DocumentCode
2463446
Title
Evolutionary dynamics of in vitro cultures of neurons in Multi Electrode Array - MEA
Author
Rodriguez, Mayra Zegarra ; Pedrino, Emerson Carlos ; Saito, José Hiroki ; Filho, João Batista Destro
Author_Institution
Fed. Univ. of Sao Carlos, Sao Paulo, Brazil
fYear
2012
fDate
14-17 Oct. 2012
Firstpage
78
Lastpage
83
Abstract
This work studies the evolution of neuronal network of in vitro cultures of neurons, in Multi-Electrode Array (MEA), using a multivariate autoregressive method and a partial directed coherence technique to obtain the causal relations between electrodes. The electrophysiological data of the hippocampal neurons of 18 days old Wistar rat embryos, were registered at Genoa University, with 3 days interval, from 25 DIV (Days In Vitro) to 46 DIV. The analysis of the obtained connectivity results, using the above mentioned statistical methods, was performed evaluating complex network properties, considering the MEA electrodes as nodes. The conclusion is that the described method is adequate to analyze the evolution of the cultured neuronal network.
Keywords
autoregressive processes; bioelectric phenomena; biomedical electrodes; medical signal processing; neurophysiology; statistical analysis; Genoa University; MEA electrodes; cultured neuronal network; electrophysiological data; evolutionary dynamics; hippocampal neurons; multielectrode array; multivariate autoregressive method; neuronal network evolution; nodes; old Wistar rat embryos; partial directed coherence technique; statistical methods; time 18 d; time 3 d; Algorithm design and analysis; Coherence; Complex networks; Electrodes; In vitro; Neurons; Time series analysis; MEA; PDC; autoregressive model; complex network; multi-electrode array; neuron culture; partial directed coherence;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on
Conference_Location
Seoul
Print_ISBN
978-1-4673-1713-9
Electronic_ISBN
978-1-4673-1712-2
Type
conf
DOI
10.1109/ICSMC.2012.6377680
Filename
6377680
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