Biology subjects

Bottenhorn, K. L.

Publications and source records attributed to Bottenhorn, K. L..

At least 19 recordsLinked to original sources

bioRxiv2026

Dual ecological-cultural pathways of sociocultural environment and resting state functional connectivity among Hispanic adolescents in the ABCD Study

Hispanic Americans face persistent health disparities rooted in complex sociocultural and bioecodevelopmental dynamics. Identifying early neurodevelopmental trajectories that confer risk or resilience during adolescence is critical for developing targeted health equity interventions. Grounded in the NIMHD Research Framework and bioecodevelopmental theory, data from 12- to 14-year-old Hispanic adolescents in the Adolescent Brain Cognitive Development (ABCD) Study were analyzed (n=236). Partial least squares correlation (PLSC) was used to evaluate multivariate associations between sociocultural measures, spanning individual, family, and community levels, and resting-state functional connectivity (rsFC) networks. Post hoc linear mixed-effects models examined how derived sociocultural-rsFC patterns predicted measures of physical and mental health, linking bioecodevelopmental patterns to adolescent well-being. PLSC revealed dual community- and family-level neural pathways of biological embedding, diverging from traditional nested bioecodevelopmental assumptions. The community pathway linked child opportunity and neighborhood disadvantage to connectivity across Cingulo-Opercular, Default, Dorsal Attention, Visual Networks. This community-rsFC profile was associated with lower respiratory functioning, reflecting an allostatic load marker of environmental stress. The family pathway linked caregiver ethnic identity and heritage acculturation to Default, Ventral Attention, Sensorimotor-Mouth, and Visual Networks connectivity, suggesting that the family system shapes neural systems underlying social attunement and identity formation. Structural community factors and familial culture impose distinct neurobiological demands on the adolescent connectome among Hispanic youth. Findings highlight respiratory health as a biological marker of environmental adversity and underscore the necessity of structural and culturally sustaining interventions to promote health equity among Hispanic youth.

neuroscience↗

bioRxiv2026

Cortical microarchitecture supports preadolescent functional brain network connectivity

A century ago, Brodmann suggested that local cortical microarchitecture dictates function, yet modern structure-function mapping overwhelmingly focuses on white matter macroarchitecture. Here, we reframe structure-function coupling by linking gray matter microarchitecture and macroscale connectomics, demonstrating how gray matter cellular and neurite density are linked to functional network organization in preadolescents. By applying partial least squares correlation to cortical microarchitecture (i.e., cellular and neurite density) estimates from diffusion MRI and network connectivity estimates from functional MRI, in 6,320 children ages 9-11 years from the U.S.-wide Adolescent Brain Cognitive Development (ABCD) Study, we identified several principles of structure-function coupling. First, we found that functional connectivity is associated with one dominant and global pattern of cellular density differences explaining nearly 80% of shared variance, but by several patterns of neurite density differences. Second, we found similar gradients of sensorimotor network connectivity related to this dominant cellular density pattern and the secondary, rostro-caudal neurite density pattern (explaining 17% of shared variance). Third, we found a profile of attention network connectivity associated with the primary neurite density pattern (44% of shared variance) and the secondary, rostro-caudal cellular density pattern (5% of shared variance). Altogether, this work suggests that cellular density (i.e., neuronal cell bodies, support cells) across cortex largely supports a sensorimotor network connectivity gradient. Conversely, there are several connectivity-related patterns of neurite density (i.e., axons, dendrites) across cortex, providing a glimpse into how local neurite connectivity may differentially support long-range functional connectivity of sensorimotor networks and attention networks.

neuroscience↗

bioRxiv2026

Developmental Differences in White Matter Microarchitecture in Youth with ADHD: Longitudinal Findings from the ABCD Study

BackgroundAttention-deficit/hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder and is a risk factor for later brain disorders. Here, we characterize the relationship between ADHD status and white matter cellularity across development and examine associations with medication, using a novel biophysical diffusion MRI model in youth aged 9 to 14 years. Methods: The ABCD Study(R) is a longitudinal cohort study with three biennial waves of brain MRI collection. Twenty-seven white matter tracts were delineated using multi-shell diffusion-weighted imaging (DWI) and tractography. Intracellular isotropic (RNI) and directional (RND) diffusion were quantified using the Restriction Spectrum Imaging (RSI) model. Longitudinal linear mixed-effect models characterize the effects of ADHD status and medication use on white matter cellularity across three waves. Results: By wave: 9,426 participants at baseline (mean [SD] age: 9.92 [0.63] years; 48.7% Female; 12.2% with ADHD), 6745 participants at 2-year (11.95 [0.65] years; 46.8% Female; 11.3% with ADHD), and 2,483 participants at 4-year (14.07 [0.69] years; 46.0% Female; 11.8% with ADHD). ADHD was associated with decreased RNI in 20 tracts at age 9, with evidence of developmental trajectory differences suggesting attenuation over early adolescence. We found enduring ADHD-associated decreases in RND of 16 tracts spanning ages 9 to 14 years, with methylphenidate effects on 2 tracts. Low-motion sensitivity analyses confirmed robust RNI findings, but not RND findings. ConclusionsADHD was associated with reductions in isotropic diffusion in white matter tracts, and possibly with complementary reductions in directional diffusion of select tracts. Isotropic diffusion findings suggest atypical glial cellularity in white matter during late childhood.

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bioRxiv2026

Prefrontal working memory activity partially mediates link between enriched neighborhood environments and episodic memory among 9-13-year-olds

BackgroundEnriched environments support neurodevelopment. The pathways linking enrichment to cognitive processes such as episodic memory among youth remain unclear. This study examined whether brain function and structure in episodic memory-implicated neurocircuitry mediate the relationship between neighborhood enrichment and episodic memory performance. MethodsWe analyzed data from the Adolescent Brain Cognitive Development Study (n = 9,028) at two timepoints (baseline: 9-11-years-old and two-year follow-up: 11-13-years-old). Neighborhood enrichment was estimated at the childs primary residential address proxied by the Child Opportunity Index 2.0 (COI). Episodic memory was assessed using the Picture Sequence Memory Test (PSMT). A multimodal neuroimaging approach examined task-based working memory-related functional activity, brain volume, and resting-state intrinsic activity in 26 bilateral brain regions, segmented using the Desikan-Killiany atlas, implicated in episodic memory. Following FDR-corrected linear mixed effects models, controlling for sociodemographic, neuroimaging factors, and site-related variability, two sets of mediation analyses were conducted per time point. ResultsGreater neighborhood enrichment (i.e., higher COI scores) was directly associated with better episodic memory, prefrontal cortex (PFC) task-based functional activity, and larger PFC and medial temporal lobe volume across timepoints. PFC task-based functional activity, but not brain volume or intrinsic activity, partially mediated these relationships. Specifically, PFC task-activity in the left and right caudal and rostral middle frontal gyri, and left pars opercularis, accounted for [~]2-7% of the mediated effect. ConclusionOur findings contribute to a rapidly growing body of literature linking environmental influences on neurocognitive outcomes during development. Given childhood and adolescence represent sensitive periods for neurodevelopment, interventions aimed at increasing neighborhood access to enriching experiences such as educational opportunities, cognitively stimulating activities, and social support may have lasting benefits for neurocognitive development.

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bioRxiv2025

ADHD Medications and Preadolescent Brain Structure: Patterns of Cortical Attenuation from the ABCD Study

Attention-deficit/hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder in the U.S., and the stimulant and nonstimulant medications used to treat ADHD are among the most widely prescribed treatments in youth. Stimulants--including amphetamine-based (AMP) and methylphenidate-based (MPH) medications--act primarily on dopaminergic and noradrenergic systems, while nonstimulants (NS) more selectively target noradrenergic pathways. Although pharmacotherapy is the most clinically effective treatment, its neurostructural effects remain poorly understood. Leveraging the Adolescent Brain Cognitive Development* Study (ABCD Study(R)), we used a machine learning approach to identify neuroanatomical targets of medications, followed by linear mixed-effects modeling to estimate the effects of ADHD status and medication class (AMP, MPH, NS) on cortical thickness, surface area, and cortical and subcortical volumes. ADHD was not associated with statistically significant differences; however, a consistent pattern emerged in which AMP and MPH effects attenuated ADHD effects, suggesting that stimulant medications may attenuate ADHD-related cortical patterns. NS medications showed a similar, albeit weaker, effect pattern. Notably, AMP and/or MPH use was associated with significant effects in the right entorhinal cortex and the right banks of the superior temporal sulcus, potentially reflecting overcompensatory effects, as well as in the left posterior cingulate, possibly indicating de novo medication-related differences.

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bioRxiv2025

Sources of outdoor air pollution exposure and child brain network development across the United States

Ambient fine particulate matter (PM2.5) pollution is a heterogeneous mixture of chemicals with documented neurotoxic effects. Developmental neuroimaging literature has linked childhood PM2.5 exposure to alterations in brain morphology, microarchitecture, and function, with implications for cognition and psychopathology. However, the extant literature remains largely cross-sectional and often considers PM2.5 a single pollutant, rather than a heterogeneous mixture of chemicals from different sources. This work addresses these gaps by leveraging estimates of exposure to six PM2.5 sources derived from positive matrix factorization, and longitudinal neuroimaging data from a large, geographically-diverse sample of Adolescent Brain Cognitive Development Study youth (N = 6,291) from across the United States (U.S.). To identify exposure-related differences in brain function and assess their geographical generalizability, we used a predictive modeling approach to assess both differences in functional brain network connectivity during childhood (9-11 years of age) and changes in functional brain network connectivity during the transition to adolescence (9-13 years of age) related to PM2.5 exposure. Childhood PM2.5 exposure from traffic emissions and industrial/residual fuel burning were linked to mixed patterns of both stronger and weaker connectivity of sensorimotor networks at ages 9-11 years. Conversely, childhood exposures to secondary pollutants (i.e., ammonium sulfates, nitrates) were linked to largely stronger connectivity of brain networks underlying higher-order cognition that decreased over the following two years. However, these patterns of exposure-related functional connectivity identified in youth across the U.S. better represented youth living in the northeast as compared to youth living in the west. Altogether, this work provides insights into the neurotoxicity of outdoor air pollution exposure in developing sensory and motor systems and potential for biomarkers of eventual psychopathology.

neuroscience↗

bioRxiv2025

Hippocampal functional connectivity changes associated with active and lecture-based physics learning

Introductory university physics courses often face the dual challenge of introducing students to new physics concepts while also addressing their preconceived notions that conflict with scientific principles. Active learning pedagogical approaches, which employ constructivist principles and emphasize active participation in the learning process, have been shown to be effective in teaching complex physics concepts. However, while the behavioral effects of constructivist methodologies are largely understood, the neurobiological underpinnings that facilitate this process remain unclear. Using functional magnetic resonance imaging (fMRI), we assessed students enrolled in either an active learning or lecture-based physics course before and after a 15-week semester of learning and examined changes in hippocampal whole-brain connectivity. We focused on the hippocampus given its critical role in learning and memory. Our findings revealed that hippocampal connectivity with brain regions in the frontal and parietal lobes decreased over time, regardless of instructional approach. Results also indicated that active learning students exhibited increased hippocampal connectivity with parietal, cerebellar, and frontal regions, reflecting experiential learning based on constructivist principles, whereas lecture-based students exhibited increased hippocampal connectivity with the fusiform gyrus, suggesting learning through passive observation. Our findings demonstrate that while some aspects of hippocampal functional connectivity may decrease over time, active vs. passive learning may preferentially enhance hippocampal connectivity during physics learning.

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bioRxiv2025

Estimating individual-level changes in functional brain connectivity and correspondence with topology changes

With the rise of precision medicine and large neuroimaging datasets, measuring brain changes on an individual level becomes more possible and more important. However, functional connectivity has some mathematical and conceptual quirks that make estimating individual-level changes more complicated than, for example, estimating structural brain changes. Here, we compared six different change scores, i.e., metrics for quantifying change in functional connectivity, using a large sample with two time points, roughly 2 years apart, of low-motion data from the ABCD Study (N=2,719, ages 9-13 years). First, we compared distributions and potential interpretations of each metric. Then, we assessed how well different metrics captured topology change estimates by comparing them to individual-level changes in clustering coefficient, betweenness centrality, and network strength. As multivariate metrics may be more reliable than single connections and researchers often interpret connectivity changes in topological terms, this offers additional insight into the implications of change score choice. Overall, our analyses revealed widely different distributions between change scores that conferred vastly different results and interpretations of functional connectivity changes between time points. Thus, we provide recommendations for each change score and its optimal (or suboptimal) use cases, depending on the population, study design, and research question.

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bioRxiv2025

Ambient Pollution Components and Sources Associated with Hippocampal Architecture and Memory in Pre-Adolescents

BackgroundAmbient air pollution poses significant risks to brain health. The hippocampus may be particularly vulnerable, yet the extent to which it is impacted in children remains unclear. MethodsUsing partial least squares correlation, we cross-sectionally analyzed air pollution, brain, and cognitive data from the Adolescent Brain Cognitive Development Study to examine how multi-pollutant exposure influences hippocampal structure and memory in 9-11-year-olds (n= 7,940). Annual average air pollution exposures included PM2.5 (total mass, 15 components, and 6 source factors), NO2, and 8-hour maximum O3. Hippocampal outcomes included microstructure measured using Restriction Spectrum Imaging and hippocampus longitudinal-axis (i.e., head, body, tail) volumes. We examined hippocampal-dependent list-learning using the Rey Auditory Verbal Learning Test. Models were adjusted for demographic, socioeconomic, and neuroimaging factors. FindingsPM2.5 total mass was associated with hippocampal microstructure, but not long-axis volume or list-learning ability. Component and source analyses provided greater specificity: higher bromine, sulfate, and vanadium exposure was related to microstructure (72% shared variance), while higher copper and zinc exposure correlated with smaller left head and right body and tail volumes (75% shared variance). Source models implicated biomass burning and traffic pollution in microstructure (61% and 32% shared variance) and industrial and traffic sources in smaller hippocampal volumes (77% shared variance). Higher exposure to several components were also linked to poorer list-learning (67% shared variance). DiscussionCo-exposure to multiple pollutants is linked to differences in hippocampal structure and memory, showing that associations are driven not only by PM2.5 total mass but also by specific components and sources. This evidence underscores the necessity of targeting source-specific (e.g., biomass burning, traffic, and industrial emissions) and constituent components (e.g., metals) of air pollution during critical developmental windows to safeguard brain health.

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bioRxiv2025

Habenula alterations in resting state functional connectivity among autistic individuals

BackgroundThe reward-based theoretical framework of autism suggests that altered reward circuitry contributes to core symptoms. Recent prior research has revealed autism-related structural alterations in the habenula, a small epithalamic structure associated with motivation and emotion; however, potential alterations in functional connectivity (FC) remain unexplored. MethodsAnatomical and resting state functional magnetic resonance imaging (rs-fMRI) data were accessed for 1,479 participants (N=661 autism; agem: 16.68{+/-}8.23 years) in the Autism Brain Imaging Data Exchange (ABIDE). To investigate habenula alterations, we conducted a whole-brain resting state FC analysis using manually delineated subject-specific seeds, followed by regression analyses to explore age and brain-behavior interactions. ResultsAcross the entire sample, extensive habenula connectivity was observed within the midbrain dopaminergic reward system. Compared to neurotypical (NT) controls, autistic participants exhibited significantly increased habenular connectivity with the bilateral middle and superior temporal gyri. From childhood to early adulthood, autistic adolescents displayed an accelerated developmental habenula FC trajectory than NTs with the cingulate gyrus. Between groups, habenula hyperconnectivity was inversely associated with behavioral scores for social motivation and communication. ConclusionsThis study provides novel evidence of habenula connectivity alterations in autism, highlighting atypical FC with sensory processing regions. Further findings suggest that habenula circuitry develops differently among autistic adolescents, with links between habenula hyperconnectivity and social behaviors. Taken together, these results contribute to emerging evidence that the dopaminergic reward system may play a critical role in the pathophysiology of autism.

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bioRxiv2025

Dynamic reconfiguration of brain coactivation states associated with active and lecture-based learning of university physics

Academic institutions are increasingly adopting active learning methods to enhance educational outcomes. Using functional magnetic resonance imaging (fMRI), we investigated neurobiological differences between active learning and traditional lecture-based approaches in university physics education. Undergraduate students enrolled in an introductory physics course underwent an fMRI session before and after a 15-week semester. Coactivation pattern (CAP) analysis was used to examine the temporal dynamics of brain states across different cognitive contexts, including physics conceptual reasoning, physics knowledge retrieval, and rest. CAP results identified seven distinct brain states, with contributions from frontoparietal, somatomotor, and visuospatial networks. Among active learning students, physics learning was associated with increased engagement of a somatomotor network, supporting an embodied cognition framework, while lecture-based students demonstrated stronger engagement of a visuospatial network, consistent with observational learning. These findings suggest significant neural restructuring over a semester of physics learning, with different instructional approaches preferentially modulating distinct patterns of brain dynamics.

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bioRxiv2024

Hormonal contraceptive intake during adolescence and cortical brain measures in the ABCD Study

Adolescence is a critical period in human development, marked by rapid changes in brain structure and function, influenced, in part, by sex steroids. During adolescence, females may initiate the use of hormonal contraception, which suppresses ovarian production of estradiol and progesterone. Here, we examined the impact of hormonal contraceptive use on adolescent brain structures using magnetic resonance imaging data from 1,234 individuals from the ABCD Study (average age = 14 years). We investigated differences in cortical thickness, surface area, and volume in hormonal contraceptive-users compared to non-users. Statistically significant differences were observed in several regions, and differences in cortical thickness of the paracentral gyrus survived familywise error correction. Estradiol, testosterone and DHEA levels negatively correlated with cortical thickness, surface area, and volume across both hormonal contraceptive-users and non-users only at an uncorrected threshold. These findings highlight the need to further study longitudinal effects of hormonal contraceptives and endogenous hormone changes on brain development in the ABCD Study and related datasets as these data become available.

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bioRxiv2024

Idiosyncrasy and generalizability of contraceptive- and hormone-related functional connectomes across the menstrual cycle

Neuroendocrinology has received little attention in human neuroscience research, resulting in a dearth of knowledge surrounding potent and dynamic modulators of cognition and behavior, as well as brain structure and function. This work addresses one such phenomenon by studying functional connectomics related to ovarian hormone fluctuations throughout the adult menstrual cycle. To do so, we used functional magnetic resonance imaging (fMRI) and hormone assessments from two dense, longitudinal datasets to assess variations in functional connectivity with respect to endogenous and exogenous endocrine factors throughout the menstrual cycle. First, we replicated prior findings that common, group-level and individual specific factors have similar relative contributions to functional brain network organization. Second, we found widespread connectivity related to hormonal contraceptive (HC) use, in addition to sparser estradiol- and progesterone-related connectivity, and differential generalizability of these subnetworks that suggests progestin-specific impacts on functional connectivity in HC users. These results provide novel insight into within-individual changes in brain organization across the menstrual cycle and the extent to which these changes are shared between individuals, illuminating understudied phenomena in reproductive health and important information for all neuroimaging studies that include participants who menstruate. Author SummaryEndocrine modulation of brain function across the menstrual cycle is poorly understood. Human neuroimaging research on the menstrual cycle has long relied on group- and or coarse, within-individual cycle stage-differences, overlooking considerable individual differences in brain organization, the menstrual cycle, and hormone concentrations. Here, we take a multi-dataset approach to identify idiosyncratic contraceptive- and hormone-related functional connectivity from within-individual neuroendocrine dynamics and then test the generalizability of this connectivity to other individuals. In doing so, we identified idiosyncratic hormone-responsive subnetworks that are somewhat generalizable to other individuals, though this generalizability is complicated by hormonal contraceptive use, potentially reflecting differential connectivity between contraceptive formulations. Thus, this work illuminates individual similarities and differences in neuroendocrine dynamics across the menstrual cycle.

neuroscience↗

bioRxiv2024

More similarity than difference: comparison of within- and between-sex variance in early adolescent brain structure

BackgroundAdolescent neuroimaging studies of sex differences in the human brain predominantly examine mean differences between males and females. This focus on between-groups differences without probing relative distributions and similarities may contribute to both conflation and overestimation of sex differences and sexual dimorphism in the developing human brain. MethodsWe aimed to characterize the variance in brain macro-and micro-structure in early adolescence as it pertains to sex at birth using a large sample of 9-11 year-olds from the Adolescent Brain Cognitive Development (ABCD) Study (N=7,723). Specifically, for global and regional estimates of gray and white matter volume, cortical thickness, and white matter microstructure (i.e., fractional anisotropy and mean diffusivity), we examined: within-and between-sex variance, overlap between male and female distributions, inhomogeneity of variance via the Fligner-Killeen test, and an analysis of similarities (ANOSIM). For completeness, we examined these sex differences using both uncorrected (raw) brain estimates and residualized brain estimates after using mixed-effects modeling to account for age, pubertal development, socioeconomic status, race, ethnicity, MRI scanner manufacturer, and total brain volume, where applicable. ResultsThe overlap between male and female distributions was universally greater than the difference (overlap coefficient range: 0.585 -0.985) and the ratio of within-sex and between-sex differences was similar (ANOSIM R range: -0.001 -0.117). All cortical and subcortical volumes showed significant inhomogeneity of variance, whereas a minority of brain regions showed significant sex differences in variance for cortical thickness, white matter volume, fractional anisotropy, and mean diffusivity. Inhomogeneity of variance was reduced after accounting for other sources of variance. Overlap coefficients were larger and ANOSIM R values were smaller for residualized outcomes, indicating greater within-and smaller between-sex differences once accounting for other covariates. ConclusionsReported sex differences in early adolescent human brain structure may be driven by disparities in variance, rather than binary, sex-based phenotypes. Contrary to the popular view of the brain as sexually dimorphic, we found more similarity than difference between sexes in all global and regional measurements of brain structure examined. This study builds upon previous findings illustrating the importance of considering variance when examining sex differences in brain structure. HighlightsO_LIHigh male/female overlap is ubiquitous across all brain features in early adolescence C_LIO_LIMale variance exceeded female variance for global and regional brain volumes C_LIO_LIBetween-and within-sex differences were similar in magnitude for all features C_LI Plain English SummaryBrain imaging research has consistently revealed differences between males and females in the shape and size of adolescent brains. Studies usually compare the average male brain to the average female brain. However, brain structure varies greatly among individuals, even within the same sex. Without looking at both the variability within people of the same sex, and the degree of similarity between the sexes, it is unclear if separating adolescent brains into male and female categories will help us understand brain development. In this study, we looked at the overlap in brain structure among male and female youths (ages 9 to 11 years). We also compared variability between sexes and within each sex. Overall, we found that, there was more similarity than difference between male and female brains. The difference between any given male and any given female was similar to the difference between two individuals of the same sex. These findings suggest that, despite some small average differences, the brains of early adolescent males and females are more alike than different at ages 9-11 years.

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bioRxiv2024

Spatiotemporal patterns in cortical development: Age, puberty, and individual variability from 9 to 13 years of age

Humans and nonhuman primate studies suggest that timing and tempo of cortical development varies neuroanatomically along a sensorimotor-to-association (S-A) axis. Prior human studies have reported a principal S-A axis across various modalities, but largely rely on cross-sectional samples with wide age-ranges. Here, we investigate developmental changes and individual variability in cortical organization along the S-A axis between the ages of 9-13 years using a large, longitudinal sample (N = 2487-3747, 46-50% female) from the Adolescent Brain Cognitive Development Study (ABCD Study(R)). This work assesses multiple aspects of neurodevelopment indexed by changes in cortical thickness, cortical microarchitecture, and resting-state functional fluctuations. First, we evaluated S-A organization in age-related changes and, then, computed individual-level S-A alignment in brain changes and assessing differences therein due to age, sex, and puberty. Varying degrees of linear and quadratic age-related brain changes were identified along the S-A axis. Yet, these patterns of cortical development were overshadowed by considerable individual variability in S-A alignment. Even within individuals, there was little correspondence between S-A patterning across the different aspects of neurodevelopment investigated (i.e., cortical morphology, microarchitecture, function). Some of the individual variation in developmental patterning of cortical morphology and microarchitecture was explained by age, sex, and pubertal development. Altogether, this work contextualizes prior findings that regional age differences do progress along an S-A axis at a group level, while highlighting broad variation in developmental change between individuals and between aspects of cortical development, in part due to sex and puberty. Significance StatementUnderstanding normative patterns of adolescent brain change, and individual variability therein, is crucial for disentangling healthy and abnormal development. We used longitudinal human neuroimaging data to study several aspects of neurodevelopment during early adolescence and assessed their organization along a sensorimotor-to-association (S-A) axis across the cerebral cortex. Age differences in brain changes were linear and curvilinear along this S-A axis. However, individual-level sensorimotor-association alignment varied considerably, driven in part by differences in age, sex, and pubertal development.

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bioRxiv2024

Dense Investigation of Variability in Affect (DIVA): A Neuroimaging Study of Premenopausal Female Participants

The rise of large neuroimaging datasets and multi-dataset mega-analyses brings the power to study interindividual differences in brain structure and function on a heretofore unseen scale. However, unknown and poorly characterized intra-individual variability continues to undermine the detection of robust brain-behavior associations and, ultimately, our understanding of the brain on the whole. Womens and reproductive health underlie variability in more than half of the population, but have long been overlooked in the study of both inter- and intra-individual differences in the brain. To this end, the Dense Investigation of Variability in Affect (DIVA) Study was designed to study intra-individual variability in the brain and behavior across the menstrual cycle in a small cohort of premenopausal female participants. The DIVA Study acquired weekly actigraphy, self-report, biospecimen, and both functional and structural magnetic resonance imaging data with concurrent peripheral physiological recordings. These data facilitate the study of several common sources of variability in the brain and behavior: the menstrual cycle and ovarian hormones, sleep, stress, exercise, and exogenous sources of hemodynamic variability.

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bioRxiv2023

Air pollution from biomass burning disrupts early adolescent cortical microarchitecture development

Exposure to outdoor particulate matter (PM2.5) represents a ubiquitous threat to human health, and particularly the neurotoxic effects of PM2.5 from multiple sources may disrupt neurodevelopment. Studies addressing neurodevelopmental implications of PM exposure have been limited by small, geographically limited samples and largely focus either on macroscale cortical morphology or postmortem histological staining and total PM mass. Here, we leverage residentially assigned exposure to six, data-driven sources of PM2.5 and neuroimaging data from the longitudinal Adolescent Brain Cognitive Development Study (ABCD Study(R)), collected from 21 different recruitment sites across the United States. To contribute an interpretable and actionable assessment of the role of air pollution in the developing brain, we identified alterations in cortical microstructure development associated with exposure to specific sources of PM2.5 using multivariate, partial least squares analyses. Specifically, average annual exposure (i.e., at ages 8-10 years) to PM2.5 from biomass burning was related to differences in neurite development across the cortex between 9 and 13 years of age. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=132 SRC="FIGDIR/small/563430v3_ufig1.gif" ALT="Figure 1"> View larger version (60K): org.highwire.dtl.DTLVardef@eed0c1org.highwire.dtl.DTLVardef@cb3dbeorg.highwire.dtl.DTLVardef@1428660org.highwire.dtl.DTLVardef@8440aa_HPS_FORMAT_FIGEXP M_FIG C_FIG

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bioRxiv2023

Meta-analytic decoding of the cortical gradient of functional connectivity

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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