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The difference between the estimated brain age and the chronological age ('brain-PAD') could become a clinical biomarker. However, most brain age models were developed for research-grade high-resolution T1-weighted MRIs, limiting their applicability to clinical-grade MRIs from various protocols. We adopted a dual-transfer learning strategy to develop a model agnostic to modality, resolution, or slice orientation. We retrained a convolutional neural network (CNN) using 6281 clinical MRIs from 1559 patients, among 7 modalities and 8 scanner models. The CNN was trained to estimate brain age from synthetic research-grade magnetization-prepared rapid gradient-echo MRIs (MPRAGEs) generated by a 'super-resolution' method. The model failed with T2-weighted Gradient-Echo MRIs. The mean absolute error (MAE) was 5.86-8.59 years across the other modalities, still higher than for research-grade MRIs, but comparable between actual and synthetic MPRAGEs for some modalities. We modeled the "regression bias" in brain age, for its correction is crucial for providing unbiased summary statistics of brain age or for personalized brain age-based biomarkers. The bias model was generalizable as its correction eliminated any correlation between brain-PAD and chronological age in new samples. Brain-PAD was reliable across modalities. We demonstrate the feasibility of brain age predictions from arbitrary clinical-grade MRIs, thereby contributing to personalized medicine.
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Procesamiento de Imagen Asistido por Computador , Imagen por Resonancia Magnética , Humanos , Procesamiento de Imagen Asistido por Computador/métodos , Imagen por Resonancia Magnética/métodos , Redes Neurales de la Computación , Encéfalo/diagnóstico por imagenRESUMEN
Background: Population-based neuroscience offers opportunities to examine important but understudied sociocultural factors such as acculturation. Acculturation refers to the extent to which an individual retains their cultural heritage and/or adopts the receiving society's culture and is particularly salient among Hispanic/Latinx immigrants. Specific acculturative orientations have been linked to vulnerability to substance use, depression, and suicide and are known to influence family dynamics between caregivers and their children. Methods: Using data from first- and second-generation Hispanic/Latinx caregivers in the Adolescent Brain Cognitive Development (ABCD) Study (N = 1057), we examined how caregivers' acculturative orientation affects their mental health, as well as the mental health and brain function of their children. Neuroimaging analyses focused on regions associated with self- and affiliation-based social processing (ventromedial prefrontal cortex, insula, and temporoparietal junction). Results: We identified 2 profiles of caregiver acculturation: bicultural (retains heritage culture while adopting U.S. culture) and detached (discards heritage culture and rejects U.S. culture). Bicultural caregivers exhibited fewer internalizing and externalizing problems than detached caregivers; furthermore, youth exhibited similar internalizing effects across caregiver profiles. In addition, youth with bicultural caregivers displayed increased resting-state brain activity (i.e., fractional amplitude of low-frequency fluctuations and regional homogeneity) in the left insula, which has been linked to psychopathology; however, differences in long-range functional connectivity were not significant. Conclusions: Caregiver acculturation is an important familial factor that has been linked to significant differences in youth mental health and insula activity. Future work should examine sociocultural and neurodevelopmental changes across adolescence to assess health outcomes and determine whether localized, corticolimbic brain effects are ultimately translated into long-range connectivity differences.
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PURPOSE: Attentional control theory (ACT) posits that elevated anxiety increases the probability of re-allocating cognitive resources needed to complete a task to processing anxiety-related stimuli. This process impairs processing efficiency and can lead to reduced performance effectiveness. Science, technology, engineering, and math (STEM) students frequently experience anxiety about their coursework, which can interfere with learning and performance and negatively impact student retention and graduation rates. The objective of this study was to extend the ACT framework to investigate the neurobiological associations between science and math anxiety and cognitive performance among 123 physics undergraduate students. PROCEDURES: Latent profile analysis (LPA) identified four profiles of science and math anxiety among STEM students, including two profiles that represented the majority of the sample (Low Science and Math Anxiety; 59.3% and High Math Anxiety; 21.9%) and two additional profiles that were not well represented (High Science and Math Anxiety; 6.5% and High Science Anxiety; 4.1%). Students underwent a functional magnetic resonance imaging (fMRI) session in which they performed two tasks involving physics cognition: the Force Concept Inventory (FCI) task and the Physics Knowledge (PK) task. FINDINGS: No significant differences were observed in FCI or PK task performance between High Math Anxiety and Low Science and Math Anxiety students. During the three phases of the FCI task, we found no significant brain connectivity differences during scenario and question presentation, yet we observed significant differences during answer selection within and between the dorsal attention network (DAN), ventral attention network (VAN), and default mode network (DMN). Further, we found significant group differences during the PK task were limited to the DAN, including DAN-VAN and within-DAN connectivity. CONCLUSIONS: These results highlight the different cognitive processes required for physics conceptual reasoning compared to physics knowledge retrieval, provide new insight into the underlying brain dynamics associated with anxiety and physics cognition, and confirm the relevance of ACT theory for science and math anxiety.
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Trastornos de Ansiedad , Ansiedad , Humanos , Universidades , Física , EstudiantesRESUMEN
Macroscale gradients have emerged as a central principle for understanding functional brain organization. Previous studies have demonstrated that a principal gradient of connectivity in the human brain exists, with unimodal primary sensorimotor regions situated at one end and transmodal regions associated with the default mode network and representative of abstract functioning at the other. The functional significance and interpretation of macroscale gradients remains a central topic of discussion in the neuroimaging community, with some studies demonstrating that gradients may be described using meta-analytic functional decoding techniques. However, additional methodological development is necessary to fully leverage available meta-analytic methods and resources and quantitatively evaluate their relative performance. Here, we conducted a comprehensive series of analyses to investigate and improve the framework of data-driven, meta-analytic methods, thereby establishing a principled approach for gradient segmentation and functional decoding. We found that a two-segment solution determined by a k-means segmentation approach and an LDA-based meta-analysis combined with the NeuroQuery database was the optimal combination of methods for decoding functional connectivity gradients. Finally, we proposed a method for decoding additional components of the gradient decomposition. The current work aims to provide recommendations on best practices and flexible methods for gradient-based functional decoding of fMRI data.
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ABSTRACT: Brain age predicted differences (brain-PAD: predicted brain age minus chronological age) have been reported to be significantly larger for individuals with chronic pain compared with those without. However, a debate remains after one article showed no significant differences. Using Gaussian Process Regression, an article provides evidence that these negative results might owe to the use of mixed samples by reporting a differential effect of chronic pain on brain-PAD across pain types. However, some remaining methodological issues regarding training sample size and sex-specific effects should be tackled before settling this controversy. Here, we explored differences in brain-PAD between musculoskeletal pain types and controls using a novel convolutional neural network for predicting brain-PADs, ie, DeepBrainNet. Based on a very large, multi-institutional, and heterogeneous training sample and requiring less magnetic resonance imaging preprocessing than other methods for brain age prediction, DeepBrainNet offers robust and reproducible brain-PADs, possibly highly sensitive to neuropathology. Controlling for scanner-related variability, we used a large sample (n = 660) with different scanners, ages (19-83 years), and musculoskeletal pain types (chronic low back [CBP] and osteoarthritis [OA] pain). Irrespective of sex, brain-PAD of OA pain participants was â¼3 to 4.7 years higher than that of CBP and controls, whereas brain-PAD did not significantly differ among controls and CBP. Moreover, brain-PAD was significantly related to multiple variables underlying the multidimensional pain experience. This comprehensive work adds evidence of pain type-specific effects of chronic pain on brain age. This could help in the clarification of the debate around possible relationships between brain aging mechanisms and pain.
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Dolor Crónico , Dolor Musculoesquelético , Osteoartritis , Femenino , Humanos , Masculino , Envejecimiento/patología , Encéfalo/diagnóstico por imagen , Encéfalo/patología , Dolor Crónico/patología , Imagen por Resonancia Magnética/métodos , Dolor Musculoesquelético/patología , Adulto Joven , Adulto , Persona de Mediana Edad , Anciano , Anciano de 80 o más AñosRESUMEN
OBJECTIVES: Pain sensitivity and the brain structure are critical in modulating pain and may contribute to the maintenance of pain in older adults. However, a paucity of evidence exists investigating the link between pain sensitivity and brain morphometry in older adults. The purpose of the study was to identify pain sensitivity profiles in healthy, community-dwelling older adults using a multimodal quantitative sensory testing protocol and to differentiate profiles based on brain morphometry. MATERIALS AND METHODS: This study was a secondary analysis of the Neuromodulatory Examination of Pain and Mobility Across the Lifespan (NEPAL) study. Participants completed demographic and psychological questionnaires, quantitative sensory testing, and a neuroimaging session. A Principal Component Analysis with Varimax rotation followed by hierarchical cluster analysis identified 4 pain sensitivity clusters (the "pain clusters"). RESULTS: Sixty-two older adults ranging from 60 to 94 years old without a specific pain condition (mean [SD] age=71.44 [6.69] y, 66.1% female) were analyzed. Four pain clusters were identified characterized by (1) thermal pain insensitivity; (2) high pinprick pain ratings and pressure pain insensitivity; (3) high thermal pain ratings and high temporal summation; and (4) thermal pain sensitivity, low thermal pain ratings, and low mechanical temporal summation. Sex differences were observed between pain clusters. Pain clusters 2 and 4 were distinguished by differences in the brain cortical volume in the parieto-occipital region. DISCUSSION: While sufficient evidence exists demonstrating pain sensitivity profiles in younger individuals and in those with chronic pain conditions, the finding that subgroups of experimental pain sensitivity also exist in healthy older adults is novel. Identifying these factors in older adults may help differentiate the underlying mechanisms contributing to pain and aging.
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Dolor Crónico , Vida Independiente , Anciano , Enfermedad Crónica , Dolor Crónico/psicología , Femenino , Humanos , Masculino , Dimensión del Dolor/métodos , Umbral del Dolor/psicología , FenotipoRESUMEN
INTRODUCTION: Psychological factors have been associated with knee osteoarthritis pain severity and treatment outcomes, yet their combined contribution to phenotypic heterogeneity is poorly understood. In particular, empirically derived psychological profiles must be replicated before they can be targeted or considered for treatment studies. The objectives of this study were to (1) confirm previously identified psychological profiles using unsupervised clustering methods in persons with knee osteoarthritis pain, (2) determine the replicability of profiles using supervised machine learning in a different sample, and (3) examine associations with clinical pain, brain structure, and experimental pain. METHODS: Participants included two cohorts of individuals with knee osteoarthritis pain recruited as part of the multisite UPLOAD1 (n = 270, mean age = 56.8 ± 7.6, male = 37%) and UPLOAD2 (n = 164, mean age = 57.73 ± 7.8, male = 36%) studies. Similar psychological constructs (e.g. optimism, coping, somatization, affect, depression, and anxiety), sociodemographic and clinical characteristics, and somatosensory function were assessed across samples. UPLOAD2 participants also completed brain magnetic resonance imaging. Unsupervised hierarchical clustering analysis was first conducted in UPLOAD1 data to derive clusters, followed by supervised linear discriminative analysis to predict group membership in UPLOAD2 data. Associations among cluster membership and clinical variables were assessed, controlling for age, sex, education, ethnicity/race, study site, and number of pain sites. RESULTS: Four distinct profiles emerged in UPLOAD1 and were replicated in UPLOAD2. Identified psychological profiles were associated with psychological variables (ps < 0.001), and clinical outcomes (ps = 0.001-0.03), indicating good internal and external validation of the cluster solution. Significant associations between psychological profiles and somatosensory function and brain structure were also found. CONCLUSIONS: This study highlights the importance of considering the biopsychosocial model in knee osteoarthritis pain assessment and treatment.
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BACKGROUND AND OBJECTIVES: Somatosensory function is critical for successful aging. Prior studies have shown declines in somatosensory function with age; however, this may be affected by testing site, modality, and biobehavioral factors. While somatosensory function declines are associated with peripheral nervous system degradation, little is known regarding correlates with the central nervous system and brain structure in particular. The objectives of this study were to examine age-related declines in somatosensory function using innocuous and noxious stimuli, across 2 anatomical testing sites, with considerations for affect and cognitive function, and associations between somatosensory function and brain structure in older adults. RESEARCH DESIGN AND METHODS: A cross-sectional analysis included 84 "younger" (n = 22, age range: 19-24 years) and "older" (n = 62, age range: 60-94 years) healthy adults who participated in the Neuromodulatory Examination of Pain and Mobility Across the Lifespan study. Participants were assessed on measures of somatosensory function (quantitative sensory testing), at 2 sites (metatarsal and thenar) using standardized procedures, and completed cognitive and psychological function measures and structural magnetic resonance imaging. RESULTS: Significant age × test site interaction effects were observed for warmth detection (p = .018, η p 2 = 0.10) and heat pain thresholds (p = .014, η p 2 = 0.12). Main age effects were observed for mechanical, vibratory, cold, and warmth detection thresholds (ps < .05), with older adults displaying a loss of sensory function. Significant associations between somatosensory function and brain gray matter structure emerged in the right occipital region, the right temporal region, and the left pericallosum. DISCUSSION AND IMPLICATIONS: Our findings indicate healthy older adults display alterations in sensory responses to innocuous and noxious stimuli compared to younger adults and, furthermore, these alterations are uniquely affected by anatomical site. These findings suggest a nonuniform decline in somatosensation in older adults, which may represent peripheral and central nervous system alterations part of aging processes.
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BACKGROUND: Autonomic dysregulation may lead to blunted sympathetic reactivity in chronic pain states. Autonomic responses are controlled by the central autonomic network (CAN). Little research has examined sympathetic reactivity and associations with brain CAN structures in the presence of chronic pain; thus, the present study aims to investigate how chronic pain influences sympathetic reactivity and associations with CAN brain region volumes. METHODS: Sympathetic reactivity was measured as change in skin conductance level (ΔSCL) between a resting reference period and walking periods for typical and complex walking tasks (obstacle and dual-task). Participants included 31 people with (n = 19) and without (n = 12) chronic musculoskeletal pain. Structural 3 T MRI was used to determine gray matter volume associations with ΔSCL in regions of the CAN (i.e., brainstem, amygdala, insula, and anterior cingulate cortex). RESULTS: ΔSCL varied across walking tasks (main effect p = 0.036), with lower ΔSCL in chronic pain participants compared to controls across trials 2 and 3 under the obstacle walking condition. ΔSCL during typical walking was associated with multiple CAN gray matter volumes, including brainstem, bilateral insula, amygdala, and right caudal anterior cingulate cortex (p's < 0.05). The difference in ΔSCL from typical-to-obstacle walking were associated with volumes of the midbrain segment of the brainstem and anterior segment of the circular sulcus of the insula (p's < 0.05), with no other significant associations. The difference in ΔSCL from typical-to-dual task walking was associated with the bilateral caudal anterior cingulate cortex, and left rostral cingulate cortex (p's < 0.05). CONCLUSIONS: Sympathetic reactivity is blunted during typical and complex walking tasks in persons with chronic pain. Additionally, blunted sympathetic reactivity is associated with CAN brain structure, with direction of association dependent on brain region. These results support the idea that chronic pain may negatively impact typical autonomic responses needed for walking performance via its potential impact on the brain.