pMAT

pMAT processes fiber photometry calcium imaging data to standardize and analyze fluorescence signals from genetically encoded fluorescent sensors recorded via implanted fiber optics in bulk brain tissue.

Key Features:

• Modular Design: Modular computational architecture enabling separation and extension of analysis routines via modules.
• Fiber Photometry Data Processing: Processes fiber photometry calcium imaging datasets to extract and analyze fluorescence signals.
• Genetically Encoded Sensor Analysis: Analyzes signals from genetically encoded fluorescent sensors that report cellular activity and neurotransmitter binding.
• Bulk Tissue and Implanted Fiber Optic Support: Handles fluorescence signals recorded through implanted fiber optics sampling bulk brain tissue.
• MATLAB Integration: Deployable within MATLAB to allow customization and extension of analysis code and routines.
• Standardization: Provides computational routines aimed at standardizing fiber photometry data analysis across experiments.

Scientific Applications:

• Neuronal Activity Monitoring: Quantifies calcium-related fluorescence signals to study neuronal activity.
• Sensor-Based Neurotransmitter Studies: Analyzes fluorescence changes from sensors reporting neurotransmitter binding.
• Anatomical and Genetic Specificity: Enables analysis of signals from neurons with specific anatomical or genetic identities across brain structures.
• Superficial and Deep-Brain Recordings: Applicable to data collected from both superficial and deep-brain sites using implanted fiber optics.

Methodology:

Standardizes fiber photometry data analysis using customizable computational modules to streamline processing from data acquisition to interpretation.