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NeuroImage

Volume 47, Issue 3, September 2009, Pages 821-835
NeuroImage

Brain mediators of cardiovascular responses to social threat: Part I: Reciprocal dorsal and ventral sub-regions of the medial prefrontal cortex and heart-rate reactivity

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Abstract

Social threat is a key component of mental “stress” and a potent generator of negative emotions and physiological responses in the body. How the human brain processes social context and drives peripheral physiology, however, is relatively poorly understood. Human neuroimaging and animal studies implicate the dorsal medial prefrontal cortex (MPFC), though this heterogeneous region is likely to contain multiple sub-regions with diverse relationships with physiological reactivity and regulation. We used fMRI combined with a novel multi-level path analysis approach to identify brain mediators of the effects of a public speech preparation task (social evaluative threat, SET) on heart rate (HR). This model provides tests of functional pathways linking experimentally manipulated threat, regional fMRI activity, and physiological output, both across time (within person) and across individuals (between persons). It thus integrates time series connectivity and individual difference analyses in the same path model. The results provide evidence for two dissociable, inversely coupled sub-regions of MPFC that independently mediated HR responses. SET caused activity increases in a more dorsal pregenual cingulate region, whose activity was coupled with HR increases. Conversely, SET caused activity decreases in a right ventromedial/medial orbital region, which were coupled with HR increases. Individual differences in coupling strength in each pathway independently predicted individual differences in HR reactivity. These results underscore both the importance and heterogeneity of MPFC in generating physiological responses to threat.

Introduction

One of the most remarkable features of the mammalian nervous system is its ability to mount coordinated behavioral and physiological responses to environmental demands. For example, when environmental cues signal a potential threat to an organism's well being, the brain produces a coordinated set of behavioral, autonomic, and metabolic changes that promote an adaptive response. As Walter Cannon (Cannon, 1932) and many others since have described, output from the brain to the peripheral autonomic nervous system and endocrine system prepares us to respond rapidly and effectively to impending threats. For example, the classic “fight or flight” response involves increases in heart rate, blood flow to the limbs, pupil dilation, slowed digestion, and other changes (Bandler et al., 2000, Obrist, 1981). The brain systems that regulate the various organ systems of the body have evolved from survival-related brainstem circuits, but also include cortical and subcortical systems central to social and emotional processes (Bandler and Shipley, 1994, Craig, 2003, Porges, 2003). Thus, understanding these brain–body information transfer systems may provide clues into the neural organization of social and emotional behavior and its consequences for the body.

Threat is one of the oldest and presumably most basic brain processes that strongly influences the body. Threat responses can be triggered by the presence of individual, simple cues (e.g., a light or tone) acting through defined circuitry in the amygdala, periaqueductal gray (PAG), and other regions (Davis, 1992, LeDoux, 2000). However, threat responses are much more often triggered by patterns of cues and conceptual knowledge stored in memory that fit together into a situational “schema,” which strongly suggests the involvement of a more complex set of cortical and subcortical processes. For example, darkness, shadows that look like human forms, the sound of a mechanical click in the silence, and the knowledge that one is walking alone in a dangerous part of the city may all combine to trigger a schema that one might call “impending threat.” Threat responses can also be triggered by social situations that involve complex appraisals of social relationships, including an individual's status, competence, and value in the eyes of others. Indeed, threats in modern human life are usually abstract and often related to the maintenance of our self-esteem, social status, and long-term prospects for mating and longevity. Threats generated by social or other cognitive processes are particularly under-studied in neuroscience, but they can offer important clues about the brain pathways involved in common types of threat in contemporary society.

The study of threat systems in the brain has important implications for health. While advantageous in the short term, threat responses that persist over time can have deleterious effects on the brain and body. Chronic perception of threat has been shown to increase the risk of heart disease (Bosma, 1998, Jain et al., 2001, Rozanski et al., 1988, Sheps, 2002), cause hippocampal deterioration (Smith et al., 1995, Stein-Behrens et al., 1994, Watanabe et al., 1992) and impairments in declarative memory (McEwen and Sapolsky, 1995), promote pro-inflammatory immune responses (Kiecolt-Glaser and Glaser, 2002), and contribute to cognitive and physical aging (Mcewen, 2007), among other adverse effects. Both threat states and their negative connotations for health are captured in early concepts of “stress” (Selye, 1956) and the more recent concept of “allostatic load” (Mcewen, 2007)— the notion that a) the brain actively maintains homeostasis through the activation of brain, autonomic, and endocrine systems, and b) chronic load on these systems by persistent threat has deleterious effects on the brain and body, contributing to a variety of health problems (Kiecolt-Glaser et al., 2002).

The brain mechanisms underlying social threat responses are just now beginning to be addressed using neuroimaging techniques. Much progress has been made in understanding the neural substrates of threat and stress in animals, but surprisingly little is known about how social and performance “stressors” affect the human brain. The goal of the present study, and its companion (Wager et al., 2009), was to investigate the cortical and subcortical systems involved in generating physiological responses to a well-validated laboratory manipulation of social threat. These studies complement and extend a small but growing literature on the neural bases of social and performance stress (Critchley, 2003, Dedovic et al., 2005, Eisenberger et al., 2007, Gianaros et al., 2004, Kern et al., 2008).

In human laboratory studies social status-related threats have been studied in the context of social evaluative threat (SET)—the condition of being judged unfavorably by other individuals in a public setting. SET has been shown to be the most potent human laboratory elicitor of a canonical feature of stress in animal models: the hypothalamicpituitary–adrenal (HPA) axis response (Dickerson and Kemeny, 2004, Kirschbaum et al., 1993). Threats to the ‘social self’ in particular elicit HPA-axis responses (Dickerson et al., 2004). Remarkably, inter-correlated autonomic, endocrine, and immune changes are produced by even acute SET challenges (Cacioppo, 1994, Cohen et al., 2000, Kiecolt-Glaser et al., 1992, Sgoutas-Emch et al., 1994). These effects are clinically relevant as well. SET challenges in patients with coronary artery disease have been shown to induce myocardial ischemia (Rozanski et al., 1988) and affect clinical measures of cardiac dysfunction, including left ventricular ejection fraction (LVEF) (Jain et al., 2001, Jain et al., 1998). Ischemic responses to SET have been shown to predict the incidence of fatal and non-fatal cardiac events over a 5-year follow-up (Jiang et al., 1996, Sheps, 2002).

In this study, we assess fMRI activity elicited by public speech preparation, a component of well-studied laboratory SET challenges, and its relationship with heart rate (HR). Both preparing and giving a speech before a critical audience induces robust cardiovascular engagement, including increased blood pressure and heart rate (HR) (Berntson et al., 1994, Cacioppo et al., 1995, Gramer and Saria, 2007, Tugade and Fredrickson, 2004, Uchino et al., 1995) that results from both increased sympathetic output and reduced parasympathetic output to the heart (Berntson et al., 1994). Public speaking stressors have produced larger cardiac chronotropic responses than math performance and reaction-time based stressors (Al'Absi et al., 1997, al'Absi et al., 2000, Berntson et al., 1994), though HR responses are comparable whether participants are giving the speech or only preparing it (Feldman et al., 2004, Gramer and Saria, 2007, Waugh et al., 2008a).

We focused on HR as an outcome measure for several reasons. First, HR increases are robustly elicited by SET, though they vary across individuals (Berntson et al., 1994). They are substantially more robust than more pure measures of sympathetic and parasympathetic activity collected over short time intervals (Berntson et al., 1994, Cacioppo et al., 1994). Studies of stressor-induced HR reactivity have estimated its internal consistency above alpha = .95 and test–retest reliability around r = .6 after one year (Cacioppo, 1994, Uchino et al., 1995). Second, they can be measured on a roughly second-by-second basis, providing the ability to analyze effective connectivity among key brain regions and HR across time. Third, HR reactivity and cardiovascular reactivity more generally predict other health-related effects of stressors on the body. Cardiovascular reactivity is heritable (Carroll et al., 1985) and is correlated with stressor-induced changes in cortisol release (Al'Absi et al., 1997, Lovallo et al., 1990) and immune function (Cacioppo, 1994, Cacioppo et al., 1995, Sgoutas-Emch et al., 1994, Uchino et al., 1995). Finally, cardiovascular reactivity measures related to HR, such as heart-rate variability and LVEF, are risk factors for cardiac dysfunction and mortality (Thayer and Lane, 2007).

The most likely locations for brain generators of cardiovascular and other peripheral responses to SET are in the medial prefrontal cortex (MPFC), which projects reciprocally to a set of interconnected “limbic” cortical regions and subcortical nuclei, including the insula, medial temporal lobes, amgydala, ventral striatum (ventral caudate and putamen), mediodorsal thalamus, hypothalamus, and PAG, as well as other important brainstem nuclei (An et al., 1998, Bandler et al., 2000, Bandler and Shipley, 1994, Barbas et al., 2003, Hsu and Price, 2007, Kondo et al., 2003, Kondo et al., 2005, Price, 1999, Saleem et al., 2008). MPFC has been broadly associated with emotional processes (Wager et al., 2008a), with dorsomedial and pregenual regions linked to PAG activation, and tasks that engage self-evaluation (Northoff et al., 2006).

In human imaging studies, the dorsal cingulate/MPFC has been linked consistently with stress-induced increases in HR and blood pressure (Critchley et al., 2000, Critchley et al., 2003, Critchley et al., 2005, Gianaros et al., 2004, Gianaros et al., 2007, Gianaros et al., 2008a) and cortisol (Eisenberger et al., 2007). More rostral and ventral areas have been associated with reduced cortisol reactivity (Eisenberger et al., 2007, Kern et al., 2008), implying a role in successful regulation or protection from stress reactivity. These studies mark an important milestone in the interrelation of human brain activity and physiology, and have confirmed and extended findings from animal models implicating the ventromedial prefrontal cortex (vmPFC), lateral orbitofrontal cortex (OFC), anterior cingulate (ACC), and anterior insula (aINS)—the same regions thought to be most critical for emotional appraisal—in physiological responses to social threat.

One limitation is that nearly all of the studies cited above (and most others) have relied primarily on between-subject correlations to make inferences about brain–physiology relationships. For example, Eisenberger et al. (2007) related individual differences in cortisol responses to brain activity responses in a separate social exclusion task. Though a promising way to examine individual differences, such correlations do not take full advantage of the capability of fMRI to make many repeated measurements of brain activity over time (typically 200–1500 per individual). Thus, these studies are limited in power by the sample size (though the Eisenberger study was particularly large compared to other fMRI studies). In addition, between-subject correlations are subject to a number of confounds related to individual differences in age, neurovascular coupling, brain morphometry, and other variables. Other studies have assessed relationships between brain activity and physiological changes across time, and tested whether these relationships are consistent across participants (Critchley et al., 2005, Gianaros et al., 2004, Lane et al., 2009). For example, in a particularly large study, Gianaros et al. (2004) mapped brain regions in which task-evoked heart period changes across a series of working memory tasks correlated with variation in task-evoked brain activity.

In this study, we extend these results by using a new kind of analysis—multi-level mediation effect parametric mapping—that is specifically designed to link experimental manipulations, brain activity, and physiological output in a single path model. A single-level version of the model was used in (Wager et al., 2008b). One advantage of the multi-level model is that it can incorporate both within-subjects longitudinal effects across time and between-subjects effects of individual differences in the same model. The first, within-subject level of the two-level model utilizes the rapid sampling capabilities of fMRI to estimate brain-physiology relationships across time. The second, between-subject level captures how activity and connectivity relate to other measures of individual differences. In addition, it can provide tests of mediation that standard general linear model-based analyses cannot.

We experimentally manipulated SET by asking participants to silently prepare a speech under time pressure (Fig. 1A). Participants believed that they would have to give their speech (they did not), which would be audiotaped during scanning and judged later by fellow students. We monitored HR continuously during fMRI imaging, and our analyses focused on establishing pathways that link the experimental SET manipulation with variations in brain activity and HR.

The overall inference that a region is critical for generating HR responses to SET includes tests at two levels of analysis. The first level of analysis tests associations between SET, brain activity, and HR across time within individuals. At this level, a region involved in generating HR responses to threat should show the following three characteristics. Activity in a brain region should: 1) increase (or decrease) in response to the SET challenge (Path a in Fig. 2); 2) predict HR changes over time, controlling for the SET manipulation (Path b in Fig. 2); and 3) Mediate the SET–HR covariance. This latter criterion can be evaluated using a mediation test, which formally tests whether the brain region explains a significant proportion of the SET–HR covariance. The second level of analysis concerns HR reactivity. If a particular brain region is a mediator of the SET–HR relationship, and this relationship underlies individual differences in HR reactivity, then the first-level a and b path strengths should be predicted by HR reactivity. That is, for those who show robust HR increases to the SET challenge, brain activity in mediating regions should be more strongly associated with both SET and HR. Inferences about brain regions that link social threat with autonomic activation draw on each of these five hypotheses (three related to dynamic co-variation across time and two related to individual differences.)

Section snippets

Participants

Thirty healthy, right-handed, native English speakers were recruited at the University of Michigan (mean age 20.3 years, 10 males) and participated in this experiment. Potential participants were initially pre-screened for scoring in the upper or lower quartile of an emotional resilience measure (ER-89) (Block and Kremen, 1996). However, none of the results presented in this paper were related to this personality trait (P > .5), so the two subgroups were combined in all analyses.

Physiological effects of SET

HR changes over time were a primary outcome measure of the SET challenge. Compared with pre-threat baseline and post-threat recovery, speech preparation induced reliable increases in HR (9.54 beats per minute, BPM, t = 4.88, P < .0001), as shown in Fig. 1C. This effect was significant when preparation was compared separately with each of the first (8.16 BPM, t = 4.18, p = .0004) and second baseline periods (10.92 BPM, t = 5.27, P < .0001). HR was lower during the post-preparation recovery period than

Discussion

Social status and perceived social and intellectual competence are extremely important factors in modern human life (Fiske et al., 2007). Threats to self-esteem and negative evaluation—or social evaluative threat (SET)—relate to social status and are among the most potent laboratory and real-life stressors in contemporary society. Because SET often arises from a complex analysis of inter-personal relationships, rather than the presence of any particular simple sensory cue, it is likely to be

Conclusion

In conclusion, these findings contribute significantly to the investigation of brain–physiology relationships in the context of social threat. The relationship between social threat and associated physiological responses (HR) was mediated by reliable and sustained increases in pre-genual cingulate/MPFC and decreases in vmPFC/mOFC. Future investigations should more specifically examine whether the dorsal/ventral distinction within the MPFC maps onto distinctions within the peripheral nervous

Acknowledgments

We would like to thank Niall Bolger for helpful discussions on path analysis, and the authors of SPM software for making it freely available. This paper was made possible with the support of grant funding from NSF 0631637 (T.W.), NIH Grant MH076136 (T.W.), NIH Grant MH59615 (B.L.F.), a pilot grant from the UM fMRI lab to S.T./C.W., positive psychology microgrant to C.W. and dissertation thesis grant to C.W.

Author contributions: Design: C.W., B.F. and S.F.T., Data collection: C.W. and D.N.,

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