P066 In-silico study on the dynamical and topological relationships between three-dimensional cultures and relative slices
Leonardo Della Mea1*, Angelo Piga2,3, Jordi Soriano3
1DIBRIS, University of Genoa, Genoa, Italy 2Department of Economics and Managements, University of Pisa, Pisa, Italy 3Institute of Complex Systems, University of Barcelona, Barcelona, Spain
*Email: leonardo.dellamea@edu.unige.it
Introduction
The in-vitro three-dimensional neuronal culture represents a pioneering technological advancement in exploring brain function and dysfunction in a more realistic environment[1], [2]. The recording of the entire network activity remains a challenge, since researches resort to methods developed for two-dimensional cultures, such as multi-electrode arrays or calcium fluorescence imaging. The question of whether the read-out layer, through which the network is recorded, reliably captures topological and dynamical properties, quickly arises. In the this study we utilized in-silico modelling of developing 3D neuronal networks to assess the reliability of a single layer of the culture in capturing dynamical and topological features of the entire parent network.
Methods The networks were constructed through the random placement of neurons within a rectangular prism. The cell’s dendritic and axonal domains were constructed upon a main trunk, consisting in concatenated segments, and a group of arborizations, depicted by spherical regions. The overlap of different cells’ dendritic and axonal arbours results in synaptogenesis. The network is then simulated as a pulsed coupled neuronal network embedding the Izhikevich model[3]. The bottom layer of neurons were drawn out to emulate the MEA recordings. Its dynamical properties -focused on the features of the network burst (NB)– and topological traits –based on small-worldness (SW)[4]and modularity (Q)[5]- were compared to the one of the entire parent cultures.
Results and discussion From a dynamical and topological perspective, statistically significant differences were observed for all the parameters measured.For the network’s slice, the mean NB sizes and dynamical variability are regularly overestimated, whereas the NB duration is underestimated. Due to slicing, a variable fraction of the neurons in the layer are exposed to the propagating front of the burst, thus, the dynamical differences observed in slices may be due the fact that NB events are very unlikely to systematically engage equal fractions of the sub-network, justifying the higher dynamical variability. In addition, the reduced size of the network makes the slices liable to wrongly capture the mean event sizes and duration; indeed, both measures depend on the network size. Modularity exhibited a monotonic decline in both 3D and slice systems, although it was marginally overestimated in the slice. The 3D network shows a bell-shaped trendof SW valuesacross the maturation, peaking in the middle of developmental phase. In contrast, the slice’s values differed, consistently under-estimating it.Sampling the edges from a network whose architecture is grounded on distance-dependent probability of connection, results in sub-networks where this feature is exacerbated. Consequently, in slices, communities are more starkly outlined and in turn Q increases and SW decreases -due to the reduction of shortcuts.
Acknowledgements The author wish to thank Prof. Jordi Soriano and Angelo Piga , for their kind advice on the experimental procedure and useful discussion. The author declare no use of Artificial Intelligence in this study. References [1] https://doi: 10.1016/j.isci.2020.101434. [2] https://doi: 10.1002/term.2508. [3] https://doi: 10.1109/TNN.2003.820440. [4] https://doi: 10.1016/j.neuroimage.2009.10.003.
