A Multiplex Connectivity Map of Valence-Arousal Emotional Model

Abstract

A high number of studies have already demonstrated an electroencephalography (EEG)-based emotion recognition system with moderate results. Emotions are classified into discrete and dimensional models. We focused on the latter that incorporates valence and arousal dimensions. The mainstream methodology is the extraction of univariate measures derived from EEG activity from various frequencies classifying trials into low/high valence and arousal levels. Here, we evaluated brain connectivity within and between brain frequencies under the multiplexity framework. We analyzed an EEG database called DEAP that contains EEG responses to video stimuli and users' emotional self-assessments. We adopted a dynamic functional connectivity analysis under the notion of our dominant coupling model (DoCM). DoCM detects the dominant coupling mode per pair of EEG sensors, which can be either within frequencies coupling (intra) or between frequencies coupling (cross-frequency). DoCM revealed an integrated dynamic functional connectivity graph (IDFCG) that keeps both the strength and the preferred dominant coupling mode. We aimed to create a connectomic mapping of valence-arousal map via employing features derive from IDFCG. Our results outperformed previous findings succeeding to predict in a high accuracy participants' ratings in valence and arousal dimensions based on a flexibility index of dominant coupling modes.

Greek High Phenolic Early Harvest Extra Virgin Olive Oil Reduces the Over-Excitation of Information Flow based on Dominant Coupling Model in patients with Mild Cognitive Impairment: An EEG Resting-State Validation Approach

“…In our previous study, we reported for the very first time that a long-term intervention with HP-EH-EVOO or MP-EVOO was associated with significant improvement in cognitive function compared to the MeDi group (Tsolaki et al, 2020). We adopted here our DoCM model which incorporates into a dFCG both the dominant coupling mode and also its functional strength between every pair of EEG sensros and acros experimental time (Antonakakis et al, 2017;Dimitriadis et al, 2017aDimitriadis et al, -c, 2018aDimitriadis et al, -d, 2019Dimitriadis, 2020 ;Marimpis et al, 2020). We detected a significant higher post-intervention reduction of NI (ΔΝΙ Total and α ) for the HP-EH-EVOO compared to the MP-EVOO and MeDi groups.…”

“…In this section, we will describe briefly our dominant intrinsic coupling model (DoCM) demonstrated in the whole repertoire of functional neuroimaging modalities (Antonakakis et al, 2017; Dimitriadis et al, 2017a-c, 2018a-d, 2019; Dimitriadis, 2020; Marimpis et al, 2020). The majority of studies so far were investigating functional connectivity independently for every frequency band while they focused mainly on within-frequency (intra-frequency) interactions.…”

“…In this section, we will describe briefly our dominant intrinsic coupling model (DoCM) demonstrated in the whole repertoire of functional neuroimaging modalities (Antonakakis et al, 2017;Dimitriadis et al, 2017aDimitriadis et al, -c, 2018aDimitriadis et al, -d, 2019Dimitriadis, 2020 ;Marimpis et al, 2020).…”

“…EEG recordings were bandpass filtered using a 3 rd order zero-phase Butterworth filter employing the filtfilt MATLAB function. The width of the temporal window was set equal to 500ms (or 250 samples) and moved forward across experimental time with a step equals to 100 ms (50 samples) which can encapsulate both slow and fast oscillations (Dimitriadis et al, 2013a(Dimitriadis et al, ,b, 2015a(Dimitriadis et al, ,b, 2016a(Dimitriadis et al, ,b,c, 2017a(Dimitriadis et al, ,b, 2018bMarimpis et al, 2020). We finally analyzed 75 secs across subjects and conditions as a common experimental time across the participants.…”

“…is created in analogy to previous studies to further exemplify the concept of DoCM model in not familiar readers(Dimitriadis, 2020 ;Marimpis et al, 2020).Fig.1Aillustrates how DoCM is defined for the first two temporal segment of eyes-closed condition from the first subject of group A between Fp1 and Fp2 EEG sensors. Following the important step of surrogate analysis, we revealed α1-β2 cross-frequency phase-to-amplitude coupling (PAC) as the dominant coupling mode (DoCM) among 28 possible coupling modes for the first two temporal segments for this particular EEG pair of sensors.…”