Biology subjects

Cardenas-Iniguez, C.

Publications and source records attributed to Cardenas-Iniguez, C..

14 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

Air Pollution, Early Adversity, and Amygdala: Environmental Correlates of Psychopathology in Preadolescents

Early life adversity (ELA) and ambient fine particulate matter (PM2.5) are hypothesized to be environmental risk factors for altered brain structure and psychopathology, but their unique and interactive effects in childhood remain unclear. This study examines the interactive associations of ELA and annual average residential PM2.5 exposure (total mass and 15 components) on total amygdala and basolateral amygdala subregion volumes and psychopathology symptoms in a subset of children (N=3,601, 45% assigned female at birth, 9-10 years) from the Adolescent Brain Cognitive Development Study. Linear mixed-effects models, adjusting for sociodemographic factors, co-pollutants, and neuroimaging covariates, showed that ELA was associated with greater bifactor model-defined general, specific internalizing, and specific externalizing symptoms of psychopathology. PM2.5 moderated ELA associations with specific externalizing symptoms, with greater symptoms in those exposed to higher ELA and higher PM2.5 exposures. Among youth with higher ELA, smaller basolateral paralaminar volumes were linked to greater general and specific externalizing symptoms. These findings underscore the importance of considering psychosocial and physical environmental co-exposures when identifying children at risk for psychopathology.

neuroscience↗

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

Patterns of brain-wide associations reflect socioeconomics

Previous brain-wide association studies (BWAS) cross-sectionally linked a specific behavioral trait, most commonly IQ or psychopathology, to variation in brain function or structure. Here, we expanded the focus of BWAS from effect sizes to interpretability and generalizability by mapping 649 variables to brain function and structure. We compared the resultant BWAS maps to other types of brain data to annotate the BWAS patterns. Socioeconomic status (SES) -- not IQ or psychopathology -- showed the strongest associations with both resting-state functional connectivity (RSFC) and cortical thickness in the Adolescent Brain Cognitive Development (ABCD) Study. A principal exposome brain pattern, anchored to sensory and motor cortex, captured 34% of the variance across all BWAS maps. This exposome pattern was strongly correlated with the SES and IQ BWAS maps and non-BWAS maps of sleep (EEG), norepinephrine (PET), and stimulants (drug trial), but not cognitive activation maps (task fMRI). Adjusting for SES, reduced brain-IQ associations by 40%. Brain with IQ associations did not generalize, as they could no longer be detected in subsamples drawn from only higher SES backgrounds, while brain with SES associations remained strong in higher-IQ-only subsamples. These findings reveal SES as the principal axis of population-level brain variation, possibly stemming from the sleep deprivation and heightened stress associated with lower SES, since socioeconomics can only indirectly affect the brain.

neuroscience↗

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

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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bioRxiv2024

Outdoor Air Pollution Relates to Amygdala Subregion Volume and Apportionment in Early Adolescents

BackgroundOutdoor air pollution is associated with an increased risk for psychopathology. Although the neural mechanisms remain unclear, air pollutants may impact mental health by altering limbic brain regions, such as the amygdala. Here, we examine the association between ambient air pollution exposure and amygdala subregion volumes in 9-10-year-olds. MethodsCross-sectional Adolescent Brain Cognitive DevelopmentSM (ABCD) Study(R) data from 4,473 participants (55.4% male) were leveraged. Air pollution was estimated for each participants primary residential address. Using the probabilistic CIT168 atlas, we quantified total amygdala and 9 distinct subregion volumes from T1- and T2-weighted images. First, we examined how criteria pollutants (i.e., fine particulate matter [PM2.5], nitrogen dioxide, ground-level ozone) and 15 PM2.5 components related with total amygdala volumes using linear mixed-effect (LME) regression. Next, partial least squares correlation (PLSC) analyses were implemented to identify relationships between co-exposure to criteria pollutants as well as PM2.5 components and amygdala subregion volumes. We also conducted complementary analyses to assess subregion apportionment using amygdala relative volume fractions (RVFs). ResultsNo significant associations were detected between pollutants and total amygdala volumes. Using PLSC, one latent dimension (LD) (52% variance explained) captured a positive association between calcium and several basolateral subregions. LDs were also identified for amygdala RVFs (ranging from 30% to 82% variance explained), with PM2.5 and component co-exposure associated with increases in lateral, but decreases in medial and central, RVFs. ConclusionsFine particulate and its components are linked with distinct amygdala differences, potentially playing a role in risk for adolescent mental health problems. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=123 SRC="FIGDIR/small/617429v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@e9f2ecorg.highwire.dtl.DTLVardef@14b677forg.highwire.dtl.DTLVardef@177f8daorg.highwire.dtl.DTLVardef@172dc0c_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2022

Profiling intra- and inter-individual differences in child and adolescent brain development

As we move toward population-level developmental neuroscience, understanding intra- and inter-individual variability in brain maturation and sources of neurodevelopmental heterogeneity becomes paramount. Large-scale, longitudinal neuroimaging studies have uncovered group-level neurodevelopmental trajectories, and while recent work has begun to untangle intra- and inter-individual differences, they remain largely unclear. Here, we aim to quantify both intra- and inter-individual variability across facets of neurodevelopment across early adolescence (ages 8.92 to 13.83 years) in the Adolescent Brain Cognitive Development (ABCD) Study and examine inter-individual variability as a function of age, sex, and puberty. Our results provide novel insight into differences in annualized percent change in macrostructure, microstructure, and functional brain development from ages 9-13 years old. These findings reveal moderate age-related intra-individual change, but age-related differences in inter-individual variability only in a few measures of cortical macro- and microstructure development. Greater inter-individual variability in brain development were seen in mid-pubertal individuals, except for a few aspects of white matter development that were more variable between prepubertal individuals in some tracts. Although both sexes contributed to inter-individual differences in macrostructure and functional development in a few regions of the brain, we found limited support for hypotheses regarding greater male-than-female variability. This work highlights pockets of individual variability across facets of early adolescent brain development, while also highlighting regional differences in heterogeneity to facilitate future investigations in quantifying and probing nuances in normative development, and deviations therefrom.

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bioRxiv2021

Scale Invariance in fNIRS as a Measurement of Cognitive Load

Scale invariant neural dynamics are a relatively new but effective means of measuring changes in brain states as a result of varied cognitive load and task difficulty. This study is the first to test whether scale invariance (as measured by the Hurst exponent, H) can be used with functional near-infrared spectroscopy (fNIRS) to quantify cognitive load. We analyzed H extracted from the fNIRS time series while participants completed an N-back working memory task. Consistent with what has been demonstrated in fMRI, the current results showed that scale-invariance analysis significantly differentiated between task and rest periods as calculated from both oxy- (HbO) and deoxy-hemoglobin (HbR) concentration changes. Results from both channel-averaged H and a multivariate partial least squares approach (Task PLS) demonstrated higher H during the 1-back task than the 2-back task. These results were stronger for H derived from HbR than from HbO. As fNIRS is relatively portable and robust to motion-related artifacts, these preliminary results shed light on the promising future of measuring cognitive load in real life settings. Author SummaryScale invariance reflects a pattern of self-similarity (or fractalness) across a time series of brain data. In human neuroscience studies using EEG and fMRI, higher scale invariance has been associated with individuals being in a state of minimal cognitive effort or while performing a relatively easy task compared to doing something more challenging. Functional near-infrared spectroscopy (fNIRS) is a flexible neuroimaging technique that can be used in naturalistic settings and measures the same underlying biological signal as fMRI. We expected that, if scale invariant brain states are indeed robust indicators of cognitive load or task difficulty, we should be able to replicate previous findings in fNIRS. Consistent with this hypothesis, we find that more scale invariant brain states are indeed associated with less cognitively demanding and more restful brain states in fNIRS data. This finding opens up a wide array of potential applications for monitoring cognitive load and fatigue in real-life settings, such as during driving, learning in schools, or during interpersonal interactions.

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bioRxiv2021

A Scale-Free Gradient of Cognitive Resource Disruptions in Childhood Psychopathology

The Hurst exponent (H) isolated in fractal analyses of neuroimaging time-series is implicated broadly in cognition. The connection between H and the mathematics of criticality makes it a candidate measure of individual differences in cognitive resource allocation. Relationships between H and multiple mental disorders have been detected, suggesting that H is transdiagnostically associated with psychopathology. Here, we demonstrate a gradient of decreased H with increased general psychopathology and attention-deficit/hyperactivity extracted factor scores during a working memory task which predicts concurrent and future working memory performance in 1,839 children. This gradient defines psychological and functional axes which indicate that psychopathology is associated with an imbalance in resource allocation between fronto-parietal and sensory-motor regions, driven by reduced resource allocation to fonto-parietal regions. This suggests the hypothesis that impaired cognitive function associated with psychopathology follows from a reduced cognitive resource pool and a reduction in resources allocated to the task at hand.

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bioRxiv2021

Electrophysiological correlates of perceptual prediction error are attenuated in dyslexia

A perceptual adaptation deficit often accompanies reading difficulty in dyslexia, manifesting in poor perceptual learning of consistent stimuli and reduced neurophysiological adaptation to stimulus repetition. However, it is not known how adaptation deficits relate to differences in feedforward or feedback processes in the brain. Here we used electroencephalography (EEG) to interrogate the feedforward and feedback contributions to neural adaptation as adults with and without dyslexia viewed pairs of faces and words in a paradigm that manipulated whether there was a high probability of stimulus repetition versus a high probability of stimulus change. We measured three neural dependent variables: expectation (the difference between prestimulus EEG power with and without the expectation of stimulus repetition), feedforward repetition (the difference between event-related potentials (ERPs) evoked by an expected change and an unexpected repetition), and feedback-mediated prediction error (the difference between ERPs evoked by an unexpected change and an expected repetition). Expectation significantly modulated prestimulus theta- and alpha-band EEG in both groups. Unexpected repetitions of words, but not faces, also led to significant feedforward repetition effects in the ERPs of both groups. However, neural prediction error when an unexpected change occurred instead of an expected repetition was significantly weaker in dyslexia than the control group for both faces and words. These results suggest that the neural and perceptual adaptation deficits observed in dyslexia reflect the failure to effectively integrate perceptual predictions with feedforward sensory processing. In addition to reducing perceptual efficiency, the attenuation of neural prediction error signals would also be deleterious to the wide range of perceptual and procedural learning abilities that are critical for developing accurate and fluent reading skills.

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bioRxiv2020

Load-Dependent Relationships between Frontal fNIRS Activity and Performance: A Data-Driven PLS Approach

Neuroimaging research frequently demonstrates load-dependent activation in the prefrontal cortex during working memory tasks such as the N-back. Most of this work has been conducted in fMRI, but functional near-infrared spectroscopy (fNIRS) is gaining traction as a less invasive and more flexible alternative to measuring cortical hemodynamics. Few fNIRS studies, however, have examined how working memory load-dependent changes in brain hemodynamics relate to performance. The current study employs a newly developed and robust statistical analysis of task-based fNIRS data in a large sample, and demonstrates the utility of data-driven, multivariate analyses to link brain activation and behavior in this modality. Seventy participants completed a standard N-back task with three N-back levels (N = 1, 2, 3) while fNIRS data were collected from frontal and parietal cortex. Overall, participants showed reliably greater fronto-parietal activation for the 2-back versus the 1-back task, suggesting fronto-parietal fNIRS measurements are sensitive to differences in cognitive load. The results for 3-back were much less consistent, potentially due to poor behavioral performance in the 3-back task. To address this, a multivariate analysis (behavioral partial least squares, PLS) was conducted to examine the interaction between fNIRS activation and performance at each N-back level. Results of the PLS analysis demonstrated differences in the relationship between accuracy and change in the deoxyhemoglobin fNIRS signal as a function of N-back level in four mid-frontal channels. Specifically, greater reductions in deoxyhemoglobin (i.e., more activation) were positively related to performance on the 3-back task, unrelated to accuracy in the 2-back task, and negatively associated with accuracy in the 1-back task. This pattern of results suggests that the metabolic demands correlated with neural activity required for high levels of accuracy vary as a consequence of task difficulty/cognitive load, whereby more automaticity during the 1-back task (less mid-frontal activity) predicted superior performance on this relatively easy task, and successful engagement of this mid-frontal region was required for high accuracy on a more difficult and cognitively demanding 3-back task. In summary, we show that fNIRS activity can track working memory load and can uncover significant associations between brain activity and performance, thus opening the door for this modality to be used in more wide-spread applications.

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bioRxiv2020

Criterion Validity and Relationships between Alternative Hierarchical Dimensional Models of General and Specific Psychopathology

Psychopathology can be viewed as a hierarchy of correlated dimensions. Many studies have supported this conceptualization, but they have used alternative statistical models with differing interpretations. In bifactor models, every symptom loads on both the general factor and one specific factor (e.g., internalizing), which partitions the total explained variance in each symptom between these orthogonal factors. In second-order models, symptoms load on one of several correlated lower-order factors. These lower-order factors load on a second-order general factor, which is defined by the variance shared by the lower-order factors. Thus, the factors in second-order models are not orthogonal. Choosing between these valid statistical models depends on the hypothesis being tested. Because bifactor models define orthogonal phenotypes with distinct sources of variance, they are optimal for studies of shared and unique associations of the dimensions of psychopathology with external variables putatively relevant to etiology and mechanisms. Concerns have been raised, however, about the reliability of the orthogonal specific factors in bifactor models. We evaluated this concern using parent symptom ratings of 9-10 year olds in the ABCD Study. Psychometric indices indicated that all factors in both bifactor and second-order models exhibited at least adequate construct reliability and estimated replicability. The factors defined in bifactor and second-order models were highly to moderately correlated across models, but have different interpretations. All factors in both models demonstrated significant associations with external criterion variables of theoretical and clinical importance, but the interpretation of such associations in second-order models was ambiguous due to shared variance among factors. General Scientific SummarySome investigators have proposed that viewing the correlated symptoms of psychopathology as a hierarchy in which all symptoms are related to both a general (p) factor of psychopathology and a more specific factor will make it easier to distinguish potential risk factors and mechanisms that are nonspecifically related to all forms of psychopathology versus those that are associated with specific dimensions of psychopathology. Parent ratings of child psychopathology items from the Adolescent Brain Cognitive Development (ABCD) Study were analyzed using two alternative statistical models of the proposed hierarchy. All factors of psychopathology defined in both bifactor and second-order models demonstrated adequate psychometric properties and criterion validity, but associations of psychopathology factors with external variables were more easily interpreted in bifactor than in second-order models.

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