AUTHOR=Marom Anat , Shor Erez , Levenberg Shulamit , Shoham Shy 

TITLE=Spontaneous Activity Characteristics of 3D “Optonets”

JOURNAL=Frontiers in Neuroscience

VOLUME=Volume 10 - 2016

YEAR=2017

URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2016.00602

DOI=10.3389/fnins.2016.00602

ISSN=1662-453X

ABSTRACT=Sporadic spontaneous network activity emerges during the early CNS development and as the number of neuronal connections rises, the maturing network gives rise to diverse and complex activity, including various types of synchronized patterns. These activity patterns have major implications for both basic research and the study of neurological disorders, and their interplay with network morphology governs developmental events such as neuronal differentiation, migration and establishment of neurotransmitter phenotypes.  Although important insights were gained by analyzing activity in 2D neural cultures, these cultures do not mimic the complex 3D architecture, resulting in limited pattern variability; a 3D in-vitro model mimicking early network development and accessible to cellular-resolution observation could thus significantly advance our understanding of the activity characteristics in the developing CNS.
Here, we longitudinally study the spontaneous activity patterns of developing 3D in-vitro neural network 'optonets', an optically-accessible bioengineered CNS model with multiple cortex-like characteristics. Optonet activity was observed using the genetically encodable calcium indicator GCaMP6m and a3D imaging solution based on a standard epi-fluorescence microscope equipped with a piezo-electric z-stage and image processing based deconvolution. Our results show how activity patterns become more complex as the network matures, and start to exhibit longer-duration activity patterns. We characterize the patterns over time, and discuss how environmental changes affect the activity patterns. The results of this study are in line with findings obtained invivo, making this method a compelling model for brain-in-a chip research.