Welcome to the Pynamic Gain documentation!

Introduction

Pynamic Gain is a Python package that facilitates the creation and analysis of Dynamic Gain calculations across multiple distributed setups. It serves three main purposes:

• Distributed setup management: Maintain an overview of setups and seeds used to ensure reproducibility and uniqueness of stimuli across multiple setups.

• Create Input Stimuli: Create input stimuli for subsequent dynamic gain calculation.

• Online Analysis: Perform real-time analysis of stimulated recordings to identify appropriate analysis windows for dynamic gain calculation.

In the future, this package will also include the dynamic gain calculation itself.

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Note

This project is under active development and will extend in the future. Please write us if you have any questions or suggestions!

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How to start:

• First Steps
• Usage
• Motivations
• API Documentation
• Advanced
• Development

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Institutions

The developer team is part of the Göttingen Campus Institute for Dynamics of Biological Networks (CIDBN).

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This project is being used in the NeuroNex Working Memory Consortium.

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Funding

This project is partially supported by the Ministry for Science and Culture of Lower Saxony (MWK)