ).…”