神经科学与心理学2016biorxiv.org编辑精选
神经科学家能理解微处理器吗？
Could a neuroscientist understand a microprocessor?
进阶 · 约 60 分钟读完前置知识：神经科学基础、实验设计基础
导读
这篇论文提出一个思想实验：用神经科学常用的研究方法（如损伤实验、电生理记录等）去分析一颗我们完全了解的微处理器，检验这些方法能否真正理解芯片的工作原理。作者借此论证传统神经科学方法可能过于粗糙，难以揭示大脑的真实工作机制，提醒学界警惕对实验结果的过度解读。
HN 关注点：是因为它用'研究芯片'这一巧妙类比质疑神经科学方法论的可靠性，引发了关于脑-计算机类比是否成立、以及现有研究范式局限性的激烈讨论。
后来怎么样
这篇论文引发了神经科学界关于研究方法有效性的广泛讨论，成为'用已知系统检验分析方法'这一思路的代表作，常被后续方法论研究引用。
HN 评论精选
这几条评论里：质疑 2 补充 2
补充指出论文标题致敬了 Lazebnik 的经典类比文章
这个标题像是在致敬 Lazebnik 的著名文章《生物学家能修好收音机吗？》
gumby查看英文原文
This title sounds like an homage to Lazebnik's famous essay "Can a biologist fix a radio?" (http://www.ncbi.nlm.nih.gov/pubmed/12242150)
补充认为方法确实粗糙但领域自知，新技术（光遗传等）已能做因果推断，前景乐观
这个思路很有趣。传统神经科学方法确实太粗糙，结果常被过度解读，神经科学家自己也知道这一点——这也是蓝脑计划等大规模电路模拟只产出'振荡统计'的原因。不过也有成功案例，比如早期电生理研究已将杏仁核与行为建立了因果联系。前景还是有的：如今的光遗传学和分子技术可以观察、激活和灭活单个神经元，从而做出因果推断。
return0查看英文原文
What a fun approach. It's true that traditional neuroscience methods are too crude to give insight to brain functions and results are often over-interpreted. Neuroscientists know that however [1], and that's why attempts to simulate large circuits like the blue brain project or the simulated cat model produced nothing more than "oscillation statistics". Despite their crudeness, there are cases where circuits (like the amygdala) were causally linked to behavior by early electrophysiology . There is hope however, as there are now optical and molecular methods that make it possible to observe , activate, and inactivate individual neurons, which allows making causal inferences[2]. 1: http://compneuro.uwaterloo.ca/files/publications/eliasmith.2013a.pdf 2: https://www.sciencedaily.com/releases/2015/05/150528142815.htm
质疑质疑论文推理草率，脑-芯片类比本身不成立，结论被过度简化
想法很酷但推理草率且傲慢。我同情作者的出发点——这个领域确实存在糟糕的统计和为博眼球而生的临时理论。但这篇论文把问题过度简化到不值一提的程度：把来自神秘领域的方法套用到我们更了解的领域，因为无法复现已有理解就断定工具有问题。脑-计算机只是类比，是明知不准确的抽象；作者自己也承认损伤电路板和损伤大脑完全不同，那凭什么用芯片损伤实验来评判脑损伤研究？
ramblenode查看英文原文
+1 for a cool and thought-provoking idea but -1 for more sloppy/faulty reasoning and arrogance than could be overlooked by a sincerely interested reader. I am sympathetic to the angle this is coming from. Yes, the field has a serious problem with shoddy statistics and post-hoc theories optimized for sexiness. But this paper vastly oversimplifies the problem domain to the point of trivializing it. The approach of this paper is to take techniques from a largely mysterious domain, apply them to a vastly different domain that we understand much better, and conclude that because we can't replicate our prior understanding of the known domain there must be a problem with the tools. My guess is that this approach looks less ridiculous on the surface because of how entrenched the brain-computer metaphor is--but don't forget it is just an anology: a knowingly incorrect abstraction. As the authors admit, lesioning a circuit board is totally different from lesioning a brain. So why on earth should we be talking about how much we can learn from brain lesions based on our understanding of microprocessor lesions? (not a rhetorical question--I am genuinely curious if I am missing something here because this absolutely confounds me)
质疑指出论文遗漏双重分离这一标准方法，且低估了拓扑结构在损伤分析中的作用
有趣的论文，但我卡在了损伤实验那部分论证上。为什么完全没提单重和双重分离（dissociation）？只讨论了单重分离，而它只能说明必要性、不能说明充分性，这在心理学与神经科学界是常识，几乎所有研究都基于双重分离。另外，论文似乎忽视了拓扑结构的重要性：描述层级越低（系统→神经元→分子），单元间连接的拓扑越关键——把芯片上晶体管的连接打乱后，行为 Y 仍可实现，但损伤晶体管 X 不再导致行为 Y 失效，所以得到的并非'大量相同的收音机'，而是大量功能相同但拓扑不同的设备。
Phemist查看英文原文
Interesting paper, thanks! I'll need to work through it more at a later time, because I got stuck at the Lesion studies argument. I'm sorry if this seems a bit ranty.. As for lesion studies, I wonder why there was no mention of single and double dissociation? Only single dissociation was discussed, and although it is tempting to say lesioned area X is uniquely responsible (a combination of necessary and sufficient) for behaviour Y, it only tells you something about its necessity, and nothing about its sufficiency. This is generally known in Psychology & Neuroscience, which is why almost all studies base themselves on double dissociation. It allows you to say sensible stuff about differences between behaviours at the same level of description (Space invaders vs Donkey Kong being different, for example), due to differences in a lower level of description. Also, I feel like the importance of topology is somewhat disregarded in discussion of these lesion studies? As we go lower down in levels of description - systems, to clusters, to individual neurons or even molecules, topology of the units of description becomes more and more important. Imagine enumerating every transistor on the chip and switching their connectedness around to the point where behaviour Y can still be performed, but lesioning transistor X no longer makes behaviour Y impossible. So we don't actually obtain a "large number of identical radios", we obtain a large number of functionally identical, but topologically different, radios, and then shoot metal particles at them to understand under which conditions area X does produce behaviour Y. This, to me, seems a lot less futile and a lot more informing then what the section on lesion studies leads me to believe?
相关资源
从这篇论文所有 HN 讨论帖的全部评论里整理出来的链接。
- 自称作者的回复
历次讨论
- 2016Hacker News 讨论帖196 分 · 50 评
同领域还值得读
神经科学家能理解微处理器吗？（2017）
Could a Neuroscientist Understand a Microprocessor? (2017)
提出一个思想实验：把神经科学常用的分析方法（损伤实验、电生理、功能定位等）应用到一个我们完全了解其原理的工程系统——6502 微处理器（运行游戏）上，检验这些方法能否真正“理解”…
神经科学与心理学2017 · 411 分 · 135 评进阶 · 约 60 分钟编辑精选大脑衰老呈现非线性转变，提示中年“关键窗口”
Brain aging shows nonlinear transitions, suggesting a midlife "critical window"
这篇 PNAS 论文研究大脑衰老的非线性变化，发现大脑老化并非匀速进行，而是在中年（约 40-60 岁）存在一个关键的"临界窗口期"，此时干预可能有效。
神经科学与心理学2025 · 295 分 · 159 评进阶 · 约 75 分钟编辑精选社交网络中大规模情绪传染的证据（2014）
Evidence of massive-scale emotional contagion through social networks (2014)
这篇 2014 年发表于 PNAS 的论文研究了 Facebook 上约 70 万用户的信息流中，减少正面或负面内容是否会传染性地影响用户自己发布内容的情绪。
神经科学与心理学2020 · 285 分 · 72 评入门 · 约 45 分钟编辑精选裸盖菇素使人类大脑去同步化
Psilocybin desynchronizes the human brain
这篇 Nature 研究用个体化的 fMRI 精密成像追踪受试者服用裸盖菇素（psilocybin）前后的脑功能连接变化，发现药物会造成大范围的脑网络「去同步化」，尤其是默认模式…
神经科学与心理学2024 · 273 分 · 259 评进阶 · 约 60 分钟编辑精选对智力的赞扬会削弱儿童的动机与表现（1998）
Praise for Intelligence Can Undermine Children's Motivation (1998)
这篇 1998 年的经典论文（Dweck 等人）通过实验研究表扬方式对儿童动机的影响：夸孩子“聪明”（表扬智力）会让他们回避挑战、害怕失败，而表扬努力则更能培养坚持性。
神经科学与心理学2016 · 253 分 · 155 评入门 · 约 45 分钟编辑精选