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Recent resilience research has increasingly emphasized the importance of focusing on investigating the protective factors in mentally healthy populations, complementing the traditional focus on psychopathology. Social support has emerged as a crucial element within the complex interplay of individual and socio-environmental factors that shape resilience. However, the neural underpinnings of the relationship between social support and resilience, particularly in healthy subjects, remain largely unexplored. With advances in neuroimaging techniques, such as ultra-high field MRI at 7T and beyond, researchers can more effectively investigate the neural mechanisms underlying these factors. Thus, our study employed ultra-high field rs-fMRI to explore how social support moderates the relationship between psychological resilience and functional connectivity in a healthy cohort. We hypothesized that enhanced social support would amplify resilience-associated connectivity within neural circuits essential for emotional regulation, cognitive processing, and adaptive problem-solving, signifying a synergistic interaction where strong social networks bolster the neural underpinnings of resilience. (n = 30). Through seed-based functional connectivity analyses and interaction analysis, we aimed to uncover the neural correlates at the interplay of social support and resilience. Our findings indicate that perceived social support significantly (p

Abstract Given the huge symptom diversity and complexity of mental disorders, an individual approach is the most promising avenue for clinical transfer and the establishment of personalized psychiatry. However, due to technical limitations, knowledge about the neurobiological basis of mental illnesses has, to date, mainly been based on findings resulting from evaluations of average data from certain diagnostic groups. We postulate that this could change substantially through the use of the emerging ultra-high-field MRI (UHF-MRI) technology. The main advantages of UHF-MRI include high signal-to-noise ratio, resulting in higher spatial resolution and contrast and enabling individual examinations of single subjects. Thus, we used this technology to assess changes in the properties of resting-state networks over the course of therapy in a naturalistic study of two depressed patients. Significant changes in several network property measures were found in regions corresponding to prior knowledge from group-level studies. Moreover, relevant parameters were already significantly divergent in both patients at baseline. In summary, we demonstrate the feasibility of UHF-MRI for capturing individual neurobiological correlates of mental diseases. These could serve as a tool for therapy monitoring and pave the way for a truly individualized and predictive clinical approach in psychiatric care.

Abstract Currently, the metabotropic glutamate receptor 5 (mGluR5) is the subject of several lines of research in the context of neurology and is of high interest as a target for positron-emission tomography (PET). Here, we assessed the feasibility of using [11C]ABP688, a specific antagonist radiotracer for an allosteric site on the mGluR5, to evaluate changes in glutamatergic neurotransmission through a mismatch-negativity (MMN) task as a part of a simultaneous and synchronized multimodal PET/MR-EEG study. We analyzed the effect of MMN by comparing the changes in nondisplaceable binding potential (BPND) prior to (baseline) and during the task in 17 healthy subjects by applying a bolus/infusion protocol. Anatomical and functional regions were analyzed. A small change in BPND was observed in anatomical regions (posterior cingulate cortex and thalamus) and in a functional network (precuneus) after the start of the task. The effect size was quantified using Kendall’s W value and was 0.3. The motor cortex was used as a control region for the task and did not show any significant BPND changes. There was a significant ΔBPND between acquisition conditions. On average, the reductions in binding across the regions were - 8.6 ± 3.2% in anatomical and - 6.4 ± 0.5% in the functional network (p ≤ 0.001). Correlations between ΔBPND and EEG latency for both anatomical (p = 0.008) and functional (p = 0.022) regions were found. Exploratory analyses suggest that the MMN task played a role in the glutamatergic neurotransmission, and mGluR5 may be indirectly modulated by these changes.

Abstract Despite numerous studies investigating resilience and personality trials, a paucity of information regarding their neurobiological commonalities at the level of the large resting-state networks (rsNWs) remains. Here we address this topic using the advantages of ultra-high-field (UHF) 7T-MRI, characterized by higher signal-to-noise ratio and increased sensitivity. The association between resilience, personality traits and three fMRI measures (fractional amplitude of low-frequency fluctuations (fALFF), degree centrality (DC) and regional homogeneity (ReHo)) determined for three core rsNWs (default mode (DMN), salience (SN), and central executive network (CEN)) were examined in 32 healthy volunteers. The investigation revealed a significant role of SN in both resilience and personality traits and a tight association of the DMN with resilience. DC in CEN emerged as a significant moderator for the correlations of resilience with the personality traits of neuroticism and extraversion. Our results indicate that the common neurobiological basis of resilience and the Big Five personality traits may be reflected at the level of the core rsNWs.

Abstract The symbiosis of neuronal activities and glucose energy metabolism is reflected in the generation of functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) signals. However, their association with the balance between neuronal excitation and inhibition (E/I-B), which is closely related to the activities of glutamate and γ-aminobutyric acid (GABA) and the receptor availability (RA) of GABAA and mGluR5, remains unexplored. This research investigates these associations during the resting state (RS) condition using simultaneously recorded PET/MR/EEG (trimodal) data. The trimodal data were acquired from three studies using different radio-tracers such as, [11C]ABP688 (ABP) (N = 9), [11C]Flumazenil (FMZ) (N = 10) and 2-[18F]fluoro-2-deoxy-d-glucose (FDG) (N = 10) targeted to study the mGluR5, GABAA receptors and glucose metabolism respectively. Glucose metabolism and neuroreceptor binding availability (non-displaceable binding potential (BPND)) of GABAA and mGluR5 were found to be significantly higher and closely linked within core resting-state networks (RSNs). The neuronal generators of EEG microstates and the fMRI measures were most tightly associated with the BPND of GABAA relative to mGluR5 BPND and the glucose metabolism, emphasising a predominance of inhibitory processes within in the core RSNs at rest. Changes in the neuroreceptors leading to an altered coupling with glucose metabolism may render the RSNs vulnerable to psychiatric conditions. The paradigm employed here will likely help identify the precise neurobiological mechanisms behind these alterations in fMRI functional connectivity and EEG oscillations, potentially benefitting individualised healthcare treatment measures.

Introduction: The insular cortex is part of a network of highly connected cerebral “rich club” - regions and has been implicated in the pathophysiology of various psychiatric and neurological disorders, of which major depressive disease is one of the most prevalent. “Rich club” vulnerability can be a contributing factor in disease development. High-resolution structural subfield analysis of insular volume in combination with cortical thickness measurements and psychological testing might elucidate the way in which the insula is changed in depression. Material and methods: High-resolution structural images of the brain were acquired using a 7T-MRI scanner. The mean grey matter volume and cortical thickness within the insular subfields were analysed using voxel-based morphometry (VBM) and surface analysis techniques respectively. Insular subfields were defined according to the Brainnetome Atlas for VBM - and the Destrieux-Atlas for cortical thickness - analysis. Thirty-three patients with confirmed major depressive disease, as well as thirty-one healthy controls matched for age and gender, were measured. The severity of depression in MDD patients was measured via a BDI-II score and objective clinical assessment (AMDP). Intergroup statistical analysis was performed using ANCOVA. An intragroup multivariate regression analysis of patient psychological test results was calculated. Corrections for multiple comparisons was performed using FDR. Results: Significant differences between groups were observed in the left granular dorsal insula according to VBM-analysis. AMDP-scores positively correlated with cortical thickness in the right superior segment of the circular insular sulcus. Conclusions: The combination of differences in grey matter volume between healthy controls and patients with a positive correlation of cortical thickness with disease severity underscores the insula’s role in the pathogeneses of MDD. The connectivity hub insular cortex seems vulnerable to disruption in context of affective disease.

The default mode network (DMN), the salience network (SN), and the central executive network (CEN) are considered as the core resting-state brain networks (RSN) due to their involvement in a wide range of cognitive tasks. Despite the large body of knowledge related to their regional spontaneous activity (RSA) and functional connectivity (FC) of these networks, less is known about the dynamics of the task-associated modulation on these parameters and the task-induced interaction between these three networks. We have investigated the effects of the visual-oddball paradigm on three fMRI measures (amplitude of low-frequency fluctuations for RSA, regional homogeneity for local FC, and degree centrality for global FC) in these three core RSN. A rest-task-rest paradigm was used and the RSNs were identified using independent component analysis (ICA) on the resting-state data. The observed patterns of change differed noticeably between the networks and were tightly associated with the task-related brain activity and the distinct involvement of the networks in the performance of the single subtasks. Furthermore, the inter-network analysis showed an increased synchronization of CEN with the DMN and the SN immediately after the task, but not between the DMN and SN. Higher pre-task inter-network synchronization between the DMN and the CEN was associated with shorter reaction times and thus better performance. Our results provide some additional insights into the dynamics within and between the triple RSN. Further investigations are required in order to understand better their functional importance and interplay.

Trimodal simultaneous acquisition of positron emission tomography (PET), magnetic resonance imaging (MRI), and electroencephalography (EEG) has become feasible due to the development of hybrid PET-MR scanners. To capture the temporal dynamics of neuronal activation on a millisecond-by-millisecond basis, an EEG system is appended to the quantitative high resolution PET-MR imaging modality already established in our institute. One of the major difficulties associated with the development of simultaneous trimodal acquisition is that the components traditionally used in each modality can cause interferences in its counterpart. The mutual interferences of MRI components and PET components on PET and MR images, and the influence of EEG electrodes on functional MRI images have been studied and reported on. Building on this, this study aims to investigate the influence of the EEG cap on the quality and quantification of PET images acquired during simultaneous PET-MR measurements. A preliminary transmission scan study on the ECAT HR+ scanner, using an Iida phantom, showed visible attenuation effect due to the EEG cap. The BrainPET-MR emission images of the Iida phantom with [18F]Fluordeoxyglucose, as well as of human subjects with the EEG cap, did not show significant effects of the EEG cap, even though the applied attenuation correction did not take into account the attenuation of the EEG cap itself.