Interplay activity-connectivity: Dynamics in patterned neuronal cultures

Tibau, Elisenda; Bendiksen, Ch.; Teller, Sara; Amigó, N.; Soriano, Jordi

doi:10.1063/1.4776501

Cited by 6 publications

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this context, an additional experimental tool that would provide valuable insight is the incorporation of connectivity guidance in the culture substrate, for instance in the form of biochemical fixation or physical trapping (Eckmann et al, 2007; Wheeler and Brewer, 2010). Dynamics in such “patterned cultures” substantially differ from standard ones due to the dictated connectivity (Shein Idelson et al, 2010; Tibau et al, 2013), and would possibly give rise to different temporal correlations.…”

Section: Discussionmentioning

confidence: 99%

Identification of neuronal network properties from the spectral analysis of calcium imaging signals in neuronal cultures

Tibau

Valencia

Soriano

2013

Front. Neural Circuits

View full text Add to dashboard Cite

Neuronal networks in vitro are prominent systems to study the development of connections in living neuronal networks and the interplay between connectivity, activity and function. These cultured networks show a rich spontaneous activity that evolves concurrently with the connectivity of the underlying network. In this work we monitor the development of neuronal cultures, and record their activity using calcium fluorescence imaging. We use spectral analysis to characterize global dynamical and structural traits of the neuronal cultures. We first observe that the power spectrum can be used as a signature of the state of the network, for instance when inhibition is active or silent, as well as a measure of the network's connectivity strength. Second, the power spectrum identifies prominent developmental changes in the network such as GABAA switch. And third, the analysis of the spatial distribution of the spectral density, in experiments with a controlled disintegration of the network through CNQX, an AMPA-glutamate receptor antagonist in excitatory neurons, reveals the existence of communities of strongly connected, highly active neurons that display synchronous oscillations. Our work illustrates the interest of spectral analysis for the study of in vitro networks, and its potential use as a network-state indicator, for instance to compare healthy and diseased neuronal networks.

show abstract

Section: Discussionmentioning

confidence: 99%

Identification of neuronal network properties from the spectral analysis of calcium imaging signals in neuronal cultures

Tibau

Valencia

Soriano

2013

Front. Neural Circuits

View full text Add to dashboard Cite

show abstract

“…These studies concluded that the neurons' degree distribution was Poisson-like, which supports an Erdős-Rényi description of the neuronal network. However, it may be possible that the connectivity degree distribution and the distribution of connectivity lengths substantially change with the spatial location of the neurons and the wiring of connections, as suggested from experiments in patterned neuronal networks [53][54][55][56].…”

Section: Discussionmentioning

confidence: 99%

Percolation of spatially constrained Erdős-Rényi networks with degree correlations

et al. 2014

Self Cite

View full text Add to dashboard Cite

Motivated by experiments on activity in neuronal cultures [J. Soriano, M. Rodríguez Martínez, T. Tlusty, and E. Moses, Proc. Natl. Acad. Sci. 105, 13758 (2008)], we investigate the percolation transition and critical exponents of spatially embedded Erdős-Rényi networks with degree correlations. In our model networks, nodes are randomly distributed in a two-dimensional spatial domain, and the connection probability depends on Euclidian link length by a power law as well as on the degrees of linked nodes. Generally, spatial constraints lead to higher percolation thresholds in the sense that more links are needed to achieve global connectivity. However, degree correlations favor or do not favor percolation depending on the connectivity rules. We employ two construction methods to introduce degree correlations. In the first one, nodes stay homogeneously distributed and are connected via a distance-and degree-dependent probability. We observe that assortativity in the resulting network leads to a decrease of the percolation threshold. In the second construction methods, nodes are first spatially segregated depending on their degree and afterwards connected with a distance-dependent probability. In this segregated model, we find a threshold increase that accompanies the rising assortativity. Additionally, when the network is constructed in a disassortative way, we observe that this property has little effect on the percolation transition.

show abstract

“…Examples of this structure-function interdependence come from experimental and theoretical studies alike (Sporns, 2010;Tomov et al, 2014a; Girardi-Schappo and de Andrade Costa, 2020): spontaneous cortical activity is sometimes observed in the form of bursts of action potentials, known as neuronal avalanches (Hesse and Gross, 2014;Carvalho et al, 2021). Nevertheless, when a group of researchers built a lattice-like network of neurons from the scratch in vitro, they did not observe these complex patterns (Tibau et al, 2013). However, adding modular structure to the lattice may do the job (Yamamoto et al, 2018).…”

Section: Building a Model Of The Brain: From Detailed Connectivity Maps To Network Organizationmentioning

confidence: 99%

Computational study of thalamocortical interactions: simulating oscillatory activity

Shimoura¹

View full text Add to dashboard Cite

Primeiramente à minha família que sempre me apoiou em minhas conquistas e dificuldades. Aos meus pais Maria Emília e Tsuguio Shimoura pela educação e encourajamento sempre presentes. Ambos sempre orgulhosos de qualquer conquista que adquiri até o momento. Infelizmente meu pai não estará presente para a finalização de mais essa etapa de minha vida, que ele esteja descansando em paz. À minha irmãSuélen e cunhado Elton, por todo apoio e suporte. Aos meus tios e padrinhos Silvia e Hélio que sempre mantiveram o incentivo e a confiança em mim. A minha tia Gláucia, primos e primas, e também aos meus avós Maria Rosa e José. Todos importantíssimos em minha vida. Também à Letícia, minha companheira, que me suportou e me deu apoio na reta final desse trabalho. Aos meus amigos(as) espalhados pelo Brasil e pelo mundo, sejam eles(as) amigos(as) adquiridos(as) na infância, no ensino médio, na faculdade, no laboratório e nos eventos acadêmicos, ou pelas situações da vida. Sem citar nomes, agradeço a todos, quem ler saberá que está incluído. Já peço desculpas de antemão, mas sou péssimo em listar esse tipo de coisa e para evitar esquecer alguém, prefiro manter assim. Apenas saibam que foram importantíssimos para a conclusão desse trabalho, seja pela ajuda acadêmica ou pelas distrações que me mantiveram mentalmente saudável dentro do possível. Ao meu orientador, Prof. Dr. Antônio Carlos Roque por todo apoio e orientação dados nesses últimos anos. Agradeço também pela confiança, respeito e, principalmente, pelo incentivo sempre presente nas apresentações/participações em diferentes congressos, cursos e workshops, experiência essa da qual foi grande valia para meu desenvolvimento como pesquisador. To the Institute of Neuroscience and Medicine -Computational and Systems Neuroscience (INM-6 / IAS-6) from Forschungszentrum Jülich where I did my v vi internship in Germany. My thanks to all people from the institute, specially to my supervisors Prof. Dr. Markus Diesmann and Dr. Sacha J. van Albada for the guidance, encouragement, patience and kindness which they received me.À FAPESP (Fundação de Amparo à Pesquisa do Estado de São Paulo) pelo financiamento de minha pesquisa de Doutorado no país (bolsa de doutorado, processo nº 2017/07688-9; e Bolsa Estágio de Pesquisa no Exterior (BEPE), processo nº 2018/08556-1).

show abstract

Interplay activity-connectivity: Dynamics in patterned neuronal cultures

Cited by 6 publications

References 0 publications

Identification of neuronal network properties from the spectral analysis of calcium imaging signals in neuronal cultures

Identification of neuronal network properties from the spectral analysis of calcium imaging signals in neuronal cultures

Percolation of spatially constrained Erdős-Rényi networks with degree correlations

Computational study of thalamocortical interactions: simulating oscillatory activity

Contact Info

Product

Resources

About