Heterosynaptic Plasticity Determines the Set Point for Cortical Excitatory-Inhibitory Balance

Field, Rachel E.; D'Amour, James A; Tremblay, Robin; Miehl, Christoph; Rudy, Bernardo; Gjorgjieva, Julijana; Froemke, Robert C.

doi:10.1016/j.neuron.2020.03.002

Cited by 69 publications

(53 citation statements)

References 66 publications

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“…Plasticity from excitatory-to-excitatory neurons was based on excitatory triplet spike-timing-dependent plasticity (eSTDP) rule, which uses triplets of pre-and postsynaptic spikes to evoke synaptic change and captures the firing rate dependency found experimentally (Sjöström et al, 2001;Pfister and Gerstner, 2006;Gjorgjieva et al, 2011) (Table3). In addition, excitatory-to-excitatory weight dynamics were stabilized by a heterosynaptic plasticity mechanism (Fiete et al, 2010;Field et al, 2020), which preserved the total sum of all incoming synaptic weights into an excitatory neuron. Plasticity from inhibitory to excitatory neurons was modeled based on an inhibitory pairwise STDP (iSTDP) rule, which allows stabilization of excitatory firing rate dynamics (Vogels et al, 2011;Litwin-Kumar and Doiron, 2014) and has been confirmed experimentally (D'amour and Froemke, 2015).…”

Section: Methodsmentioning

confidence: 99%

“…We proposed inhibitory plasticity as the key mechanism that allows for adaptation to repeated stimulus presentation and the generation of novelty responses in our model. Many experimental studies have characterized spiketiming-dependent plasticity (STDP) of synapses from inhibitory onto excitatory neurons (Holmgren and Zilberter, 2001;Woodin et al, 2003;Haas et al, 2006;Maffei et al, 2006;Wang and Maffei, 2014;D'amour and Froemke, 2015;Field et al, 2020). In theoretical studies, network models usually include inhibitory plasticity to dynamically stabilize recurrent network dynamics (Vogels et al, 2011;Litwin-Kumar and Doiron, 2014;Zenke et al, 2015).…”

Section: Inhibitory Plasticity As An Adaptive Mechanismmentioning

confidence: 99%

“…One line of evidence to speak against inhibitory plasticity argues that SSA might be independent of NMDA activation (Farley et al, 2010). Inhibitory plasticity, on the contrary, seems to be NMDA receptor-dependent (D'amour and Froemke, 2015;Field et al, 2020). However, there exists some discrepancy in how exactly NMDA receptors are involved in SSA (Ross and Hamm, 2020), since blocking NMDA receptors can disrupt the MMN (Tikhonravov et al, 2008;Chen et al, 2015).…”

Section: Inhibitory Plasticity As An Adaptive Mechanismmentioning

confidence: 99%

“…Presenting a novel stimulus leads to a short-term disruption of the E/I balance, triggering inhibitory plasticity, which aims to restore the E/I balance (Fig. 4) (Vogels et al, 2011;D'amour and Froemke, 2015;Field et al, 2020). Disinhibition, which effectively disrupts the E/I balance, allows for flexible control of adapted and novelty responses (Fig.…”

Section: Functional Implications Of Adapted and Novelty Responsesmentioning

confidence: 99%

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The generation of cortical novelty responses through inhibitory plasticity

Schulz

Miehl

Berry

et al. 2020

Preprint

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Animals depend on fast and reliable detection of novel stimuli in their environment. Indeed, neurons in multiple sensory areas respond more strongly to novel in comparison to familiar stimuli. Yet, it remains unclear which circuit, cellular and synaptic mechanisms underlie those responses. Here, we show that inhibitory synaptic plasticity readily generates novelty responses in a recurrent spiking network model. Inhibitory plasticity increases the inhibition onto excitatory neurons tuned to familiar stimuli, while inhibition for novel stimuli remains low, leading to a network novelty response. Generated novelty responses do not depend on the exact temporal structure but rather on the distribution of presented stimuli. By including tuning of inhibitory neurons, the network further captures stimulus-specific adaptation. Finally, we suggest that disinhibition can control the amplification of novelty responses. Therefore, inhibitory plasticity provides a flexible, biologically-plausible mechanism to detect the novelty of bottom-up stimuli, enabling us to make numerous experimentally testable predictions.

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Section: Methodsmentioning

confidence: 99%

Section: Inhibitory Plasticity As An Adaptive Mechanismmentioning

confidence: 99%

Section: Inhibitory Plasticity As An Adaptive Mechanismmentioning

confidence: 99%

Section: Functional Implications Of Adapted and Novelty Responsesmentioning

confidence: 99%

See 2 more Smart Citations

The generation of cortical novelty responses through inhibitory plasticity

Schulz

Miehl

Berry

et al. 2020

Preprint

Self Cite

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show abstract

“…The need to understand how the interaction between excitatory and inhibitory synapses mediates plasticity and dynamic homeostasis [ 17 , 18 ] calls for the study of heterogeneous multi-population feed-forward and recurrent models. A plethora of mechanisms for excitatory-inhibitory (E-I) balance of input currents onto a neuron have been proposed [ 19 , 20 ].…”

Section: Introductionmentioning

confidence: 99%

Optimal learning with excitatory and inhibitory synapses

Ingrosso

2020

PLoS Comput Biol

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Characterizing the relation between weight structure and input/output statistics is fundamental for understanding the computational capabilities of neural circuits. In this work, I study the problem of storing associations between analog signals in the presence of correlations, using methods from statistical mechanics. I characterize the typical learning performance in terms of the power spectrum of random input and output processes. I show that optimal synaptic weight configurations reach a capacity of 0.5 for any fraction of excitatory to inhibitory weights and have a peculiar synaptic distribution with a finite fraction of silent synapses. I further provide a link between typical learning performance and principal components analysis in single cases. These results may shed light on the synaptic profile of brain circuits, such as cerebellar structures, that are thought to engage in processing time-dependent signals and performing on-line prediction.

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Contributions of dysfunctional plasticity mechanisms to the development of atypical perceptual processing

Moppert,

Mercado

2024

Developmental Psychobiology

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Experimental studies of sensory plasticity during development in birds and mammals have highlighted the importance of sensory experiences for the construction and refinement of functional neural circuits. We discuss how dysregulation of experience‐dependent brain plasticity can lead to abnormal perceptual representations that may contribute to heterogeneous deficits symptomatic of several neurodevelopmental disorders. We focus on alterations of somatosensory processing and the dynamic reorganization of cortical synaptic networks that occurs during early perceptual development. We also discuss the idea that the heterogeneity of strengths and weaknesses observed in children with neurodevelopmental disorders may be a direct consequence of altered plasticity mechanisms during early development. Treating the heterogeneity of perceptual developmental trajectories as a phenomenon worthy of study rather than as an experimental confound that should be overcome may be key to developing interventions that better account for the complex developmental trajectories experienced by modern humans.

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Heterosynaptic Plasticity Determines the Set Point for Cortical Excitatory-Inhibitory Balance

Cited by 69 publications

References 66 publications

The generation of cortical novelty responses through inhibitory plasticity

The generation of cortical novelty responses through inhibitory plasticity

Optimal learning with excitatory and inhibitory synapses

Contributions of dysfunctional plasticity mechanisms to the development of atypical perceptual processing

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