psychopy-aurora 0.1.0

PsychoPy plugin providing Builder components for NIRx Aurora API integration.

PsychoPy Aurora Plugin (psychopy-aurora)

A PsychoPy Builder plugin that allows you to control NIRx Aurora data acquisition directly from your PsychoPy experiment — without custom scripting.

The plugin provides Builder components to:

• Connect to the Aurora Data Acquisition API
• Run basic setup (device/config selection and signal optimization)
• Start and stop recordings at routine boundaries
• Send event triggers (1–255) via Aurora’s REST API or via LSL markers

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Features

Builder Components

1. AuroraRecorder

• Discovers and connects to Aurora via LSL
• Initializes device and configuration
• Runs signal optimization
• Sets subject and experiment metadata
• Optionally starts/stops recording at routine boundaries

2. AuroraTrigger (REST)

• Sends triggers to Aurora via:

  POST /api/v1/recording/trigger
  

• Uses the active global Aurora connection
• Trigger ID can be a number or PsychoPy variable (e.g., from a conditions file)
• Supports trigger on routine begin or end

3. AuroraTriggerLSL

• Creates an LSL marker outlet
• Uses the trigger_in_stream_name from the selected Aurora configuration
• Pushes int32 trigger samples at routine begin/end
• Useful for LSL-based synchronization pipelines

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Requirements

• Python >= 3.8
• PsychoPy (recent versions recommended)
• Aurora Data Acquisition API running on the same network
• LSL installed and working

Runtime dependencies:

• requests
• pydantic
• pylsl
• rich

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Installation

Install from source (recommended for development)

pip install -e .

Build wheel

python -m build
pip install dist/psychopy_aurora-*.whl

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How It Works

1. Aurora Discovery

The plugin searches for an LSL stream named:

Aurora_API

It then verifies connectivity using:

GET /api/v1/ping

Once connected, all communication is done via:

http://<ip>:<port>/api/v1

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Typical Experiment Workflow

Step 1 – Setup Routine

Add AuroraRecorder:

• Connect to Aurora
• Select device and configuration
• Run signal optimization
• (Optional) Start recording

Step 2 – Task Routine(s)

Add one of:

• AuroraTrigger (REST-based triggers)
• AuroraTriggerLSL (LSL marker triggers)

Place trigger component at stimulus onset routine.

Step 3 – End Routine

Use AuroraRecorder with:

• “Stop recording” enabled

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Example Trigger Usage

If using a conditions file with a column:

trigger

Set Trigger ID to:

trigger

If using a fixed trigger:

9

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Troubleshooting

“No Aurora instance found”

• Ensure Aurora API is running
• Ensure LSL is active
• Verify network connectivity

Triggers not appearing

• REST: Ensure recording is active
• LSL: Ensure outlet was successfully created

Output directory

Current implementation sets output directory to:

%USERPROFILE%/Documents/AuroraTest

Consider making this configurable in future versions.

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Development

Install dev dependencies:

pip install -e .[dev]

Project uses setuptools packaging.

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License

GNU General Public License v3.0 © NIRx Medizintechnik GmbH