Although aberrant brain regional responses are reported in social anxiety disorder (SAD), little is known about resting-state functional connectivity at the macroscale network level. This study aims to identify functional network abnormalities using a multivariate data-driven method in a relatively large and homogenous sample of SAD patients, and assess their potential diagnostic value.

Forty-six SAD patients and 52 demographically-matched healthy controls (HC) were recruited to undergo clinical evaluation and resting-state functional MRI scanning. We used group independent component analysis to characterize the functional architecture of brain resting-state networks (RSNs) and investigate between-group differences in intra-/inter-network functional network connectivity (FNC). Furtherly, we explored the associations of FNC abnormalities with clinical characteristics, and assessed their ability to discriminate SAD from HC using support vector machine analyses.

SAD patients showed widespread intra-network FNC abnormalities in the default mode network, the subcortical network and the perceptual system (i.e. sensorimotor, auditory and visual networks), and large-scale inter-network FNC abnormalities among those high-order and primary RSNs. Some aberrant FNC signatures were correlated to disease severity and duration, suggesting pathophysiological relevance. Furthermore, intrinsic FNC anomalies allowed individual classification of SAD v. HC with significant accuracy, indicating potential diagnostic efficacy.

SAD patients show distinct patterns of functional synchronization abnormalities both within and across large-scale RSNs, reflecting or causing a network imbalance of bottom-up response and top-down regulation in cognitive, emotional and sensory domains. Therefore, this could offer insights into the neurofunctional substrates of SAD.

Psychoradiology is a term that describes a growing interest in relating psychiatry and radiological images, proposing a radiological approach in the management of major psychiatric illnesses. This includes the diagnosis, the planning of the treatment and the study of the clinical course.

The objective of this communication is to review the current status of the importance and indications of neuroimaging tests in psychiatry.

A literature review has been carried out to review this issue.

In schizophrenia, longitudinal studies have been carried out that compare the anatomical structures between a first psychotic episode and in a chronic state, locating regional changes that progress as the disease does. Anatomical alterations have also been detected among patients with a predominance of positive symptoms or negative symptoms. Although more and more studies demonstrate a certain common genetic and radiological basis between bipolar disorder and schizophrenia, imaging techniques can also show specific findings that differentiate one pathology from the other. The neuroimaging tests used in psychiatry are: • Brain CT, recommended when a first psychotic episode is suspected. • MRI: recommended in processes of cognitive deterioration, to evaluate white matter and for pregnant patients. It is also recommended to evaluate injuries that could have a poor prognosis with the application of electroconvulsive therapy. • Functional tests (PET and SPECT) are often used to screen some types of dementia such as Alzheimer’s or for research.

New advances and knowledge in psychiatry and radiology must be integrated for better clinical practice.

No significant relationships.

Persistent psychological distress associated with the coronavirus disease 2019 (COVID-19) pandemic has been well documented. This study aimed to identify pre-COVID brain functional connectome that predicts pandemic-related distress symptoms among young adults.

Baseline neuroimaging studies and assessment of general distress using the Depression, Anxiety and Stress Scale were performed with 100 healthy individuals prior to wide recognition of the health risks associated with the emergence of COVID-19. They were recontacted for the Impact of Event Scale-Revised and the Posttraumatic Stress Disorder Checklist in the period of community-level outbreaks, and for follow-up distress evaluation again 1 year later. We employed the network-based statistic approach to identify connectome that predicted the increase of distress based on 136-region-parcellation with assigned network membership. Predictive performance of connectome features and causal relations were examined by cross-validation and mediation analyses.

The connectome features that predicted emergence of distress after COVID contained 70 neural connections. Most within-network connections were located in the default mode network (DMN), and affective network-DMN and dorsal attention network-DMN links largely constituted between-network pairs. The hippocampus emerged as the most critical hub region. Predictive models of the connectome remained robust in cross-validation. Mediation analyses demonstrated that COVID-related posttraumatic stress partially explained the correlation of connectome to the development of general distress.

Brain functional connectome may fingerprint individuals with vulnerability to psychological distress associated with the COVID pandemic. Individuals with brain neuromarkers may benefit from the corresponding interventions to reduce the risk or severity of distress related to fear of COVID-related challenges.