Rewiring of neuronal networks during synaptic silencing

Wrosch, Jana K.; Einem, Vicky von; Breininger, Katharina; Dahlmanns, Marc; Maier, Andreas; Kornhuber, Johannes; Groemer, Teja W.

doi:10.1038/s41598-017-11729-5

Cited by 9 publications

(15 citation statements)

References 81 publications

(82 reference statements)

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“…To examine this expectation, we raised networks of cultured rat cortical neurons from Day 1 in culture in TTX (1 M), CNQX (10 M), and APV (50 M), potent inhibitors of voltage gated sodium channels, AMPA-type and NMDA-type glutamate receptors, respectively. No overt effects on cell viability were observed, in agreement with many early studies (van Huizen et al, 1985, Ramakers et al, 1993Craig et al, 1994;Verderio et al, 1994;Benson and Cohen, 1996;Murthy et al, 2001) as well as more recent ones (Wrosch et al, 2017;Hobbiss et al, 2018).…”

Section: Distributions Of Synaptic Sizes In Chronically Silenced Netwsupporting

confidence: 91%

Activity Dependent and Independent Determinants of Synaptic Size Diversity

Hazan

Ziv

2020

J. Neurosci.

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The extraordinary diversity of excitatory synapse sizes is commonly attributed to activity-dependent processes that drive synaptic growth and diminution. Recent studies also point to activity-independent size fluctuations, possibly driven by innate synaptic molecule dynamics, as important generators of size diversity. To examine the contributions of activity-dependent and independent processes to excitatory synapse size diversity, we studied glutamatergic synapse size dynamics and diversification in cultured rat cortical neurons (both sexes), silenced from plating. We found that in networks with no history of activity whatsoever, synaptic size diversity was no less extensive than that observed in spontaneously active networks. Synapses in silenced networks were larger, size distributions were broader, yet these were rightward-skewed and similar in shape when scaled by mean synaptic size. Silencing reduced the magnitude of size fluctuations and weakened constraints on size distributions, yet these were sufficient to explain synaptic size diversity in silenced networks. Model-based exploration followed by experimental testing indicated that silencing-associated changes in innate molecular dynamics and fluctuation characteristics might negatively impact synaptic persistence, resulting in reduced synaptic numbers. This, in turn, would increase synaptic molecule availability, promote synaptic enlargement, and ultimately alter fluctuation characteristics. These findings suggest that activity-independent size fluctuations are sufficient to fully diversify glutamatergic synaptic sizes, with activity-dependent processes primarily setting the scale rather than the shape of size distributions. Moreover, they point to reciprocal relationships between synaptic size fluctuations, size distributions, and synaptic numbers mediated by the innate dynamics of synaptic molecules as they move in, out, and between synapses.

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Section: Distributions Of Synaptic Sizes In Chronically Silenced Netwsupporting

confidence: 91%

Activity Dependent and Independent Determinants of Synaptic Size Diversity

Hazan

Ziv

2020

J. Neurosci.

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“…In particular, the use of small living neuronal networks as laboratories for connectivity studies has gained substantial attention. Two technologies to monitor activity in these living systems have become central, namely calcium fluorescence imaging [5], [6], [7], [8], [9] and multi-electrode arrays (MEAs) [10], [11], [12], [13], [14], [15]. The interest of these studies is not only to quantify the mechanisms shaping neuron-to-neuron interactions, but also to understand up…”

Section: Introductionmentioning

confidence: 99%

Neuronal Spatial Arrangement Shapes Effective Connectivity Traits of in vitro Cortical Networks

Tibau

Ludl

Rüdiger

et al. 2020

IEEE Trans. Netw. Sci. Eng.

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We studied effective connectivity in rat cortical cultures with various degrees of spatial aggregation, ranging from homogeneous networks to highly aggregated ones. We considered small cultures 3 mm in diameter and that contained about 2000 neurons. Spatial inhomogeneity favored an increase of metric correlations and connectivity among neighboring neurons. Effective connectivity was determined from spontaneous activity recordings using calcium fluorescence imaging. We used generalized transfer entropy as tool to infer the effective connectivity. We carried out numerical simulations to build networks that mimicked the experimental ones and to test the reliability of the connectivity-inference algorithm. Effective connectivity traits were investigated during the development of the cultures over two weeks, and along the gradual blockade of excitatory connections through CNQX. We observed that the average effective connectivity rapidly increased during culture development. At DIV 15 the average excitatory in-degree was measured ask in E 50 for homogeneous and semi aggregated networks, andk in E 120 for aggregated ones, and with 20% inhibition. Aggregated cultures exhibited assortative traits and a high resilience to chemical damage, while the other cultures were dissassortative or neutral, and less resilient. Our work illustrates the role of metric correlations in spatially embedded networks in shaping connectivity and activity traits in living neuronal networks.

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“…This spike estimation yielded a binary time log for each cell with zeros (indicating no spiking activity) and ones (indicating spikes) in the different time frames. Based on these binary spiking data, we reconstructed effective neuronal networks in the cultures with a previously published machine learning model (Wrosch et al 2017). A number of methods have been proposed to infer connectivity from spiking activity (Salinas and Sejnowski 2001; Xu et al Stetter et al 2012;Wrosch et al 2017;Lungarella et al 2007;Schreiber 2000).…”

Section: Image Processing and Network Reconstructionmentioning

confidence: 99%

“…Networks of neurons are studied at many different levels and are presented in the mathematical form of a graph which consists of nodes (building blocks of the network-on different scales these may be single neurons, groups of neurons, or distinct brain areas) and edges (the connections linking the nodes) (Bassett and Sporns 2017;Wrosch et al 2017). Depending on the nature of relationship between the network nodes that we focus on, we can generally distinguish three types of neuronal networks: Anatomical networks represent physical connections (Bullmore and Sporns 2009), functional networks describe the statistical dependence between the activities of two nodes without specifying the cause of correlation (Bullmore and Sporns 2009;Feldt et al 2011), and finally, effective networks determine the influence that the activity of one node has on another node (Feldt et al 2011;Bullmore and Sporns 2009).…”

Section: Introductionmentioning

confidence: 99%

Common network effect-patterns after monoamine reuptake inhibition in dissociated hippocampus cultures

et al. 2022

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The pharmacological treatment of major depressive disorder with currently available antidepressant drugs is still unsatisfying as response to medication is delayed and in some patients even non-existent. To understand complex psychiatric diseases such as major depressive disorder and their treatment, research focus is shifting from investigating single neurons towards a view of the entire functional and effective neuronal network, because alterations on single synapses through antidepressant drugs may translate to alterations in the entire network. Here, we examined the effects of monoamine reuptake inhibitors on in vitro hippocampal network dynamics using calcium fluorescence imaging and analyzing the data with means of graph theoretical parameters. Hypothesizing that monoamine reuptake inhibitors operate through changes of effective connectivity on micro-scale neuronal networks, we measured the effects of the selective monoamine reuptake inhibitors GBR-12783, Sertraline, Venlafaxine, and Amitriptyline on neuronal networks. We identified a common pattern of effects of the different tested monoamine reuptake inhibitors. After treatment with GBR-12783, Sertraline, and Venlafaxine, the connectivity degree, measuring the number of existing connections in the network, was significantly decreased. All tested substances led to networks with more submodules and a reduced global efficiency. No monoamine reuptake inhibitor did affect network-wide firing rate, the characteristic path length, or the network strength. In our study, we found that monoamine reuptake inhibition in neuronal networks in vitro results in a sharpening of the network structure. These alterations could be the basis for the reorganization of a large-scale miswired network in major depressive disorder.

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Rewiring of neuronal networks during synaptic silencing

Cited by 9 publications

References 81 publications

Activity Dependent and Independent Determinants of Synaptic Size Diversity

Activity Dependent and Independent Determinants of Synaptic Size Diversity

Neuronal Spatial Arrangement Shapes Effective Connectivity Traits of in vitro Cortical Networks

Common network effect-patterns after monoamine reuptake inhibition in dissociated hippocampus cultures

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