DocumentCode :
718394
Title :
High-density MEAs reveal lognormal firing patterns in neuronal networks for short and long term recordings
Author :
Amin, Hayder ; Maccione, Alessandro ; Zordan, Stefano ; Nieus, Thierry ; Berdondini, Luca
Author_Institution :
Neurosci. & Brain Technol. Dept., Ist. Italiano di Tecnol. (IIT), Genoa, Italy
fYear :
2015
fDate :
22-24 April 2015
Firstpage :
1000
Lastpage :
1003
Abstract :
Neurons communicate in the brain via spikes. Understanding the balance between the fast-firing minority and slow-firing majority in a neuronal population is therefore a fundamental step to unravel the nature of communication and of operation within and across neuronal assemblies. Recent in vivo observations show that many functional and structural parameters of the brain follow a skewed nature and typically manifest lognormal distributions of patterns. Here, we show for the first time that high-density microelectrode array (HD-MEA) reveal such a lognormal-like distribution of the firing patterns also in in vitro grown hippocampal neuronal networks, and already after 10 minutes of recording. Additionally, we demonstrate that the electrode density plays a key role for obtaining such a distribution in cultures. Overall, our findings show that in vitro neural networks recorded with CMOS-MEAs might contribute in investigating the organization and function of neuronal networks by revealing, with similarities with results obtained in vivo, the relationships among different skewed distributions at multiple scales, i.e. from synapses, single cells and micro-circuits up to large-scale networks.
Keywords :
CMOS integrated circuits; bioelectric phenomena; biomedical electrodes; brain; log normal distribution; microelectrodes; neurophysiology; CMOS-MEA; brain; fast-firing minority; high-density microelectrode array; in vitro grown hippocampal neuronal networks; large-scale networks; lognormal firing patterns; lognormal-like distribution; long term recordings; microcircuits; neuronal population; short term recordings; single cells; skewed distributions; slow-firing majority; synapses; time 10 min; Arrays; Biological neural networks; Electrodes; Firing; In vitro; Layout; Spatial resolution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Engineering (NER), 2015 7th International IEEE/EMBS Conference on
Conference_Location :
Montpellier
Type :
conf
DOI :
10.1109/NER.2015.7146795
Filename :
7146795
Link To Document :
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