Stria terminalis, amygdala, and temporoparietal junction networks facilitate efficient emotion processing under expectations

Abstract

Rapid emotion processing is an ecologically essential ability for survival in social environments in which threatening or advantageous encounters dynamically and rapidly occur. Efficient emotion recognition is subserved by different processes, depending on one's expectations; however, the underlying functional and structural circuitry is still poorly understood. In this study, we delineate brain networks that subserve fast recognition of emotion in situations either congruent or incongruent with prior expectations. For this purpose, we used multimodal neuroimaging and investigated performance on a dynamic emotion perception task. We show that the extended amygdala structural and functional networks relate to speed of emotion processing under threatening conditions. Specifically, increased microstructure of the right stria terminalis, an amygdala white‐matter pathway, was related to faster detection of emotion during actual presentation of anger or after cueing anger. Moreover, functional connectivity of right amygdala with limbic regions was related to faster detection of anger congruent with cue, suggesting selective attention to threat. On the contrary, we found that faster detection of anger incongruent with cue engaged the ventral attention “reorienting” network. Faster detection of happiness, in either expectancy context, engaged a widespread frontotemporal‐subcortical functional network. These findings shed light on the functional and structural circuitries that facilitate speed of emotion recognition and, for the first time, elucidate a role for the stria terminalis in human emotion processing.

Opposing relationships of childhood threat and deprivation with stria terminalis white matter

“…Another study by Dzafic et al showed that greater ST microstructure was associated with faster recognition of anger following an anger cue during a dynamic emotional perception task (Dzafic et al, 2019). Their findings suggest that individuals with greater ST microstructure have more efficient emotion processing under threat (Dzafic et al, 2019). In the context of our findings, in which greater SED is associated with greater ST structural integrity, these studies suggest a potential neural adaptation in which greater ability to orient to threat or recognize emotion may yield enhanced situational awareness of threat, therefore enhancing likelihood of survival.…”

“…Koller et al showed that greater ST FA is associated with greater orienting bias toward threat in a saccadic decision task (Koller et al, 2019). Another study by Dzafic et al showed that greater ST microstructure was associated with faster recognition of anger following an anger cue during a dynamic emotional perception task (Dzafic et al, 2019). Their findings suggest that individuals with greater ST microstructure have more efficient emotion processing under threat (Dzafic et al, 2019).…”

“…The ST has been carefully mapped in non-human primates using neuroanatomical and neuroimaging techniques (Oler et al, 2017). Several studies have examined and/or mapped the ST in humans (Avery et al, 2014;Dzafic, Oestreich, Martin, Mowry, & Burianová, 2019;Eluvathingal et al, 2006;Folloni et al, 2019;Kamali et al, 2015;Koller, Hatton, Rogers, & Rafal, 2019;Krüger, Shiozawa, Kreifelts, Scheffler, & Ethofer, 2015;Kwon, Byun, Ahn, Son, & Jang, 2011;Tromp et al, 2019) and Rafal et al have examined the ST in humans and non-human primates (Rafal et al, 2015). The majority of these human ST and MFB studies have used standard diffusion tensor imaging (DTI); thus, detailed tractography of the ST and MFB using high-resolution diffusion weighted imaging (DWI) (e.g., multi-shell DWI and/or diffusion spectrum imaging) in human brain is of interest.…”

Functional Interplay Between Posterior Parietal Cortex and Hippocampus During Detection of Memory Targets and Non-targets

“…Seed PLS is a multivariate statistical method widely used to investigate the relation between activity in a selected brain region (seed voxel) and activity in the rest of the brain, across task conditions (McIntosh et al, 1997;Schreurs et al, 1997;McIntosh, 1999;Della-Maggiore et al, 2000). Based on previous evidence on the differential role of the anterior and posterior hippocampus in episodic memory retrieval (Poppenk et al, 2013), and on the findings from the whole-brain PLS analysis, functional seed values were extracted from a region of interest with a neighborhood size of one voxel (i.e., including the seed voxel plus one voxel adjacent to the peak voxel in each direction; see also Marstaller and Burianová, 2015;Ziaei et al, 2017;Dzafic et al, 2019) centered in the left anterior hippocampus (MNI coordinates: x = −30, y = −10, z = −20) and the left posterior hippocampus (MNI coordinates: x = −26, y = −26, z = −22), to examine, respectively, task-related functional connectivity during detection of memory targets (i.e., including hits in the incentiveold condition and CRs in the incentive-new condition in the analysis) and detection of items that were not the target of memory (i.e., including hits in the incentive-new condition and CRs in the incentive-old condition in the analysis). The analytical procedure for the seed PLS functional connectivity analysis was the following: first, the BOLD values from the hippocampal seed regions were extracted for each event of interest (detection of memory targets and non-targets) across 8 time points from the onset of the trial.…”

Large-Scale Morphological Network Efficiency of Human Brain: Cognitive Intelligence and Emotional Intelligence

“…Previous studies have reported that both anatomical (white matter [WM] tractography) and functional network efficiencies were related to cognitive intelligence (Li et al, 2009 ; van den Heuvel et al, 2009 ; Langer et al, 2012 ) and EI (Smith et al, 2018b ; Dzafic et al, 2019 ) in adolescence, adults, and elderly groups. However, most of them focused on one age group, and no study investigated whether, and how, the associations between the human brain network efficiency and intelligence changed from young adults to the middle-aged group.…”