Causal inference in cognitive neuroscience.

IF 3.2 2区 心理学 Q1 PSYCHOLOGY, EXPERIMENTAL
Wiley Interdisciplinary Reviews-Cognitive Science Pub Date : 2023-09-01 Epub Date: 2023-04-09 DOI:10.1002/wcs.1650
David Danks, Isaac Davis
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引用次数: 2

Abstract

Causal inference is a key step in many research endeavors in cognitive science and neuroscience, and particularly cognitive neuroscience. Statistical knowledge is sufficient for prediction and diagnosis, but causal knowledge is required for action and intervention. Most statistics courses and textbooks emphasize the difficulty of causal inference, focusing on the maxim that "correlation does not mean causation": there can be multiple causal possibilities, often many of them, consistent with given observed statistics. This paper focuses instead on the conceptual issues and assumptions that confront causal and other kinds of inference, primarily focusing on cognitive neuroscience. We connect inference methods with goals and challenges, and provide concrete guidance about how to select appropriate tools for the scientific task. This article is categorized under: Psychology > Theory and Methods Philosophy > Foundations of Cognitive Science.

Abstract Image

认知神经科学中的因果推理。
因果推理是认知科学和神经科学,特别是认知神经科学中许多研究工作的关键一步。统计知识足以进行预测和诊断,但行动和干预需要因果知识。大多数统计学课程和教科书都强调因果推断的难度,重点是“相关性并不意味着因果关系”这句格言:可以有多种因果可能性,通常是其中的许多,与给定的观察到的统计数据一致。本文转而关注因果推理和其他推理所面临的概念问题和假设,主要关注认知神经科学。我们将推理方法与目标和挑战联系起来,并就如何为科学任务选择合适的工具提供具体指导。本文分类如下:心理学>理论与方法哲学>认知科学基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.30
自引率
7.70%
发文量
50
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