Biology subjects

Ramduny, J.

Publications and source records attributed to Ramduny, J..

8 recordsLinked to original sources

bioRxiv2026

Area-level context and functional brain organization across the lifespan

The neighborhoods children grow up in are associated with cognitive and mental health outcomes across the lifespan. Yet how neighborhood-level factors are quantified, and how they relate to large-scale functional brain connectivity, remains an emerging area of investigation. This scoping review synthesizes empirical evidence on associations between area-level factors and resting-state functional brain connectivity and network organization. We included studies assessing resting-state fMRI functional connectivity or rs-fMRI-derived intrinsic activity in relation to validated area-level deprivation indices guided by Trinidad et al.s (2022) inventory, the Opportunity Atlas, or geocoded crime exposure from the Uniform Crime Reporting program. Of the 28 studies meeting inclusion criteria, the evidence base was unevenly distributed across the lifespan; 25 of 28 (89.3%) examined perinatal, childhood, or adolescent samples, while only one examined adults exclusively. The literature was also methodologically non-independent, over half drew on the Adolescent Brain and Cognitive Development (ABCD) Study, and the Area Deprivation Index was the most commonly used measure (k = 16, 57.1%). Therefore, apparent convergence partly reflects shared data and instruments rather than independent replication. Where directions could be compared, higher area-level disadvantage was associated predominantly with lower within-network connectivity in association and control systems and higher connectivity in somatomotor systems, with several findings attenuating once area-level exposure was isolated from household socioeconomic status. Geographic resolution varied but was rarely justified. Progress will require greater theoretical intentionality in selecting area-level measures, transparent justification of geographic resolution, treatment of dataset and measure non-independence, and investment in understudied developmental periods and non-US contexts.

neuroscience↗

bioRxiv2026

Distinct associations between multimodal brain measures and psychopathology domains predict adolescent functioning

Adolescent psychopathology is partly rooted in measurable disruptions across key neural networks, yet the field still lacks an integrated, multimodal understanding of these brain-behavior links. Here, we examined how structural, microstructural, and functional measures across corticostriatal, corticolimbic, and executive control networks relate to psychopathology domains and explored how these associations predicted future psychosocial functioning. We used data from the Adolescent Brain Cognitive DevelopmentSM Study (n=5,408) and ran a regularized canonical correlation analysis to identify distinct modes of covariation between multiple brain measures and psychopathology domains when youth were 13-14 years old. The resulting canonical brain and psychopathology scores were used to predict school-related impairment one year later. First, higher diffusivity and decreased activation during a reward task across all three networks as well as lower corticostriatal surface area were related to higher broad psychopathology. Second, lower corticolimbic diffusivity, executive control volume and surface area, and cortical thickness across all three networks as well as higher corticostriatal and corticolimbic volumes were related to higher anxiety but lower externalizing. For the first mode, higher psychopathology scores predicted more school-related impairment one year later. For the second mode, higher brain and higher psychopathology scores predicted less school-related impairment one year later. Identifying how specific neural measures align with psychopathology domains, as well as how both forecast reallilworld functioning, advances the conceptualization of adolescent mental health. This approach clarifies which levels of analysis provide distinct versus shared information about youth functioning and highlights potential mechanisms that may inform future targets for change.

neuroscience↗

bioRxiv2024

Integrating multi-system environmental factors to predict brain and behavior in adolescents

ObjectiveEnvironmental factors have long been shown to influence brain structure and adolescent psychopathology. However, almost no research has included environmental factors spanning micro-to-macro-systems, brain structure, and psychopathology in an integrated framework. Here, we assessed the ways and degree to which multi-system environmental factors during late childhood predict subcortical volume and psychopathology during early adolescence. MethodWe used the baseline and 2-year follow-up data from the Adolescent Brain Cognitive DevelopmentSM Study (N = 2,766). A Bayesian latent profile analysis was applied to obtain distinct multi-system environmental profiles during late childhood. The profiles were used in a path analysis to predict their direct and indirect effects on subcortical volume and psychopathology during early adolescence. ResultsBayesian latent profile analysis revealed nine environmental profiles. Two distinct profiles predicted greater externalizing problems in adolescents: (i) adversity across, family, school, and neighborhood systems and (ii) family conflict and low school involvement. In contrast, a profile of family and neighborhood affluence predicted fewer externalizing difficulties. Further, family and neighborhood affluence predicted higher subcortical volume, which in turn, predicted fewer externalizing problems; whereas, family economic and neighborhood adversity predicted lower subcortical volume, which in turn, predicted greater externalizing difficulties. ConclusionWe captured direct and indirect influences of environmental factors across multiple systems on externalizing psychopathology. Specifying the equifinal pathways to externalizing psychopathology serves to provide an evidence base for establishing different types of interventions based on the needs and risk profiles of youth. Diversity and Inclusion StatementThe current study is part of the ongoing Adolescent Brain Cognitive DevelopmentSM Study (ABCD Study(R)) for which youth are recruited from elementary schools in the United States that are informed by gender, race, ethnicity, socioeconomic status, and urbanicity. The ABCD Study(R) aims to recruit youth longitudinally by sampling the sociodemographic makeup of the US population. Two of the authors self-identifies as a member of one or more historically underrepresented racial and/or ethnic groups in science. One of the authors identifies as a part of an underrepresented gender group in science. The authors also are representative of the communities for which data was collected and contributed to design, analysis, and/or interpretation of the work. Finally, every effort was made to cite the work of authors from underrepresented and minoritized groups in academic research.

neuroscience↗

bioRxiv2024

Increasing the representation of minoritized youth for inclusive and reproducible brain-behavior associations

Population neuroscience datasets allow researchers to estimate reliable effect sizes for brain-behavior associations because of their large sample sizes. However, these datasets undergo strict quality control to mitigate sources of noise, such as head motion. This practice often excludes a disproportionate number of minoritized individuals. We employ motion-ordering and motion-ordering+resampling (bagging) to test if these methods preserve functional MRI (fMRI) data in the Adolescent Brain Cognitive Development Study (N=5,733). Black and Hispanic youth exhibited excess head motion relative to data collected from White youth, and were discarded disproportionately when using conventional approaches. Both methods retained more than 99% of Black and Hispanic youth. They produced reproducible brain-behavior associations across low-/high-motion racial/ethnic groups based on motion-limited fMRI data. The motion-ordering and bagging methods are two feasible approaches that can enhance sample representation for testing brain-behavior associations and fulfill the promise of consortia datasets to produce generalizable effect sizes across diverse populations.

neuroscience↗

bioRxiv2024

Using fingerprinting as a testbed for strategies to improve reproducibility of functional connectivity

Reproducible functional connectivity-based biomarkers have remained elusive despite the promise of deeply phenotyped consortia. An important component of reproducibility is reliability over repeated measures, often measured by the intraclass correlation coefficient (ICC). Here, we test the use of functional connectome fingerprinting as a way to select pre- and post-processing parameters. We hypothesized that whichever parameters yielded the best fingerprint accuracies would also improve the ICC across scans. Using five datasets from the Consortium for Replicability and Reproducibility, we found that higher identification accuracies were achieved when using: (I) global signal regression; (II) finer brain parcellations; (III) cortical regions compared to subcortical and cerebellar structures; (IV) medial frontal and frontoparietal networks relative to the whole-brain; (V) discriminative edges; (VI) longer scan duration; and (VII) lower sample size. We observed that the ICC was consistently "poor" across the five datasets even with the application of two optimal fingerprint-informed pipelines. The fingerprint-informed pipelines may enable comparison, benchmarking, and adjudication of functional connectivity-based analysis pipelines or novel analytic approaches, as a means to enhance their reproducibility in heterogeneous populations. Key PointsO_LIConnectome-based fingerprinting can provide a useful testbed for reproducible functional connectivity analysis pipelines. C_LIO_LIFingerprint-informed pipelines offer an intuitive and less resource intensive way to select data pre-/post-processing parameters for improving the reproducibility of the functional connectome. C_LIO_LIConnectome-based fingerprinting offers an alternative approach to test-retest reliability. C_LI

neuroscience↗

bioRxiv2024

Data rescue in high-motion youth cohorts for robust and reproducible brain-behavior relationships

Recognition of the detrimental impact of participant motion on functional connectivity measures has led to the adoption of increasingly stringent quality control standards to minimize potential motion artifacts. These stringent standards can lead to the exclusion of many participants, creating a tension with a countervailing requirement for large sample sizes that can provide adequate statistical power, particularly for brain-behavior association studies. Here, we test and validate two techniques aimed at mitigating the impact of head motion on functional connectivity estimates, and show that these techniques enable the retention of a substantial proportion of participants who would otherwise be excluded based on motion criteria, such as a minimum mean framewise displacement (FD) threshold. Specifically, we first show that functional connectomes computed using time series data that have been ordered according to motion (i.e., framewise displacement -- FD) and (1) subsetted to include the lowest-motion time points ("motion ordered") or (2) subsetted and resampled ("bagged") are reproducible, in that they enable the successful identification of an individual from a group using functional connectome fingerprinting. Second, we demonstrate that motion-ordered and bagged functional connectomes yield robust brain-behavior associations, which, when examined as a function of sample size, are comparable to those obtained using the standard full time series. Finally, we show that the utility of both approaches lies in maximizing participant inclusivity by allowing for the retention of high-motion participants that would otherwise be discarded. Given equivalent performance of the two approaches across these tests of reproducibility, validity, and utility, we conclude by recommending motion-ordering to enable data rescue, maximize inclusivity, and address the need for adequately powered samples in functional connectivity research, while maintaining stringent data quality standards. While our findings were reproducible across different head motion thresholds and edges in the functional connectome, we outline possibilities for further validation and assessment of generalization using other behavioral phenotypes and consortia datasets.

neuroscience↗

bioRxiv2021

Right fronto-parietal networks mediate the neurocognitive benefits of enriched environments.

Exposure to enriched environments (EE) throughout a lifetime, providing so called reserve, protects against cognitive decline in later years. It has been hypothesised that high levels of alertness necessitated by EE might strengthen the right fronto-parietal networks (FPN) to facilitate this neurocognitive resilience. We have previously shown that EE offset age-related deficits in selective attention by preserving grey matter within right fronto-parietal regions. Here, using neurite orientation dispersion and density imaging (NODDI), we examined the relationship between EE, microstructural properties of fronto-parietal white matter association pathways (three branches of the superior longitudinal fasciculus, SLF), structural brain health (atrophy), and attention (alertness, orienting and executive control) in a group of older adults. We show that EE is associated with a lower orientation dispersion index (ODI) within the right SLF1 which in turn mediates the relationship between EE and alertness, as well as grey- and white-matter atrophy. This suggests that EE may induce white matter plasticity (and prevent age-related dispersion of axons) within the right FPN to facilitate the preservation of neurocognitive health in later years.

neuroscience↗

bioRxiv2021

The Association Between Poor Sleep and Accelerated Brain Ageing

The ageing brain undergoes widespread gray (GM) and white matter (WM) degeneration. But numerous studies indicate large heterogeneity in the age-related brain changes, which can be attributed to modifiable lifestyle factors, including sleep. Inadequate sleep has been previously linked to GM atrophy and WM changes. However, the reported findings are highly inconsistent. By contrast to previous research independently characterizing patterns of either the GM or the WM changes, we used here linked independent component analysis (FLICA) to examine covariation in GM and WM in a group of older adults. Next, we employed a novel technique to estimate the brain age delta (i.e. difference between chronological and apparent brain age assessed using neuroimaging data) and study its associations with sleep quality and sleep fragmentation, hypothesizing that poor sleep accelerates brain ageing. FLICA revealed a number of multimodal (including both GM and WM) neuroimaging components, associated with age, but also with sleep quality and sleep fragmentation. Brain age delta estimates were highly sensitive in detecting the effects of sleep problems on the ageing brain. Specifically, we show significant associations between brain age delta and poor sleep quality, suggesting two years deviation above the chronological age. Our findings indicate that sleep problems in healthy older adults should be considered a risk factor for accelerated brain ageing.

neuroscience↗