Neural correlates of emotional processing in panic disorder: A mini review of functional magnetic resonance imaging studies

Topological Data Analysis Captures Task-Driven fMRI Profiles in Individual Participants: A Classification Pipeline Based on Persistence

BOLD-based fMRI is the most widely used method for studying brain function. The BOLD signal while valuable, is beset with unique vulnerabilities. The most notable of these is the modest signal to noise ratio, and the relatively low temporal and spatial resolution. However, the high dimensional complexity of the BOLD signal also presents unique opportunities for functional discovery. Topological Data Analyses (TDA), a branch of mathematics optimized to search for specific classes of structure within high dimensional data may provide particularly valuable applications. In this investigation, we acquired fMRI data in the anterior cingulate cortex (ACC) using a basic motor control paradigm. Then, for each participant and each of three task conditions, fMRI signals in the ACC were summarized using two methods: a) TDA based methods of persistent homology and persistence landscapes and b) non-TDA based methods using a standard vectorization scheme. Finally, using machine learning (with support vector classifiers), classification accuracy of TDA and non-TDA vectorized data was tested across participants. In each participant, TDA-based classification out-performed the non-TDA based counterpart, suggesting that our TDA analytic pipeline better characterized task- and condition-induced structure in fMRI data in the ACC. Our results emphasize the value of TDA in characterizing task- and condition-induced structure in regional fMRI signals. In addition to providing our analytical tools for other users to emulate, we also discuss the unique role that TDA-based methods can play in the study of individual differences in the structure of functional brain signals in the healthy and the clinical brain.

Abnormal causal connectivity of prefrontal-limbic circuit by structural deficits in drug-naive anxiety disorders

BACKGROUND

Structural and functional deficits in the prefrontal-limbic circuit have been revealed in patients with anxiety disorders. However, the effect of structural abnormalities on causal connectivity within this circuit remains unclear. This study aimed to investigate causal connectivity in the prefrontal-limbic circuit associated with structural deficits in drug-naive patients with generalized anxiety disorder (GAD) and panic disorder (PD) and the changes after treatment.

METHODS

A total of 64 GAD patients, 54 PD patients and 61 healthy controls (HCs) completed the resting-state magnetic resonance imaging scans at baseline. Among them, 96 patients with anxiety disorders (52 in GAD group and 44 in PD group) completed a 4-week paroxetine treatment. Voxel-based morphometry and Granger causality analysis (GCA) were applied to analyze the data based on the human brainnetome atlas.

RESULTS

Patients with GAD and PD showed decreased gray matter volume (GMV) in the bilateral A24cd subregions of cingulate gyrus. Whole-brain analysis revealed decreased GMV in the left cingulate gyrus in patients with PD. Hence, the left A24cd subregion was selected as a seed. Compared with HCs, unidirectional causal connectivity between the limbic-superior temporal gyrus (STG) temporal pole and the limbic-precentral/middle frontal gyrus was enhanced in patients with GAD and PD (from the left A24cd subregion of cingulate gyrus to the right STG temporal pole, and from the left A24cd subregion of cingulate gyrus to the right precentral/middle frontal gyrus). Compared with patients with PD, the limbic-precuneus unidirectional causal connectivity was enhanced in patients with GAD, and the cerebellum crus1 - limbic connectivity has a positive feedback effect.

CONCLUSIONS

The anatomical defects in the left A24cd subregion of cingulate gyrus may partially affect the prefrontal-limbic circuit, and the unidirectional causal effect from the left A24cd subregion to the right STG temporal pole may be an imaging change shared by anxiety disorders. The causal effect of the left A24cd subregion of cingulate gyrus to precuneus might be related to the neurobiology of GAD.

Retinal Changes in Panic Disorder Patients

AIM

Optical coherence tomography (OCT) is a novel method that allows high resolution cross-sectional imaging of biological tissues. It was suggested that changes in the cranial structure or functions would be reflected in the retina. OCT has been an important method in the diagnosis and follow-up of diseases via morphometric or quantitative retinal measurements. Panic disorder (PD) is an anxiety disorder, where free radicals, inflammatory processes and neurotransmitter transmission disorders play a role in the etiology. The present study aimed to demonstrate neurodegeneration in PD by the comparison of PD patient and control OCT data.

MATERIAL AND METHOD

The study group included 21 PD patients who met the study criteria. The control group included 21 healthy individuals without any known psychiatric or organic disease, including eye disease, and gender-matched to the patient group. All participants underwent detailed psychiatric and eye examinations. Central macular thickness (CMT), macular volume (MV), mean and retinal nerve fiber layer thickness (RNFL), ganglion cell layer thickness (GCLT), and central choroidal thickness (CCT) were measured in both eyes of all participants with OCT. A sociodemographic data form, Clinical Global Impression Scale (CGIS), and Panic Disorder Severity Scale (PDSS) were administered to the participants.

RESULTS

In the study, it was determined that the CMT values of the PD patients were lower when compared to the controls in the OCT examination. There was a statistically significant difference between the CMT of the PD patient group and the control group; the CMT was lower in the patient group. There were no significant differences between the groups based on GCLT, RNFL superior, RNFL inferior, RNFL nasal, RNFL temporal, and CCT. There was no significant correlation between CGIS, PDSS scores and OCT measurements.

CONCLUSION

This is the first study in the literature where patients with a PD diagnosis were analyzed based on the OCT method. OCT, which is a simple, noninvasive and relatively inexpensive method that the patient could easily adapt to during imaging, could be employed as a supplementary method in the diagnosis and follow-up of PD patients.

Structural and functional neuroimaging of the effects of the gut microbiome

Interactions between intestinal microbiota and the central nervous system profoundly influence brain structure and function. Over the past 15 years, intense research efforts have uncovered the significant association between gut microbial dysbiosis and neurologic, neurodegenerative, and psychiatric disorders; however, our understanding of the effect of gut microbiota on quantitative neuroimaging measures of brain microstructure and function remains limited. Many current gut microbiome studies specifically focus on discovering correlations between specific microbes and neurologic disease states that, while important, leave critical mechanistic questions unanswered. To address this significant gap in knowledge, quantitative structural and functional brain imaging has emerged as a vital bridge and as the next step in understanding how the gut microbiome influences the brain. In this review, we examine the current state-of-the-art, raise awareness of this important topic, and aim to highlight immense new opportunities-in both research and clinical imaging-for the imaging community in this emerging field of study. Our review also highlights the potential for preclinical imaging of germ-free and gnotobiotic models to significantly advance our understanding of the causal mechanisms by which the gut microbiome alters neural microstructure and function. KEY POINTS: • Alterations to the gut microbiome can significantly influence brain structure and function in health and disease. • Quantitative neuroimaging can help elucidate the effect of gut microbiota on the brain and with future translational advances, neuroimaging will be critical for both diagnostic assessment and therapeutic monitoring.