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101. In vivo T1 mapping of neonatal brain tissue at 64 mT.

Author

Padormo, Francesco, Cawley, Paul, Dillon, Louise, Hughes, Emer, Almalbis, Jennifer, Robinson, Joanna, Maggioni, Alessandra, Botella, Miguel De La Fuente, Cromb, Dan, Price, Anthony, Arlinghaus, Lori, Pitts, John, Luo, Tianrui, Zhang, Dingtian, Deoni, Sean C. L., Williams, Steve, Malik, Shaihan, O′Muircheartaigh, Jonathan, Counsell, Serena J., and Rutherford, Mary

Subjects
BRAIN mapping, GRAY matter (Nerve tissue), WHITE matter (Nerve tissue), NEURAL development, TISSUES
Abstract

Purpose: Ultralow‐field (ULF) point‐of‐care MRI systems allow image acquisition without interrupting medical provision, with neonatal clinical care being an important potential application. The ability to measure neonatal brain tissue T1 is a key enabling technology for subsequent structural image contrast optimization, as well as being a potential biomarker for brain development. Here we describe an optimized strategy for neonatal T1 mapping at ULF. Methods: Examinations were performed on a 64‐mT portable MRI system. A phantom validation experiment was performed, and a total of 33 in vivo exams were acquired from 28 neonates with postmenstrual age ranging from 31+4 to 49+0 weeks. Multiple inversion‐recovery turbo spin‐echo sequences were acquired with differing inversion and repetition times. An analysis pipeline incorporating inter‐sequence motion correction generated proton density and T1 maps. Regions of interest were placed in the cerebral deep gray matter, frontal white matter, and cerebellum. Weighted linear regression was used to predict T1 as a function of postmenstrual age. Results: Reduction of T1 with postmenstrual age is observed in all measured brain tissue; the change in T1 per week and 95% confidence intervals is given by dT1 = −21 ms/week [−25, −16] (cerebellum), dT1 = −14 ms/week [−18, −10] (deep gray matter), and dT1 = −35 ms/week [−45, −25] (white matter). Conclusion: Neonatal T1 values at ULF are shorter than those previously described at standard clinical field strengths, but longer than those of adults at ULF. T1 reduces with postmenstrual age and is therefore a candidate biomarker for perinatal brain development. [ABSTRACT FROM AUTHOR]

Published
2023
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107. Youth Well-being During the COVID-19 Pandemic

Author

Blackwell, Courtney K., primary, Mansolf, Maxwell, additional, Sherlock, Phillip, additional, Ganiban, Jody, additional, Hofheimer, Julie A., additional, Barone, Charles J., additional, Bekelman, Traci A., additional, Blair, Clancy, additional, Cella, David, additional, Collazo, Shaina, additional, Croen, Lisa A., additional, Deoni, Sean, additional, Elliott, Amy J., additional, Ferrara, Assiamira, additional, Fry, Rebecca C., additional, Gershon, Richard, additional, Herbstman, Julie B., additional, Karagas, Margaret R., additional, LeWinn, Kaja Z., additional, Margolis, Amy, additional, Miller, Rachel L., additional, O’Shea, T. Michael, additional, Porucznik, Christina A., additional, and Wright, Rosalind J., additional

Published
2022
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109. Additional file 1 of Gestational diabetes mellitus, prenatal maternal depression, and risk for postpartum depression: an Environmental influences on Child Health Outcomes (ECHO) Study

Author

Shuffrey, Lauren C., Lucchini, Maristella, Morales, Santiago, Sania, Ayesha, Hockett, Christine, Barrett, Emily, Carroll, Kecia N., Cioffi, Camille C., Dabelea, Dana, Deoni, Sean, Dunlop, Anne L., Deutsch, Arielle, Fifer, William P., Firestein, Morgan R., Hedderson, Monique M., Jacobson, Melanie, Kelly, Rachel S., Kerver, Jean M., Mason, W. Alex, Mirzakhani, Hooman, O’Connor, Thomas G., Trasande, Leonardo, Weiss, Scott, Wright, Rosalind, Zhu, Yeyi, Crum, Rosa M., Lee, Seonjoo, Elliott, Amy J., and Monk, Catherine

Abstract

Additional file 1.

Published
2022
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110. Unsupervised data-driven stratification of mentalizing heterogeneity in autism

Author

Lombardo, Michael V., Lai, Meng-Chuan, Auyeung, Bonnie, Holt, Rosemary J., Allison, Carrie, Smith, Paula, Chakrabarti, Bhismadev, Ruigrok, Amber N. V., Suckling, John, Bullmore, Edward T., Bailey, Anthony J., Baron-Cohen, Simon, Bolton, Patrick F., Bullmore, Edward T., Carrington, Sarah, Catani, Marco, Chakrabarti, Bhismadev, Craig, Michael C., Daly, Eileen M., Deoni, Sean C. L., Ecker, Christine, Happé, Francesca, Henty, Julian, Jezzard, Peter, Johnston, Patrick, Jones, Derek K., Lai, Meng-Chuan, Lombardo, Michael V., Madden, Anya, Mullins, Diane, Murphy, Clodagh M., Murphy, Declan G. M., Pasco, Greg, Ruigrok, Amber N. V., Sadek, Susan A., Spain, Debbie, Stewart, Rose, Suckling, John, Wheelwright, Sally J., Williams, Steven C., Ellie Wilson, C., Ecker, Christine, Craig, Michael C., Murphy, Declan G. M., Happé, Francesca, and Baron-Cohen, Simon

Published
2016
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112. Residential MRI: Development of A Mobile Anywhere-Everywhere MRI Lab

Author

Deoni, Sean CL, primary, Medeiros, Paul, additional, Deoni, Alexandra T., additional, Burton, Phoebe, additional, Beauchemin, Jennifer, additional, D’Sa, Viren, additional, Boskamp, Eddy, additional, By, Samantha, additional, McNulty, Chris, additional, Mileski, William, additional, Welch, Brian E., additional, and Huentelman, Matthew, additional

Published
2021
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113. Relationship Between Cortical Gyrification, White Matter Connectivity, and Autism Spectrum Disorder

Author

Ecker, C., Andrews, D., DellʼAcqua, F., Daly, E., Murphy, C., Catani, M., Thiebaut de Schotten, M., Baron-Cohen, S., Lai, M.C., Lombardo, M.V., Bullmore, E.T., Suckling, J., Williams, S., Jones, D.K., Chiocchetti, A., Murphy, D.G.M., Bailey, Anthony J., Baron-Cohen, Simon, Bolton, Patrick F., Bullmore, Edward T., Carrington, Sarah, Catani, Marco, Chakrabarti, Bhismadev, Craig, Michael C., Daly, Eileen M., Deoni, Sean C.L., Ecker, Christine, Happé, Francesca, Henty, Julian, Jezzard, Peter, Johnston, Patrick, Jones, Derek K., Lai, Meng-Chuan, Lombardo, Michael V., Madden, Anya, Mullins, Diane, Murphy, Clodagh M., Murphy, Declan G.M., Pasco, Greg, Ruigrok, Amber N.V., Sadek, Susan A., Spain, Debbie, Stewart, Rose, Suckling, John, Wheelwright, Sally J., Williams, Steven C., and Wilson, C.Ellie

Published
2016
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129. Simultaneous high‐resolution T2‐weighted imaging and quantitative T 2 mapping at low magnetic field strengths using a multiple TE and multi‐orientation acquisition approach.

Author

Deoni, Sean C. L., O'Muircheartaigh, Jonathan, Ljungberg, Emil, Huentelman, Mathew, and Williams, Steven C. R.

Subjects
MAGNETIC flux density, MAGNETIC resonance imaging, INTRACLASS correlation, BRAIN imaging, SPATIAL resolution
Abstract

Purpose: Low magnetic field systems provide an important opportunity to expand MRI to new and diverse clinical and research study populations. However, a fundamental limitation of low field strength systems is the reduced SNR compared to 1.5 or 3T, necessitating compromises in spatial resolution and imaging time. Most often, images are acquired with anisotropic voxels with low through‐plane resolution, which provide acceptable image quality with reasonable scan times, but can impair visualization of subtle pathology. Methods: Here, we describe a super‐resolution approach to reconstruct high‐resolution isotropic T2‐weighted images from a series of low‐resolution anisotropic images acquired in orthogonal orientations. Furthermore, acquiring each image with an incremented TE allows calculations of quantitative T2 images without time penalty. Results: Our approach is demonstrated via phantom and in vivo human brain imaging, with simultaneous 1.5 × 1.5 × 1.5 mm3 T2‐weighted and quantitative T2 maps acquired using a clinically feasible approach that combines three acquisition that require approximately 4‐min each to collect. Calculated T2 values agree with reference multiple TE measures with intraclass correlation values of 0.96 and 0.85 in phantom and in vivo measures, respectively, in line with previously reported brain T2 values at 150 mT, 1.5T, and 3T. Conclusion: Our multi‐orientation and multi‐TE approach is a time‐efficient method for high‐resolution T2‐weighted images for anatomical visualization with simultaneous quantitative T2 imaging for increased sensitivity to tissue microstructure and chemical composition. [ABSTRACT FROM AUTHOR]

Published
2022
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130. Family SES Is Associated with the Gut Microbiome in Infants and Children

Author

Lewis, Candace R., primary, Bonham, Kevin S., additional, McCann, Shelley Hoeft, additional, Volpe, Alexandra R., additional, D’Sa, Viren, additional, Naymik, Marcus, additional, De Both, Matt D., additional, Huentelman, Matthew J., additional, Lemery-Chalfant, Kathryn, additional, Highlander, Sarah K., additional, Deoni, Sean C. L., additional, and Klepac-Ceraj, Vanja, additional

Published
2021
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131. Traveling Slow Oscillations During Sleep: A Marker of Brain Connectivity in Childhood

Author

Kurth, Salome, Riedner, Brady A., Dean, Douglas C., O'Muircheartaigh, Jonathan, Huber, Reto, Jenni, Oskar G., Deoni, Sean C L., LeBourgeois, Monique K., Kurth, Salome, Riedner, Brady A., Dean, Douglas C., O'Muircheartaigh, Jonathan, Huber, Reto, Jenni, Oskar G., Deoni, Sean C L., and LeBourgeois, Monique K.

Abstract

Slow oscillations, a defining characteristic of the nonrapid eye movement sleep electroencephalogram (EEG), proliferate across the scalp in highly reproducible patterns. In adults, the propagation of slow oscillations is a recognized fingerprint of brain connectivity and excitability. In this study, we (1) describe for the first time maturational features of sleep slow oscillation propagation in children (n = 23; 2-13 years) using high-density (hd) EEG and (2) examine associations between sleep slow oscillatory propagation characteristics (ie, distance, traveling speed, cortical involvement) and white matter myelin microstructure as measured with multicomponent Driven Equilibrium Single Pulse Observation of T1 and T2-magnetic resonance imaging (mcDESPOT-MRI). Results showed that with increasing age, slow oscillations propagated across longer distances (average growth of 0.2 cm per year; R(21) = 0.50, p < .05), while traveling speed and cortical involvement (ie, slow oscillation expanse) remained unchanged across childhood. Cortical involvement (R(20) = 0.44) and slow oscillation speed (R(20) = −0.47; both p < .05, corrected for age) were associated with myelin content in the superior longitudinal fascicle, the largest anterior-posterior, intrahemispheric white matter connectivity tract. Furthermore, slow oscillation distance was moderately associated with whole-brain (R(21) = 0.46, p < .05) and interhemispheric myelin content, the latter represented by callosal myelin water fraction (R(21) = 0.54, p < .01, uncorrected). Thus, we demonstrate age-related changes in slow oscillation propagation distance, as well as regional associations between brain activity during sleep and the anatomical connectivity of white matter microstructure. Our findings make an important contribution to knowledge of the brain connectome using a noninvasive and novel analytic approach. These data also have implications for understanding the emergence of neurodevelopmental disorders and the ro

Published
2021

132. Across-night dynamics in traveling sleep slow waves throughout childhood

Author

Schoch, Sarah F., Riedner, Brady A., Deoni, Sean C., Huber, Reto, LeBourgeois, Monique K., Kurth, Salome, Schoch, Sarah F., Riedner, Brady A., Deoni, Sean C., Huber, Reto, LeBourgeois, Monique K., and Kurth, Salome

Abstract

Study Objectives Sleep slow waves behave like traveling waves and are thus a marker for brain connectivity. Across a night of sleep in adults, wave propagation is scaled down, becoming more local. Yet, it is unknown whether slow wave propagation undergoes similar across-night dynamics in childhood—a period of extensive cortical rewiring. Methods High-density electroencephalography (EEG; 128 channels) was recorded during sleep in three groups of healthy children: 2.0-4.9 years (n = 11), 5.0-8.9 years (n = 9) and 9.0-16.9 years (n = 9). Slow wave propagation speed, distance, and cortical involvement were quantified. To characterize across-night dynamics, the 20% most pronounced (highest amplitude) slow waves were subdivided into five time-based quintiles. Results We found indications that slow wave propagation distance decreased across a night of sleep. We observed an interesting interaction of across-night slow wave propagation dynamics with age (p < 0.05). When comparing the first and last quintiles, there was a trend level difference between age groups: 2- to 4.9-year-old children showed an 11.9% across-night decrease in slow wave propagation distance, which was not observed in the older two age groups. Regardless of age, cortical involvement decreased by 10.4%-23.7% across a night of sleep. No across-night changes were observed in slow wave speed. Conclusions Findings provide evidence that signatures of brain connectivity undergo across-night dynamics specific to maturational periods. These results suggest that across-night dynamics in slow wave propagation distance reflect heightened plasticity in underlying cerebral networks specific to developmental periods.

Published
2021

139. Brain Differences in Infants at Differential Genetic Risk for Late-Onset Alzheimer Disease: A Cross-sectional Imaging Study

Author

Dean, Douglas C., III, Jerskey, Beth A., Chen, Kewei, Protas, Hillary, Thiyyagura, Pradeep, Roontiva, Auttawat, OʼMuircheartaigh, Jonathan, Dirks, Holly, Waskiewicz, Nicole, Lehman, Katie, Siniard, Ashley L., Turk, Mari N., Hua, Xue, Madsen, Sarah K., Thompson, Paul M., Fleisher, Adam S., Huentelman, Matthew J., Deoni, Sean C. L., and Reiman, Eric M.

Published
2014
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143. Intrinsic excitation-inhibition imbalance affects medial prefrontal cortex differently in autistic men versus women

Author

Trakoshis, Stavros, Martínez-Cañada, Pablo, Rocchi, Federico, Canella, Carola, You, Wonsang, Chakrabarti, Bhismadev, Ruigrok, Amber NV, Bullmore, Edward T, Suckling, John, Markicevic, Marija, Zerbi, Valerio, MRC AIMS Consortium, Baron-Cohen, Simon, Gozzi, Alessandro, Lai, Meng-Chuan, Panzeri, Stefano, Bailey, Anthony J, Bolton, Patrick F, Carrington, Sarah, Catani, Marco, Craig, Michael C, Daly, Eileen M, Deoni, Sean CL, Ecker, Christine, Happé, Francesca, Henty, Julian, Jezzard, Peter, Johnston, Patrick, Jones, Derek K, Lombardo, Michael V, Madden, Anya, Mullins, Diane, Murphy, Clodagh M, Murphy, Declan GM, Pasco, Greg, Sadek, Susan A, Spain, Debbie, Stewart, Rose, Wheelwright, Sally J, Williams, Steven C, Zerbi, Valerio [0000-0001-7984-9565], Gozzi, Alessandro [0000-0002-5731-4137], Panzeri, Stefano [0000-0003-1700-8909], Lombardo, Michael V [0000-0001-6780-8619], and Apollo - University of Cambridge Repository

Subjects
sex/gender, Mouse, fMRI, autism, excitation, heterogeneity, Human Biology and Medicine, behavioral disciplines and activities, inhibition, Research Article, Neuroscience, Human
Abstract

Excitation-inhibition (E:I) imbalance is theorized as an important pathophysiological mechanism in autism. Autism affects males more frequently than females and sex-related mechanisms (e.g., X-linked genes, androgen hormones) can influence E:I balance. This suggests that E:I imbalance may affect autism differently in males versus females. With a combination of in-silico modeling and in-vivo chemogenetic manipulations in mice, we first show that a time-series metric estimated from fMRI BOLD signal, the Hurst exponent (H), can be an index for underlying change in the synaptic E:I ratio. In autism we find that H is reduced, indicating increased excitation, in the medial prefrontal cortex (MPFC) of autistic males but not females. Increasingly intact MPFC H is also associated with heightened ability to behaviorally camouflage social-communicative difficulties, but only in autistic females. This work suggests that H in BOLD can index synaptic E:I ratio and that E:I imbalance affects autistic males and females differently.

Published
2020
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144. Gut microbial genes are associated with neurocognition and brain development in healthy children

Author

Bonham, Kevin S., Bruchhage, Muriel M. K., Rowland, Sophie, Volpe, Lexie, Dyer, Kellyn, D’Sa, Viren, Huttenhower, Curtis, Deoni, Sean C. L., and Klepac-Ceraj, Vanja

Subjects
digestive, oral, and skin physiology, digestive system
Abstract

Both the brain and microbiome of humans develop rapidly in the first years of life, enabling extensive signaling between the gut and central nervous system (dubbed the “gut-brain axis” 1,2 ). While emerging evidence implicates gut microorganisms and microbiota composition in cognitive outcomes and neurodevelopmental disorders (e.g., autism), the role of the gut microbial metabolism on typical neurodevelopment has not been explored in detail.

Published
2020
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147. Reply to H Wang and M Chichlowski

Author

Sauder, Katherine A., Couzens, Lance, Bailey, Regan L., Hockett, Christine W., Switkowski, Karen M., Lyall, Kristen, Kerver, Jean M., Dabelea, Dana, Maldonado, Luis E., O’Connor, Thomas G., Deoni, Sean CL., Glueck, Deborah H., and Catellier, Diane J.

Published
2023
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