Functional Brain Imaging Research Articles

Functional connectivity in resting-state networks relates to short-term global cognitive functioning in cardiac arrest survivors.

Long-term cognitive impairment is common in cardiac arrest survivors. Screening to identify patients at risk is recommended. Functional magnetic resonance brain imaging (fMRI) holds potential to contribute to prediction of cognitive outcomes. In this study, we investigated the possible value of early changes in resting-state networks for predicting short and long-term cognitive functioning of cardiac arrest survivors. We performed a prospective multicenter cohort study in cardiac arrest survivors in three Dutch hospitals. Resting-state fMRI scans were acquired within a month after cardiac arrest. We primarily focused on functional connectivity within the default-mode network (DMN) and salience network (SN), and additionally explored functional connectivity in seven other networks. Cognitive outcome was measured using the Montreal Cognitive Assessment (MoCA) during hospital admission and at 3 and 12 months, and by neuropsychological examination (NPE) at 12 months. We tested mixed effects models to evaluate the value of connectivity within the networks for predicting global cognitive outcomes at the three time points, and long-term cognitive outcomes in the memory, attention, and executive functioning domains. We included 80 patients (age 60 ± 11 years, 72 (90%) male). MoCA scores increased significantly between hospital admission and 3 months (ΔMoCAhospital-3M = 2.89, p < 0.01), but not between 3 and 12 months (ΔMoCA3M-12M = 0.38, p = 0.52). Connectivity within the DMN, SN, and dorsal attention network (DAN) was positively related to global cognitive functioning during hospital admission (βDMN = 0.85, p = 0.03; βSN = 1.48, p < 0.01; βDAN = 0.96, p = 0.01), but not at 3 and 12 months. Network connectivity was also unrelated to long-term memory, attention, or executive functioning. Resting-state functional connectivity in the DMN, SN, and DAN measured in the first month after cardiac arrest is related to short-term global, but not long-term global or domain-specific cognitive performance of survivors. These results do not support the value of functional connectivity within these RSNs for prediction of long-term cognitive performance after cardiac arrest.

Highfield imaging of the subgenual anterior cingulate cortex in uni- and bipolar depression.

The subgenual Anterior Cingulate Cortex (sgACC), as a part of the Anterior Cingulate Cortex and the limbic system plays a crucial role in mood regulation. Previous structural and functional brain imaging studies of the sgACC have revealed alterations of Gray Matter (GM) volumes and Blood Oxygenation Level Dependent signals (BOLD) in patients with Major Depressive Disorder (MDD) and Bipolar Disorder (BD), suggesting potential biomarker traits for affective disorders. In this study we investigated the gray matter volume of the sgACC in 3 different patient groups: 40 MDD patients, of which 20 were medicated (MDDm) and 20 were unmedicated (MDDu), and 21 medicated BD patients, and compared them with 23 healthy volunteers. We examined GM volume alteration using high-resolution 7T Magnetic Resonance Imaging (MRI) which produced quantitative maps of the spin-lattice relaxation time (T1). T1 maps provide high contrast between gray and white matter, and at 7 Tesla voxels with submillimeter resolution can be acquired in a reasonable scan time. We developed a semi-automatic segmentation protocol based on refined landmarks derived from previous volumetric studies using quantitative T1 maps as raw input data for automatic tissue segmentation of GM, WM and CSF (cerebrospinal fluid) tissue. The sgACC ROI was then superimposed on these tissue probability maps and traced manually by two independent raters (F.B., M.M.) following our semi-automatic segmentation protocol. Interrater reliability was calculated on a subset of 10 brain scans for each hemisphere, showing an Intra-Class Correlation coefficient (ICC) r = 0.96 for left sgACC and r = 0.84 for right sgACC respectively. In summary, we have developed a reproducible and reliable semi-automatic segmentation protocol to measure gray matter volume in the sgACC. Based on previous findings from meta-analyses on morphometric studies of the sgACC, we hypothesized that patients with MDD would have lower gray matter sgACC volumes compared to healthy subjects. Post-hoc analysis revealed smaller subgenual volumes for the left hemisphere in both the medicated (MDDm) and non-medicated (MDDu) group versus healthy controls (p = .001, p = .008) respectively. For the right hemisphere, the (MDDu) and BD group exhibited significantly lower subgenual volumes than healthy controls (p < .001, p = .004) respectively. To our knowledge, this is the first morphometric MRI study using T1 maps obtained in high-resolution 7 Tesla MRI to compare MDD and BD patients with healthy controls.

Enhanced efficiency in the bilingual brain through the inter-hemispheric cortico-cerebellar pathway in early second language acquisition

Bilingualism has a profound impact on the structure and function of the brain, but it is not yet well understood how this experience influences brain functional organization. We examine a large sample (151 participants) of monolinguals and bilinguals with varied age of second language acquisition, who underwent resting-state functional magnetic brain imaging. Whole-brain network analyses reveal higher global efficiency in bilingual individuals than monolinguals, indicating enhanced functional integration in the bilingual brain. Moreover, the age at which the second language was acquired correlated with this increased efficiency, suggesting that earlier exposure to a second language has lasting positive effects on brain functional organization. Further investigation using the network-based statistics approach indicates that this effect is primarily driven by heightened functional connectivity between association networks and the cerebellum. These findings show that the timing of bilingual learning experience alters the brain functional organization at both global and local levels.

Functional Near-Infrared Spectroscopy in neurodegenerative disease: a review.

In recent years, with the aggravation of aging, the incidence of neurodegenerative diseases is increasing year by year, and the prognosis of patients is poor. Functional Near-Infrared Spectroscopy (fNIRS) is a new and non-invasive neuroimaging technology, which has been gradually deepened in the application research of neurodegenerative diseases by virtue of its unique neurooxygen signal brain functional imaging characteristics in monitoring the disease condition, making treatment plans and evaluating the treatment effect. In this paper, the mechanism of action and technical characteristics of fNIRS are briefly introduced, and the application research of fNIRS in different neurodegenerative diseases is summarized in order to provide new ideas for future related research and clinical application.

Emotional engagement with close friends in adolescence predicts neural correlates of empathy in adulthood

ABSTRACT Empathy requires the ability to understand another’s point of view and is critical for motivating a person to help others. However, little is known about the link between experiences of empathic emotional engagement in close friendships during adolescence and neural correlates of empathy in adulthood. Beginning in 1998, N = 88 participants drawn from a demographically diverse community sample were observed annually from ages 13 to 21 and rated on the amount of emotional engagement displayed toward a close friend during a support task. At approximately age 24, participants underwent functional brain imaging while a partner or stranger was under distress. Contrary to predictions, greater emotional engagement with close friends during adolescence corresponded prospectively with reduced temporal pole activity (a region associated with cognitive empathy and perspective taking) while observing threats directed at others. Results have implications for understanding the neurodevelopmental roots of empathy.

Meeting the multidimensional self: fostering selfhood at the interface of Creative Arts Therapies and neuroscience.

Intriguing explorations at the intersection of the fields of neuroscience and psychology are driven by the quest to understand the neural underpinnings of "the self" and their psychotherapeutic implications. These translational efforts pertain to the unique Creative Arts Therapies (CATs) and the attributes and value of the self-related processes they offer. The self is considered as a multi-layered complex construct, comprising bodily and mental constituents, subjective-objective perspectives, spatial and temporal dimensions. Neuroscience research, mostly functional brain imaging, has proposed cogent models of the constitution, development and experience of the self, elucidating how the multiple dimensions of the self are supported by integrated hierarchical brain processes. The psychotherapeutic use of the art-forms, generating aesthetic experiences and creative processes, touch upon and connect the various layers of self-experience, nurturing the sense of self. The present conceptual analysis will describe and interweave the neural mechanisms and neural network configuration suggested to lie at the core of the ongoing self-experience, its deviations in psychopathology, and implications regarding the psychotherapeutic use of the arts. The well-established, parsimonious and neurobiologically plausible predictive processing account of brain-function will be discussed with regard to selfhood and consciousness. The epistemic affordance of the experiential CATs will further be portrayed, enabling and facilitating the creation of updated self-models of the body in the world. The neuropsychological impact of the relational therapeutic encounter will be delineated, acknowledging the intersubjective brain synchronization through communicative verbal and non-verbal means and aesthetic experiences. The recognition and assimilation of neuroscientific, phenomenological and clinical perspectives concerning the nested dimensionality of the self, ground the relational therapeutic process and the neuroplastic modulations that CATs have to offer on the premise of fostering, shaping and integrating selfhood.

Mapping connectivity and network alterations in youth depression by functional brain imaging

Mapping connectivity and network alterations in youth depression by functional brain imaging

Mesoscale Brain Mapping: Bridging Scales and Modalities in Neuroimaging - A Symposium Review.

Advances in the spatiotemporal resolution and field-of-view of neuroimaging tools are driving mesoscale studies for translational neuroscience. On October 10, 2023, the Center for Mesoscale Mapping (CMM) at the Massachusetts General Hospital (MGH) Athinoula A. Martinos Center for Biomedical Imaging and the Massachusetts Institute of Technology (MIT) Health Sciences Technology based Neuroimaging Training Program (NTP) hosted a symposium exploring the state-of-the-art in this rapidly growing area of research. "Mesoscale Brain Mapping: Bridging Scales and Modalities in Neuroimaging" brought together researchers who use a broad range of imaging techniques to study brain structure and function at the convergence of the microscopic and macroscopic scales. The day-long event centered on areas in which the CMM has established expertise, including the development of emerging technologies and their application to clinical translational needs and basic neuroscience questions. The in-person symposium welcomed more than 150 attendees, including 57 faculty members, 61 postdoctoral fellows, 35 students, and four industry professionals, who represented institutions at the local, regional, and international levels. The symposium also served the training goals of both the CMM and the NTP. The event content, organization, and format were planned collaboratively by the faculty and trainees. Many CMM faculty presented or participated in a panel discussion, thus contributing to the dissemination of both the technologies they have developed under the auspices of the CMM and the findings they have obtained using those technologies. NTP trainees who benefited from the symposium included those who helped to organize the symposium and/or presented posters and gave "flash" oral presentations. In addition to gaining experience from presenting their work, they had opportunities throughout the day to engage in one-on-one discussions with visiting scientists and other faculty, potentially opening the door to future collaborations. The symposium presentations provided a deep exploration of the many technological advances enabling progress in structural and functional mesoscale brain imaging. Finally, students worked closely with the presenting faculty to develop this report summarizing the content of the symposium and putting it in the broader context of the current state of the field to share with the scientific community. We note that the references cited here include conference abstracts corresponding to the symposium poster presentations.

Immunomodulatory treatment may change functional and structural brain imaging in severe mental disorders

Neuroinflammation has been implicated in the pathophysiology of schizophrenia and obsessive-compulsive disorder (OCD) and deviations in brain structure and connectivity are seen in these disorders. Here, we explore the effects of a potent immunomodulatory treatment on neuroimaging. In a pilot study of rituximab treatment in schizophrenia and OCD, a subgroup (n = 13) underwent structural and functional magnetic resonance imaging before and 5 months after treatment, to study longitudinal changes in resting-state functional connectivity (rsFC) and voxel-based morphometry (VBM).A hypothesis-free exploratory whole-brain analysis was performed twice to assess changes in rsFC, using anterior cingulate cortex, anterior insula, posterior insula and nucleus accumbens as seed regions. There were significant interactions (diagnosis x time) in connectivity between right posterior insula and two clusters encompassing basal ganglia and anterior frontal pole, and between left anterior insula and a cluster in basal ganglia, where connectivity decreased in OCD and increased in schizophrenia. The increase of connectivity after rituximab, between left anterior insula and parts of cerebellum and lingual gyrus and between left posterior insula and parts of cerebellum, correlated with improved global psychosocial functioning according to the Personal and Social Performance Scale, especially in schizophrenia. VBM analysis identified two clusters with increased grey matter volumes (GMV) after rituximab, one in right insula overlapping one of the seed regions with significant rsFC changes. This pilot study implies that rituximab may influence both brain structure and connectivity and that GMV changes and rsFC changes are regionally associated.

Mapping neural correlates of biological motion perception in autistic children using high-density diffuse optical tomography

BackgroundAutism spectrum disorder (ASD), a neurodevelopmental disorder defined by social communication deficits plus repetitive behaviors and restricted interests, currently affects 1/36 children in the general population. Recent advances in functional brain imaging show promise to provide useful biomarkers of ASD diagnostic likelihood, behavioral trait severity, and even response to therapeutic intervention. However, current gold-standard neuroimaging methods (e.g., functional magnetic resonance imaging, fMRI) are limited in naturalistic studies of brain function underlying ASD-associated behaviors due to the constrained imaging environment. Compared to fMRI, high-density diffuse optical tomography (HD-DOT), a non-invasive and minimally constraining optical neuroimaging modality, can overcome these limitations. Herein, we aimed to establish HD-DOT to evaluate brain function in autistic and non-autistic school-age children as they performed a biological motion perception task previously shown to yield results related to both ASD diagnosis and behavioral traits.MethodsWe used HD-DOT to image brain function in 46 ASD school-age participants and 49 non-autistic individuals (NAI) as they viewed dynamic point-light displays of coherent biological and scrambled motion. We assessed group-level cortical brain function with statistical parametric mapping. Additionally, we tested for brain-behavior associations with dimensional metrics of autism traits, as measured with the Social Responsiveness Scale-2, with hierarchical regression models.ResultsWe found that NAI participants presented stronger brain activity contrast (coherent > scrambled) than ASD children in cortical regions related to visual, motor, and social processing. Additionally, regression models revealed multiple cortical regions in autistic participants where brain function is significantly associated with dimensional measures of ASD traits.LimitationsOptical imaging methods are limited in depth sensitivity and so cannot measure brain activity within deep subcortical regions. However, the field of view of this HD-DOT system includes multiple brain regions previously implicated in both task-based and task-free studies on autism.ConclusionsThis study demonstrates that HD-DOT is sensitive to brain function that both differentiates between NAI and ASD groups and correlates with dimensional measures of ASD traits. These findings establish HD-DOT as an effective tool for investigating brain function in autistic and non-autistic children. Moreover, this study established neural correlates related to biological motion perception and its association with dimensional measures of ASD traits.

Cerebro-spinal somatotopic organization uncovered through functional connectivity mapping

Abstract Somatotopy, the topographical arrangement of sensorimotor pathways corresponding to distinct body parts, is a fundamental feature of the human central nervous system (CNS). Traditionally, investigations into brain and spinal cord somatotopy have been conducted independently, primarily utilizing body stimulations or movements. To date, however, no study has probed the somatotopic arrangement of cerebro-spinal functional connections in vivo in humans. In this study, we used simultaneous brain and cervical spinal cord functional magnetic resonance imaging (fMRI) to demonstrate how the coordinated activities of these two CNS levels at rest can reveal their shared somatotopy. Using functional connectivity analyses, we mapped preferential correlation patterns between each spinal cord segment and distinct brain regions, revealing a somatotopic gradient within the cortical sensorimotor network. We then validated this large-scale somatotopic organization through a complementary data-driven analysis, where we effectively identified spinal cord segments through the connectivity profiles of their voxels with the sensorimotor cortex. These findings underscore the potential of resting-state cerebro-spinal cord fMRI to probe the large-scale organization of the human sensorimotor system with minimal experimental burden, holding promise for gaining a more comprehensive understanding of normal and impaired somatosensory-motor functions.

Improving source estimation of retinotopic MEG responses by combining data from multiple subjects

Abstract Magnetoencephalography (MEG) is a functional brain imaging modality, which measures the weak magnetic field arising from neuronal activity. The source amplitudes and locations are estimated from the sensor data by solving an ill-posed inverse problem. Commonly used solutions for these problems operate on data from individual subjects. Combining the measurements of multiple subjects has been suggested to increase the spatial resolution of MEG by leveraging the intersubject differences for increased information. In this article, we compare 3 multisubject analysis methods on a retinotopic mapping dataset recorded from 20 subjects. The compared methods are eLORETA with source-space averaging, minimum Wasserstein estimates (MWE), and MWE with source-space averaging. The results were quantified by the geodesic distances between early (60–100 ms) MEG peak activations and fMRI-based retinotopic target points in the primary visual cortex (V1). By increasing the subject count from 1 to 10, the median distances decreased by 6.6–9.4 mm (33–46%) compared with the single-subject median distances of around 20 mm. The observed peak activation locations with multisubject analysis also comply better with the established retinotopic maps of the primary visual cortex. Our results suggest that higher spatial accuracy can be achieved by pooling data from multiple subjects. The strength of MWE lies in individualized and sparse source estimates, but in our data, averaging eLORETA estimates across individuals in source space outperformed MWE in spatial accuracy.

Moving beyond processing- and analysis-related variation in resting-state functional brain imaging.

When fields lack consensus standard methods and accessible ground truths, reproducibility can be more of an ideal than a reality. Such has been the case for functional neuroimaging, where there exists a sprawling space of tools and processing pipelines. We provide a critical evaluation of the impact of differences across five independently developed minimal preprocessing pipelines for functional magnetic resonance imaging. We show that, even when handling identical data, interpipeline agreement was only moderate, critically shedding light on a factor that limits cross-study reproducibility. We show that low interpipeline agreement can go unrecognized until the reliability of the underlying data is high, which is increasingly the case as the field progresses. Crucially we show that, when interpipeline agreement is compromised, so too is the consistency of insights from brain-wide association studies. We highlight the importance of comparing analytic configurations, because both widely discussed and commonly overlooked decisions can lead to marked variation.

Evolution of a central dopamine circuit underlies adaptation of light-evoked sensorimotor response in the blind cavefish, Astyanax mexicanus.

Adaptive behaviors emerge in novel environments through functional changes in neural circuits. While relationships between circuit function and behavior have been well studied, how evolution shapes those circuits and leads to behavioral adpation is poorly understood. The Mexican cavefish, Astyanax mexicanus, provides a unique genetically amendable model system, equipped with above ground eyed surface fish and multiple evolutionarily divergent populations of blind cavefish that have evolved in complete darkness. These differences in environment and vision provide an opprotunity to examine how a neural circuit is functionally influenced by the presence of light. Here, we examine differences in the detection, and behavioral response induced by non visual light reception. Both populations exhibit photokinetic behavior, with surface fish becoming hyperactive following sudden darkness and cavefish becoming hyperactive following sudden illumination. To define these photokinetic neural circuits, we integrated whole brain functional imaging with our Astyanax brain atlas for surface and cavefish responding to light changes. We identified the caudal posterior tuberculum as the central modulator for both light or dark stimulated photokinesis. To unconver how spatiotemporal neuronal activity differed between surface fish and cavefish, we used stable pan-neuronal GCaMP Astyanax transgenics to show that a subpopulation of darkness sensitve neurons in surface fish are now light senstive in cavefish. Further functional analysis revealed that this integrative switch is dependent on dopmane signaling, suggesting a key role for dopamine and a highly conserved dopamine circuit in modulating the evolution of a circuit driving an essential behavior. Together, these data shed light into how neural circuits evolved to adapte to novel settings, and reveal the power of Astyanax as a model to elucidate mechanistic ingiths underlying sensory adaptation.

Eye-brain connections revealed by multimodal retinal and brain imaging genetics

The retina, an anatomical extension of the brain, forms physiological connections with the visual cortex of the brain. Although retinal structures offer a unique opportunity to assess brain disorders, their relationship to brain structure and function is not well understood. In this study, we conducted a systematic cross-organ genetic architecture analysis of eye-brain connections using retinal and brain imaging endophenotypes. We identified novel phenotypic and genetic links between retinal imaging biomarkers and brain structure and function measures from multimodal magnetic resonance imaging (MRI), with many associations involving the primary visual cortex and visual pathways. Retinal imaging biomarkers shared genetic influences with brain diseases and complex traits in 65 genomic regions, with 18 showing genetic overlap with brain MRI traits. Mendelian randomization suggests bidirectional genetic causal links between retinal structures and neurological and neuropsychiatric disorders, such as Alzheimer’s disease. Overall, our findings reveal the genetic basis for eye-brain connections, suggesting that retinal images can help uncover genetic risk factors for brain disorders and disease-related changes in intracranial structure and function.

Resting-State Functional Connectivity Predicts Cochlear-Implant Speech Outcomes.

Cochlear implants (CIs) have revolutionized hearing restoration for individuals with severe or profound hearing loss. However, a substantial and unexplained variability persists in CI outcomes, even when considering subject-specific factors such as age and the duration of deafness. In a pioneering study, we use resting-state functional near-infrared spectroscopy to predict speech-understanding outcomes before and after CI implantation. Our hypothesis centers on resting-state functional connectivity (FC) reflecting brain plasticity post-hearing loss and implantation, specifically targeting the average clustering coefficient in resting FC networks to capture variation among CI users. Twenty-three CI candidates participated in this study. Resting-state functional near-infrared spectroscopy data were collected preimplantation and at 1 month, 3 months, and 1 year postimplantation. Speech understanding performance was assessed using consonant-nucleus-consonant words in quiet and Bamford-Kowal-Bench sentences in noise 1-year postimplantation. Resting-state FC networks were constructed using regularized partial correlation, and the average clustering coefficient was measured in the signed weighted networks as a predictive measure for implantation outcomes. Our findings demonstrate a significant correlation between the average clustering coefficient in resting-state functional networks and speech understanding outcomes, both pre- and postimplantation. This approach uses an easily deployable resting-state functional brain imaging metric to predict speech-understanding outcomes in implant recipients. The results indicate that the average clustering coefficient, both pre- and postimplantation, correlates with speech understanding outcomes.

Spurious correlations in surface-based functional brain imaging.

The study of functional MRI data is increasingly performed after mapping from volumetric voxels to surface vertices. Processing pipelines commonly used to achieve this mapping produce meshes with uneven vertex spacing, with closer neighbours in sulci compared to gyri. Consequently, correlations between the fMRI time series of neighbouring sulcal vertices are stronger than expected. However, the causes, extent, and impacts of this bias are not well understood or widely appreciated. We explain the origins of these biases, and using in-silico models of fMRI data, illustrate how they lead to spurious results. The bias leads to leakage of anatomical cortical folding information into fMRI time series. We show that many common analyses can be affected by this "gyral bias", including test-retest reliability, fingerprinting, functional parcellations, regional homogeneity, and brain-behaviour associations. Finally, we provide recommendations to avoid or remedy this spatial bias.

Diffuse optical tomography of the brain: effects of inaccurate baseline optical parameters and refinements using learned post-processing.

Diffuse optical tomography (DOT) uses near-infrared light to image spatially varying optical parameters in biological tissues. In functional brain imaging, DOT uses a perturbation model to estimate the changes in optical parameters, corresponding to changes in measured data due to brain activity. The perturbation model typically uses approximate baseline optical parameters of the different brain compartments, since the actual baseline optical parameters are unknown. We simulated the effects of these approximate baseline optical parameters using parameter variations earlier reported in literature, and brain atlases from four adult subjects. We report the errors in estimated activation contrast, localization, and area when incorrect baseline values were used. Further, we developed a post-processing technique based on deep learning methods that can reduce the effects due to inaccurate baseline optical parameters. The method improved imaging of brain activation changes in the presence of such errors.

Central imaging based on near-infrared functional imaging technology can be useful to plan management in patients with chronic lateral ankle instability

BackgroundNear infrared brain functional imaging (FNIRS) has been used for the evaluation of brain functional areas, the imaging differences of central activation of cognitive-motor dual tasks between patients with chronic lateral ankle instability (CLAI) and healthy population remain unclear. This study aimed to evaluated the role of central imaging based on FNIRS technology on the plan management in patients with CLAI, to provide insights to the clinical treatment of CLAI.MethodsCLAI patients treated in our hospital from January 1, 2021 to June 31, 2022 were selected. Both CLAI patients and health controls were intervened with simple task and cognitive-motor dual task under sitting and walking conditions, and the changes of oxygenated hemoglobin concentration in bilateral prefrontal cortex (PFC), premotor cortex (PMC) and auxiliary motor area (SMA) were collected and compared.ResultsA total of 23 participants were enrolled. There were significant differences in the fNIRS ΔHbO2 of barefoot subtractive walking PFC-R and barefoot subtractive walking SMA-R between experimental and control group (all P < 0.05). There was no significant difference in ΔHbO2 between the experimental group and the control group in other states (P > 0.05). There was no significant difference in ΔHbO2 between the experimental group and the control group in each state of the brain PMC region.ConclusionAdaptive alterations may occur within the relevant brain functional regions of individuals with CLAI. The differential activation observed between the PFC and the SMA could represent a compensatory mechanism emerging from proprioceptive afferent disruptions following an initial ankle sprain.

Building national patient registries in Mexico: insights from the MexOMICS Consortium.

To introduce MexOMICS, a Mexican Consortium focused on establishing electronic databases to collect, cross-reference, and share health-related and omics data on the Mexican population. Since 2019, the MexOMICS Consortium has established three electronic-based registries: the Mexican Twin Registry (TwinsMX), Mexican Lupus Registry (LupusRGMX), and the Mexican Parkinson's Research Network (MEX-PD), designed and implemented using the Research Electronic Data Capture web-based application. Participants were enrolled through voluntary participation and on-site engagement with medical specialists. We also acquired DNA samples and Magnetic Resonance Imaging scans in subsets of participants. The registries have successfully enrolled a large number of participants from a variety of regions within Mexico: TwinsMX (n = 2,915), LupusRGMX (n = 1,761) and MEX-PD (n = 750). In addition to sociodemographic, psychosocial, and clinical data, MexOMICS has collected DNA samples to study the genetic biomarkers across the three registries. Cognitive function has been assessed with the Montreal Cognitive Assessment in a subset of 376 MEX-PD participants. Furthermore, a subset of 267 twins have participated in cognitive evaluations with the Creyos platform and in MRI sessions acquiring structural, functional, and spectroscopy brain imaging; comparable evaluations are planned for LupusRGMX and MEX-PD. The MexOMICS registries offer a valuable repository of information concerning the potential interplay of genetic and environmental factors in health conditions among the Mexican population.