追问Newsletter第2期 | 动物研究能在多大程度上帮助我们理解人脑?
在不久前结束的TCCI NeuroChat(神聊)全球华人青年科学家认知科学会议中,天桥脑科学研究院(TCCI)联合Neurochat主办方发起“追问”活动,向此次会议演讲者征集了最受大家关注的神经科学问题。我们已经邀请资深科学家教授回答这些问题,并将在后续发表这些问答并组织更多相关活动,敬请期待。
罗艺博士的问题“What do you think are the biggest breakthroughs in social neuroscience in the recent 10 years? And what are you most excited to see develop in the future?”目前已经得到加州理工学院Ralph Adolphs教授的回答,点击此处查看详情。
而青年科学家提出的有关神经科学研究方法的问题,我们也收到了纽约大学György Buzsáki教授的回答,以下为具体内容。
György Buzsáki
纽约大学医学院Biggs神经科学教授
美国国家科学院院士,美国科学促进会会士,欧洲科学院院士
Buzsáki教授是一位系统神经科学家,是被引率最高的神经科学家之一,他的研究主要关注大脑振荡、睡眠、记忆和相关疾病等领域,以其两阶段记忆巩固模型,发现支持认知、神经句法和脑节律的神经细胞集合,以及他在神经科学领域的创新技术而闻名。2019年出版著作《大脑由内向外》(The Brain from Inside Out)。
Q
动物研究能在多大程度上帮助我们理解人脑?
To what extent would animal research help to understand the human brain?
除非你给我一个“理解”的计量标尺,我才可以回答这个问题。对每个人来说,“许多”“非常”“极其”等词语的含义是不同的,没有统一的量化标准。科学论述总是从定量测量开始的,这就需要相应的可量化的仪器或计量方法。比如,有了时钟后,用时刻表示时间;有了标尺后,用距离表示空间;有了IQ单位后,用智力值表示智力。
Give me a yardstick that has units of "understanding" and I can give you an answer. A lot, greatly, tremendously, etc are not quantitative terms with the same meaning to everyone. Scientific discourse always starts with quantitative measurements, which requires instruments or means with units. Time became time with the clocks, space became distance with the rod, intelligence became intelligence with the introduction of IQ units.
除此之外,我还想知道,除了动物研究,我们还有什么方法可以了解人脑呢?动物研究之所以重要,至少有两个原因。首先,要想了解神经元回路或认知,则需要能观察单个神经元或单个峰电位的分辨率。这是因为神经元之间通过峰电位交流。其他的间接测量法都需要转换为峰电位,或估计其与峰电位之间的关系。在人身上进行这样的研究,是行不通的(为了自身利益而在身上安装电极的少数病人除外)。其次,且可能更重要的是,了解某些功能和解决方法是如何发展的,往往是理解问题的关键。与在复杂的大脑进行研究相比,在最简单、最纯粹的形式下检验一种作用机制,可能会提供更多的见解。例如,大脑演化出了独特的伴随放电现象,来区别神经元活动是由外界刺激引起的还是由自身活动引起的(如其他人发出的声音或你自己发出的声音)。该机制在蟋蟀中的呈现形式非常简单,但同样的原则也适用于更复杂的操作(如识别自我和非我)或疾病(如精神分裂症)。
Apart from these comments, I can ask what else is there for us to understand the human brain than animal research? Research on animals is important for at least two different reasons. First, understanding neuronal circuits or cognition requires methods that allow single neuron, single spike resolution. The reason is that the neurons communicate with spikes. Every other indirect measure needs to be converted to spikes or estimation of the relationship to spikes. Such research is ethically not feasible in humans (save a few patients who have electrodes for their own benefits). Second, and perhaps more importantly, understanding how certain functions and solutions developed is often a key to understanding. Examining a mechanism in its simplest and purest form can provide more insight than searching for the same principles in more complex brains. For example, corollary discharge is an extraordinary invention of brain evolution that allows for distinguishing neuronal activity arising from the impact of the external world or from self-organized activity, such as the sound you make or made by others. This mechanism can be studied in its pure form e.g., in a cricket but the same principle is present in more complex operations such as distinguishing the self from non-self or in disease, such as schizophrenia.
Q
我们距离缩小微观、回路层面神经科学与研究复杂认知过程的人类神经科学之间的差距还有多远?
How far are we from bridging the gap between microscopic, circuit-level neuroscience and human neuroscience studying complex cognitive processes such as knowledge and language?
同上,我认为问题在于测量单位(或缺乏测量单位)。科学的进步并不是一帆风顺或可预测的。因此,预测科研发现的里程碑这项工作,还是留给政客、远见者或预言家吧。
Again, my problem is with the units of measurement (or the lack of it). Progress in science is not smooth or predictable. Thus, predicting milestones of discovery is a job left for politicians and visionaries (or fortunate tellers who are in the same category).
在没有回路层面操作的情况下,很难对单个细胞的功能进行研究,反之亦然。任何层次的好研究都应该既与上一层级相关联,也与下一层级相关联。以语言为例,语言包括语音、信息整合、语义三个方面。大脑节律对于信息整合至关重要。然而,产生语言所需的所有网络振荡,以相同的形状和形式存在于所有哺乳动物中。因此,语言的一个关键成分是基于一个已研究地非常清楚的机制(该机制还承担许多其他功能)。语义和语法的大脑机制当然更加复杂,但它们也是由与写这些文字或只是移动我的手臂一样的基本回路机制产生的。
Understanding single cell functions without circuit operations or vice versa is difficult. Good research at any level should always have a link to the level below and the level above. Take language as an example. Language has phonemic, information packaging and semantic aspects. Brain rhythms are crucial for the information packaging aspect. Yet, all network oscillations that are needed to produce speech are present in all mammals in the same shape and form. Thus, a key ingredient of language is based on an already available mechanism that serves many other functions. The brain mechanisms of semantic knowledge and syntax are surely more complicated but they also produced by the same kind of fundamental circuit mechanisms as writing this text or just moving my arm.
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