Neural Statistics Compiler for Automated Analysis of Multielectrode Array (MEA) Data

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The Neural Statistics Compiler is a project aimed at facilitating the investigation of early neuronal network dynamics in neurodevelopmental and neurodegenerative disorders using multielectrode array (MEA) technology. MEA data analysis requires sophisticated electrophysiological techniques such as spike sorting, multidimensional analysis, and machine learning. However, these techniques are typically not part of the training repertoire of developmental and molecular biologists.

Recognizing the need for collaboration between researchers with varying levels of expertise, the Neural Statistics Compiler offers an automated solution for data exploration, mining, and extraction. It streamlines the process of data wrangling, manipulation, and cleaning, while also performing comprehensive time series-based and statistical analyses on high-throughput electrophysiological data. By automating these tasks, the Neural Statistics Compiler empowers researchers who may not possess extensive expertise in electrophysiology to effectively analyze complex MEA datasets.

The Neural Statistics Compiler project is currently in development, and its anticipated release is planned for the upcoming publication by Pradeepan et al., scheduled for 2023 (in prep). With the introduction of this innovative tool, researchers will gain access to an automated platform that significantly simplifies the analysis of MEA data, eliminating the barriers posed by technical complexity. By democratizing data analysis, the Neural Statistics Compiler will foster collaborations and enable researchers from diverse backgrounds to contribute to the study of early neuronal network dynamics.

Simple and straight forward user interface

Automatically detects electrophysiological activity features and statistics

Filter plots based on treatment/condition groups

Output and download statistics for external analysis