CellExplorer

CellExplorer analyzes extracellular electrophysiological recordings to extract standardized physiological metrics, classify neuron types by electrophysiological characteristics, and detect putative monosynaptic connections to relate physiological properties to a repository of "ground truth" neurons from various genetic lines.

Key Features:

• Processing Module: Calculates standardized physiological metrics from extracellular recordings, classifies neurons based on electrophysiological characteristics, and detects putative monosynaptic connections.
• Flexible Data Structure: Integrates and manages diverse electrophysiological datasets and enables comparison with a repository of "ground truth" neurons from various genetic lines.

Scientific Applications:

• Neuron-type characterization: Quantifies and classifies single neurons to link physiological signatures with genetically identified neuron types.
• Cortical circuit analysis: Detects putative monosynaptic connections to inform analyses of circuit connectivity and synaptic relationships.
• Comparative electrophysiology: Enables comparison of standardized metrics across datasets and genetic backgrounds to study neuronal diversity.

Methodology:

Processes extracellular electrophysiological data to extract physiological metrics, applies classification algorithms to categorize neurons, detects putative monosynaptic connections, and uses a flexible data structure to integrate comparative datasets.