audiomath: A neuroscientist's sound toolkit.

Area of Science:

• Neuroscience
• Computational Neuroscience
• Bioacoustics

Background:

• Auditory stimuli are crucial in neuroscientific research, requiring specialized software for generation, manipulation, presentation, and recording.
• Existing tools often have disparate functionalities, necessitating significant integration effort and engineering for precise stimulus timing verification.
• Accurate stimulus timing is a persistent challenge in developing neuroscientific applications.

Purpose of the Study:

• To introduce audiomath, a Python sound software library designed for neuroscientists.
• To unify audio generation, manipulation, visualization, decoding, encoding, recording, and playback functionalities.
• To provide insights into the challenges of precise stimulus timing and measurement, based on software development experience.

Main Methods:

• Development of the audiomath Python library with an object-oriented interface.
• Integration of specialized tools for measuring and optimizing stimulus timing.
• Analysis of audio latency across various hardware, operating systems, and configurations.

Main Results:

• audiomath simplifies auditory stimulus development by unifying diverse functionalities.
• The library offers specialized tools for precise stimulus timing measurement and optimization.
• Latency measurements reveal interactions between hardware, software, and stimulus presentation performance, highlighting potential pitfalls.

Conclusions:

• audiomath streamlines the development of neuroscientific applications by unifying audio-related tasks.
• The library aids in navigating the complexities of low-latency, low-jitter stimulus delivery and measurement.
• audiomath empowers researchers to prioritize and achieve specific application goals in auditory stimulus presentation.