Comparative Bioacoustics Group, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands.
Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music Aarhus/Aalborg, Aarhus, Denmark.
BMC Res Notes. 2023 Jul 5;16(1):135. doi: 10.1186/s13104-023-06396-x.
Researchers in animal cognition, psychophysics, and experimental psychology need to randomise the presentation order of trials in experimental sessions. In many paradigms, for each trial, one of two responses can be correct, and the trials need to be ordered such that the participant's responses are a fair assessment of their performance. Specifically, in some cases, especially for low numbers of trials, randomised trial orders need to be excluded if they contain simple patterns which a participant could accidentally match and so succeed at the task without learning.
We present and distribute a simple Python software package and tool to produce pseudorandom sequences following the Gellermann series. This series has been proposed to pre-empt simple heuristics and avoid inflated performance rates via false positive responses. Our tool allows users to choose the sequence length and outputs a .csv file with newly and randomly generated sequences. This allows behavioural researchers to produce, in a few seconds, a pseudorandom sequence for their specific experiment. PyGellermann is available at https://github.com/YannickJadoul/PyGellermann .
动物认知、心理物理学和实验心理学的研究人员需要在实验过程中随机化试验的呈现顺序。在许多范式中，对于每一次试验，两种反应中有一种是正确的，并且需要对试验进行排序，以便参与者的反应能够公平地评估他们的表现。具体来说，在某些情况下，特别是对于试验次数较少的情况，如果试验顺序中包含参与者可能偶然匹配的简单模式，并且无需学习即可成功完成任务，则需要排除随机试验顺序。
我们提出并分发了一个简单的 Python 软件包和工具，用于生成遵循 Gellermann 序列的伪随机序列。该序列已被提议用于预先阻止简单的启发式方法，并通过虚假阳性反应避免过高的性能率。我们的工具允许用户选择序列长度，并输出一个包含新生成的随机序列的.csv 文件。这允许行为研究人员在几秒钟内为他们的特定实验生成一个伪随机序列。PyGellermann 可在 https://github.com/YannickJadoul/PyGellermann 获得。
