The Temporal and Spatial Dynamics of Cortical Emotion Processing in Different Brain Frequencies as Assessed Using the Cluster-Based Permutation Test: An MEG Study

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.

[1]  R. Oostenveld,et al.  Nonparametric statistical testing of EEG- and MEG-data , 2007, Journal of Neuroscience Methods.

[2]  Michela Balconi,et al.  Appetitive vs. defensive responses to emotional cues. Autonomic measures and brain oscillation modulation , 2009, Brain Research.

[3]  Robert Oostenveld,et al.  FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data , 2010, Comput. Intell. Neurosci..

[4]  L. Aftanas,et al.  Affective picture processing: event-related synchronization within individually defined human theta band is modulated by valence dimension. , 2001, Neuroscience Letters.

[5]  L. Schmidt,et al.  Cross-regional cortical synchronization during affective image viewing , 2010, Brain Research.

[6]  Matthias M. Müller,et al.  Processing of affective pictures modulates right-hemispheric gamma band EEG activity , 1999, Clinical Neurophysiology.

[7]  Antonio Schettino,et al.  Electrophysiological correlates of the interplay between low-level visual features and emotional content during word reading , 2018, Scientific Reports.

[8]  Thomas Elbert,et al.  Emotion Processing in the Visual Brain: A MEG Analysis , 2008, Brain Topography.

[9]  Matthias M. Müller,et al.  Effects of emotional arousal in the cerebral hemispheres: a study of oscillatory brain activity and event-related potentials , 2001, Clinical Neurophysiology.

[10]  Eric Maris,et al.  Randomization tests for ERP topographies and whole spatiotemporal data matrices. , 2004, Psychophysiology.

[11]  A. Engel,et al.  Beta-band oscillations—signalling the status quo? , 2010, Current Opinion in Neurobiology.

[12]  Angelo Gemignani,et al.  The dynamics of EEG gamma responses to unpleasant visual stimuli: From local activity to functional connectivity , 2012, NeuroImage.

[13]  Begoña García-Zapirain,et al.  Comparison of background EEG activity of different groups of patients with idiopathic epilepsy using Shannon spectral entropy and cluster-based permutation statistical testing , 2017, PloS one.

[14]  Vitória Piai,et al.  Statistically comparing EEG/MEG waveforms through successive significant univariate tests: how bad can it be? , 2015, Psychophysiology.

[15]  Richard Coppola,et al.  Convergent BOLD and Beta-Band Activity in Superior Temporal Sulcus and Frontolimbic Circuitry Underpins Human Emotion Cognition. , 2015, Cerebral cortex.

[16]  S. Taulu,et al.  Applications of the signal space separation method , 2005, IEEE Transactions on Signal Processing.

[17]  C. Braun,et al.  Waves of regret: A meg study of emotion and decision-making , 2013, Neuropsychologia.

[18]  Romke Rouw,et al.  Detecting high-level and low-level properties in visual images and visual percepts , 1997, Cognition.

[19]  E. Maris Statistical testing in electrophysiological studies. , 2012, Psychophysiology.

[20]  Fernando Maestú,et al.  Tracking the effect of emotional distraction in working memory brain networks: Evidence from an MEG study. , 2017, Psychophysiology.

[21]  Thomas E. Nichols,et al.  luster-based computational methods for mass univariate analyses f event-related brain potentials / fields : A simulation study , 2022 .

[22]  Erol Başar,et al.  Facial affect manifested by multiple oscillations. , 2009, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[23]  E. Basar,et al.  A review of brain oscillations in perception of faces and emotional pictures , 2014, Neuropsychologia.

[24]  Subramanian Ramanathan,et al.  DECAF: MEG-Based Multimodal Database for Decoding Affective Physiological Responses , 2015, IEEE Transactions on Affective Computing.

[25]  E. Basar,et al.  Principles of oscillatory brain dynamics and a treatise of recognition of faces and facial expressions. , 2006, Progress in brain research.

[26]  Robert Oostenveld,et al.  FieldTrip Made Easy: An Analysis Protocol for Group Analysis of the Auditory Steady State Brain Response in Time, Frequency, and Space , 2018, Front. Neurosci..

[27]  V Diekmann,et al.  Slower theta activity over the midfrontal cortex in schizophrenic patients , 1990, Acta psychiatrica Scandinavica.

[28]  Atsuko Gunji,et al.  Event-related oscillations in structural and semantic encoding of faces , 2012, Clinical Neurophysiology.

[29]  Y. Benjamini,et al.  False Discovery Rate–Adjusted Multiple Confidence Intervals for Selected Parameters , 2005 .

[30]  Sonja A. Kotz,et al.  The temporal dynamics of processing emotions from vocal, facial, and bodily expressions , 2011, NeuroImage.

[31]  M. Junghöfer,et al.  Contextual information resolves uncertainty about ambiguous facial emotions: Behavioral and magnetoencephalographic correlates , 2020, NeuroImage.

[32]  P. Lang Behavioral treatment and bio-behavioral assessment: computer applications , 1980 .

[33]  Tijl Grootswagers,et al.  Neural signatures of dynamic emotion constructs in the human brain , 2017, Neuropsychologia.

[34]  Abraham Goldstein,et al.  Child brain exhibits a multi-rhythmic response to attachment cues , 2018, Social cognitive and affective neuroscience.

[35]  Muhammad Hisyam Lee,et al.  Penalized logistic regression with the adaptive LASSO for gene selection in high-dimensional cancer classification , 2015, Expert Syst. Appl..

[36]  Jasna Martinovic,et al.  Electrocortical amplification for emotionally arousing natural scenes: The contribution of luminance and chromatic visual channels , 2015, Biological Psychology.

[37]  L. Aftanas,et al.  Time-dependent cortical asymmetries induced by emotional arousal: EEG analysis of event-related synchronization and desynchronization in individually defined frequency bands. , 2002, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[38]  Rasha Abdel Rahman,et al.  Group-Level EEG-Processing Pipeline for Flexible Single Trial-Based Analyses Including Linear Mixed Models , 2018, Front. Neurosci..

[39]  O. Witte,et al.  Abnormal Emotional Processing and Emotional Experience in Patients with Peripheral Facial Nerve Paralysis: An MEG Study , 2020, Brain sciences.

[40]  S. Taulu,et al.  Spatiotemporal signal space separation method for rejecting nearby interference in MEG measurements , 2006, Physics in medicine and biology.

[41]  Andreas A. Ioannides,et al.  Mapping the Spatiotemporal Evolution of Emotional Processing: An MEG Study Across Arousal and Valence Dimensions , 2018, Front. Hum. Neurosci..

[42]  Fernando Maestú,et al.  Choice of Magnetometers and Gradiometers after Signal Space Separation , 2017, Sensors.

[43]  E. Basar,et al.  Gender differences influence brain's beta oscillatory responses in recognition of facial expressions , 2007, Neuroscience Letters.

[44]  M. Balconi,et al.  Brain oscillations and BIS/BAS (behavioral inhibition/activation system) effects on processing masked emotional cues. ERS/ERD and coherence measures of alpha band. , 2009, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[45]  Qing Lu,et al.  Impaired prefrontal–amygdala effective connectivity is responsible for the dysfunction of emotion process in major depressive disorder: A dynamic causal modeling study on MEG , 2012, Neuroscience Letters.

[46]  Dejan Draschkow,et al.  Cluster-based permutation tests of MEG/EEG data do not establish significance of effect latency or location. , 2019, Psychophysiology.

[47]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[48]  Y. Benjamini,et al.  THE CONTROL OF THE FALSE DISCOVERY RATE IN MULTIPLE TESTING UNDER DEPENDENCY , 2001 .

[49]  Erol Basar,et al.  Emotional face expressions are differentiated with brain oscillations. , 2007, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[50]  Trevor Hastie,et al.  An Introduction to Statistical Learning , 2013, Springer Texts in Statistics.

[51]  M Esslen,et al.  Brain areas and time course of emotional processing , 2004, NeuroImage.

[52]  Michela Balconi,et al.  BIS/BAS, cortical oscillations and coherence in response to emotional cues , 2009, Brain Research Bulletin.

[53]  H. Gong,et al.  The processing bias for threatening cues revealed by event-related potential and event-related oscillation analyses , 2012, Neuroscience.

[54]  Panagiotis D. Bamidis,et al.  A Framework Combining Delta Event-Related Oscillations (EROs) and Synchronisation Effects (ERD/ERS) to Study Emotional Processing , 2009, Comput. Intell. Neurosci..

[55]  R. Tibshirani Regression Shrinkage and Selection via the Lasso , 1996 .