Biology subjects

Hanson, J. L.

Publications and source records attributed to Hanson, J. L..

6 recordsLinked to original sources

bioRxiv2025

Neuroanatomy Reflects Individual Variability In Impulsivity in Youth

Individual differences in neural circuits underlying emotional regulation, motivation, and decision-making are implicated in many psychiatric illnesses. Interindividual variability in these circuits may manifest, at least in part, as individual differences in impulsivity at both normative and clinically significant levels. Impulsivity reflects a tendency towards rapid, unplanned reactions to internal or external stimuli without considering potential negative consequences coupled with difficulty inhibiting responses. Here, we use multivariate brain-based predictive models to explore the neural bases of impulsivity across multiple behavioral scales, neuroanatomical features (cortical thickness, surface area, and gray matter volume), and sexes (females and males) in a large sample of youth from the Adolescent Brain Cognitive Development (ABCD) Study at baseline (n=9,099) and two-year follow-up (n=6,432). Impulsivity is significantly associated with neuroanatomical variability, and these associations vary across behavioral scales and neuroanatomical features. Impulsivity broadly maps onto cortical thickness in dispersed regions (e.g., inferior frontal, lateral occipital, superior frontal, entorhinal), as well as surface area and gray matter volume in specific medial (e.g., parahippocampal, cingulate) and polar (e.g., frontal and temporal) territories. Importantly, while many relationships are stable across sexes and time points, others are sex-specific and dynamic. These results highlight the complexity of the relationships between neuroanatomy and impulsivity across scales, features, sexes, and time points in youth. These findings suggest that neuroanatomy, in combination with other biological and environmental factors, reflects a key driver of individual differences in impulsivity in youth. As such, neuroanatomical markers may help identify youth at increased risk for developing impulsivity-related illnesses. Furthermore, this work emphasizes the importance of adopting a multidimensional and sex-specific approach in neuroimaging and behavioral research.

neuroscience↗

bioRxiv2025

Inhibitory and disinhibitory VIP IN-mediated circuits in neocortex

Cortical GABAergic interneurons (INs) expressing the neuropeptide vasoactive-intestinal peptide (VIP) predominantly function by inhibiting dendritic-targeting somatostatin (SST) expressing INs, thereby disinhibiting pyramidal cells (PCs) and facilitating cortical circuit plasticity. VIP INs are a molecularly heterogeneous group, but the physiological significance of this diversity is unclear at present. Here, we have characterized the functional diversity of VIP INs in the primary somatosensory cortex (vS1) using intersectional genetic approaches. We found that VIP INs are comprised of four primary populations that exhibit different laminar distributions, axonal and dendritic arbors, intrinsic electrophysiological properties, and efferent connectivity. Furthermore, we observe that these populations are differentially activated by long-range inputs, and display distinct responses to neuromodulation by endocannabinoids, acetylcholine and noradrenaline. Stimulation of VIP IN subpopulations in vivo results in differential effects on the cortical network, thus providing evidence for specialized modes of VIP IN-mediated regulation of PC activity during cortical information processing.

neuroscience↗

bioRxiv2023

Impact of Socioeconomic Status on Amygdala and Hippocampus Subdivisions in Children and Adolescents

Socioeconomic status (SES) in childhood can impact behavioral and brain development. Past work has consistently focused on the amygdala and hippocampus, two brain areas critical for emotion, memory, and learning. While there are SES differences in total amygdala and hippocampal volumes, there are many unanswered questions in this domain connected to neurobiological specificity and whether these effects vary by participant age or sex. To address these gaps, we combined multiple large neuroimaging datasets of children and adolescents with information about neurobiology and SES (N=2,765). We examined subdivisions of the amygdala and hippocampus, derived from Freesurfer, using linear mixed effects models. Higher SES was associated with larger volumes across all three amygdala subdivisions examined, the superficial cortical division, basolateral complex, and centromedial region. Within the hippocampus, SES was specifically related to volumes in the head, with no significant associations for the body or tail. Contrary to our hypotheses, we found no significant interactions between SES and participant age or sex after correcting for multiple comparisons, suggesting these associations were relatively consistent across the developmental period examined (ages 5-18) and similar for males and females. These results fill in important gaps regarding the neurobiological specificity of SES effects, demonstrating associations across functionally distinct subdivisions of these critical brain structures.

neuroscience↗

bioRxiv2021

Lower neural value signaling in the prefrontal cortex is related to childhood family income and depressive symptomatology during adolescence

Lower family income during childhood is related to increased rates of adolescent depression, though the specific mechanisms are poorly understood. Evidence suggests that individuals with depression demonstrate hypoactivation in brain regions involved in reward learning and decision-making processes (e.g., portions of the prefrontal cortex). Separately, lower family income has been associated with neural alterations in similar regions. We examined associations between family income, depression, and brain activity during a reward learning and decision-making fMRI task in a sample of adolescents (full n=94; usable n=78; mean age=15.4 years). We identified neural regions representing 1) expected value (EV), the learned subjective value of an object, and 2) prediction error, the difference between EV and the actual outcome received. Regions of interest related to reward learning were examined in connection to childhood family income and parent-reported adolescent depressive symptoms. As hypothesized, lower activity in the subgenual anterior cingulate (sACC) for EV in response to approach stimuli was associated with lower childhood family income, as well as greater symptoms of depression measured one-year after the neuroimaging session. These results are consistent with the hypothesis that lower early family income leads to disruptions in reward and decision-making brain circuitry, which leads to adolescent depression.

neuroscience↗

bioRxiv2019

Variations in Structural MRI Quality Impact Measures of Brain Anatomy: Relations with Age

Subject motion can introduce noise into neuroimaging data and result in biased estimations of brain structure. In-scanner motion can compromise data quality in a number of ways and varies widely across developmental and clinical populations. However, quantification of structural image quality is often limited to proxy or indirect measures gathered from functional scans; this may be missing true differences related to these potential artifacts. In this study, we take advantage of novel informatic tools, the CAT12 toolbox, to more directly measure image quality from T1-weighted images to understand if these measures of image quality: 1) relate to rigorous quality-control checks visually completed by human raters; 2) are associated with sociodemographic variables of interest; 3) influence regional estimates of cortical surface area, cortical thickness, and subcortical volumes from the commonly-used Freesurfer tool suite. We leverage public-access data that includes a community-based sample of children and adolescents, spanning a large age-range (N=388; ages 5-21). Interestingly, even after visually inspecting our data, we find image quality significantly impacts derived cortical surface area, cortical thickness, and subcortical volumes from multiple regions across the brain ([~]23.4% of all areas investigated). We believe these results are important for research groups completing structural MRI studies using Freesurfer or other morphometric tools. As such, future studies should consider using measures of image quality to minimize the influence of this potential confound in group comparisons or studies focused on individual differences.

neuroscience↗

bioRxiv2017

Integrative Structural Brain Network Analysis In Diffusion Tensor Imaging

In diffusion tensor imaging, structural connectivity between brain regions is often measured by the number of white matter fiber tracts connecting them. Other features such as the length of tracts or fractional anisotropy (FA) are also used in measuring the strength of connectivity. In this study, we investigated the effects of incorporating the number of tracts, the tract length and FA-values into the connectivity model. Using various node-degree based graph theory features, the three connectivity models are compared. The methods are applied in characterizing structural networks between normal controls and maltreated children, who experienced maltreatment while living in post-institutional settings before being adopted by families in the US.

neuroscience↗