Valence, Arousal, and Gender Effect on Olfactory Cortical Network Connectivity: A Study Using Dynamic Causal Modeling for EEG

Abstract

The cortical network including the piriform (PC), orbitofrontal (OFC), and entorhinal (EC) cortices allows the complex processing of behavioral, cognitive, and context-related odor information and represents an access gate to the subcortical limbic regions. Among the several factors that influence odor processing, their hedonic content and gender differences play a relevant role. Here, we investigated how these factors influence EEG effective connectivity among the mentioned brain regions during emotional olfactory stimuli. To this aim, we acquired EEG data from twenty-one healthy volunteers, during a passive odor task of odorants with different valence. We used Dynamic Causal Modeling (DCM) for EEG and Parametric Empirical Bayes (PEB) to investigate the modulatory effects of odors' valence on the connectivity strengths of the PC-EC-OFC network. Moreover, we controlled for the influence of arousal and gender on such modulatory effects. Our results highlighted the relevant role of the forward and backward PC-EC connections in odor's brain processing. On the one hand, the EC-to-PC connection was inhibited by both pleasant and unpleasant odors, but not by the neutral one. On the other hand, the PC-to-EC forward connection was found to be modulated (posterior probability (Pp)>0.95) by the arousal level associated with an unpleasant odor. Finally, the whole network dynamics showed several significant gender-related differences (Pp>0.95) suggesting a better ability in odor discrimination for the female gender.

Combining electrodermal activity analysis and dynamic causal modeling to investigate the visual-odor multimodal integration during face perception

“…The methodology proposed in this study could represent an effective means to quantitatively study the effect of sympathetic arousal on both the ERPs and effective connectivity. Indeed, in previous studies, we adopted subjective ratings as a means to quantify arousal and investigate its central correlates at the connectivity level [71,99]. However, affective ratings may deviate from physiological responses [71], which are supposed instead to represent an objective window on emotional stimuli processing (see e.g.…”

“…Indeed, in previous studies, we adopted subjective ratings as a means to quantify arousal and investigate its central correlates at the connectivity level [71,99]. However, affective ratings may deviate from physiological responses [71], which are supposed instead to represent an objective window on emotional stimuli processing (see e.g. [100]).…”

“…We reduced the data to the first four principal components (PC) or modes of EEG channels' mixture. Such a choice is a tradeoff between the computational cost of DCM model inversion and the percentage of variance explained by the data [69][70][71]. Notably, reducing ERP data to their first four PC is indicated as sufficient to capture the components of interest [63].…”