94 research outputs found
Leveraging Individual Differences to Gain Insight Into the Developing Functional Connectome
No full textStudying individual differences in functional connectomes provides a powerful framework to tackle questions in developmental human neuroscience. In this work, I use such a framework to study a multitude of factors, ranging from data quality control issues to building predictive models of clinically relevant phenotypes in neurodiverse youth. The first empirical chapter explores how factors related to the reliability of functional connections, namely the amount of scan data, in-scanner head motion, and the spatiotemporal resolution of data acquisition affect the detection of individual differences. In the second empirical chapter, I demonstrate that individual differences in connectomes are stable in developing populations. That is, connectivity signatures specific to an individual are retained across years, even in periods of rapid brain development. In the third empirical chapter, I describe the successful implementation of a desensitization protocol that allowed the collection of high-quality, low-motion data necessary to detect and leverage individual differences in a neurodiverse sample. In the fourth empirical chapter, I use the data obtained through the work of chapter three to demonstrate that robust connectome-based signatures of sustained attention can be generated in neurodiverse youth. I go on to show such a signature generalizes to predict attention in neurotypical young adults, of special interest given developmental differences in the youth and adult samples. In sum, this body of work suggests the power of focusing on individual differences in functional connectivity research and provides a foundation for linking such differences to clinically-actionable behaviors in developing populations
sj-pdf-1-jcb-10.1177_0271678X221082016 - Supplemental material for The lateral entorhinal cortex is a hub for local and global dysfunction in early Alzheimer’s disease states
No full textSupplemental material, sj-pdf-1-jcb-10.1177_0271678X221082016 for The lateral entorhinal cortex is a hub for local and global dysfunction in early Alzheimer’s disease states by Francesca Mandino, Ling Yun Yeow, Renzhe Bi, Lee Sejin, Han Gyu Bae, Seung Hyun Baek, Chun-Yao Lee, Hasan Mohammad, Corey Horien, Chai Lean Teoh, Jasinda H Lee, Mitchell KP Lai, Sangyong Jung, Yu Fu, Malini Olivo, John Gigg and Joanes Grandjean in Journal of Cerebral Blood Flow & Metabolism</p
The individual functional connectome is unique and stable over months to years
No full textAbstractFunctional connectomes computed from fMRI provide a means to characterize individual differences in the patterns of BOLD synchronization across regions of the entire brain. Using four resting-state fMRI datasets with a wide range of ages, we show that individual differences of the functional connectome are stable across three months to three years. Medial frontal and frontoparietal networks appear to be both unique and stable, resulting in high ID rates, as did a combination of these two networks. We conduct analyses demonstrating that these results are not driven by head motion. We also show that the edges demonstrating the most individualized features tend to connect nodes in the frontal and parietal cortices, while edges contributing the least tend to connect cross-hemispheric homologs. Our results demonstrate that the functional connectome is stable across years and is not an idiosyncratic aspect of a specific dataset, but rather reflects stable individual differences in the functional connectivity of the brain.Research highlightsWhole-brain functional connectivity profiles obtained from four resting-state fMRI datasets are unique and stable across 3 months-3 years in adolescents, young adults, and older adultsMedial frontal and frontoparietal networks tended to be both unique and stableIndividual edges in the frontal and parietal cortices tended to be most discriminative of individual subjects</jats:sec
Brain handedness associations depend on how and when handedness is measured
No full textAbstract Hand preference is ubiquitous, intuitive, and often simplified to right- or left-handed. Accordingly, differences between right- and left-handed individuals in the brain have been established. Nevertheless, considering handedness as a binarized construct fails to capture the variability of brain-handedness associations across different domains or activities. Further, hand-use changes across generations (e.g., letter writing vs. texting) such that individuals of different ages live in different environments. As a result, brain-handedness associations may depend on how and when handedness is measured. We used two large datasets, the Human Connectome Project-Development (HCP-D; n = 465; age = 5–21 years) and Human Connectome Project-Aging (HCP-A; n = 368; age = 36–100 years), to investigate generational differences in brain-handedness associations. Nine items from the Edinburgh Handedness Inventory were associated with resting-state functional connectomes. We show that brain-handedness associations differed across the two cohorts. Moreover, these differences depended on the way handedness was measured. Given that brain-handedness associations differ across handedness measures and datasets, we caution against a one-size-fits-all approach to neuroimaging studies of this complex trait
Considering factors affecting the connectome-based identification process: Comment on Waller et al.
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