DeePhys

DeePhys facilitates functional phenotyping of in vitro neuronal networks recorded with high-density microelectrode arrays to characterize electrophysiological phenotypes of human induced pluripotent stem cell (iPSC)-derived neurons.

Key Features:

• MATLAB implementation: Implemented as a MATLAB-based platform for computational analysis of electrophysiological data.
• Modular workflow: Provides a flexible, modular workflow that can be adapted to specific experimental needs.
• High-density MEA compatibility: Processes electrophysiological recordings obtained from high-density microelectrode arrays.
• Feature extraction: Extracts a variety of quantitative features from spike-sorted data at both individual cell and network levels.
• Developmental analysis: Supports examination of neuronal networks across developmental stages.
• Integrative extensibility: Designed to incorporate additional novel features for expanded analyses.
• Machine-learning integration: Leverages machine-learning-assisted approaches to enhance analysis and interpretation of complex electrophysiological data.

Scientific Applications:

• iPSC-derived neuron phenotyping: Phenotypes human induced pluripotent stem cell-derived neurons, including dopaminergic neurons from patients and healthy individuals.
• Phenotypic screening: Conducts phenotypic screenings to identify disease-specific electrophysiological characteristics.
• Pharmacological evaluation: Evaluates effects of pharmacological interventions on neuronal and network function.
• Developmental trajectory analysis: Analyzes how neuronal network properties evolve over developmental time.

Methodology:

Performs data-driven analysis of electrophysiological recordings from high-density microelectrode arrays using spike-sorted data, quantitative feature extraction at single-cell and network levels, and machine-learning-assisted analysis.