模式
神经影像学
神经科学
大脑活动与冥想
透视图(图形)
计算机科学
统一
比例(比率)
认知科学
脑功能
心理学
认知心理学
脑电图
人工智能
物理
社会学
程序设计语言
量子力学
社会科学
作者
Eli J. Müller,Brandon Munn,Kevin Aquino,James M. Shine,P. A. Robinson
标识
DOI:10.3389/fnhum.2022.1062487
摘要
Neuroscience has had access to high-resolution recordings of large-scale cortical activity and structure for decades, but still lacks a generally adopted basis to analyze and interrelate results from different individuals and experiments. Here it is argued that the natural oscillatory modes of the cortex-cortical eigenmodes-provide a physically preferred framework for systematic comparisons across experimental conditions and imaging modalities. In this framework, eigenmodes are analogous to notes of a musical instrument, while commonly used statistical patterns parallel frequently played chords. This intuitive perspective avoids problems that often arise in neuroimaging analyses, and connects to underlying mechanisms of brain activity. We envisage this approach will lead to novel insights into whole-brain function, both in existing and prospective datasets, and facilitate a unification of empirical findings across presently disparate analysis paradigms and measurement modalities.
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