All of the software allows for use of experimental control and management, resulting in good time performances for experiments. It is necessary, for example, to have a jitter of <1 ms to be able to interpret the cortical responses with a temporal precision of ∼10 ms.Ī wide range of software is available to present stimulations to human participants in behavioral and electrophysiological (including EEG) experiments, such as famous programs like Presentation ( ), OpenSesame ( Mathôt et al., 2012), Eprime ( Taylor and Marsh, 2017), Psychopy ( Peirce, 2007), and Psychtoolbox ( Borgo et al., 2012), the latter in MATLAB. The temporal accuracy of the analysis is directly dependent on the temporal accuracy of the stimulation system. This will therefore influence analysis and results, particularly in research areas in which a strong temporal accuracy is required, as for example in time-locked behavior or brain activity analysis (e.g., reaction time, evoked related potentials, phase coherence). For example, hardware and software variations are likely to lead to deviations in the presentation and synchronization timing (i.e., onset and jitter). Even small differences in terms of hardware or software might have repercussions, which are not always tested and reported in studies and can lead to important sources of error impacting the replication in studies ( Plant and Quinlan, 2013). These are likely to vary from one laboratory to another because of differences in operating system, drivers, or updates between studies. Even when using fixed software, there is still a wide variability because of computer hardware and installations. Currently, software for stimulation protocols in behavioral and electrophysiological assessments (e.g., having subjects hear a specific auditory stimuli) can be expensive and proprietary, and often requires technical support (whether open source or not).
Working with such low-cost, powerful, and collaborative hardware and software tools allows people to create their own specific, adapted, and shareable system that can be standardized across different collaborative sites, while being extremely simple and robust in use.Ĭollaboration between centers is not always easy with regard to hardware and software compatibility. It is inexpensive, easy to build, share, and improve on. The present system shows high performances and results along with excellent feedback from users.
This solution achieves the high timing accuracy and sound quality important in auditory cognition experiments, while being simple to use and open source. We compare its sound performances with those of a wide variety of materials and configurations. This article outlines a system composed by a Raspberry Pi coupled with Python programming and associated with a HifiBerry sound card. Currently, there is no easy to use, inexpensive, and shareable solution that could improve collaborations and data comparisons across different sites and contexts. In auditory behavioral and EEG experiments, the variability of stimulation solutions, for both software and hardware, adds unnecessary technical constraints.