Neural correlates of individual differences in fear learning

Abstract

Variability in fear conditionability is common, and clarity regarding the neural regions responsible for individual differences in fear conditionability could uncover brain-based biomarkers of resilience or vulnerability to trauma-based psychopathologies (e.g., post-traumatic stress disorder). In recent years, neuroimaging work has yielded a detailed understanding of the neural mechanisms underlying fear conditioning common across participants, however only a minority of studies have investigated the brain basis of inter-individual variation in fear learning. Moreover, the majority of these studies have employed small sample sizes (mean n = 17; range n = 5–27) and all have failed to meet the minimum recommended sample size for functional magnetic resonance imaging (fMRI) studies of individual differences. Here, using fMRI, we analyzed blood-oxygenation level dependent (BOLD) response recorded simultaneously with skin conductance response (SCR) and ratings of unconditioned stimulus (US) expectancy in 49 participants undergoing Pavlovian fear conditioning. On average, participants became conditioned to the conditioned stimulus (CS+; higher US expectancy ratings and SCR for the CS+ compared to the unpaired conditioned stimulus, CS−); the CS+ also robustly increased activation in the bilateral insula. Amygdala activation was revealed from a regression analysis that incorporated individual differences in fear conditionability (i.e., a between-subjects regressor of mean CS+ > CS− SCR). By replicating results observed using much smaller sample sizes, the results confirm that variation in amygdala reactivity covaries with individual differences in fear conditionability. The link between behavior (SCR) and brain (amygdala reactivity) may be a putative endophenotype for the acquisition of fear memories.

Convergence of fMRI and ERP measures of emotional face processing in combat‐exposed U. S. military veterans

“…Amygdala activation (e.g., Killgore et al, 2013; Shah, Klumpp, Angstadt, Nathan, & Phan, 2009; Siegle, Thompson, Carter, Steinhauer, & Thase, 2007; Simmons et al, 2011), insula activation (Paulus & Stein, 2006) and the LPP (e.g., Foti et al, 2010; Kujawa et al, 2015; MacNamara & Hajcak, 2010; MacNamara, Kotov, et al, 2015; MacNamara et al, 2013) elicited by unpleasant stimuli may be aberrant in various anxiety, depressive and trauma-related psychopathologies. Here, diagnosis or symptoms of PTSD did not moderate associations between the LPP elicited by faces and fMRI BOLD response in any of the BOLD regions identified.…”

“…In line with prior work (e.g., Cuthbert et al, 2000;Foti et al, 2009;MacNamara, Foti, & Hajcak, 2009), the LPP was evident by 500 ms after stimulus onset at centropartial recording sites. 1 A 2-mm or higher cutoff for movement is widely used in the literature for task-based fMRI (e.g., Duval et al, 2017;Epstein et al, 2007;Gilat et al, 2017;Kim et al, 2013;MacNamara et al, 2015;Rabinak et al, 2014), especially with clinical samples, who may show more movement and are more difficult to recruit. Nonetheless, different types of data (e.g., resting state) may require more stringent parameters because, unlike task-based fMRI, motion artifacts are not suppressed by averaging (Caballero-Gaudes & Reynolds, 2017).…”

“…Given evidence that the LPP is altered in a number of psychiatric disorders (e.g., Foti et al, 2010; MacNamara & Hajcak, 2010; MacNamara, Kotov, & Hajcak, 2015; MacNamara et al, 2013; Weinberg & Hajcak, 2011), and given the potential for ERPs to translate to the clinic (i.e., increased cost-effectiveness and ease of administration compared to fMRI), a better understanding of correspondence between fMRI and ERP measures across the psychiatric continuum is desirable. In addition, despite the widespread use of facial stimuli in fMRI (and ERP) research, no prior work has examined correlations between the LPP and fMRI BOLD elicited by faces.…”

“… 1 A 2mm or higher cutoff for movement is widely used in the literature for task-based fMRI (e.g., Duval et al, 2017; Epstein et al, 2007; Gilat et al, 2017; Kim et al, 2013; MacNamara, Rabinak, et al, 2015; Rabinak et al, 2014), especially with clinical samples, who may show more movement and are more difficult to recruit. Nonetheless, different types of data (e.g., resting state) may require more stringent parameters, because unlike task-based fMRI, motion artifacts are not suppressed by averaging.…”

Limbic correlates of fearlessness and disinhibition in incarcerated youth: Exploring the brain–behavior relationship with the Hare Psychopathy Checklist: Youth Version

“…The rationale for the first part of the hypothesis tested in this study comes from human research showing that the amygdala plays a greater role in fear conditioning than the hippocampus (Shechner et al, 2014). In fact, individual differences in fear conditionability have been found to be stable, heritable, and specific to neural areas in and around the amygdala (MacNamara et al, 2015). The rational for the second part of the hypothesis comes from human research showing that the hippocampus is more consistently associated with behavioral inhibition than the amygdala (Cherbuin et al, 2008).…”