Amygdala responses to masked and low spatial frequency fearful faces: a preliminary fMRI study in panic disorder

Ottaviani, Cristina; Cevolani, Daniela; Nucifora, Valeria; Borlimi, Rosita; Agati, R.; Leonardi, Marco; Plato, Giovanni De; Brighetti, Gianni

doi:10.1016/j.pscychresns.2011.12.010

Cited by 49 publications

(39 citation statements)

References 57 publications

(62 reference statements)

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“…Also, they found that socially anxious participations were more sensitive than non-anxious people to facial information with LSF in the implicit task (Langner et al, 2012). However, Ottaviani et al (2012) reported that LSF information was not a crucial factor for the perception of facial expressions in patients with PD (Ottaviani et al, 2012).…”

Section: P100 Componentmentioning

confidence: 96%

“…However, it is still controversial whether or not LSF information plays an important role in the perception of facial expressions in the presence of anxiety disorders. In previous studies, researchers argued that patients with anxiety disorders responded sensitively to facial expressions with LSF (Langner et al, 2009(Langner et al, , 2012Ottaviani et al, 2012). Langner et al (2009) presented participants with SF-dependent face images that were masked by random bubble patterns; they found that socially anxious people additionally used LSF facial expressions to discriminate between angry and neutral faces, compared to nonanxious people (Langner et al, 2009).…”

Section: P100 Componentmentioning

confidence: 99%

“…According to a previous fMRI study, there was no significant difference in brain activity between patients with PD and HCs when processing facial expressions (fear and neutral) with different SFs (LSF and BSF) (Ottaviani et al, 2012). The authors also mentioned that LSF information was "not so crucial" for subcortical area responses during the processing of fearful faces.…”

Section: Introductionmentioning

confidence: 95%

See 2 more Smart Citations

Influence of spatial frequency and emotion expression on face processing in patients with panic disorder

Shim

Kim

Yoon

et al. 2016

Journal of Affective Disorders

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Section: P100 Componentmentioning

confidence: 96%

Section: P100 Componentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 95%

See 1 more Smart Citation

Influence of spatial frequency and emotion expression on face processing in patients with panic disorder

Shim

Kim

Yoon

et al. 2016

Journal of Affective Disorders

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“…Hyperarousal is a characteristic feature of several forms of panic disorders (Ottaviani et al, 2012) and disorders associated with anxiety. Examples are posttraumatic stress disorder (Edmondson and Cohen, 2013; Perez et al, 2012), attention deficit hyperactivity disorder (Antshel et al, 2013; Hanson et al, 2012), general anxiety disorder (Brunet et al, 2013; Hoge et al, 2013), insomnia (Hantsoo et al, 2013; Killgore et al, 2013; Vincent and Walsh, 2013; Wallhausser-Franke et al, 2013), and Fragile X syndrome (Berry-Kravis et al, 2012; Heilman et al, 2011).…”

Section: When Sighs Enhance Breathing Variability and Induce Hyperamentioning

confidence: 99%

“…For example, “balanced amygdala activation” in response to fearful stimuli may turn into reduced amygdala activation, as is characteristic for panic disorders (Ottaviani et al, 2012), or into a hyperactive amygdala, which would be equally maladaptive. But before discussing these wider network interactions, we would like to focus on the question of how breathing and sighing are generated within the CNS, as this is at the core of this review.…”

Section: The Pre-bötzinger Complex An Essential Brain Region For Tmentioning

confidence: 99%

The Integrative Role of the Sigh in Psychology, Physiology, Pathology, and Neurobiology

Ramirez

2014

Progress in Brain Research

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“Sighs, tears, grief, distress” expresses Johann Sebastian Bach in a musical example for the relationship between sighs and deep emotions. This review explores the neurobiological basis of the sigh and its relationship with psychology, physiology, and pathology. Sighs monitor changes in brain states, induce arousal, and reset breathing variability. These behavioral roles homeostatically regulate breathing stability under physiological and pathological conditions. Sighs evoked in hypoxia evoke arousal and thereby become critical for survival. Hypoarousal and failure to sigh have been associated with sudden infant death syndrome. Increased breathing irregularity may provoke excessive sighing and hyperarousal, a behavioral sequence that may play a role in panic disorders. Essential for generating sighs and breathing is the pre-Bötzinger complex. Modulatory and synaptic interactions within this local network and between networks located in the brainstem, cerebellum, cortex, hypothalamus, amygdala, and the periaqueductal gray may govern the relationships between physiology, psychology, and pathology. Unraveling these circuits will lead to a better understanding of how we balance emotions and how emotions become pathological.

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Defining biotypes for depression and anxiety based on large-scale circuit dysfunction: a theoretical review of the evidence and future directions for clinical translation

2016

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Complex emotional, cognitive and self-reflective functions rely on the activation and connectivity of large-scale neural circuits. These circuits offer a relevant scale of focus for conceptualizing a taxonomy for depression and anxiety based on specific profiles (or biotypes) of neural circuit dysfunction. Here, the theoretical review first outlined the current consensus as to what constitutes the organization of large-scale circuits in the human brain identified using parcellation and meta-analysis. The focus is on neural circuits implicated in resting reflection (“default mode”), detection of “salience”, affective processing (“threat” and “reward”), “attention” and “cognitive control”. Next, the current evidence regarding which type of dysfunctions in these circuits characterize depression and anxiety disorders was reviewed, with an emphasis on published meta-analyses and reviews of circuit dysfunctions that have been identified in at least two well-powered case:control studies. Grounded in the review of these topics, a conceptual framework is proposed for considering neural circuit-defined “biotypes”. In this framework, biotypes are defined by profiles of extent of dysfunction on each large-scale circuit. The clinical implications of a biotype approach for guiding classification and treatment of depression and anxiety is considered. Future research directions will develop the validity and clinical utility of a neural circuit biotype model that spans diagnostic categories and helps to translate neuroscience into clinical practice in the real world.

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Amygdala responses to masked and low spatial frequency fearful faces: a preliminary fMRI study in panic disorder

Cited by 49 publications

References 57 publications

Influence of spatial frequency and emotion expression on face processing in patients with panic disorder

Influence of spatial frequency and emotion expression on face processing in patients with panic disorder

The Integrative Role of the Sigh in Psychology, Physiology, Pathology, and Neurobiology

Defining biotypes for depression and anxiety based on large-scale circuit dysfunction: a theoretical review of the evidence and future directions for clinical translation

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