ArticleBrain sciences2020
The Temporal and Spatial Dynamics of Cortical Emotion Processing in Different Brain Frequencies as Assessed Using the Cluster-Based Permutation Test: An MEG Study.
Article in Brain sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- State-base dynamic functional connectivity analysis of fMRI data during facial emotional processing.Brain imaging and behavior · 2025Article
- Temporal dynamics of affective scene processing in the healthy adult human brain.Neuroscience and biobehavioral reviews · 2025Review
- Understanding the role of emotion in decision making process: using machine learning to analyze physiological responses to visual, auditory, and combined stimulation.Frontiers in human neuroscience · 2023Article
- Testing EEG functional connectivity between sensorimotor and face processing visual regions in individuals with congenital facial palsy.Frontiers in systems neuroscience · 2023Article
- Dynamic Functional Connectivity of Emotion Processing in Beta Band with Naturalistic Emotion Stimuli.Brain sciences · 2022Article
- Comparative analysis of default mode networks in major psychiatric disorders using resting-state EEG.Scientific reports · 2021Article
- The Right Hemisphere Is Responsible for the Greatest Differences in Human Brain Response to High-Arousing Emotional versus Neutral Stimuli: A MEG Study.Brain sciences · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
The processing of emotions in the human brain is an extremely complex process that extends across a large number of brain areas and various temporal processing steps. In the case of magnetoencephalography (MEG) data, various frequency bands also contribute differently. Therefore, in most studies, the analysis of emotional processing has to be limited to specific sub-aspects. Here, we demonstrated that these problems can be overcome by using a nonparametric statistical test called the cluster-based permutation test (CBPT). To the best of our knowledge, our study is the first to apply the CBPT to MEG data of brain responses to emotional stimuli. For this purpose, different emotionally impacting (pleasant and unpleasant) and neutral pictures were presented to 17 healthy subjects. The CBPT was applied to the power spectra of five brain frequencies, comparing responses to emotional versus neutral stimuli over entire MEG channels and time intervals within 1500 ms post-stimulus. Our results showed significant clusters in different frequency bands, and agreed well with many previous emotion studies. However, the use of the CBPT allowed us to easily include large numbers of MEG channels, wide frequency, and long time-ranges in one study, which is a more reliable alternative to other studies that consider only specific sub-aspects.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.