Untangling cross-frequency coupling in neuroscience

By Juhan Aru, Jaan Aru, Viola Priesemann, Michael Wibral, Raul Vicente. bioRxiv, 2014

538 citations recorded by the source corpus.

Cross-frequency coupling (CFC) has been proposed to coordinate neural dynamics across spatial and temporal scales. Despite its potential relevance for understanding healthy and pathological brain function, the standard CFC analysis and physiological interpretation come with fundamental problems. For example, apparent CFC can appear because of spectral correlations due to common non-stationarities that may arise in the total absence of interactions between neural frequency components. To provide a road map towards an improved mechanistic understanding of CFC, we organize the available and potential novel statistical/modeling approaches according to their biophysical interpretability. While we do not provide solutions for all the problems described, we provide a list of practical recommendations to avoid common errors and to enhance the interpretability of CFC analysis. Highlights Fundamental caveats and confounds in the methodology of assessing CFC are discussed. Significant CFC can be observed without any underlying physiological coupling. Non-stationarity of a time-series leads to spectral correlations interpreted as CFC. We offer practical recommendations, which can relieve some of the current confounds. Further theoretical and experimental work is needed to ground the CFC analysis.

Subfields: Cognitive Neuroscience, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/2f575d52fb8c9e0d2d0abb2b327808243fde87f0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

1. André Moraes Bastos
2. Jan-Mathijs Schoffelen
3. Pascal Fries

Citations in the corpus

• Neural Cross-Frequency Coupling: Connecting Architectures, Mechanisms, and Functions. (2015, unknown): “Recently, the development of novel statistical methods has allowed discrimination between the different coupling modes in recorded data [21 – 25].”
• A Tutorial Review of Functional Connectivity Analysis Methods and Their Interpretational Pitfalls (2016, methodology): “We will also not review methods that quantify phase-amplitude coupling as they are beyond the scope of this review and have been discussed extensively elsewhere (Canolty and Knight, 2010; Aru et al., 2015).”
• Intracranial EEG signals disentangle multi-areal neural dynamics of vicarious pain perception (2024, methodology): “The employment of varying bandwidth rather than fi xed bandwidth for the amplitude component was to ensure that the band of amplitude component was suf fi ciently large to contain the peaks produced by the low-frequency phase 99,100 .”
• Theta-gamma phase-amplitude coupling: physiological basics, analysis methods, and perspectives of translation into clinical practice (2022, unknown): “В частности, при расчёте сопряжения между компонентами одного сигнала значимый результат может возникать при наличии нелинейных (не синусных) колебаний, которые могут генерироваться одной популяцией [11].”
• Prefrontal Hierarchical Control of Corticomuscular Coherence in Stroke (2026, unknown): “Studies of PAC were initially conducted in the cognitive neurosciences [26], [30], [31], but recent investigations have expanded clinically to include cohorts with neuromuscular disorders [28], [32], including stroke [6], [33] and Parkinson’s disease [34].”