TetroMate: Your Google Assistant for Tetrode Lowering

TetroMate is a Google Assistant agent designed to simplify and automate the process of documenting tetrode movements during electrophysiology experiments. It allows researchers to:

• Log adjustments: Record tetrode movements (up/down, number of turns) using natural language voice commands.
• Track cell activity: Note observations about cell activity (e.g., ripples, theta waves, cell count).
• Mark experimental stages: Define markers for different experimental sessions and epochs.
• Set brain area: Specify the brain area where each tetrode is currently located.
• Track depth: Query the current depth of a tetrode in turns and millimeters.
• Generate summaries: Automatically create organized summaries of lowering sessions, including a visually appealing depth chart.
• Store data securely: All data is directly saved to a Google Sheet, ensuring data integrity and accessibility.

Benefits:

• Hands-free logging: Focus on the experiment while documenting data using voice commands.
• Reduced errors: Minimize manual data entry mistakes and inconsistencies.
• Organized data: Easily access and analyze lowering session data.
• Time-saving: Streamline the documentation process and free up time for other tasks.

Getting Started

1. Set up a Google Cloud Platform Project:

   • Create a new project on Google Cloud Platform (https://cloud.google.com/).
   • Enable the Google Sheets API.
   • Create a service account and download its JSON key file.

2. Create a Google Sheet:

   • Create a new Google Sheet to store your experimental data.
   • Add worksheets named "Raw," "Summary," "Mapping", and "Prediction". The "Prediction" sheet can be used to store prior experiment statistics.

3. Configure TetroMate:

   • Open tetromate_webserver.py and modify the following:
     • path: Point to the path of your downloaded service account JSON key file.
     • url_configuration_file: Path to a file containing the URL of your Google Sheet.
     • screw_type: Specify the type of screw drive being used ("openefizz," "roshan," or "aught80").
     • const_depth_mm: Set a constant depth offset (in millimeters) if necessary.
     • continuous_explode: Adjust for whether your tetrode drive can adjust multiple tetrodes simultaneously.

4. Deploy TetroMate:

   • Use a tool like ngrok (https://ngrok.com/) to expose your local Flask server to the internet.
   • Update the webhook URL in agent.json with your ngrok URL.

5. Create a Dialogflow Agent:

   • Create a new Dialogflow agent (https://dialogflow.cloud.google.com/).
   • Import the agent.json file into your Dialogflow agent.
   • Configure the fulfillment to use your ngrok webhook URL.

6. Integrate with Google Assistant:

   • Connect your Dialogflow agent to Google Assistant.
   • Test your agent through the Google Assistant simulator or on a Google Assistant-enabled device.

Usage

Once deployed, you can use natural language commands to interact with TetroMate through Google Assistant:

• Adjust tetrode: "Lower 3 turns on tetrode 5."
• Record ripples: "Ripples are 2."
• Set area: "Area is CA1 for tetrodes 1, 2, and 3."
• Get depth: "What is the depth of tetrode 7?"
• Create summary: "Generate a pretty table."
• Backup data: "Backup my data."
• Undo last entry: "Undo."
• Add notes: "Note: strong cell activity observed."
• Set marker: "Marker: Session 2."

Contributing

Contributions to TetroMate are welcome! Please feel free to submit issues or pull requests on this repository.

License

This project is licensed under the MIT License - see the LICENSE file for details.