Interbrain synchrony (IBS) is thought to reflect the flow of information between individuals and interpersonal mechanisms like empathy and bonding. Previous research suggests that IBS varies according to different factors, including interpersonal bond type, individual characteristics, emotional valence and physical presence/absence. This study investigated how IBS in mother-child dyads varies during imagined emotional situations, focusing on valence and imagined presence/absence of the mother. We used functional near-infrared spectroscopy (fNIRS) hyperscanning to measure IBS over the right prefrontal cortex, dorsolateral prefrontal cortex and temporoparietal junction in 38 mother-child dyads (child age: 10–14 years). Results showed that IBS differed across valence only when participants imagined the mother being present, with higher IBS in negative situations than in positive ones. Furthermore, in scenarios imagined with the mother present, IBS was associated with the mother’s personal distress —negative correlation in positive scenarios, and positive correlation in negative scenarios—and with children’s secure base support scores—negative association in the frontopolar cortex. These findings suggest that mothers and children perceive being together differently, depending on emotional valence, social context and individual differences. Overall, our results suggest that IBS reflects dyadic emotional processing and highlight associations with individual traits in dyadic neural synchrony.

IntroductionSchizophrenia (SCZ) and autism spectrum disorder (ASD) are neurodevelopmental disorders with similar impairments in several neuropsychological domains, namely in executive function, hampering their differential diagnosis. We asked if brain activation and connectivity patterns within central nodes of the frontoparietal network (FPN), critical for executive control, are distinctively altered in these clinical populations during a working-memory task (n-back).MethodsForty-five male adults (15 SCZ,15 ASD,15 controls) matched for age, education level, and handedness, underwent 3T brain fMRI during a n-back executive task. We functionally defined three core hubs of the FPN (primary outcome measure: dorsolateral prefrontal cortex -DLPFC and intraparietal sulcus -IPS), and the insula (secondary outcomes), a relevant connecting hub of the salience network (SN).ResultsNo significant differences were observed between SCZ and ASD. In contrast, we found significant connectivity differences which were higher for the SCZ group, particularly between the DLPFC-IPS and insula-IPS. Differences between SCZ and ASD dominated in the left hemisphere.DiscussionThe distinct cortical activation and connectivity patterns in SCZ (increased connectivity within FPN and FPN-SN), as compared to ASD and controls, are consistent with a fundamental change in executive function in psychosis.

Abstract Significance High inter-subject variability and limited reproducibility in functional near-infrared spectroscopy (fNIRS) research may partly reflect global systemic physiology and signal quality differences, possibly distorting task-evoked hemodynamic responses. Aim We investigate how signal quality relates to inter-subject variability in motor-task fNIRS responses and introduce a large, open, multi-task, near whole-head fNIRS dataset with extensive peripheral physiology and short-channel recordings. Approach Fifty-seven participants completed resting-state, motor action, motor imagery, emotion recognition, visual, and auditory tasks during fNIRS recording. Peripheral measures included pulse oximetry, heart rate, blood oxygen saturation, respiration, room temperature, galvanic skin response, electrocardiogram, and electromyography. Signal quality was assessed using the scalp coupling index (SCI), coefficient of variation (CV), signal-to-noise ratio (SNR) and a spectral measure here coined the coupling SNR (cSNR). Results Quality metrics were weakly to moderately correlated, except SNR and CV, which showed the expected inverse relationship. All quality metrics were significantly related to channel length and associated with task-related activation estimates. Group-level analyses validated activation in expected task-related regions. Conclusions The assessed metrics capture complementary features of fNIRS signal quality and may help explain individual activation differences. The dataset provides a comprehensive, open resource enabling future evaluation of physiological correction methods and confound mitigation.

Abstract The mechanistic role of the third visual pathway in autism spectrum disorder (ASD) remains unknown. We previously developed a neurofeedback therapy for autism targeting the posterior superior temporal sulcus (pSTS), a region in this network that underlies the perception and imagery of emotional facial expressions, resulting in improvements in adaptive behavior and recognition of fear in facial expressions. Here, we investigated the impact of this 5-session therapy on the functional connectivity of that core region of the third visual pathway. We found evidence for a profound reorganization of this network with treatment-induced decreases in connectivity between low-level visual areas, the pSTS, and the posterior occipital face area (OFA), and increased connectivity with higher-level visual regions (fusiform face area - FFA), right middle STS (mSTS), and parietal cortex. These changes, suggesting the restoration of connectivity in regions known to be underconnected in ASD, such as mSTS and pSTS, and in a set of regions belonging to the temporoparietal junction and the ventral attention network, which are known to be involved in broader aspects of social cognition, were positively associated with clinical improvements. The demonstration of treatment response associated with network reconfiguration paves the way for multicentric trials to probe this observed reorganization as a treatment target.

Abstract Brain decoding from fMRI data using artificial neural networks traditionally operates at the regional level, identifying which brain areas activate during tasks but ignoring how these regions interact through structural networks. While Graph Neural Networks can capture connectivity, they require prohibitively large datasets for typical neuroscience studies. We introduce a message-passing mechanism that allows a shallow neural network to incorporate structural connectivity, enabling network-level interpretation from limited data. Using motor task data from 30 Human Connectome Project subjects, we evaluate seven structural connectivity matrices derived from deterministic and probabilistic tractography. Our approach achieves 83.0% classification accuracy while revealing functional network organization. We demonstrate that sparser, anatomy-driven connectivity matrices outperform dense alternatives, and that normalizing for network size improves model performance. Critically, our method is capable of exposing structural pathways contributing towards classification, distinguishing between complete network recruitment and selective regional activation. This approach bridges the gap between high-performance brain decoding and biological fidelity of the model, enhancing neuroscientific understanding, with implications for analyzing network dysfunctions in neurological disorders such as Alzheimer’s disease (AD), attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder, mild cognitive impairment (MCI), and schizophrenia.

IntroductionMusic is a universal language that transcends cultures and is deeply rooted in human evolutionary history. Its creation and appreciation recruit the limbic and reward systems, leading to the evocation of emotions ranging from happiness and sadness to tenderness and grief. Here, we investigate the potential of music as an interventional tool in a novel neurofeedback connectivity-based experiment. MethodsThis study proposes a musical interface for real-time functional magnetic resonance imaging neurofeedback that is adaptable to diverse experimental paradigms, namely the ones aiming at improving mood and other affective dimensions. Using a previously developed motor imagery connectivity-based approach, we evaluate its feasibility and efficacy by comparing the modulation of bilateral premotor cortex activity during functional runs with real versus sham (random) feedback in 22 healthy adults. We also assess its performance against a visual feedback interface. The experiment involves a 50-minute MRI session, including anatomical scans, a premotor cortex functional localizer run, and four neurofeedback runs (two with active feedback and two with sham feedback). Pre- and post-session questionnaires assess the neurobehavioral impact on mood, musical background (as a potential predictor of neurofeedback success), and subjective feedback experiences. During neurofeedback, participants perform motor imagery of finger-tapping, with feedback delivered as a dynamic, pre-validated chord progression that evolves or regresses based on the functional connectivity between left and right premotor cortex.ResultsWe found that our implementation of music-based feedback was successful, with participants managing to modulate their own connectivity using the proposed interface. The modulation performance was similar for active and sham runs, possibly due to the power of music to boost neuromodulation, but the network recruitment was stronger for active neurofeedback, including in the insula, putamen, and target regions of interest. Behaviorally, we found a decrease in tension and an improvement in the overall mood of the participants after the session. DiscussionWhen comparing our results to previous neurofeedback data with a visual interface, we found stronger brain activations, in particular in neurofeedback-relevant regions such as the insula and the putamen. This work shows that it is possible to directly modulate interhemispheric connectivity using a real-time functional magnetic resonance imaging musical interface with potential effects on mood and recruitment of saliency and learning networks.

Music is a universal language that transcends cultures and is deeply rooted in human evolutionary history. Its creation and appreciation recruit the brain’s limbic and reward systems, leading to the evocation of emotions ranging from happiness and sadness to tenderness and grief. Here, we explore the potential of music as an interventional tool in a novel neurofeedback experiment. This study introduces and validates a musical interface for real-time fMRI neurofeedback that is adaptable to various experimental paradigms. Using a previously developed motor imagery connectivity-based framework, we evaluate its feasibility and efficacy by comparing the modulation of bilateral premotor cortex (PMC) activity during functional runs with real versus sham (random) feedback in 22 healthy adults. We also assess its performance against a visual feedback interface. The experiment involves a 50-minute MRI session, including anatomical scans, a PMC functional localizer run, and four neurofeedback runs (two with active feedback and two with sham feedback). Pre- and post-session questionnaires assess mood (looking at the behavioral impact of the NF session), musical background (in search of predictors of NF success), and subjective feedback experiences. During neurofeedback, participants perform motor imagery of finger-tapping, with feedback delivered as a dynamic, pre-validated chord progression that evolves or regresses based on the correlation between left and right PMC activity. We found that our implementation of music-based feedback was successful, with participants managing to modulate their own connectivity using the proposed interface. The modulation performance was similar for active and sham NF runs, possible due to the power of music to boost neuromodulation, but the network recruitment was stronger for active NF, including in the insula, putamen, and target ROIs. Behaviorally, we found a decrease in tension and an improvement in the overall mood of the participants after the session. When comparing our results to previous NF data with a visual interface, we found stronger brain activations, in particular in NF-relevant regions such as the insula and the putamen. This work highlights the potential of musical feedback as a more intuitive and engaging interface in neurofeedback protocols, paving the way for enhanced participant experience and training outcomes. ### Competing Interest Statement The authors have declared no competing interest.

Music conveys both basic emotions, like joy and sadness, and complex ones, such as tenderness and nostalgia. Its effects on emotion regulation and reward have attracted much research attention, as the neural correlates of music-evoked emotions may inform neurorehabilitation interventions. Here, we used fMRI to decode and examine the neural correlates of perceived valence and arousal in music excerpts. Twenty participants were scanned while listening to 96 music excerpts, classified beforehand into four categories varying in valence and arousal. Music modulated activity in cortical regions, most noticeably in music-specific subregions of the auditory cortex, thalamus, and regions of the reward network such as the amygdala. Using multivoxel pattern analysis, we created a computational model to decode the perceived valence and arousal of the music excerpts with above-chance accuracy. We further explored associations between musical features and brain activity in valence-, arousal-, reward-, and auditory-related networks. The results emphasize the involvement of distinct musical features, notably expressive features such as vibrato and tonal and spectral dissonance in valence, arousal, and reward brain networks. Using ecologically valid music stimuli, we contribute to delineating the neural correlates of music-evoked emotions with potential implications in the development of novel music-based neurorehabilitation strategies.

Non-invasive electrocutaneous stimulation, which applies an electrical current flowing through the skin’s surface to elicit a tactile percept, can be used in combination with functional magnetic resonance imaging (fMRI) to obtain somatotopic maps that illustrate the spatial patterns and functional organization of the primary somatosensory cortex (S1). However, accessibility to this technique, combined with fMRI, is limited, especially for applications requiring multiple stimulation channels. This study presents the development and assessment of a novel multichannel electrocutaneous stimulation device designed for non-invasive somatosensory stimulation of the upper limbs in human participants within a magnetic resonance (MR) environment. The current-controlled, voltage-limited stimulation device features 20 stimulation channels that can be individually configured to deliver various non-simultaneous combinations of personalized electrical pulses, tailored to the subject, stimulation site, and paradigm. It was designed with a modular assembly to ensure compatibility with the MR environment. The assessment of the device consisted of four stages. First, the feasibility of generating controllable electrical stimuli outside the MR environment was validated using an electrical circuit equivalent to the impedance of the human body and the electrode-skin interface. Subsequently, safety and compatibility were evaluated in a 3 Tesla Magnetom Prisma fit scanner using a phantom. Next, the device's capacity to generate perceptible tactile sensations and user acceptability were assessed by testing the device on a single participant outside the MR environment. Finally, structural and functional data were acquired from three participants during a somatosensory stimulation experiment as a proof of concept to confirm the brain activity elicited by stimulation. These assessments confirmed the device’s capacity to generate controllable electrical stimuli both outside and in the MR environment, its compatibility and safety in this MR environment, and its effectiveness in eliciting brain activity in the expected brain areas without causing any discomfort to the participant. This study paves the way for future research on somatotopic mapping of S1 using this device.

How people make decisions under dyadic interactions is a relevant topic in social neuroscience, often studied using economic game theory approaches. A relevant question is whether neural correlates of neuroeconomic decision-making can be generalized to other contexts, such as health-related decision-making. We developed a functional neuroimaging paradigm to study trust-based decision-making during patient-doctor dyadic interactions (n = 35) as compared with classical investor-trustee interaction in neuroeconomic tasks. We found that the health-related self-consequential task activates a very similar network to the neuroeconomics one. Both proactive (higher investment) versus conservative investment attitudes and positive versus negative feedback led to very similar activation patterns between the health and the economic contexts. This shows that trust-based decision-making shares similar neural correlates across the economic and health domains.

Music, a universal element in human societies, possesses a profound ability to evoke emotions and influence mood. This systematic review explores the utilization of music to allow self-control of brain activity and its implications in clinical neuroscience. Focusing on music-based neurofeedback studies, it explores methodological aspects and findings to propose future directions. Three key questions are addressed: the rationale behind using music as a stimulus, its integration into the feedback loop, and the outcomes of such interventions. While studies emphasize the emotional link between music and brain activity, mechanistic explanations are lacking. Additionally, there is no consensus on the imaging or behavioral measures of neurofeedback success. The review suggests considering whole-brain neural correlates of music stimuli and their interaction with target brain networks and reward mechanisms when designing music-neurofeedback studies. Ultimately, this review aims to serve as a valuable resource for researchers, facilitating a deeper understanding of music's role in neurofeedback and guiding future investigations.

Measuring perception thresholds in electrocutaneous stimulation offers valuable insights into sensory processing and supports the creation of personalized methods for diagnosing and treating somatosensory disorders. This study uses a custom non-invasive electrocutaneous stimulation device to test the impact of stimulation frequency, position along the upper limb, and participants’ gender on the perception thresholds. The device targeted 20 stimulation positions on the dorsal side of the right upper limb of 24 healthy participants. Perception thresholds for each participant and stimulation position were determined by a staircase procedure at two frequencies (30 Hz and 100 Hz). Our findings highlight the complex interplay between gender and stimulation position while suggesting that frequency does not significantly influence perception thresholds under these conditions. While males exhibited higher perception thresholds overall, the spatial pattern of perception thresholds along the upper limb thresholds were in general higher at the middle finger and hand compared to the forearm and upper arm. However, the interaction between gender and stimulation position indicates that the magnitude of these differences varies depending on the specific position. These results underscore the necessity of considering gender- and position-specific differences when analyzing somatosensory thresholds across the upper limb.

Music is a uniquely powerful stimulus for evoking complex and deeply felt emotions. While previous research has identified neural correlates of music-evoked emotional responses, less is known about how these felt emotions are represented in the brain, particularly when elicited by familiar, personally meaningful music. Here, we used a personalized fMRI paradigm in which participants (N = 20) each selected musical excerpts corresponding to the nine emotion categories defined by the Geneva Emotional Music Scale. These self-selected excerpts were presented during functional MRI scanning. We first examined the neural correlates of music-evoked emotion by comparing brain activity during music listening to that during exposure to white noise. The maps were consistent with previous research, highlighting clusters in sensory and limbic regions. We then used multivoxel pattern analysis to decode emotion categories from whole-brain activation patterns. The results revealed that music-evoked emotions could be reliably discriminated based on distributed neural activity, with consistent involvement of the superior temporal gyrus, supplementary motor area, amygdala, and cerebellum, among other auditory, motor, and interoceptive regions. These findings provide new insight into the neural encoding of musical emotions and highlight the value of personalized, music-based paradigms for research in auditory and affective neuroscience. ### Competing Interest Statement The authors have declared no competing interest.

How can music, a universal feature of human societies with the powerful ability to evoke meaningful emotions and influence mood, be used to control brain activity? Music therapy is a well-established discipline, but clinical neuroscience implications of its use remain to be established, in particular in the context of brain modulation. This literature review offers a comprehensive investigation into music-based neurofeedback studies, providing an overview of the underlying reasoning and methodological facets explored in previous music-based neurofeedback research. Through a critical assessment of the results obtained from thirteen studies, we delve into the methodologies and their limitations to propose potential hypotheses and approaches that could steer the development of innovative methodologies incorporating music-based neurofeedback. Our review is organized around three primary questions. Firstly, we address the question of why music is utilized as a stimulus instead of other alternatives, seeking to identify the primary motivations and any specific hypotheses on the use of music in these interventions. Secondly, we explore how music is integrated into the feedback loop, examining the various paradigms and stages of incorporating music as a central component. Lastly, we investigate the principal outcomes of the reviewed studies, aiming to identify the main findings and uncover potential neural correlates associated with the intervention. We found that most studies justify the choice of music as the neurofeedback interface given the link between music and emotion. The mechanistic explanation for the musical features used is generally absent, and there is no consensus regarding the imaging and/or behavioral success measure of NF. In sum, we discuss that when designing a music-NF study, one should consider the whole-brain neural correlates of music stimuli and their interaction with the target brain network and the reward mechanisms, to optimize the feedback intervention and test its specificity. This review intends to contribute as a valuable resource for researchers in the field, aiding in the development of a deeper understanding of music and neurofeedback and offering guidance for future investigations in this promising domain.

Background Deficits in executive function (EF) are consistently reported in autism spectrum disorders (ASD). Tailored cognitive training tools, such as neurofeedback, focused on executive function enhancement might have a significant impact on the daily life functioning of individuals with ASD. We report the first real-time fMRI neurofeedback (rt-fMRI NF) study targeting the left dorsolateral prefrontal cortex (DLPFC) in ASD.Methods Thirteen individuals with autism without intellectual disability and seventeen neurotypical individuals completed a rt-fMRI working memory NF paradigm, consisting of subvocal backward recitation of self-generated numeric sequences. We performed a region-of-interest analysis of the DLPFC, whole-brain comparisons between groups and, DLPFC-based functional connectivity.Results The ASD and control groups were able to modulate DLPFC activity in 84% and 98% of the runs. Activity in the target region was persistently lower in the ASD group, particularly in runs without neurofeedback. Moreover, the ASD group showed lower activity in premotor/motor areas during pre-neurofeedback run than controls, but not in transfer runs, where it was seemingly balanced by higher connectivity between the DLPFC and the motor cortex. Group comparison in the transfer run also showed significant differences in DLPFC-based connectivity between groups, including higher connectivity with areas integrated into the multidemand network (MDN) and the visual cortex.Conclusions Neurofeedback seems to induce a higher between-group similarity of the whole-brain activity levels (including the target ROI) which might be promoted by changes in connectivity between the DLPFC and both high and low-level areas, including motor, visual and MDN regions.

Real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback (NF), a training method for the self-regulation of brain activity, has shown promising results as a neurorehabilitation tool, depending on the ability of the patient to succeed in neuromodulation. This study explores connectivity-based structural and functional success predictors in an NF n-back working memory paradigm targeting the dorsolateral prefrontal cortex (DLPFC). We established as the NF success metric the linear trend on the ability to modulate the target region during NF runs and performed a linear regression model considering structural and functional connectivity (intrinsic and seed-based) metrics. We found a positive correlation between NF success and the default mode network (DMN) intrinsic functional connectivity and a negative correlation with the DLPFC-precuneus connectivity during the 2-back condition, indicating that success is associated with larger uncoupling between DMN and the executive network. Regarding structural connectivity, the salience network emerges as the main contributor to success. Both functional and structural classification models showed good performance with 77% and 86% accuracy, respectively. Dynamic switching between DMN, salience network and central executive network seems to be the key for neurofeedback success, independently indicated by functional connectivity on the localizer run and structural connectivity data.

Functional magnetic resonance imaging (fMRI) allows to observe neural activity in real-time but tracking the neural correlates of perceptual decision as a function of interhemispheric connectivity has remained difficult. Recent advances in image acquisition, namely with the surfacing of multiband sequences, have led us to investigate this mechanism using higher temporal resolution approaches. We were able to better capture the hemodynamic responses to rapid changes in neural activity concomitantly with a task requiring either perceptual interhemispheric segregation or integration, shortening the gap to other neuroimaging techniques, which is particularly significant when considering the study of dynamic connectivity patterns. Here, we tested the hypothesis whether interhemispheric connectivity in the visual cortex relates to interhemispheric integration, when presented with bistable moving stimuli at four distinct temporal resolutions. Based on this connectivity metric, we could discern perceptual state transitions related to connectivity. First, we found that activation response metrics to visual motion in our target region of interest, the human visual motion complex hMT+, are stable across temporal resolutions. Then, we investigated interhemispheric connectivity between homologous hMT + in response to bistable moving stimuli, for all resolutions, which was critical for replication of perception related interhemispheric synchrony. The established relation between perceptual coherence and increased synchrony across the hemispheres suggests the feasibility of a real-time fMRI neurofeedback based on interhemispheric connectivity. Accordingly, we could infer perceptual states based on this connectivity metric while designing a rule that could even be used to generate feedback. We further showed that higher resolution sequences are beneficial when implementing feedback interfaces based on interhemispheric functional connectivity, both regarding the delay and the accuracy of the feedback itself. Regarding the use of real time fMRI and neurofeedback strategies, higher resolution sequences are likely needed, when relying on connectivity metrics.

Functional magnetic resonance imaging (fMRI) has been extensively used as a tool to map the brain processes related to somatosensory stimulation. This mapping includes the localization of task-related brain activation and the characterization of brain activity dynamics and neural circuitries related to the processing of somatosensory information. However, the magnetic resonance (MR) environment presents unique challenges regarding participant and equipment safety and compatibility. This study aims to systematically review and analyze the state-of-the-art methodologies to assess the safety and compatibility of somatosensory stimulation devices in the MR environment. A literature search, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement guidelines, was performed in PubMed, Scopus, and Web of Science to find original research on the development and testing of devices for somatosensory stimulation in the MR environment. Nineteen records that complied with the inclusion and eligibility criteria were considered. The findings are discussed in the context of the existing international standards available for the safety and compatibility assessment of devices intended to be used in the MR environment. In sum, the results provided evidence for a lack of uniformity in the applied testing methodologies, as well as an in-depth presentation of the testing methodologies and results. Lastly, we suggest an assessment methodology (safety, compatibility, performance, and user acceptability) that can be applied to devices intended to be used in the MR environment.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42021257838.

Executive functions and motivation have been established as key aspects for neurofeedback success. However, task-specific influence of cognitive strategies is scarcely explored. In this study, we test the ability to modulate the dorsolateral prefrontal cortex, a strong candidate for clinical application of neurofeedback in several disorders with dysexecutive syndrome, and investigate how feedback contributes to better performance in a single session. Participants of both neurofeedback (n = 17) and sham-control (n = 10) groups were able to modulate DLPFC in most runs (with or without feedback) while performing a working memory imagery task. However, activity in the target area was higher and more sustained in the active group when receiving feedback. Furthermore, we found increased activity in the nucleus accumbens in the active group, compared with a predominantly negative response along the block in participants receiving sham feedback. Moreover, they acknowledged the non-contingency between imagery and feedback, reflecting the impact on motivation. This study reinforces DLPFC as a robust target for neurofeedback clinical implementations and enhances the critical influence of the ventral striatum, both poised to achieve success in the self-regulation of brain activity.

This paper introduces a prototype for clinical research documentation using the structured information model HL7 CDA and clinical terminology (SNOMED CT). The proposed solution was integrated with the current electronic health record system (EHR-S) and aimed to implement interoperability and structure information, and to create a collaborative platform between clinical and research teams. The framework also aims to overcome the limitations imposed by classical documentation strategies in real-time healthcare encounters that may require fast access to complex information. The solution was developed in the pediatric hospital (HP) of the University Hospital Center of Coimbra (CHUC), a national reference for neurodevelopmental disorders, particularly for autism spectrum disorder (ASD), which is very demanding in terms of longitudinal and cross-sectional data throughput. The platform uses a three-layer approach to reduce components' dependencies and facilitate maintenance, scalability, and security. The system was validated in a real-life context of the neurodevelopmental and autism unit (UNDA) in the HP and assessed based on the functionalities model of EHR-S (EHR-S FM) regarding their successful implementation and comparison with state-of-the-art alternative platforms. A global approach to the clinical history of neurodevelopmental disorders was worked out, providing transparent healthcare data coding and structuring while preserving information quality. Thus, the platform enabled the development of user-defined structured templates and the creation of structured documents with standardized clinical terminology that can be used in many healthcare contexts. Moreover, storing structured data associated with healthcare encounters supports a longitudinal view of the patient's healthcare data and health status over time, which is critical in routine and pediatric research contexts. Additionally, it enables queries on population statistics that are key to supporting the definition of local and global policies, whose importance was recently emphasized by the COVID pandemic.