Mean diffusivity related to collectivism among university students in Japan

Collectivism is an important factor for coping with stress in one’s social life. To date, no imaging studies have revealed a direct association between collectivism and white matter structure. Collectivism is positively related to independence, harm avoidance, rejection sensitivity, cooperativeness, external locus of control, and self-monitoring and negatively related to need for uniqueness. Accordingly, we hypothesised that the neural structures underpinning collectivism are those that are also involved with its relationship using magnetic resonance imaging (MRI). This study aimed to identify the brain structures associated with collectivism in healthy young adults (n = 797), using regional grey and white matter volume, fractional anisotropy, and mean diffusivity (MD) analyses of MRI data. Scores on the collectivism scale were positively associated with MD values in the bilateral dorsolateral prefrontal cortex, left orbitofrontal cortex, inferior frontal gyrus, right superior temporal gyrus, ventral posterior cingulate cortex, globus pallidus, and calcarine cortex using the threshold-free cluster enhancement method with family-wise errors corrected to P < 0.05 at the whole-brain level. No significant associations between were found collectivism and other measures. Thus, the present findings supported our hypothesis that the neural correlates of collectivism are situated in regions involved in its related factors

Oscillation-specific nodal alterations in early to middle stages Parkinsons disease.

Background: Different oscillations of brain networks could carry different dimensions of brain integration. We aimed to investigate oscillation-specific nodal alterations in patients with Parkinsons disease (PD) across early stage to middle stage by using graph theory-based analysis. Methods: Eighty-eight PD patients including 39 PD patients in the early stage (EPD) and 49 patients in the middle stage (MPD) and 36 controls were recruited in the present study. Graph theory-based network analyses from three oscillation frequencies (slow-5: 0.01-0.027 Hz; slow-4: 0.027-0.073 Hz; slow-3: 0.073-0.198 Hz) were analyzed. Nodal metrics (e.g. nodal degree centrality, betweenness centrality and nodal efficiency) were calculated. Results: Our results showed that (1) a divergent effect of oscillation frequencies on nodal metrics, especially on nodal degree centrality and nodal efficiency, that the anteroventral neocortex and subcortex had high nodal metrics within low oscillation frequencies while the posterolateral neocortex had high values within the relative high oscillation frequency was observed, which visually showed that network was perturbed in PD; (2) PD patients in early stage relatively preserved nodal properties while MPD patients showed widespread abnormalities, which was consistently detected within all three oscillation frequencies; (3) the involvement of basal ganglia could be specifically observed within slow-5 oscillation frequency in MPD patients; (4) logistic regression and receiver operating characteristic curve analyses demonstrated that some of those oscillation-specific nodal alterations had the ability to well discriminate PD patients from controls or MPD from EPD patients at the individual level; (5) occipital disruption within high frequency (slow-3) made a significant influence on motor impairment which was dominated by akinesia and rigidity. Conclusions: Coupling various oscillations could provide potentially useful information for large-scale network and progressive oscillation-specific nodal alterations were observed in PD patients across early to middle stages

Predicting social anxiety in young adults with machine learning of resting-state brain functional radiomic features

Social anxiety is a symptom widely prevalent among young adults, and when present in excess, can lead to maladaptive patterns of social behavior. Recent approaches that incorporate brain functional radiomic features and machine learning have shown potential for predicting certain phenotypes or disorders from functional magnetic resonance images. In this study, we aimed to predict the level of social anxiety in young adult participants by training machine learning models with resting-state brain functional radiomic features including the regional homogeneity, fractional amplitude of low-frequency fluctuation, fractional resting-state physiological fluctuation amplitude, and degree centrality. Among the machine learning models, the XGBoost model achieved the best performance with balanced accuracy of 77.7% and F1 score of 0.815. Analysis of input feature importance demonstrated that the orbitofrontal cortex and the degree centrality were most relevant to predicting the level of social anxiety among the input brain regions and the input type of radiomic features, respectively. These results suggest potential validity for predicting social anxiety with machine learning of the resting-state brain functional radiomic features and provide further understanding of the neural basis of the symptom.ope

Network abnormalities in generalized anxiety pervade beyond the amygdala-prefrontal cortex circuit: insights from graph theory

Generalized anxiety (GAD) has excessive anxiety and uncontrollable worry as core symptoms. Abnormal cerebral functioning underpins the expression and perhaps pathogenesis of GAD: Studies implicate impaired communication between the amygdala and the pre-frontal cortex (PFC). Our aim was to longitudinally investigate whether such network abnormalities are spatially restricted to this circuit or if the integrity of functional brain networks is globally disrupted in GAD. We acquired resting-state functional magnetic resonance imaging data from 16 GAD patients and 16 matched controls at baseline and after 1 year. Using network modelling and graph-theory, whole-brain connectivity was characterized from local and global perspectives. Overall lower global efficiency, indicating sub-optimal brain-wide organization and integration, was present in patients with GAD compared to controls. The amygdala and midline cortices showed higher betweenness centrality, reflecting functional dominance of these brain structures. Third, lower betweenness centrality and lower degree emerged for PFC, suggesting weakened inhibitory control. Overall, network organization showed impairments consistent with neurobiological models of GAD (involving amygdala, PFC, and cingulate cortex) and further pointed to an involvement of temporal regions. Such impairments tended to progress over time and predict anxiety symptoms. A graph-analytic approach represents a powerful approach to deepen our understanding of GAD

Evidenze dell'ansia sociale in fMRI: una revisione della letteratura

L’esperienza del vivere l’ansia e la paura sociale si presenta come un fenomeno comune alla totalità degli esseri umani, nel senso che tutti, almeno una volta nella vita, abbiamo sperimentato la particolare sensazione di vulnerabilità e di pericolo che insorge in occasione di eventi ritenuti importanti, quando si deve fornire la prova della propria competenza, o magari quando ci si viene a trovare improvvisamente al centro dell’attenzione (Bruni, 2009). L’ansia sociale appare come esperienza perfettamente compatibile con il concetto di normalità, soprattutto se si tiene conto che, per la maggior parte delle persone, le manifestazioni di natura ansiosa sono di natura lieve e transitoria, talvolta persino stimolanti. Il problema nasce nel momento in cui ritrovarsi in un contesto sociale può diventare il presupposto di una grave e pervasiva paura, tale da essere palesemente incompatibile con il raggiungimento degli obiettivi personali e con lo svolgimento di una vita soddisfacente. I disturbi d’ansia sono tra le psicopatologie con maggior tasso d’incidenza; in particolare, ha stimolato la mia attenzione il Disturbo d’Ansia Sociale (SAD, Social Anxiety Disorder) oltre che per la sua frequenza di manifestazione, soprattutto per il precoce esordio e per l’invalidità che comporta quotidianamente in specie, nei rapporti sociali. Nella mia trattazione espongo preliminarmente e brevemente la natura del SAD, prendendo in esame: l’eziologia, l’esordio e lo sviluppo della malattia nei pazienti, i criteri principali necessari alla diagnosi e la comorbilità del disturbo. Nel secondo capitolo vengono da me descritte le tecniche di visualizzazione del disturbo mettendo in risalto il funzionamento e i principi dell’fMRI. L’obiettivo principale del mio lavoro di analisi si sostanzia nel terzo capitolo, nel quale emergono le evidenze degli studi fino ad ora fatti sul SAD in fMRI. Nelle conclusioni emege, dai vari studi presi in esame, come e quanto gli studi condotti in fMRI permettano la valutazione in vivo del cervello umano, portando ad una migliore comprensione del suo substrato anatomico, funzionale e metabolico seppur si palesino anche degli oggettivi limiti di vario genere

Disrupted brain gray matter connectome in social anxiety disorder: a novel individualized structural covariance network analysis

Phenotyping approaches grounded in structural network science can offer insights into the neurobiological substrates of psychiatric diseases, but this remains to be clarified at the individual level in social anxiety disorder (SAD). Using a recently developed approach combining probability density estimation and Kullback-Leibler divergence, we constructed single-subject structural covariance networks (SCNs) based on multivariate morphometry (cortical thickness, surface area, curvature, and volume) and quantified their global/nodal network properties using graph-theoretical analysis. We compared network metrics between SAD patients and healthy controls (HC) and analyzed the relationship to clinical characteristics. We also used support vector machine analysis to explore the ability of graph-theoretical metrics to discriminate SAD patients from HC. Globally, SAD patients showed higher global efficiency, shorter characteristic path length, and stronger small-worldness. Locally, SAD patients showed abnormal nodal centrality mainly involving left superior frontal gyrus, right superior parietal lobe, left amygdala, right paracentral gyrus, right lingual, and right pericalcarine cortex. Altered topological metrics were associated with the symptom severity and duration. Graph-based metrics allowed single-subject classification of SAD versus HC with total accuracy of 78.7%. This finding, that the topological organization of SCNs in SAD patients is altered toward more randomized configurations, adds to our understanding of network-level neuropathology in SAD

FROM INEQUALITY TO INFLAMMATION: EXPLORING INTERNAL AND EXTERNAL CONTRIBUTIONS TO AFFECTIVE PROCESSING

From influencing our social interactions to molding our physical and mental health, how our brain processes affective stimuli plays a crucial role in healthy human functioning. Utilizing results from 3 unique studies, the current dissertation aims to contribute empirical support for newer theoretical assertions that affective processing is significantly influenced by prior as well as internal physiological information to support allostasis. In Chapter 2, I explore how one’s contextual history may differentially shape how the brain processes affective information by examining the link between socioeconomic position and efficiency within the allostatic interoceptive network. In Chapter 3, I explore inflammation as one source of physiological information that can influence affective processing. In Chapter 4, I examine how shifting inflammation may alter affective processing via changes in motivated behavior. This dissertation closes with a synthesis of the studies discussed and a discussion of 3 future studies that aim to respond to the remaining outstanding questions.Doctor of Philosoph

The Role of Amygdala Subregions in the Neurobiology of Social Anxiety Disorder

Social anxiety is characterised by fear and/or avoidance of social situations in which an individual may be scrutinised by others. Social anxiety is thought to exist as a spectrum, with individuals on the high-end experiencing frequent and severe anxiety in the context of social situations. When severe social anxiety is accompanied by distress and functional impairment, a diagnosis of social anxiety disorder (SAD) can be made. SAD is a prevalent and debilitating disorder that can be unremitting and pervasive in the absence of intervention. Current psychotherapeutic and pharmacotherapeutic treatments for SAD demonstrate limited efficacy in remitting symptoms. Therefore, it is important to achieve a better understanding of the neurobiological mechanisms implicated in this disorder and identify potential neural treatment targets to develop more efficacious treatments. This thesis aimed to further investigate the neurobiological mechanisms implicated in SAD (vs. controls) and the associations between neural functioning and social anxiety as a dimensional symptom, with a focus on the amygdala and four of its subregions (the amygdalostriatal, basolateral, centromedial, and superficial subregions). This was due to previous findings in the neuroimaging literature in SAD having consistently implicated the amygdala, albeit with mixed findings of both increased and decreased functioning in those with SAD compared to controls. In the literature to date, however, most studies had examined the amygdala as a singular homogenous region due to methodological limitations in being able to examine the functionally and structurally distinct subnuclei that make up this region. By examining the amygdala subregions through the use of multiband functional magnetic resonance imaging (fMRI), this thesis additionally sought to determine whether the mixed findings in the literature to date may be a result of amygdala subregion-specific activity and connectivity patterns. This was achieved through three research studies. Firstly, Study 1 involved a comprehensive systematic review that summarised the literature on resting-state neuroimaging in SAD with a focus on fMRI studies and findings specific to the amygdala and its subregions (Chapter 3). This was followed by two empirical studies which investigated the role of the amygdala and its subregions during resting-state (Study 2) and emotion processing (Study 3) fMRI paradigms (Chapters 5 and 6, respectively). Findings from the systematic review (Study 1) highlighted the mixed findings in the resting-state neuroimaging literature in SAD to date, along with methodological limitations relating to neuroimaging acquisition and analysis. The empirical studies sought to address these limitations and demonstrated differing amygdala subregion activity and connectivity patterns at rest and during emotion processing. In the resting-state fMRI study (Study 2), there were no statistically significant differences in functional connectivity of the amygdala and its subregions in those with SAD compared to controls. However, social anxiety severity was found to be positively associated with connectivity between the superficial subregion and the supramarginal gyrus. The superficial subregion, along with the basolateral and centromedial subregions, were also implicated in the task-based emotion processing fMRI study (Study 3). In response to happy, angry, and fearful faces, those with SAD (vs. controls) had hyperactivation of the superficial subregion, hypoconnectivity between the superficial subregion and the precuneus, and hyperconnectivity between the basolateral subregion and broader brain regions (i.e., the pre/postcentral gyrus and the supramarginal gyrus). Additionally, social anxiety severity was positively associated with superficial and centromedial activation. Overall, the findings from this thesis provide novel information to the current understanding of the neurobiology of SAD by demonstrating amygdala subregion-specific alterations. This has important implications for research, theory, and clinical practice that are detailed in the thesis discussion (Chapter 7). Briefly, in terms of research, findings from the thesis provide support for the continuing investigation of SAD using both dimensional and categorical approaches. This was evident by the findings from the two empirical papers which demonstrated positive associations between subregional activity and connectivity patterns and social anxiety severity. With regards to theory, differences in neural patterns that were observed at rest (Study 2) and during emotion processing (Study 3) provide support for distinct neurobiological models to be constructed based on whether those with SAD are in the absence or presence of social stimuli. This is in contrast to the most recently proposed neurobiological model of SAD which was informed by a combination of resting-state and task-based fMRI data. Finally, with regards to clinical practice, the findings from this thesis provide preliminary evidence of the superficial, basolateral, and centromedial subregions of the amygdala as being potential treatment targets that can be used to inform the development of more efficacious treatments for SAD