Despite the increasing exploration of complex emotions in neuroscience, the neural mechanisms that underlie awe remain almost unexplored. This study represents a pioneering investigation of the functional brain mechanisms that underlie laboratory-induced experiences of awe, in a sample of 34 healthy young adults, made possible with an experimental setup that integrates natural virtual reality (VR) scenarios (three awe-inducing, one awe-neutral), concurrent electroencephalography (EEG) recordings, and emotional questionnaires. Linear and nonlinear analyses, power spectral density, power spectral entropy and wavelet entropy, were applied to 2-s EEG epochs across four frequency bands. Channel-level EEG features were used for statistical comparisons between awe-inducing and awe-neutral VR scenarios (Friedman test, p < 0.05), and entered in general linear model analyses to find the EEG correlates of subjective awe intensity across all VR scenarios. Our results showed similar as well as distinct patterns among scenarios. Recurring metrics increases were those found in selective channels spanning from the frontal and temporal lobes (theta, alpha, beta, gamma bands) to the parietal (beta) and occipital (gamma) lobes, whereas scenario- and metric-specific changes were mainly found in the parietal and occipital lobes. Metrics associated with subjective awe intensity were found in the frontal (theta, alpha, beta, gamma) and right temporal (theta, alpha, gamma) lobes. In conclusion, our VR-EEG experimental and analysis setup offered new insights into frequency-specific neural activity associated with different VR-based instances of awe. These findings underscore the potential of VR as a valuable tool in emotional neuroscience, setting the ground for future applications for mental health interventions.

Major depressive disorder (MDD) is a heterogeneous, systemic disease often associated with cardiac autonomic dysfunction, yet neurophysiological mechanisms linking altered autonomic regulation to brain function remain largely unexplored to date. Here, we investigate functional brain correlates of cardiac autonomic modulation in MDD by integrating heart rate variability (HRV) with brain functional magnetic resonance imaging (fMRI). Forty participants (20 late-onset MDD patients, 20 healthy controls) undergo simultaneous electrocardiography and resting-state fMRI. HRV-derived autonomic regressors representing low-frequency and parasympathetic activity are estimated using time-varying bivariate autoregressive modeling and used to drive voxel-wise fMRI analysis via a general linear model. Group-level analyses assess diagnosis effects, controlling for age and sex. Post-hoc correlations are computed between HRV-related fMRI responses and clinical severity. Distinct patterns of brain-autonomic coupling emerge in MDD. Altered fMRI responses to autonomic dynamics are observed within central autonomic network regions, including the insula, cingulate gyrus, and hippocampus. The right insula shows consistent hypoactivation across multiple autonomic contrasts, with its response negatively correlating with depression severity. These findings provide preliminary evidence of altered brain-autonomic integration in MDD, particularly within interoceptive, self-referential, and affective networks. HRV-fMRI integration emerges as a promising multimodal framework for identifying multi-organ markers of cardiac autonomic dysfunction in psychiatric disorders.

Introduction Bipolar disorder (BD) is a severe psychiatric condition characterized by recurrent episodes of mania and depression. A critical aspect of BD is phase switching, the rapid transition between affective states, which remains poorly understood at the neurobiological level. Recent neuroimaging advancements, particularly in diffusion tensor imaging (DTI) and tractography, have provided insights into the structural white matter (WM) alterations associated with mood transitions.Methods We conducted an integrated diffusion neuroimaging study to investigate WM modifications in BD patients experiencing manic and depressive phases, as well as those undergoing phase switching. Thirty-two BD type I patients (14 manic, 18 depressive) and 20 healthy controls underwent Magnetic Resonance Imaging scanning, including DTI-based analyses. WM integrity was assessed using Tract-Based Spatial Statistics (TBSS) and tractography to explore fractional anisotropy (FA) differences.Results Compared to healthy controls and depressive BD patients, manic BD patients exhibited significant FA reductions in the corpus callosum, anterior limb of the internal capsule, and thalamic projections. Tractography revealed local FA alterations in fronto-limbic and occipito-parietal pathways, suggesting disrupted structural connectivity. Phase switching was associated with reduced FA in the right superior longitudinal fasciculus III, indicating its potential role as a neurobiomarker of mood instability.Conclusion Our findings highlight widespread WM abnormalities in BD, particularly in manic phases, and suggest a neurobiological signature for phase switching. Understanding these alterations can improve early detection, targeted interventions, and personalized treatment approaches for BD.

Bipolar disorder (BD) shows different clinical manifestations according to illness onset (early vs late onset). Its etiology is multifaceted and no reliable biomarkers are available. However, clinical manifestations of BD may stem from disruption in white matter (WM) integrity within brain networks or selective epigenetic alterations, including plasma neural derived extracellular vesicles (NDEVs). In this context, this study further explores the existence of similar epigenetic expression patterns in NDVEs, such as micro-ribonucleic acid (miRNA), and seeks to correlate them with biological markers obtained through Diffusion Tensor Imaging and with clinical data. 23 early onset BD (35% males) (EOBD), 15 late-onset BD (47% males) (LOBD), and 18 healthy controls (44% males) (HC) were recruited. Fractional anisotropy (FA) was investigated through Tract-Based Spatial Statistics. NDEVs were isolated from plasma, and their miRNA content was profiled using real-time polymerase chain reaction. Compared to HC, miR-20a and miR-299-5p were upregulated in EOBD, while miR-323-3p expression was reduced in both EOBD and LOBD patients relative to HC. Moreover, compared to HC, EOBD and LOBD showed decreased FA in the left posterior thalamic radiation and the left anterior corona radiata, respectively. Finally, after Bonferroni correction, EOBD patients showed a negative correlation between miR-323-3p and FA in the left tapetum. Our results shed light on a possible interaction between miRNA expression and WM modifications in BD. However, further research is needed to better characterize the role of miRNA by FA interaction in BD pathophysiology.

Abstract Objective Fetal brain magnetic resonance imaging (MRI) provides insights into the architecture of the human brain. Recently, an increasing interest has been posed on transient brain structures, such as the ganglionic eminence (GE), to better understand potential derailments or anomalies in neurodevelopment. In this work, we define a spatio-temporal atlas of the GE from 19 to 36 gestational weeks (GW) in a 0.5-mm isotropic resolution. Materials and methods We extended the T2-weighted developing Human Connectome Project atlas with 19 and 20 GW and generated GE label maps spanning 19–36 GW. The GE label maps were generated via an averaging ensemble strategy of the segmentations performed by three expert neuroradiologists. Results The segmentations conducted by the experts achieved 0.91 ± 0.06 Dice similarity coefficient throughout the whole range of GW, indicating a strong agreement in this task. The GE reached its maximum volume expansion at around 21 GW, followed by a pronounced reduction throughout pregnancy (R 2 = 0.98, ranged 40‒500 mm3), highlighting an inverse relationship to the whole brain volume and cortical gray matter. This is accompanied by an increased number of small and fragmented components, correlating with known dynamics of GE migration toward target structures. Conclusion The proposed spatio-temporal GE MRI atlas supports the monitoring during pregnancy of this fascinating brain structure. It may aid in better understanding prodromic signs of potential future clinical conditions attributable to GE alterations. Moreover, it could be used as a repository of knowledge to develop innovative atlas-based deep learning models for biometric, volumetric, and shape analysis. Relevance statement The spatio-temporal fetal MRI atlas of the GE allows researchers to study its evolution and potential future clinical conditions attributable to GE alterations in pregnancy. The GE reached its maximum volume expansion around 21 GW, followed by a pronounced reduction throughout the pregnancy. Key Points The development of GE is a resource for monitoring pregnancy. We propose a spatio-temporal GE MRI atlas from 19 to 36 weeks of gestation. The GE reached its maximum expansion at around 21 weeks of gestation, followed by a progressive decline throughout pregnancy. Graphical Abstract

Diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) provide complementary insights into brain connectivity, with DTI capturing structural connectivity (SC) and fMRI measuring functional connectivity (FC). Integrating these modalities offers the potential to deepen our understanding on the brain structural-functional coupling. In this study, a novel integrated DTI-fMRI approach was designed to explore the possibility to predict brain functional connections based on the underlying structural pathways.An asymmetric DTI-driven fMRI model was developed to investigate the role of brain structure, via a linear combination of DTI-derived features, in shaping FC within a normative framework. The model was trained on healthy young adults (n=12, 27.2 ± 0.8 years, 6M/6F) using a 4-fold cross-validation framework. The final model fitted on the training set was preliminarily tested on an independent set of healthy volunteers across a broader age range (n=14, 55.4 ± 18.2 years, 8M/6F). In the test set, any age-related variations in the model predictive performances were assessed.Cross-validation results showed that SC strength, path length, and physical distance between network nodes exhibited significant effects on FC prediction. When applied to the independent test set, the model’s whole-brain similarity between actual and estimated FC was not associated with age or sex, suggesting stable structure-function coupling during adulthood and between males and females. In contrast, age-related differences were found at the link-level reconstruction error between actual and estimated FC, mainly in the connections of frontal areas.These findings underscore the potential for DTI-fMRI integration for investigating the complex relationships between brain structural architecture and dynamic functions both in physiology and in disease.

Diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) are powerful neuroimaging techniques providing complementary information on brain structural (SC) and functional (FC) connectivity, respectively. Integrating them gives a deeper understanding of brain structural-functional interplay, which is particularly relevant in the search for brain markers of psychiatric illnesses like major depressive disorder (MDD). In this study, a novel DTI-driven fMRI approach was developed and preliminarily tested to identify any alterations in structural-functional network coupling in MDD. FC was estimated from DTI-derived features within a normative healthy control (HC) framework, using linear and quadratic models. SC strength, shortest path length, and physical distance showed significant influences on FC prediction in the linear model, whereas path length was non-significant in the quadratic version. The models were applied to a pilot test set of MDD and HC, comparing the predictive performance of the models between the two groups. The results showed reduced whole-brain similarity between estimated and measured FC in MDD vs. HC. These findings were confirmed on a smaller scale, showing significant differences in the model reconstruction error of ROI-to-ROI connectivity in key resting-state networks. These results suggest that altered brain structural-functional interactions may underlie MDD, providing new insights into potential biomarkers.

INTRODUCTION:Bipolar disorder (BD) patients present an increased risk of suicide attempts. Most current machine learning (ML) studies predicting suicide attempts are cross-sectional, do not employ time-dependent variables, and do not assess more than one modality. Therefore, we aimed to predict 12-month suicide attempts in a sample of BD patients, using clinical and brain imaging data. METHODS:A sample of 163 BD patients were recruited and followed up for 12 months. Gray matter volumes and cortical thickness were extracted from the T1-weighted images. Based on previous literature, we extracted 56 clinical and demographic features from digital health records. Support Vector Machine was used to differentiate BD subjects who attempted suicide. First, we explored single modality prediction (clinical features, GM, and thickness). Second, we implemented a multimodal stacking-based data fusion framework. RESULTS:During the 12 months, 6.13% of patients attempted suicide. The unimodal classifier based on clinical data reached an area under the curve (AUC) of 0.83 and balanced accuracy (BAC) of 72.7%. The model based on GM reached an AUC of 0.86 and BAC of 76.4%. The multimodal classifier (clinical + GM) reached an AUC of 0.88 and BAC of 83.4%, significantly increasing the sensitivity. The most important features were related to suicide attempts history, medications, comorbidities, and depressive polarity. In the GM model, the most relevant features mapped in the frontal, temporal, and cerebellar regions. CONCLUSIONS:By combining models, we increased the detection of suicide attempts, reaching a sensitivity of 80%. Combining more than one modality proved a valid method to overcome limitations from single-modality models and increasing overall accuracy.

Behavioral variant of Frontotemporal Dementia (bvFTD) and Bipolar Disorder (BD) share overlapping symptoms, complicating diagnosis. BvFTD, especially linked to C9orf72 expansions, often mimics BD, highlighting the need for reliable biomarkers. This study aimed to differentiate bvFTD from BD using miRNA profiles in neural-enriched extracellular vesicles (NEVs). A cohort of 100 subjects was analyzed: 40 bvFTD (20 sporadic, 20 C9orf72 carriers), 40 BD, and 20 healthy controls. NEVs were isolated from plasma and profiled using real-time PCR. Among 754 miRNAs, 11 were significantly deregulated in bvFTD and BD. MiR-152-5p was downregulated in sporadic bvFTD, while let-7b, let-7e, miR-18b, and miR-142-5p were altered in C9orf72 carriers. BD patients showed distinct patterns in miR-331-5p, miR-335, and miR-345 compared to bvFTD. Bioinformatics analyses revealed that let-7e, let-7b, miR-18b, and miR-142-5p share common long non-coding RNA (lncRNA) targets, including XIST, NEAT1, and OIP5-AS1, suggesting their involvement in molecular networks relevant to C9orf72-related bvFTD. These miRNA signatures can differentiate bvFTD from BD, especially in C9orf72-related cases, and offer insights into disease pathways. Further research is needed to validate these findings and explore their clinical application.

Depression is a leading cause of disability that exerts an impact on neurocognitive functions. Individuals with major depressive disorder (MDD) have shown alterations of processes underlying response inhibition, which is the cognitive process that permits the suppression of habitual or natural behavioural responses to stimuli to select a more appropriate response that is coherent with the goal; these alterations have been correlated with cognitive deficits, especially in older adults. Electrophysiological (EEG) and functional magnetic resonance imaging (fMRI) studies have investigated the neuronal and hemodynamic process underlying inhibition through tasks measuring the ability to suppress a dominant response when non-target stimuli are shown and reported differences between healthy controls (HCs) and MDD subjects. However, these were unimodal studies that provided an incomplete picture of the phenomenon, due to the single technique sensitivity and limited by the characteristics of each technique itself. In this study, we performed an EEG-driven fMRI analysis to explore the different hemodynamic correlates of specific event-related potentials (ERPs) of inhibitory control in late-onset MDD during a visuomotor Go/No-Go task. The dataset was composed of 18 older adult HCs and 18 late-onset MDD patients. Behavioral analysis showed higher response time to target stimuli in inhibitory blocks and lower percentage of correct answers for target stimuli in MDD compared to HCs. ERP analysis revealed the inhibitory effect for both N2 and P3 in both groups. Moreover, EEG-driven fMRI analysis showed alterations in the MDD group in the superior temporal gyrus and cerebellar areas for N2 correlates, whereas in the supramarginal, left rolandic, and Heschl's areas for P3 correlates. The study showed the potentiality of the EEG-fMRI integration for investigating complex cognitive processes. Specifically, the EEG-driven fMRI analyses showed different correlates for separate cognitive processing steps, N2 and P3, highlighting differences between MDD and HC.

INTRODUCTION:Awe is a complex emotion unveiling a positive and mixed nature, which resembles the Romantic feeling of the Sublime. It has increasingly become the object of scientific investigation in the last twenty years. However, its underlying brain mechanisms are still unclear. To fully capture its nature in the lab, researchers have increasingly relied on virtual reality (VR) as an emotion-elicitation method, which can resemble even complex phenomena in a limited space. In this work, a multidisciplinary team proposed a novel experimental protocol integrating VR, electroencephalography (EEG), and transcranial magnetic stimulation (TMS) to investigate the brain mechanisms of this emotion. METHODS:A group of bioengineers, psychologists, psychiatrists, and philosophers designed the SUBRAIN study, a single-center, one-arm, non-randomized interventional study to explore the neural processes underlying awe experiences. The study is ongoing and is expected to enroll fifty adults between 20 and 40 years of age. Currently, more than 40 individuals have been enrolled. The experimental protocol includes different steps: (i) screening, (ii) enrollment, (iii) pre-experimental assessment, (iv) VR experimental assessment, and (v) post-experimental debriefing. The brain's electrical activity is recorded using the EEG while participants navigated three immersive awe-inducing VR environments and a neutral one. At the same time, the cortical excitability and connectivity is investigated by performing a TMS-EEG session right after each VR navigation. Along with cerebral signals, self-reported questionnaires were used to assess the VR-induced changes in the emotional state of the subjects. This data is then analyzed to delve into the cerebral mechanisms of awe. DISCUSSION:This study protocol is the first one that tries to fully understand the neural bases of awe by eliciting and studying this phenomenon in VR. The pairing of awe-inducing VR experiences and questionnaires investigating participants' affect and emotions, with non-invasive neural techniques, can provide a novel and extensive knowledge on this complex phenomenon. The protocol can inform on the combination of different instruments showing a reproducible and reliable setting for the investigation of induced complex emotions.

Introduction. Although the interaction between the brain and the heart, through the autonomic nervous system, is an established phenomenon, multimodal studies that have explored their bidirectional interplay are still limited.Aim. In this context, the objective of the present study was to investigate the coupling between sympathetic and vagal dynamics and brain functional connectivity during resting state, thanks to simultaneously acquired electrocardiogram and functional magnetic resonance imaging (fMRI) data.Methods. Twenty healthy controls (67.42 ± 10.81 years, 60% females) were included in the study. Unimodal fMRI and heart rate variability (HRV) results were integrated in a joint analysis framework. Trivariate dynamic functional connectivity (dFC) features were correlated with time-varying HRV parameters to identify brain regions involved in autonomic modulation. Results. In a data-driven approach, the present analysis allowed to extract triplets of brain regions whose dFC was coupled with both sympathetic and vagal activity dynamics. The identified brain regions often belonged to the central autonomic network, which is a network of brain structures that are involved in the regulation of autonomic processes at high central level. Conclusion. The present multimodal HRV and fMRI dFC analysis provided new findings on the physiological brain-heart interactions, paving the way to explore the same mechanisms in disorders of the brain-heart axis.

Amyloid deposition within stenotic aortic valves (AVs) also appears frequent in the absence of cardiac amyloidosis, but its clinical and pathophysiological relevance has not been investigated. We will elucidate the rate of isolated AV amyloid deposition and its potential clinical and pathophysiological significance in aortic stenosis (AS). In 130 patients without systemic and/or cardiac amyloidosis, we collected the explanted AVs during cardiac surgery: 57 patients with calcific AS and 73 patients with AV insufficiency (41 with AV sclerosis and 32 without, who were used as controls). Amyloid deposition was found in 21 AS valves (37%), 4 sclerotic AVs (10%), and none of the controls. Patients with and without isolated AV amyloid deposition had similar clinical and echocardiographic characteristics and survival rates. Isolated AV amyloid deposition was associated with higher degrees of AV fibrosis (p = 0.0082) and calcification (p < 0.0001). Immunohistochemistry analysis suggested serum amyloid A1 (SAA1), in addition to transthyretin (TTR), as the protein possibly involved in AV amyloid deposition. Circulating SAA1 levels were within the normal range in all groups, and no difference was observed in AS patients with and without AV amyloid deposition. In vitro, AV interstitial cells (VICs) were stimulated with interleukin (IL)-1β which induced increased SAA1-mRNA both in the control VICs (+6.4 ± 0.5, p = 0.02) and the AS VICs (+7.6 ± 0.5, p = 0.008). In conclusion, isolated AV amyloid deposition is frequent in the context of AS, but it does not appear to have potential clinical relevance. Conversely, amyloid deposition within AV leaflets, probably promoted by local inflammation, could play a role in AS pathophysiology.

Introduction Awe is a complex emotion unveiling a positive and mixed nature, which resembles the Romantic feeling of the Sublime. It has increasingly become the object of scientific investigation in the last twenty years. However, its underlying brain mechanisms are still unclear. To fully capture its nature in the lab, researchers have increasingly relied on virtual reality (VR) as an emotion-elicitation method, which can resemble even complex phenomena in a limited space. In this work, a multidisciplinary team proposed a novel experimental protocol integrating VR, electroencephalography (EEG), and transcranial magnetic stimulation (TMS) to investigate the brain mechanisms of this emotion.Methods A group of bioengineers, psychologists, psychiatrists, and philosophers designed the SUBRAIN study, a single-center, one-harm, non-randomized interventional study to explore the neural processes underlying awe experiences. The study will be performed on fifty adults. The experimental protocol includes different steps: (i) screening, (ii) enrollment, (iii) pre-experimental assessment, (iv) VR experimental assessment, and (v) post-experimental debriefing. The brain’s electrical activity is recorded using the EEG while participants navigated three immersive awe-inducing VR environments (VREs) and a neutral one. At the same time, the cortical excitability and connectivity is investigated by performing a TMS-EEG session right after each VR navigation. Along with cerebral signals, self-reported questionnaires were used to assess the VR-induced changes in the emotional state of the subjects. This data is then analyzed to delve into the cerebral mechanisms of awe.Discussion This study protocol is the first one that tries to fully understand the neural bases of awe by eliciting and studying this phenomenon in VR. The pairing of awe-inducing VR experiences and questionnaires investigating participants’ affect and emotions, with non-invasive neural techniques, can provide a novel and extensive knowledge on this complex phenomenon. The protocol can inform on the combination of different instruments showing a reproducible and reliable setting for the investigation of induced complex emotions.### Competing Interest StatementThe authors have declared no competing interest.### Clinical Protocols[osf.io/vn9ub][1]### Funding StatementYes### Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.Not ApplicableThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:The study protocol conforms to the Helsinki Declaration and has been approved by the competent Ethical Committee of the Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan (OSMAMI-26/01/2021-0002688-U).I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.Not ApplicableI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).Not ApplicableI have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.Not Applicable [1]: http://osf.io/vn9ub

Alcohol and tobacco consumption is socially accepted and widespread among adolescents. Adolescence is a very sensitive period for neurodevelopment, characterized by significant changes in cognitive and emotional functioning, and by the morphological maturation of brain tissues, especially of the white matter (WM). Research using advanced diffusion neuroimaging has revealed that alcohol and tobacco use during adolescence and young adulthood can have detrimental effects on neurodevelopmental trajectories of WM, by delaying the growth of this brain tissue and disrupting its integrity. Specifically, alcohol consumption has been associated with reduction of fractional anisotropy (FA) mainly in corpus callosum and fronto-temporal networks, unveiling compromised connectivity and reduced cognitive functioning. Similarly, nicotine exposure from tobacco use has been linked to decreased FA in critical brain regions, potentially impairing cognitive processes like attention, inhibition and emotional codification. Furthermore, these effects appear to be dose-dependent and gender-dependent, with heavier and more frequent substance use leading to more pronounced alterations in WM integrity according to biological gender. Additionally, the adolescent brain is particularly vulnerable to the neurotoxic effects of alcohol and tobacco, as it is still undergoing significant neurodevelopment, including myelination of WM tracts. Understanding the precise mechanisms underlying these neurodevelopmental changes and their long-term consequences on cognitive and behavioral outcomes is an ongoing area of research. Given the potential long-lasting impacts of alcohol and tobacco use on WM during adolescence and young adulthood, preventive efforts and early interventions are essential to mitigate the potential harm and promote healthy brain development in this vulnerable population.

This scientific research represents a novel investigation into the neural underpinnings of the complex awe emotion, made possible with an innovative experimental setup that integrates nature-based Virtual Reality scenarios (nVRs) with the concurrent recording of electroencephalography (EEG) signals. The noninvasive EEG technique enables to capture brain electrical activity in real time and therefore holds great promise in elucidating the neural dynamics associated with complex emotional experiences. A group of 15 healthy volunteers participated in the study; EEG recordings were performed at baseline (closed-eyes resting-state without VR), and during the participants’ navigation within four immersive nVRs, three designed to elicit the profound feeling of awe and one of reference. To unveil the neural underpinnings associated with awe experiences, linear and nonlinear frequency analyses, Power Spectral Density (PSD) and Power Spectral Entropy (PSE), were computed for each 2-second EEG signal epoch within four main EEG frequency bands. The Friedman test was applied to each channel to compare (i) awe-inducing vs. reference nVRs, highlighting the effect of awe, and (ii) reference nVRs vs. baseline condition, highlighting the effect of VR. The Friedman test results (p<0.01) showed that both PSD and PSE captured similar patterns within the comparison reference nVRs vs. baseline. In contrast, greater differences between the two methods were found in the awe-inducing vs. reference nVRs comparison, showing PSD and PSE changes that were specific to each awe-inducing nVRs. The VR-EEG experimental setup, combined with linear and nonlinear EEG analysis methodologies, enabled us to comprehensively investigate the frequency-specific brain activity underlying diverse awe-inducing experimental conditions. Our findings give valuable insights into the neural underpinnings of awe experiences, confirming the potential of immersive VR in emotional neuroscience.

Fetal Magnetic Resonance Imaging (MRI) is an important noninvasive diagnostic tool to characterize the central nervous system (CNS) development, significantly contributing to pregnancy management. In clinical practice, fetal MRI of the brain includes the acquisition of fast anatomical sequences over different planes on which several biometric measurements are manually extracted. Recently, modern toolkits use the acquired two-dimensional (2D) images to reconstruct a Super-Resolution (SR) isotropic volume of the brain, enabling three-dimensional (3D) analysis of the fetal CNS.We analyzed 17 fetal MR exams performed in the second trimester, including orthogonal T2-weighted (T2w) Turbo Spin Echo (TSE) and balanced Fast Field Echo (b-FFE) sequences. For each subject and type of sequence, three distinct high-resolution volumes were reconstructed via NiftyMIC, MIALSRTK, and SVRTK toolkits. Fifteen biometric measurements were assessed both on the acquired 2D images and SR reconstructed volumes, and compared using Passing-Bablok regression, Bland-Altman plot analysis, and statistical tests.Results indicate that NiftyMIC and MIALSRTK provide reliable SR reconstructed volumes, suitable for biometric assessments. NiftyMIC also improves the operator intraclass correlation coefficient on the quantitative biometric measures with respect to the acquired 2D images. In addition, TSE sequences lead to more robust fetal brain reconstructions against intensity artifacts compared to b-FFE sequences, despite the latter exhibiting more defined anatomical details.Our findings strengthen the adoption of automatic toolkits for fetal brain reconstructions to perform biometry evaluations of fetal brain development over common clinical MR at an early pregnancy stage.