Abstract：
A common research protocol in cognitive neuroscience is to train subjects to perform deliberately designed experiments while recording brain activity, with the aim of understanding the brain mechanisms underlying cognition. However, how the results of this protocol of research can be applied in technology is seldom discussed. Here, I review the studies on time processing of the brain as examples of this research protocol, as well as two main application areas of neuroscience (neuroengineering and brain-inspired artificial intelligence). Time processing is a fundamental dimension of cognition, and time is also an indispensable dimension of any real-world signal to be processed in technology. Therefore, one may expect that the studies of time processing in cognition profoundly influence brain-related technology. Surprisingly, I found that the results from cognitive studies on timing processing are hardly helpful in solving practical problems. This awkward situation may be due to the lack of generalizability of the results of cognitive studies, which are under well-controlled laboratory conditions, to real-life situations. This lack of generalizability may be rooted in the fundamental unknowability of the world (including cognition). Overall, this paper questions and criticizes the usefulness and prospect of the abovementioned research protocol of cognitive neuroscience. I then give three suggestions for future research. First, to improve the generalizability of research, it is better to study brain activity under real-life conditions instead of in well-controlled laboratory experiments. Second, to overcome the unknowability of the world, we can engineer an easily accessible surrogate of the object under investigation, so that we can predict the behavior of the object under investigation by experimenting on the surrogate. Third, the paper calls for technology-oriented research, with the aim of technology creation instead of knowledge discovery.
摘要：
认知神经科学中一个常见的研究协议是训练受试者在记录大脑活动的同时进行故意设计的实验，目的是了解认知背后的大脑机制。然而,很少讨论该协议的研究结果如何应用于技术。这里,我回顾了关于大脑时间处理的研究，作为这个研究方案的例子，以及神经科学的两个主要应用领域（神经工程和大脑启发的人工智能）。时间处理是认知的一个基本维度,时间也是任何现实世界信号在技术中处理的不可或缺的维度。因此,人们可能会期望认知中时间处理的研究会对大脑相关技术产生深远的影响。令人惊讶的是,我发现认知研究对时间处理的结果对解决实际问题几乎没有帮助。这种尴尬的局面可能是由于认知研究结果缺乏概括性,在良好控制的实验室条件下，现实生活中的情况。这种普遍性的缺乏可能源于世界的根本不可知性（包括认知）。总的来说,本文对上述认知神经科学研究方案的有用性和前景进行了质疑和批评。对今后的研究提出三点建议。首先,为了提高研究的普遍性，最好是在现实生活条件下研究大脑活动，而不是在控制良好的实验室实验中。第二,为了克服世界的不可知性，我们可以设计一个容易接近的被调查对象的代理人，这样我们就可以通过在代理人上进行实验来预测被调查对象的行为。第三，论文呼吁以技术为导向的研究，目的是创造技术而不是发现知识。
