ArticleHuman brain mapping2007
Comparison of different cortical connectivity estimators for high-resolution EEG recordings.
Article in Human brain mapping, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 129 papers.
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Who cites it
129 citing papers in PubMed.
- Trial
- Classifying different emotional states by means of EEG-based functional connectivity patterns.PloS one · 2014Trial
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- Develop an emotion recognition system using jointly connectivity between electroencephalogram and electrocardiogram signals.Heliyon · 2025Article
- Neural control meets biomechanics in the motor assessment of neurological disorders: a narrative review.Frontiers in neural circuits · 2025Review
- Body Surface Potential Mapping: A Perspective on High-Density Cutaneous Electrophysiology.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Virtual resection evaluation based on sEEG propagation network for drug-resistant epilepsy.Scientific reports · 2024Article
- EEG-based schizophrenia detection using fusion of effective connectivity maps and convolutional neural networks with transfer learning.Cognitive neurodynamics · 2024Article
- A Comparative Study of Causality Detection Methods in Root Cause Diagnosis: From Industrial Processes to Brain Networks.Sensors (Basel, Switzerland) · 2024Article
- EEG signatures of cognitive decline after mild SARS-CoV-2 infection: an age-dependent study.BMC medicine · 2024Article
- Article
- Prediction of treatment response in major depressive disorder using a hybrid of convolutional recurrent deep neural networks and effective connectivity based on EEG signal.Physical and engineering sciences in medicine · 2024Article
- An evaluation of inter-brain EEG coupling methods in hyperscanning studies.Cognitive neurodynamics · 2024Article
- EEG Information Transfer Changes in Different Daily Fatigue Levels During Drowsy Driving.IEEE open journal of engineering in medicine and biology · 2024Article
- Sleep Spindle-Related EEG Connectivity in Children with Attention-Deficit/Hyperactivity Disorder: An Exploratory Study.Entropy (Basel, Switzerland) · 2023Article
- Identifying good practices for detecting inter-regional linear functional connectivity from EEG.NeuroImage · 2023Article
- Connectivity Analysis in EEG Data: A Tutorial Review of the State of the Art and Emerging Trends.Bioengineering (Basel, Switzerland) · 2023Review
- Parallel Factorization to Implement Group Analysis in Brain Networks Estimation.Sensors (Basel, Switzerland) · 2023Article
- Time-Varying Functional Connectivity of Rat Brain during Bipedal Walking on Unexpected Terrain.Cyborg and bionic systems (Washington, D.C.) · 2023Article
69 more citing papers are in PubMed but not listed here.
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14 authors.
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Abstract
The aim of this work is to characterize quantitatively the performance of a body of techniques in the frequency domain for the estimation of cortical connectivity from high-resolution EEG recordings in different operative conditions commonly encountered in practice. Connectivity pattern estimators investigated are the Directed Transfer Function (DTF), its modification known as direct DTF (dDTF) and the Partial Directed Coherence (PDC). Predefined patterns of cortical connectivity were simulated and then retrieved by the application of the DTF, dDTF, and PDC methods. Signal-to-noise ratio (SNR) and length (LENGTH) of EEG epochs were studied as factors affecting the reconstruction of the imposed connectivity patterns. Reconstruction quality and error rate in estimated connectivity patterns were evaluated by means of some indexes of quality for the reconstructed connectivity pattern. The error functions were statistically analyzed with analysis of variance (ANOVA). The whole methodology was then applied to high-resolution EEG data recorded during the well-known Stroop paradigm. Simulations indicated that all three methods correctly estimated the simulated connectivity patterns under reasonable conditions. However, performance of the methods differed somewhat as a function of SNR and LENGTH factors. The methods were generally equivalent when applied to the Stroop data. In general, the amount of available EEG affected the accuracy of connectivity pattern estimations. Analysis of 27 s of nonconsecutive recordings with an SNR of 3 or more ensured that the connectivity pattern could be accurately recovered with an error below 7% for the PDC and 5% for the DTF. In conclusion, functional connectivity patterns of cortical activity can be effectively estimated under general conditions met in most EEG recordings by combining high-resolution EEG techniques, linear inverse estimation of the cortical activity, and frequency domain multivariate methods such as PDC, DTF, and dDTF.
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