Classifying social anxiety disorder using multivoxel pattern analyses of brain function and structure

Frick, Andreas; Gingnell, Malin; Marquand, André F.; Howner, Katarina; Fischer, Håkan; Kristiansson, Marianne; Williams, Steven; Fredrikson, Mats; Furmark, Tomas

doi:10.1016/j.bbr.2013.11.003

Cited by 63 publications

(69 citation statements)

References 25 publications

(30 reference statements)

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“…However, subsequent studies could not substantiate these results to the same degree Shenas et al, 2014). Two studies on SAD have been published in small samples, reporting accuracies above 80% (Frick et al, 2014;Liu et al, 2013). Multivariate patterns in these studies were derived from different MRI modalities indicating that features relevant for disorder classification can be extracted and analysed across modalities.…”

Section: Obsessive Compulsive Social Anxiety Post-traumatic Stress mentioning

confidence: 94%

“…Multivariate patterns in these studies were derived from different MRI modalities indicating that features relevant for disorder classification can be extracted and analysed across modalities. In general informative features were found to be distributed across widespread brain areas (Frick et al, 2014;Liu et al, 2013) and not easily localisable to brain regions usually associated with anxieties, such as the limbic lobes (Damsa et al, 2009). An additional study showed that structural images can be used as a diagnostic medium for different specific phobias, which could reliably be classified based on grey and white matter densities (Lueken et al, 2014).…”

Section: Obsessive Compulsive Social Anxiety Post-traumatic Stress mentioning

confidence: 98%

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From estimating activation locality to predicting disorder: A review of pattern recognition for neuroimaging-based psychiatric diagnostics

Wolfers

Buitelaar

Beckmann

et al. 2015

Neuroscience & Biobehavioral Reviews

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Psychiatric disorders are increasingly being recognised as having a biological basis, but their diagnosis is made exclusively behaviourally. A promising approach for 'biomarker' discovery has been based on pattern recognition methods applied to neuroimaging data, which could yield clinical utility in future. In this review we survey the literature on pattern recognition for making diagnostic predictions in psychiatric disorders, and evaluate progress made in translating such findings towards clinical application. We evaluate studies on many criteria, including data modalities used, the types of features extracted and algorithm applied. We identify problems common to many studies, such as a relatively small sample size and a primary focus on estimating generalisability within a single study. Furthermore, we highlight challenges that are not widely acknowledged in the field including the importance of accommodating disease prevalence, the necessity of more extensive validation using large carefully acquired samples, the need for methodological innovations to improve accuracy and to discriminate between multiple disorders simultaneously. Finally, we identify specific clinical contexts in which pattern recognition can add value in the short to medium term.

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Section: Obsessive Compulsive Social Anxiety Post-traumatic Stress mentioning

confidence: 94%

Section: Obsessive Compulsive Social Anxiety Post-traumatic Stress mentioning

confidence: 98%

From estimating activation locality to predicting disorder: A review of pattern recognition for neuroimaging-based psychiatric diagnostics

Wolfers

Buitelaar

Beckmann

et al. 2015

Neuroscience & Biobehavioral Reviews

Self Cite

253

242

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“…With respect to correlations between anxiety and brain structures, controversies remain. One study suggested that social anxiety disorder implicates GM alterations over the whole brain 24 . On the other hand, this syndrome may be characterized by disrupted neural activity in the fear network composed of the amygdala, anterior cingulate cortex, hippocampus, and insula.…”

Section: Discussionmentioning

confidence: 99%

Cortical correlates of affective syndrome in dementia due to Alzheimer’s disease

Hayata

Bergo

Rezende

et al. 2015

Arq. Neuro-Psiquiatr.

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Neuropsychiatric syndromes (NPS) in dementia due to Alzheimer' s disease (AD) have received growing attention across clinical centers and research settings in the last few decades. The high prevalence of NPS and their increasing severity in AD patients aggravate the disease' s course and cause distress for caregivers. These symptoms, once considered secondary behavior due to cognitive and functional impairment in dementia, have shown patterns of temporal course, which do not necessarily follow the linear decline of cognitive impairment.Several NPS seem to be more prevalent and clinically prominent in distinct stages of the disease. Depression is the most common syndrome in mild-to-moderate AD, while delusions, hallucinations, and aggression seem to be more common as the disease progresses, whereas apathy remains across all stages of AD, worsening as the global deterioration aggravates. However, these manifestations, also detected in mild cognitive impairment (MCI), increase the risk of dementia and may occur in prodromal AD.Moreover, aberrant vocalizations commonly emerge when patients are in advanced stages of dementia. Despite the fact that NPS and cognitive alterations may considerably overlap, these findings suggest distinct etiologies for both conditions. Furthermore, over the course of the disease, the prevalence of NPS reaches 50-90% of patients with dementia AbstrACtNeuropsychiatric symptoms in Alzheimer's disease (AD) are prevalent, however their relationship with patterns of cortical atrophy is not fully known. Objectives: To compare cortical atrophy's patterns between AD patients and healthy controls; to verify correlations between neuropsychiatric syndromes and cortical atrophy. Method: 33 AD patients were examined by Neuropsychiatric Inventory (NPI). Patients and 29 controls underwent a 3T MRI scanning. We considered four NPI syndromes: affective, apathy, hyperactivity and psychosis. Correlations between structural imaging and neuropsychiatric scores were performed by Freesurfer. Results were significant with a p-value < 0.05, corrected for multiple comparisons. Results: Patients exhibited atrophy in entorhinal cortices, left inferior and middle temporal gyri, and precuneus bilaterally. There was correlation between affective syndrome and cortical thickness in right frontal structures, insula and temporal pole. Conclusion: Cortical thickness measures revealed atrophy in mild AD. Depression and anxiety symptoms were associated with atrophy of right frontal, temporal and insular cortices.Keywords: depression, anxiety, MRI, neurodegenerative disease, neuropsychiatry. resumo Os sintomas neuropsiquiátricos na doença de Alzheimer (DA) são prevalentes, porém suas relações com padrões de atrofia cortical não são totalmente compreendidas. Objetivos: Comparar padrões de atrofia cortical entre DA e controles; verificar se há correlações entre sintomas neuropsiquiátricos e atrofia cortical. Método: 33 pacientes com DA foram examinados pelo Inventário Neuropsiquiátrico. Os pacientes e 29 controles foram submeti...

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“…The amygdala thus undoubtedly plays a critical role in salience, vigilance‐avoidance and stress processing, and amygdala activity constitutes a potential biomarker for social anxiety, e.g., Ref . However, future research also needs to address some the concerns raised above (and other ones, see Ref ) regarding the role of the amygdala and the emotion network in social anxiety.…”

Section: The Emotion Networkmentioning

confidence: 99%

Social anxiety disorder: a critical overview of neurocognitive research

Cremers

Roelofs

2016

WIRES Cognitive Science

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Social anxiety is a common disorder characterized by a persistent and excessive fear of one or more social or performance situations. Behavioral inhibition is one of the early indicators of social anxiety, which later in life may advance into a certain personality structure (low extraversion and high neuroticism) and the development of maladaptive cognitive biases. While there are several effective psycho- and pharmacotherapy options, a large number of patients benefit insufficiently from these therapies. Brain and neuroendocrine research can help uncover both the biological basis of social anxiety and potentially provide indicators, 'biomarkers,' that may be informative for early disease detection or treatment response, above and beyond self-report data. Several large-scale brain networks related to emotion, motivation, cognitive control, and self-referential processing have been identified, and are affected in social anxiety. Social anxiety is further characterized by increased cortisol response and lower testosterone levels. These neuroendocrine systems are also related to altered connectivity patterns, such as reduced amygdala-prefrontal coupling. Much work is needed however to further elucidate such interactions between neuroendocrine functioning and large-scale brain networks. Despite the great promise of brain research in uncovering the neurobiological basis of social anxiety, several methodological and conceptual issues also need to be considered. WIREs Cogn Sci 2016, 7:218-232. doi: 10.1002/wcs.1390 For further resources related to this article, please visit the WIREs website.

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Classifying social anxiety disorder using multivoxel pattern analyses of brain function and structure

Cited by 63 publications

References 25 publications

From estimating activation locality to predicting disorder: A review of pattern recognition for neuroimaging-based psychiatric diagnostics

From estimating activation locality to predicting disorder: A review of pattern recognition for neuroimaging-based psychiatric diagnostics

Cortical correlates of affective syndrome in dementia due to Alzheimer’s disease

Social anxiety disorder: a critical overview of neurocognitive research

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