A Causal Formulation of Spike-Wave Duality
神经尖峰—波二重性的因果表述AI 解读 ↓
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神经尖峰—波二重性的因果表述
- 研究问题
- 脑活动中的群体波是否具有独立因果作用，还是仅反映神经元尖峰的动态；需要什么结构假设或实验才能区分二者？
- 方法与思路
- 作者在结构因果模型中以干预分布不变性定义附带现象，并通过 do 演算推导可删除变量而不损失因果解释力的充分性证书。
- 材料陈述的贡献
- 摘要称，框架明确观察数据的局限，给出变量可删除的充分条件，并说明不同尖峰—波因果结构下应如何解释干预。
- 阅读关注点
- 应核对附带现象的形式定义、充分性证书对应的图结构、删除变量后的效应保持范围，以及可实现实验与模型干预的对应关系。
- 阅读边界
- 这是 arXiv 预印本，不能据此确认同行评审或期刊接收；摘要未给出证书细节，作者也未宣称解决尖峰—波争论或验证具体脑机制。
原文摘要
Understanding the relationship between brain activity and behavior is a central goal of neuroscience. Despite significant advances, a fundamental dichotomy persists: neural activity manifests as both discrete spikes of individual neurons and collective waves of populations. Both neural codes correlate with behavior, yet correlation alone cannot determine whether waves exert a causal influence or merely reflect spiking dynamics without causal efficacy. According to the Causal Hierarchy Theorem, no amount of observational data--however extensive--can settle this question; causal conclusions require explicit structural assumptions or careful experiment designs that directly correspond to the causal effect of interest. We develop a formal framework that makes this limitation precise and constructive. Formalizing epiphenomenality via the invariance of interventional distributions in Structural Causal Models (SCMs), we derive a certificate of sufficiency from Pearl's do-calculus that specifies when variables can be removed from the model without loss of causal explainability and clarifies how interventions should be interpreted under different causal structures of spike-wave duality. The purpose of this work is not to resolve the spike-wave debate, but to reformulate it. We shift the problem from asking which signal matters most to asking under what conditions any signal can be shown to matter at all. This reframing distinguishes prediction from explanation and offers neuroscience a principled route for deciding when waves belong to mechanism and when they constitute a byproduct of underlying coordination