Skip to content
naulon

No retraction, correction or concern found when last checked on Oct 19, 2026.

From the heart to the mind: cardiac vagal tone modulates top-down and bottom-up visual perception and attention to emotional stimuli

Gewnhi Park, Julian F. Thayer

Frontiers in Psychology · 2014 · Review

doi:10.3389/fpsyg.2014.00278

Abstract

The neurovisceral integration model (Thayer and Lane, 2000) posits that cardiac vagal tone, indexed by heart rate variability (HRV), can indicate the functional integrity of the neural networks implicated in emotion-cognition interactions. Our recent findings begin to disentangle how HRV is associated with both top-down and bottom-up cognitive processing of emotional stimuli. Higher resting HRV is associated with more adaptive and functional top-down and bottom-up cognitive modulation of emotional stimuli, which may facilitate effective emotion regulation. Conversely, lower resting HRV is associated with hyper-vigilant and maladaptive cognitive responses to emotional stimuli, which may impede emotion regulation. In the present paper, we recapitulate the neurovisceral integration model and review recent findings that shed light on the relationship between HRV and top-down and bottom-up visual perception and attention to emotional stimuli, which may play an important role in emotion regulation. Further implications of HRV on individual well-being and mental health are discussed.

Full text

From PubMed Central, U.S. National Library of Medicine, as current on Oct 19, 2026. Paragraph numbers are ours, so an answer can point at one.

When the mind is strongly excited, we might expect that it would instantly affect in a direct manner the heart; and this is universally acknowledged and felt to be the case. Claude Bernard also repeatedly insists, and this deserves especial notice, that when the heart is affected it reacts on the brain; and the state of the brain again reacts through the pneumo-gastric nerve on the heart; so that under any excitement there will be much mutual action and reaction between these, the two most important organs of the body.

, p. 69

As far back as the early 20th century, the work of Claude Bernard highlighted the importance of the brain–heart connection in understanding the interplay between emotion and cognition. More recently,, ) proposed the neurovisceral integration model, which suggests that neural networks implicated in autonomic, emotional, and cognitive self-regulation are also involved in the control of cardiac autonomic activity. Behavioral and neuroimaging studies have identified several pathways by which cardiac vagal tone is linked to neural networks implicated in emotional and cognitive self-regulation (for a review, see ). Our recent research begins to uncover how cardiac vagal tone indexed by heart rate variability (HRV) is associated with top-down and bottom-up visual perception and attention to emotional stimuli, which may play a critical role in regulating the impact of negative emotion – termed as emotion regulation. Higher resting HRV is associated with more adaptive top-down and bottom-up cognitive modulation of emotional stimuli, which may allow for effective regulation of the impact of negative emotion. In contrast, lower resting HRV is associated with hyper-vigilant and maladaptive cognitive responses to emotional stimuli, which may be detrimental to emotion regulation. The present paper briefly describes the neurovisceral integration model and then reviews our recent experiments that shed light on the interaction between cardiac vagal tone and top-down and bottom-up visual perception and attention to emotional stimuli.

SELF-REGULATION AND THE CENTRAL AUTONOMIC NETWORK (CAN)

Self-regulation refers to the ability to regulate thoughts, emotions, and behaviors, thereby allowing people to choose responses that are appropriate for different situational demands. Several neural mechanisms associated with cognitive, emotional, and autonomic self-regulation have been identified, one of which is the central autonomic network (CAN;;; ). The CAN has been implicated in making visceromotor, neuroendocrine, and behavioral responses that are adaptive and flexible for various environmental demands. The structures of the CAN include the anterior cingulate, the insula, the ventromedial prefrontal cortices, the central nucleus of the amygdala, the paraventricular and related nuclei of the hypothalamus, the periaquaductual gray matter, the parabrachial nucleus, the nucleus of the solitary tract (NTS), the nucleus ambiguous, the ventrolateral medulla, the ventromedial medulla, and the medullary tegmental field, among others (see Figure 1;; ). These brain structures in the CAN are reciprocally connected, and information can flow in both top-down and bottom-up fashions. They are also loosely connected so that it is easy to recruit additional structures that are necessary to make specific behavioral changes.

In particular, the prefrontal-subcortical inhibitory circuits within the CAN play a critical role in self-regulatory function (for a review, see ). Under normal circumstances, the prefrontal cortex identifies safety cues from the environment and exerts its inhibitory control over sympathoexcitatory subcortical circuits, including the central nucleus of the amygdala. This prefrontal regulation makes it possible for an organism to make responses that are optimal for different situational demands. In threatening and uncertain situations, the prefrontal inhibitory regulation diminishes and sympathoexcitatory subcortical circuits make default threat responses. As such, prefrontal-subcortical inhibitory circuits play a role in various regulatory behaviors, including appetite, attitudes, and prejudice. Reduced prefrontal regulation can lead to hyperactive subcortical activity, which results in prolonged activation of defensive behavior mechanisms, including hyper-vigilance and perseverative cognition (e.g., worry or rumination;; ). Not surprisingly, the disruption of prefrontal-subcortical circuits has been associated with a wide range of psychopathologies, including depression, anxiety, schizophrenia, and addictive behavior (for a review, see ).

THE NEUROVISCERAL INTEGRATION MODEL AND HEART RATE VARIABILITY

According to the neurovisceral integration model, the functioning of prefrontal-subcortical inhibitory circuits critical for self-regulation is linked with the heart via the vagus nerve that provides inhibitory inputs to the heart (see also;; ). Several neuroimaging and pharmacological studies have identified the link between inhibitory prefrontal-subcortical circuits and cardiac vagal tone indexed by vagally mediated resting HRV (;;; for a review, see ). Most noticeably, a recent meta-analysis revealed that resting HRV is tied to the functioning of prefrontal-subcortical circuits, such that higher resting HRV is associated with the effective functioning of prefrontal-subcortical inhibitory circuits that support flexible and adaptive responses to environmental demands. Indeed, research has indicated that people with higher resting HRV exhibit effective behavioral responses (e.g., faster response times and better accuracy) on executive cognitive tasks as well as flexible and adaptive emotional responding. In contrast, lower resting HRV is associated with hypoactive prefrontal regulation; this results in hyperactive subcortical structures, which leads to maladaptive cognitive and emotional self-regulation. For example, people with lower resting HRV often fail to recognize safety cues or to habituate to novel, neutral stimuli (hyper-vigilance; for a review, see;; ). Additionally, people with lower resting HRV responded to neutral stimuli with heightened startle and neural responses as if the stimuli were emotionally negative. Evidently there is a link between HRV and the prefrontal-subcortical circuits critical for cognitive and emotional self-regulation.

HRV AND TOP-DOWN AND BOTTOM-UP VISUAL PERCEPTION OF EMOTIONAL STIMULI

We investigated whether resting HRV is associated with top-down and bottom-up visual perception of emotional facial expressions. To further isolate neuro-cognitive mechanisms, we presented faces at different spatial frequencies which are defined as the energy distribution in the scale specified as the number of cycles per degree of visual angle and/or the number of cycles per image (see Figure 2 from;; ). Broad spatial frequency (BSF) images contain all spatial frequency ranges and can be filtered to contain either high or low spatial frequencies. Research has indicated that distinctive visual pathways are selectively sensitive to different ranges of spatial frequency information. For example, the parvocellular pathway, which mediates perception of color and contrast, is sensitive to high spatial frequency (HSF) information. HSF fearful faces, in particular, elicited greater activity in the cortical structures, including the posterior cingulate, the motor cortex, the medial prefrontal cortex, and the lateral orbitofrontal cortex. The magnocellular pathway, which mediates perception of depth, motion, and low contrast black-and-white information, is sensitive to low spatial frequency (LSF) information. LSF fearful faces, in particular, are processed via the retinotectal pathway, the phylogenetically old visual pathway that directs information from the retina through the superior colliculus and pulvinar nucleus of the thalamus to the amygdala. As a result, greater amygdala activity was elicited by blurred and coarse LSF fearful faces. Therefore, emotional messages at LSF appear to be processed directly via the amygdala and subcortical mechanisms.

It has been suggested that discriminating emotions using HSF information is difficult, whereas discriminating emotions using LSF information is relatively easy. When statistical properties of fearful and neutral faces with different spatial frequency information were analyzed, the statistical distributions of HSF fearful and neutral faces overlapped completely so that it was difficult for observers to discriminate emotion using HSF information; however, the statistical distributions of LSF fearful and neutral faces were so distinctive that it was easy to discriminate emotion using LSF information. As such, discriminating emotions using LSF is an easy task, whereas discriminating emotions using HSF is a difficult task that may require greater executive function mediated by the prefrontal cortex. In our recent study, participants were presented with fearful and neutral faces at BSF, HSF, and LSF for 200 ms and asked to discriminate the emotion of each face as quickly and accurately as possible. The results showed that people with higher resting HRV were capable of identifying HSF fearful faces more accurately than people with lower resting HRV. Thus, as predicted, there was a positive association between HRV and task performance (e.g., accuracy) on discriminating the emotion of HSF fearful faces.

Furthermore, we examined whether the top-down influence of different processing goals would modulate the relationship between HRV and the bottom-up visual perception of HSF fearful faces. A previous study revealed that the utilization of spatial frequency information depends on processing goals. When people were asked to discriminate the emotion of hybrid face stimuli (i.e., happy, neutral, and angry), they primarily utilized LSF information. In contrast, when people were asked to discriminate whether the stimuli were expressive or not, they utilized HSF information. Thus, the utilization of HSF information facilitates the discrimination of expressiveness. Consistent with this view, our results showed that the positive relationship between resting HRV and task performance observed in the emotion discrimination task diminished in the expressiveness discrimination task. The studies provided initial evidence that cardiac vagal tone is positively associated with the bottom-up processing of visual discrimination of emotion in HSF fearful faces, which is modulated by the top-down influence of different processing goals.

HRV AND TOP-DOWN AND BOTTOM-UP EMOTIONAL ATTENTION

Research has indicated that neural structures implicated in attentional systems, such as the pulvinar, the cingulate, and the fronto-parietal cortex, influence and are influenced by affective processing (; for a review, see ). Also, attentional systems play an important role in emotional regulation by allowing an organism to select and focus on optimal responses from a broad behavioral repertoire and to inhibit less functional responses. Our research demonstrates that individual differences in resting HRV are associated with the ability to control different attentional systems in response to emotional stimuli.

Emotional attention refers to a phenomenon in which emotional stimuli are more likely to modulate one’s attention (; see, for a review). Emotional attention has been extensively studied using Posner’s spatial cuing paradigm (for a review, see; ) to disentangle how different attentional components are involved in affective processing. In the spatial cuing task, a cue can either accurately predict the location of a subsequent target (valid) or not (invalid;;; see Figure 3). Two different types of attentional orienting have been identified: (a) exogenous and (b) endogenous attentional orienting. Exogenous orienting is characterized as a bottom-up, reflexive orienting mode that is associated with neural activity of the posterior attention system, which includes the superior parietal cortex, pulvinar, and superior colliculus. Exogenous orienting is typically observed when the duration between the onset of a cue and the onset of a target [stimulus-onset asynchrony (SOA)] is short, peaking at 150 ms. Endogenous orienting is characterized as a top-down, voluntary attentional mode, and is associated with the anterior attention system, which includes the anterior cingulate and prefrontal cortex. Endogenous orienting is typically observed when the majority of the cues are valid at long SOAs (e.g., >300 ms). People notice that a target is more likely to appear where a preceding cue is presented and strategically exert voluntary attentional control.

A number of empirical studies have reported that when emotional stimuli (e.g., fearful faces) are presented as cues in the task, people are faster to detect targets in valid trials (faster attentional engagement) and slower to disengage attention away from cues in invalid trials (slower attentional disengagement;;;;; ). However, faster engagement to and slower disengagement from fearful faces are construed as maladaptive because faster engagement indicates hyper-vigilance to threatening stimuli, and slower attentional disengagement indicates the failure to inhibit attention from them. For example, it has been well established that people with high anxiety exhibit faster attentional engagement to and slower attentional disengagement from threatening stimuli compared to healthy controls.

Neuroimaging studies have revealed that fearful face cues facilitate attentional engagement through the neural mechanisms of the posterior attentional system, which includes the superior parietal cortex, pulvinar, and superior colliculus. Therefore, the neural mechanisms associated with exogenous orienting are also involved in controlling attentional engagement to fearful faces cues. Not only that, but the same subcortical structures are implicated in processing LSF fearful faces. Taking the evidence together, attentional engagement to LSF fearful face cues under the exogenous attention mode can be construed as a bottom-up mode of emotional attention because they are all associated with activity in subcortical neural mechanisms.

In contrast, attentional disengagement from fearful face cues in invalid trials is associated with increased activity of the ventromedial prefrontal cortex, including the rostral anterior cingulate cortex. Thus, both attentional disengagement from fearful face cues and endogenous attention are associated with activity in prefrontal neural structures. Not only that, but the prefrontal structures are also implicated in processing HSF fearful faces. Taking the evidence together, attentional disengagement from HSF fearful face cues under the endogenous mode can be construed as a top-down mode of emotional attention because they are all associated with activity in cortical neural mechanisms. We then examined the relationship between HRV and top-down and bottom-up aspects of emotional attention.

People with lower resting HRV showed significantly faster attentional engagement to LSF fearful faces relative to people with higher resting HRV at short SOAs (250 ms; Experiment 1), suggesting hyper-vigilant responses to threatening stimuli primilarly tapping into subcortical mechanisms. However, with longer SOAs, (960 ms), people with lower resting HRV showed significantly slower attentional disengagement from HSF fearful faces relative to people with higher resting HRV, suggesting the failure to inhibit attention from threatening stimuli primarily tapping into cortical mechanisms. These findings provide initial evidence that individual differences in resting HRV are associated with top-down and bottom-up emotional attention. People with higher resting HRV – associated with highly functional emotional and cognitive self-regulatory systems – show more adaptive top-down and bottom-up emotional attention, which may facilitate effective emotion regulation. In contrast, people with lower resting HRV – associated with poor emotional and cognitive self-regulatory systems – show maladaptive top-down and bottom-up emotional attention, which may be detrimental to emotion regulation.

In addition, another study by our group provides further evidence that individual differences in resting HRV predict the functioning of inhibitory attentional mechanisms critical for top-down emotional attention. The inhibition of return (IOR) refers to the inhibitory attentional mechanism that prevents one’s attention from going back to previously attended areas, thereby facilitating adaptive search. Although people’s attention is initially drawn to the location of a stimulus, it is diverted to explore new locations when the location of the stimuli is irrelevant to the task and there is time to shift. Extensive research has revealed that there are at least two separate neural mechanisms of IOR: (a) collicular (retinotectal) and (b) cortical mechanisms, including the temporo-parietal cortex and anterior cingulate cortex, which are typically associated with attentional control. We examined whether individual differences in HRV would predict the IOR to emotional and neutral face cues. Furthermore, we explored whether the relationship between HRV and IOR to emotional stimuli depended on different neural pathways of IOR.

To dissociate the roles of the collicular and cortical pathways of IOR, we utilized LSF and HSF fearful facial stimuli, which are selectively sensitive to collicular (retinotectal) and cortical mechanisms, respectively. In general, people with lower resting HRV failed to demonstrate the IOR effect, indicating reduced inhibitory function. In contrast, people with higher resting HRV demonstrated a typical IOR effect, which was even more pronounced in response to HSF fearful faces that tapped into the cortical based IOR. These findings demonstrate that people with higher resting HRV are capable of controlling inhibitory attention, highly instrumental in top-down emotional attention, whereas people with low resting HRV are less capable of controlling it.

PHASIC HRV AND COGNITIVE EMOTION REGULATION

There is a growing body of evidence suggesting that changes in cardiac activity indexed by phasic HRV are linked with self-regulatory effort. However, whether phasic HRV suppression or enhancement is associated with the exertion of self-regulatory effort may depend on the context in which phasic HRV changes occur. Phasic HRV suppression has been construed as an autonomic response to stress, which reflects the withdrawal of cardiac vagal control and the activation of the defensive systems to cope with a stressor. For example, when people were exposed to a video clip triggering stress such as depicting an escalating conflict, asked to perform a difficult mental stress task, or engaging in worry and fear or anger imagery, phasic HRV suppression was observed. Conversely, phasic HRV enhancement has been construed as the exertion of self-regulatory effort while engaging in emotional regulation (e.g., employing emotion self-regulatory methods such as suppression or reappraisal) or performing a task that requires self-regulatory effort. For example, phasic HRV enhancement was observed when participants were instructed to eat only carrots, which demanded greater self-regulatory effort, compared to when instructed to eat only cookies, demanded less self-regulatory effort. Phasic HRV enhancement was even more pronounced in people with higher resting HRV. Additionally, greater phasic HRV enhancement was observed, when female participants were exposed to an upsetting film and then asked to regulate emotion by engaging in emotion suppression (i.e., suppressing emotional expressions) or emotion reappraisal (i.e., reappraising a situation to generate desired emotions), compared to controls. Thus, engaging in both emotion suppression and reappraisal was associated with phasic HRV enhancement. Furthermore, a recent neuroimaging finding revealed that phasic HRV enhancement was correlated with greater activation in the subgenual anterior cingulate cortex associated with emotional regulation.

We recently examined the extent to which individual differences in self-regulatory capacity, indexed by resting HRV, were associated with the exertion of self-regulatory effort, indexed by phasic HRV, in response to emotional versus neutral distractors under different levels of cognitive load. Participants were instructed to detect a target letter, either X or N, among letter strings superimposed on either fearful or neutral distractor faces. Letter strings consisted of six target letters under low load and one target letter and five non-target letters under high load (see Figure 4). People with higher and lower resting HRV were not different in task performance under low load. However, under high load, people with higher resting HRV were faster in conditions with neutral distractors, but not with fearful distractors, whereas people with lower resting HRV were slower in conditions with both fearful and neutral distractors. More importantly, people with lower resting HRV showed phasic HRV suppression, which suggested making an autonomic stress response, in the conditions with fearful distractor faces under both low and high load. Thus, people with lower resting HRV appeared to make autonomic stress responses to trivial threat cues as if the cues were significant stressors. Conversely, people with higher resting HRV showed phasic HRV enhancement, which suggested making greater self-regulatory effort, under low load with fearful distractors and an absence of phasic HRV suppression under high load. Thus, people with higher resting HRV were capable of exerting emotion regulatory effort in response to fearful distractors under low load when processing resources were available under low load. However, people with higher resting HRV did not make an autonomic stress response, even under high load when task performance could be potentially stressful. The results are consistent with a previous study reporting that phasic HRV enhancement were observed in healthy individuals with higher resting HRV and phasic HRV suppression in patients suffering from social anxiety disorder characterized by lower resting HRV in response to emotionally negative stimuli. Our study further clarified that the availability of processing resources under different levels of load plays an important role in the effect of resting HRV on phasic HRV changes. As such, there is a growing body of literature suggesting that resting cardiac vagal tone is associated with the ability to flexibly control autonomic responses as well as selective attention, which may promote further emotion regulation and autonomic flexibility.

IMPLICATION OF HRV ON INDIVIDUAL WELL-BEING AND MENTAL HEALTH

Results of extensive research have indicated that low resting HRV is typically observed in people with various psychopathologies, including generalized anxiety disorder, panic disorder, depression, bipolar disorder, and schizophrenia. Furthermore, healthy individuals with lower resting HRV demonstrate heightened activity in the middle occipital gyrus and the cuneus during visual perception of emotional and neutral stimuli, which are typically observed in people with high risk of psychosis. Another line of research has indicated that cognitive processing of emotional stimuli may significantly contribute to the etiology and maintenance of various psychopathologies, such as anxiety, depression, and schizophrenia. For example, it has been well established that people with high anxiety are characterized by attentional bias favoring threatening stimuli. Schizophrenic patients also exhibit impaired visual perception of emotional facial expressions (see, for a review). However, there has been limited evidence linking HRV to bottom-up and top-down cognitive processing of emotional stimuli. Our research systematically examine the relationship between HRV and top-down and bottom-up visual perception and emotion attention and provide evidence that lower resting HRV is associated with hyper-vigilant and maladaptive bottom-up and impaired top-down cognitive response to emotional stimuli. These studies raise the possibility that lower resting HRV may be a predisposing factor that increases the susceptibility of developing emotional and psychiatric problems.

Furthermore, several studies provided evidence that resting HRV is associated with the ability to control autonomic responses. People with lower resting HRV showed an autonomic stress response, phasic HRV suppression, to fearful stimuli, indicating that they interpret seemingly mild stimuli as a significant stressor. This hyper-vigilant autonomic stress response will trigger a cascade of psychological and physiological defensive responses, which eventually puts wear and tear on a host of physiological systems. Indeed, lower resting HRV has been frequently observed in people suffering from various health problems, such as hypertension, diabetes, high cholesterol, obesity, arthritis, and some cancers. Therefore, the failure in effective cognitive processing of emotion stimuli may impact not only mental and psychology well-being but also physical health.

CONCLUSION

The current review presented evidence of an underlying interaction between individual differences in cardiac vagal tone and top-down and bottom-up cognitive processing of emotional stimuli, which promotes further regulatory behaviors and autonomic flexibility. To further dissociate top-down and bottom-up mechanisms, we utilized stimuli with different spatial frequency ranges designed to tap into either top-down or bottom-up neural mechanisms of emotional processing. These studies provide evidence that higher resting HRV is associated with flexible and adaptive top-down and bottom-up cognitive processing, which facilitates effective emotion regulation. In contrast, lower resting HRV is associated with hyper-vigilant and maladaptive bottom-up and impaired top-down cognitive response to emotional stimuli, which is detrimental to emotion regulation. The results of these studies raise the possibility that maladaptive cognitive processing of emotional stimuli observed in people with lower HRV may be detrimental to emotional and physical health, which explains why people with a wide range of psychopathologies and health issues exhibit lower HRV.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References 80

  1. 1.

    Ahern G. L. Sollers J. J. Lane R. D. Labiner D. M. Herring A. M. Weinand M. E. (2001 ). Heart rate and heart rate variability changes in the intracarotid sodium amobarbital (ISA) test. Epilepsia 42 912–921

    Not in our library10.1046/j.1528-1157.2001.042007912.x

  2. 2.

    Bär K.-J. Berger S. Metzner M. Boettger M. K. Schulz S. C. Ramachandraiah C. T. (2009 ). Autonomic dysfunction in unaffected first-degree relatives of patients suffering from schizophrenia. Schizophr. Bull. 36 1050–1058

    Not in our library10.1093/schbul/sbp024

  3. 3.

    Bär K.-J. Wernich K. Boettger S. Cordes J. Boettger M. K. Loffler S. (2008 ). Relationship between cardiovagal modulation and psychotic state in patients with paranoid schizophrenia. Psychiatry Res. 157 255–257

    Not in our library10.1016/j.psychres.2007.04.021

  4. 4.

    Bartolomeo P. Sieroff E. Decaix C. Chokron S. (2001 ). Modulating the attentional bias in unilateral neglect: the effects of the strategic set. Exp. Brain Res. 137 432–444

    Not in our library10.1007/s002210000642

  5. 5.

    Beauchaine T. P Gatzke-Kopp L. Mead H. K. (2007 ). Polyvagal theory and development psychopathology: emotion dysregulation and conduct problems from preschool to adolescence. Biol. Psychol. 74 174–184

    Not in our library10.1016/j.biopsycho.2005.08.008

  6. 6.

    Benarroch E. (1993 ). The central autonomic network: functional organization, dysfunction, and perspective. Mayo Clin. Proc. 68 988–1001

    Not in our library10.1016/s0025-6196(12)62272-1

  7. 7.

    Berger A. Henik A. Rafal R. (2005 ). Competition between endogenous and exogenous orienting of visual attention. J. Exp. Psychol. Gen. 134 207–221

    Not in our library10.1037/0096-3445.134.2.207

  8. 8.

    Butler E. A. Wilhelm F. H. Gross J. J. (2006 ). Respiratory sinus arrhythmia, emotion, and emotion regulation during social interaction. Psychophysiology 43 612–622

    Not in our library10.1111/j.1469-8986.2006.00467.x

  9. 9.

    Callicott J. H. Mattay V. S. Verchinski B. A. Marenco S. Egan M. F. Weinberger D. R. (2003 ). Complexity of prefrontal cortical dysfunction in schizophrenia: more than up or down. Am. J. Psychiatry 160 2209–2215

    Not in our library10.1176/appi.ajp.160.12.2209

  10. 10.

    Castro M. N. Vigo D. E. Weidema H. Fahrer R. D. Chu E. M. Achaval D. (2008 ). Heart rate variability response to mental arithmetic stress in patients with schizophrenia: autonomic response to stress in schizophrenia. Schizophr. Res. 99 294–303

    Not in our library10.1016/j.schres.2007.08.025

  11. 11.

    Cisler J. M Koster E. H. W. (2010 ). Mechanisms of attentional biases towards threat in anxiety disorders: an integrative review. Clin. Psychol. Rev. 30 203–216

    Not in our library10.1016/j.cpr.2009.11.003

  12. 12.

    Coull J. T. Frith C. D. Buchel C. Nobre A. C. (2000 ). Orienting attention in time: behavioral and neuroanatomical distinction between exogenous and endogenous shifts. Neuropsychologia 38 808–819

    Not in our library10.1016/s0028-3932(99)00132-3

  13. 13.

    Darwin C. (1872 ). The Expression of Emotions in Man and Animals. London: John Murray.

    Not in our library

  14. 14.

    Davidson R. J. Pizzagalli D. Nitschke J. B. Putnam K. (2002 ). Depression: perspectives from affective neuroscience. Annu. Rev. Psychol. 53 545–574

    Not in our library10.1146/annurev.psych.53.100901.135148

  15. 15.

    Edwards J. Jackson H. J. Pattison P. E. (2002 ). Emotion recognition via facial expression and affective prosody in schizophrenia: a methodological review. Clin. Psychol. Rev. 22 789–832

    Not in our library10.1016/s0272-7358(02)00130-7

  16. 16.

    Ellis R. J. Thayer J. F. (2010 ). Music and autonomic nervous system (dys)function. Music Percept. 27 317–326

    Not in our library10.1525/mp.2010.27.4.317

  17. 17.

    El-Sheikh M. Hinnant J. B. Erath S. (2011 ). Developmental trajectories of delinquency symptoms in childhood: the role of marital conflict and autonomic nervous system activity. J. Abnorm. Psychol. 120 16–32

    Not in our library10.1037/0012-1649.39.2.222

  18. 18.

    Fox E. Russo R. Dutton K. (2002 ). Attentional bias for threat: evidence for delayed disengagement from emotional faces. Cogn. Emot. 16 355–379

    Not in our library10.1080/02699930143000527

  19. 19.

    Friedman B. H. (2007 ). An autonomic flexibility-neurovisceral integration model of anxiety and cardiac vagal tone. Biol. Psychol. 74 185–199

    Not in our library10.1016/j.biopsycho.2005.08.009

  20. 20.

    Friedman B. H. Thayer J. F. (1998 ). Autonomic balance revisited: panic anxiety and heart rate variability. J. Psychosom. Res. 44 133–151

    Not in our library10.1016/s0022-3999(97)00202-x

  21. 21.

    Gaebler M. Danielsa J. K. Lamkea J.-P. Fydrichb T. Walter H. (2013 ). Heart rate variability and its neural correlates during emotional face processing in social anxiety disorder. Biol. Psychol. 94 319–330

    Not in our library10.1016/j.biopsycho.2013.06.009

  22. 22.

    Goffaux V. Hault B. Michel C. Vuong Q. C. Rossion B. (2005 ). The respective role of low and high spatial frequencies in supporting configural and featural processing of faces. Perception 34 77–86

    Not in our library10.1068/p5370

  23. 23.

    Gross J. J. (1998 ). Antecedent- and response-focused emotion regulation: divergent consequences for experience, expression, and physiology. J. Pers. Soc. Psychol. 74 224–237

    Not in our library10.1037/0022-3514.74.1.224

  24. 24.

    Gross J. J Thompson R. A. (2007 ). “Emotion regulation: conceptual foundations,” in Handbook of Emotion Regulation ed. Gross J. J. (New York, NY:Guilford Press) 3–24

    Not in our library

  25. 25.

    Hansen A. L. Johnsen B. H. Thayer J. F. (2003 ). Vagal influence on working memory and attention. Int. J. Psychophysiol. 48 263–274

    Not in our library10.1016/s0167-8760(03)00073-4

  26. 26.

    Heatherton T. F. Wagner D. D. (2011 ). Cognitive neuroscience of self-regulation failure. Trends Cogn. Sci. 15 132–139

    Not in our library10.1016/j.tics.2010.12.005

  27. 27.

    Holmes A. Green S. Vuilleumier P. (2005 ). The involvement of distinct visual channels in rapid attention towards fearful facial expressions. Cogn. Emot. 19 899–922

    Not in our library10.1080/02699930441000454

  28. 28.

    Huang-Pollock C. L. Jigg J. L. (2003 ). Searching for the attention deficit in attention deficit hyperactivity disorder: the case of visuospatial orienting. Clin. Psychol. Rev. 23 801–830

    Not in our library10.1016/s0272-7358(03)00073-4

  29. 29.

    Johnstone T. van Reekum C. M. Urry H. L. Kalin N. H. Davidson R. J. (2007 ). Failure to regulate: counterproductive recruitment of top-down prefrontal-subcortical circuitry in major depression. J. Neurosci. 27 8877–8884

    Not in our library10.1523/jneurosci.2063-07.2007

  30. 30.

    Kim M. J. Whalen P. J. (2009 ). The structural integrity of an amygdala–prefrontal pathway predicts trait anxiety. J. Neurosci. 29 11614–11618

    Not in our library10.1523/jneurosci.2335-09.2009

  31. 31.

    Klein R. M. MacInnes W. J. (1999 ). Inhibition of return is a foraging facilitator in visual search. Psychol. Sci. 10 346–352

    Not in our library10.1111/1467-9280.00166

  32. 32.

    Koster E. H. W. Crombez G. Verschuere B. Damme S. V. Wiersema J. R. (2006 ). Components of attentional bias to threat in high trait anxiety: facilitated engagement, impaired disengagement, and attentional avoidance. Behav. Res. Ther. 44 1757–1771

    Not in our library10.1016/j.brat.2005.12.011

  33. 33.

    Lane R. D. McRae K. Reiman E. M. Chen K. Ahern G. L. Thayer J. F. (2009 ). Neural correlates of heart rate variability during emotion. Neuroimage 44 213–222

    Not in our library10.1016/j.neuroimage.2008.07.056

  34. 34.

    Lane R. D. Weidenbacher H. Smith R. Fort C. Thayer J. F Allen J. J. B. (2013 ). Subgenual anterior cingulate cortex activity covariation with cardiac vagal control is altered in depression. J. Affect. Disord. 150 565–570

    Not in our library10.1016/j.jad.2013.02.005

  35. 35.

    Lee S. H. Park G. (2011 ). “Psychophysiological markers of anxiety disorders and anxiety symptoms,” in Anxiety Disorders ed. Kalinin V. (Rijeka:InTech) 203–226 Retrieved from: http://www.intechopen.com/books/anxiety-disorders/psychophysiologicalmarkers-of-anxiety-disorders-and-anxiety-symptoms

    Not in our library

  36. 36.

    Levy M. (1971 ). Sympathetic–parasympathetic interactions in the heart. Circ. Res. 29 437–445

    Not in our library10.1161/01.res.29.5.437

  37. 37.

    Lewis D. A. Hashimoto T. Volk D. W. (2005 ). Cortical inhibitory neurons and schizophrenia. Nat. Rev. Neurosci. 6 312–324

    Not in our library10.1038/nrn1648

  38. 38.

    Li C. S. R. Sinha R. (2008 ). Inhibitory control and emotional stress regulation: neuroimaging evidence for frontal–limbic dysfunction in psycho-stimulant addiction. Neurosci. Biobehav. Rev. 32 581–597

    Not in our library10.1016/j.neubiorev.2007.10.003

  39. 39.

    Livingstone M. Hubel D. (1988 ). Segregation of form, color, movement, and depth: anatomy, physiology, and perception. Science 240 740–749

    Not in our library10.1126/science.3283936

  40. 40.

    Lyonfields J. D. Borkovec T. D. Thayer J. F. (1995 ). Vagal tone in generalized anxiety disorder and the effects of aversive imagery and worrisome thinking. Behav. Ther. 26 457–466

    Not in our library10.1016/s0005-7894(05)80094-2

All 80 references

Cited by papers we hold 4

Reads

Read by people on this page

None yet.

Checked or read by AI through naulon

None yet.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

Are you an author?

Is this your paper?

Claim it to add your note and be paid when agents cite it. Free.