Modeling Organoid Population Electrophysiology Dynamics

Improving models to investigate neurodegenerative disease, neurodevelopmental disease, neuro-toxicology and neuropharmacology is critical to improve our basic understanding of the human nervous system, as well as to accelerate discovery of interventions and drugs. Improved models of the human central nervous system could enable critical discoveries related to functional changes induced by sensory stimulation or toxic exposures. Neural organoids, complex three-dimensional cell cultures derived from adult human stem cells, have been grown with complex connectivity and neuroanatomy. Moreover, these cultures have been interfaced with bi-directional electrical stimulation and recording, as well as chemical stimulation. This effort sought to develop new computational techniques which could be applied to comparative studies using neural organoids. In particular, we adapted CEBRA, a state of the art model from the in vivo modeling literature, to generate 2D and 3D embeddings (projections into structured low-dimensional spaces) of high dimensional neural organoid electrophysiology data. This can be done in an unsupervised or semi-supervised manner. Results indicate these embeddings can be quickly and reliably generated and serve as a low-dimensional, interpretable embeddings for characterizing changes in neural organoid activity over time, as well as clustering results around known bursting phenomena. Moreover, we demonstrate that mixtures of von Mises-Fisher distributions can be used as a parametric model for these embedding spaces to enable statistics hypothesis testing. This technique may enable new types of comparative studies using neural organoids, and may be critical for creating a representation for quantitative comparison and validation of neural organoid models against human and animal data. Looking ahead, this work could allow the formulation of a new class of experiments investigating the functional impact of toxins, genetic manipulations, or pharmacological interventions on human neurons.