De acuerdo con las teorías actuales sober las emociones, un episodio emocional esta caracterizado por una sincronización en diferentes areas cerebrales. En este interesante estudio, unos investigadores se preguntaron cuáles son esas areas realizando una tarea experimental para ver cada emoción mediante fMRI, logrando un importante aporte para entender cómo las emociones son procesadas en el cerebro.
According to componential emotion theories (CET / Motivation, Emotion & Craving), an emotional episode (with associated subjective feeling) is characterized by a high degree of synchronization among different cognitive and bodily components, namely the appraisal (often trigger of emotion episode), motivation (determined by action tendencies), expression (e.g. facial expressions) and physiological (e.g. autonomous nervous system / Physiology & Behavior) components (Scherer, 2009).
While imaging studies of emotions have traditionally focused on discrete (e.g. fear) and dimensional (e.g. valence) emotion theories, CET has rarely been explored. In this fMRI study (1), the researchers address this gap by acquiring data for each component and using an interactive task that manipulates appraisals instead of emotion categories per see.
26 subjects took part in this experiment (3T Siemens, GE-EPI, TE=32ms, 48 axial slices, TR=600ms, MB factor=6) (For MRI). They designed a novel paradigm where subjects controlled an avatar that navigated different mazes with the goal of collecting as many points as possible (Fig. 1.1B). They manipulated 2 appraisals (Brain Stimulation)(goal conduciveness (GC), control potential (CP)) in a 3x2 factorial design (Fig. 1.1A). GC was manipulated by introducing (in different trials) 3 monster types (bad, neutral, good) (Decision Making).
Touching the different monsters would result in different outcomes for the subjects (Fig. 1.1B, right-hand table). CP was manipulated by introducing 2 possible power levels (No power, Power, self-activated) that would change the outcome of touching the monsters (Fig. 1.1B). To go to the next trial, subjects had to reach a teleporter placed behind a closed door that opened 8s after trial onset. At this point, a countdown period (CD) was introduced that set a delay to reach the teleporter (4-6s). If the teleporter was not reached in time, all points gathered during the trial were lost.
The motivation component was measured using behavioral proxies for action tendencies, such as coins eaten, monster touches head-to-head or tail-to-head, and the amount of time spend during CD. They also measured peripheral physiology (pulse, respiration, electrodermal activity (EDA)) and facial (zygomaticus and corrugator muscles) electromyography (EMG).
The motivation measures were converted into parametric regressors. After pre-processing, cardiac and respiratory instantaneous rates and EMG power for the two muscles were calculated, while phasic EDA responses were extracted. Apart from the EDA, all-time courses were convolved with the HRF. All these signals were entered in a computational model to derive a continuous emotion synchronization index (SYNCH) between the different components (Meuleman et al, 2015).
fMRI data were preprocessed using standard pipelines (SPM12) and corrected for motion and physiological noise using RETROICOR. At the first level, these data were entered into GLM analyses and the resulting contrast images were entered in second-level analyses to allow inferences at the population level. Results for the component analyses are reported at p<0.05 (FWE). Inferences that test for brain areas that are correlated with the synchronization index are reported at p<0.05 (FWE) at the cluster level using an uncorrected voxel threshold of p=0.001.
Behaviorally, the appraisal manipulations elicited different emotions and action tendencies patterns across conditions. At the brain level, each emotion component was associated with a distributed pattern of activations (Fig. 1.2). In particular, the SYNCH correlated with medial occipital areas and the bilateral striatum, an area that has been previously suggested to play an important role in emotion synchronization (Peron et al, 2013).
By approaching emotions from a componential perspective at the brain level and using a novel and interactive task that allows studying emotions from this angle, this study constitutes an important first step for a more comprehensive understanding of emotion processing in a behaviorally active context.
(1) Decomposing emotions at the brain level using a novel and interactive emotion elicitation task. (2019) Joana Leitao, Ben Meuleman, Patrik Vuilleumier.
(2) Meuleman, Ben. (2015) Computational modeling of appraisal theory of emotion. Université de Genève. PhD Thesis. https://archive-ouverte.unige.ch/unige:83638
(3) Péron J, Frühholz S, Vérin M, Grandjean D. (2013) Subthalamic nucleus: a key structure for emotional component synchronization in humans. Neurosci Biobehav Rev.; 37(3):358-73.
(4) Scherer KR (2009). The dynamic architecture of emotion: Evidence for the component process model. Cogn Emot; 23:1307–1351.