🔬 Electrophysiology–Calcium Imaging Alignment and Analysis

This repository contains MATLAB scripts for aligning electrophysiological recordings (ABF files) with either calcium imaging videos (TIFF stacks) or extracted calcium traces (CSV files) using TTL synchronization signals.

These tools are designed to assist in the synchronization, visualization, and quantitative analysis of ex vivo or in vitro experiments combining patch-clamp electrophysiology with simultaneous calcium imaging.

---

📁 Repository Contents in Main folder

1. align_ephys_video.m

Purpose:
Align electrophysiology (ABF) recordings with the corresponding imaging frames from a TIFF video using the camera TTL signal.

Main features:

• Loads ABF electrophysiology recordings (abfload function).
• Detects camera TTL pulses used to trigger each imaging frame.
• Aligns ephys data with video frames based on TTL events.
• Allows manual correction for deleted or missing frames.
• Displays a synchronized animation of:
  • the calcium imaging video,
  • electrophysiological trace(s),
  • TTL channel activity.

Typical use case:
When the user wants to visually verify frame-to-frame correspondence between electrophysiological data and raw calcium imaging movies.

Key inputs:

ephys_file = "\\path\\to\\your\\recording.abf";
video_file = "\\path\\to\\your\\video.tif";

Key output:
Animated plot showing real-time alignment between imaging frames and ephys signals.

---

2. align_ephys_caTrace.m

Purpose:
Align electrophysiology recordings (ABF) with processed calcium traces (CSV) extracted from imaging data.
Generates a combined dataset suitable for further signal processing and quantitative analysis.

Main features:

• Loads electrophysiology data (.abf) and calcium signals (.csv).
• Uses TTL events to synchronize electrophysiological samples with imaging frames.
• Merges both datasets into a single table.
• Interactive channel selection for plotting ephys signals.
• Generates aligned plots of:
  • Electrophysiology signals,
  • Calcium ΔF/F traces.
• Performs optional interpolation to match ephys sampling frequency.
• Includes basic analysis examples:
  • Cross-correlation between patched cell and calcium signal.
  • Spike-triggered averaging of calcium responses.

Typical use case:
When calcium traces have already been extracted (e.g., via Inscopix IDPS) and need to be aligned and compared to electrophysiological recordings.

Key inputs:

ephys_file = "\\path\\to\\your\\recording.abf";
catrace_file = "\\path\\to\\your\\calcium_traces.csv";

Key outputs:

• Figures displaying:
  • Ephys channel selection and plotting,
  • Aligned ephys–calcium traces,
  • Spike-triggered calcium responses.

---

⚙️ Dependencies

These scripts rely on the following MATLAB functions and toolboxes:

• abfload.m — for reading .abf electrophysiology files.
• Signal Processing Toolbox — for findpeaks, xcov, etc.
• Image Processing Toolbox — for imshow, tiffreadVolume.

---

🧠 Workflow Summary

1. Record synchronized ephys and imaging data using a TTL line for the camera trigger.
2. Extract calcium traces
3. Run one of the scripts:
   • align_ephys_video.m — for frame-by-frame video alignment.
   • align_ephys_caTrace.m — for calcium trace alignment and quantitative analysis.
4. Inspect alignment and results using the generated plots.
5. Export merged data for further custom analysis.

---

📊 Example Outputs

• Animated alignment plot
  Displays real-time synchronization between imaging frames and electrophysiology signal.

• Merged ephys–calcium plots
  Shows ΔF/F traces aligned to the electrophysiological activity of the patched neuron.

• Spike-triggered calcium response
  Computes average calcium signal around action potentials detected in the ephys trace.

---

🧩 Notes & Tips

• TTL amplitude is assumed to be ~5V. Modify TTL_on and tolerance if your setup differs.
• The script asks for manual correction if frames were removed at the beginning of the video.
• Ensure your .csv calcium file includes frame-by-frame ΔF/F data (first column = frame number or time).
• The props.csv file should contain ROI metadata (optional but recommended).

---

🧑‍🔬 Author

Andrea Locarno, Ph.D.
Postdoctoral Researcher in Christian Broberger´s Lab
Date: Oct-2025