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ICCVAM Biennial Report 2018-2019

Biennial Progress Report 2018-2019 Interagency Coordinating Committee on the Validation of Alternative Methods
https://ntp.niehs.nih.gov/go/884101

Computational Neuronal Network Analysis for Extrapolation of iPSC Findings to Human In Vivo Effects

AFRL is developing an in silico mechanistic model of an in vitro experimental system consisting of human iPSC-derived dopaminergic neurons cultured on microelectrode arrays. While microelectrode array recordings of cultured neurons are useful for large, high-throughput experiments, cultured neurons form synaptic connections randomly rather than functionally as in the central nervous system, making it difficult to compare the firing activity recorded via microelectrode array to activity patterns produced by the human brain. This model should make it possible to extrapolate in vitro results to an expected impact on brain functions such as cognition and memory. An initial version of the model was implemented in the NEST modeling software. This combined platform contained neuronal types similar to those found in the human iPSC-derived neuronal cultures, parameterized using human and rodent data from the literature. Some key aspects of the behavior of the human iPSC-derived neurons could not be accurately represented due to limitations in the NEST software; the model was able to reproduce biological firing patterns qualitatively, but with unrealistically fast kinetics. The model is currently being redeveloped in the NEURON modeling software, which allows a more detailed implementation of neuronal mechanisms. This will allow the key behaviors of the human iPSC-derived neurons to be represented accurately.

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