Open Ephys

Create a signal chain with a Source node and a Bandpass Filter.

Add a 'Phase Detector' plugin set to the target frequency (e.g., 8Hz theta).

Connect the detector to a 'TTL Generator' node.

Route the TTL pulse to an LED driver via the I/O board.

Initialize the Neuropixels Source node.

Set the recording node to 'Binary' format for high-speed disk I/O.

Enable the 'LFP Viewer' to monitor probe drift in real-time.

Monitor disk space via the built-in GUI indicator.

Connect the camera trigger signal to a digital input on the Acquisition Board.

Add the 'Event Viewer' node to the signal chain.

Use the 'Record Node' to save the digital events alongside the neural data.

Extract timestamps in Python to align .mp4 frames with spike times.

Add a 'Spike Sorter' node to the chain.

Define manual thresholds for specific channels.

Use the PCA visualizer to cluster waveforms into units.

Adjust probe depth until high-quality units are isolated.

Add a 'Spectrogram' node after the filter.

Select specific channels representing the target brain region.

Observe the 1-4Hz (Delta) vs 8-12Hz (Alpha) power ratio in real-time.

Flag specific segments in the recording using the 'Event Button' node.

Connect two Acquisition Boards via a sync cable.

Instantiate two Source nodes in the GUI.

Separate the signal chains into distinct recording streams.

Verify clock synchronization using the 'Sync' status indicator.

Stream raw data via the ZeroMQ interface to a Python script.

Apply a pre-trained Deep Learning model for denoising in Python.

Stream the cleaned data back into the GUI via the 'Network Source' node.

Record the cleaned stream for analysis.