Role of major burst leaders in modular hippocampal networks
M Bisio, V Pasquale, A Bosca… - 2015 7th …, 2015 - ieeexplore.ieee.org
M Bisio, V Pasquale, A Bosca, L Berdondini, M Chiappalone
2015 7th International IEEE/EMBS Conference on Neural Engineering …, 2015•ieeexplore.ieee.orgThe development of in vitro neuronal models constituted by patterned networks is of
significant interest in the neuroscientific community and requires the convergence of
electrophysiological studies with micro/nano-fabrication techniques. In this paper we make
use of a methodology to induce self-organization of networks into two connected sub-
populations grown onto commercially available Micro Electrode Arrays (MEAs) in order to
understand the role ofburst leaders' in generating the collective synchronous events (ie …
significant interest in the neuroscientific community and requires the convergence of
electrophysiological studies with micro/nano-fabrication techniques. In this paper we make
use of a methodology to induce self-organization of networks into two connected sub-
populations grown onto commercially available Micro Electrode Arrays (MEAs) in order to
understand the role ofburst leaders' in generating the collective synchronous events (ie …
The development of in vitro neuronal models constituted by patterned networks is of significant interest in the neuroscientific community and requires the convergence of electrophysiological studies with micro/nano-fabrication techniques. In this paper we make use of a methodology to induce self-organization of networks into two connected sub-populations grown onto commercially available Micro Electrode Arrays (MEAs) in order to understand the role of `burst leaders' in generating the collective synchronous events (i.e. network bursts) spontaneously arising in dissociated cultures. Considering the multitude of connections shown by uniform neuronal cultures, the restraint of neurite outgrowth along specific pathways ensures a considerable control over network complexity. Here we exploit this topological configuration to investigate whether and how network burst generation is affected by the development of the network. Our results constitute important evidence that engineered neuronal networks are a powerful platform to systematically approach questions related to the dynamics of neuronal assemblies.
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