From Complexity to Simplicity: Using Python Instead of PsychoPy for fNIRS Data Collection

TL;DR

This paper introduces a Python-based method for fNIRS data collection that simplifies the setup by eliminating the need for a separate device, enabling marker transmission and data collection on a single computer.

Contribution

The authors present a novel Python implementation for direct marker transmission in fNIRS studies, replacing the traditional PsychoPy setup and reducing hardware complexity.

Findings

Streamlined data collection process with Python implementation

Elimination of additional hardware for marker transmission

Enhanced accessibility and efficiency in fNIRS studies

Abstract

Functional near-infrared spectroscopy (fNIRS) is a non-invasive optical technique that measures brain activity by estimating blood oxygenation using near-infrared light. Traditionally, PsychoPy is used in many studies to send task-specific markers, requiring a separate device to interface with the fNIRS data collection system. In this work, we present a Python-based implementation to send markers directly, eliminating the need for an additional device. This approach allows researchers to run both marker transmission and fNIRS data collection on the same computer, simplifying the setup and enhancing accessibility. This streamlined solution reduces hardware requirements and makes fNIRS studies more efficient.