Lareo Angel, Forlim Caroline G, Pinto Reynaldo D, Varona Pablo, Rodriguez Francisco de Borja
Grupo de Neurocomputación Biológica, Departamento de Ingeniería Informática, Escuela Politécnica superior, Universidad Autónoma de Madrid Madrid, Spain.
Department of Data Analysis, Faculty of Psychology and Educational Sciences, Ghent University Ghent, Belgium.
Front Neuroinform. 2016 Oct 6;10:41. doi: 10.3389/fninf.2016.00041. eCollection 2016.
Closed-loop activity-dependent stimulation is a powerful methodology to assess information processing in biological systems. In this context, the development of novel protocols, their implementation in bioinformatics toolboxes and their application to different description levels open up a wide range of possibilities in the study of biological systems. We developed a methodology for studying biological signals representing them as temporal sequences of binary events. A specific sequence of these events (code) is chosen to deliver a predefined stimulation in a closed-loop manner. The response to this code-driven stimulation can be used to characterize the system. This methodology was implemented in a real time toolbox and tested in the context of electric fish signaling. We show that while there are codes that evoke a response that cannot be distinguished from a control recording without stimulation, other codes evoke a characteristic distinct response. We also compare the code-driven response to open-loop stimulation. The discussed experiments validate the proposed methodology and the software toolbox.
闭环活动依赖刺激是评估生物系统中信息处理的一种强大方法。在此背景下,新型协议的开发、它们在生物信息学工具箱中的实现以及它们在不同描述层面的应用,为生物系统研究开辟了广泛的可能性。我们开发了一种将生物信号表示为二元事件时间序列来进行研究的方法。选择这些事件的特定序列(代码)以闭环方式提供预定义刺激。对这种代码驱动刺激的响应可用于表征系统。该方法在一个实时工具箱中实现,并在电鱼信号的背景下进行了测试。我们表明,虽然有些代码引发的响应与无刺激的对照记录无法区分,但其他代码会引发独特的特征响应。我们还将代码驱动的响应与开环刺激进行了比较。所讨论的实验验证了所提出的方法和软件工具箱。