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180 results on '"Craven, Alexander R."'

1. Virtual Ontogeny of Cortical Growth Preceding Mental Illness

Author

Patel, Yash, Shin, Jean, Abé, Christoph, Agartz, Ingrid, Alloza, Clara, Alnæs, Dag, Ambrogi, Sonia, Antonucci, Linda A, Arango, Celso, Arolt, Volker, Auzias, Guillaume, Ayesa-Arriola, Rosa, Banaj, Nerisa, Banaschewski, Tobias, Bandeira, Cibele, Başgöze, Zeynep, Cupertino, Renata Basso, Bau, Claiton HD, Bauer, Jochen, Baumeister, Sarah, Bernardoni, Fabio, Bertolino, Alessandro, Bonnin, Caterina Del Mar, Brandeis, Daniel, Brem, Silvia, Bruggemann, Jason, Bülow, Robin, Bustillo, Juan R, Calderoni, Sara, Calvo, Rosa, Canales-Rodríguez, Erick J, Cannon, Dara M, Carmona, Susanna, Carr, Vaughan J, Catts, Stanley V, Chenji, Sneha, Chew, Qian Hui, Coghill, David, Connolly, Colm G, Conzelmann, Annette, Craven, Alexander R, Crespo-Facorro, Benedicto, Cullen, Kathryn, Dahl, Andreas, Dannlowski, Udo, Davey, Christopher G, Deruelle, Christine, Díaz-Caneja, Covadonga M, Dohm, Katharina, Ehrlich, Stefan, Epstein, Jeffery, Erwin-Grabner, Tracy, Eyler, Lisa T, Fedor, Jennifer, Fitzgerald, Jacqueline, Foran, William, Ford, Judith M, Fortea, Lydia, Fuentes-Claramonte, Paola, Fullerton, Janice, Furlong, Lisa, Gallagher, Louise, Gao, Bingchen, Gao, Si, Goikolea, Jose M, Gotlib, Ian, Goya-Maldonado, Roberto, Grabe, Hans J, Green, Melissa, Grevet, Eugenio H, Groenewold, Nynke A, Grotegerd, Dominik, Gruber, Oliver, Haavik, Jan, Hahn, Tim, Harrison, Ben J, Heindel, Walter, Henskens, Frans, Heslenfeld, Dirk J, Hilland, Eva, Hoekstra, Pieter J, Hohmann, Sarah, Holz, Nathalie, Howells, Fleur M, Ipser, Jonathan C, Jahanshad, Neda, Jakobi, Babette, Jansen, Andreas, Janssen, Joost, Jonassen, Rune, Kaiser, Anna, Kaleda, Vasiliy, Karantonis, James, King, Joseph A, Kircher, Tilo, Kochunov, Peter, Koopowitz, Sheri-Michelle, Landén, Mikael, Landrø, Nils Inge, and Lawrie, Stephen

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Psychology, Neurosciences, Genetics, Mental Health, Serious Mental Illness, Mental Illness, Women's Health, Brain Disorders, Preterm, Low Birth Weight and Health of the Newborn, Pregnancy, Pediatric, Perinatal Period - Conditions Originating in Perinatal Period, Behavioral and Social Science, Prevention, Schizophrenia, 2.1 Biological and endogenous factors, 2.3 Psychological, social and economic factors, Neurological, Reproductive health and childbirth, Mental health, Good Health and Well Being, Attention Deficit Disorder with Hyperactivity, Autism Spectrum Disorder, Bipolar Disorder, Cerebral Cortex, Child, Depressive Disorder, Major, Female, Humans, Infant, Newborn, Magnetic Resonance Imaging, Premature Birth, Cortical growth, Cortical surface area, Mental illness, Neurodevelopment, Neurogenesis, Psychiatric disorders, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Biological sciences, Biomedical and clinical sciences
Abstract

BackgroundMorphology of the human cerebral cortex differs across psychiatric disorders, with neurobiology and developmental origins mostly undetermined. Deviations in the tangential growth of the cerebral cortex during pre/perinatal periods may be reflected in individual variations in cortical surface area later in life.MethodsInterregional profiles of group differences in surface area between cases and controls were generated using T1-weighted magnetic resonance imaging from 27,359 individuals including those with attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, schizophrenia, and high general psychopathology (through the Child Behavior Checklist). Similarity of interregional profiles of group differences in surface area and prenatal cell-specific gene expression was assessed.ResultsAcross the 11 cortical regions, group differences in cortical area for attention-deficit/hyperactivity disorder, schizophrenia, and Child Behavior Checklist were dominant in multimodal association cortices. The same interregional profiles were also associated with interregional profiles of (prenatal) gene expression specific to proliferative cells, namely radial glia and intermediate progenitor cells (greater expression, larger difference), as well as differentiated cells, namely excitatory neurons and endothelial and mural cells (greater expression, smaller difference). Finally, these cell types were implicated in known pre/perinatal risk factors for psychosis. Genes coexpressed with radial glia were enriched with genes implicated in congenital abnormalities, birth weight, hypoxia, and starvation. Genes coexpressed with endothelial and mural genes were enriched with genes associated with maternal hypertension and preterm birth.ConclusionsOur findings support a neurodevelopmental model of vulnerability to mental illness whereby prenatal risk factors acting through cell-specific processes lead to deviations from typical brain development during pregnancy.

Published
2022

2. Neurobiological mechanisms of ECT and TMS treatment in depression: study protocol of a multimodal magnetic resonance investigation

Author

Frid, Leila Marie, Kessler, Ute, Ousdal, Olga Therese, Hammar, Åsa, Haavik, Jan, Riemer, Frank, Hirnstein, Marco, Ersland, Lars, Erchinger, Vera Jane, Ronold, Eivind Haga, Nygaard, Gyrid, Jakobsen, Petter, Craven, Alexander R., Osnes, Berge, Alisauskiene, Renata, Bartsch, Hauke, Le Hellard, Stephanie, Stavrum, Anne-Kristin, Oedegaard, Ketil J., and Oltedal, Leif

Published
2023
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4. Frequency drift in MR spectroscopy at 3T.

Author

Hui, Steve CN, Mikkelsen, Mark, Zöllner, Helge J, Ahluwalia, Vishwadeep, Alcauter, Sarael, Baltusis, Laima, Barany, Deborah A, Barlow, Laura R, Becker, Robert, Berman, Jeffrey I, Berrington, Adam, Bhattacharyya, Pallab K, Blicher, Jakob Udby, Bogner, Wolfgang, Brown, Mark S, Calhoun, Vince D, Castillo, Ryan, Cecil, Kim M, Choi, Yeo Bi, Chu, Winnie CW, Clarke, William T, Craven, Alexander R, Cuypers, Koen, Dacko, Michael, de la Fuente-Sandoval, Camilo, Desmond, Patricia, Domagalik, Aleksandra, Dumont, Julien, Duncan, Niall W, Dydak, Ulrike, Dyke, Katherine, Edmondson, David A, Ende, Gabriele, Ersland, Lars, Evans, C John, Fermin, Alan SR, Ferretti, Antonio, Fillmer, Ariane, Gong, Tao, Greenhouse, Ian, Grist, James T, Gu, Meng, Harris, Ashley D, Hat, Katarzyna, Heba, Stefanie, Heckova, Eva, Hegarty, John P, Heise, Kirstin-Friederike, Honda, Shiori, Jacobson, Aaron, Jansen, Jacobus FA, Jenkins, Christopher W, Johnston, Stephen J, Juchem, Christoph, Kangarlu, Alayar, Kerr, Adam B, Landheer, Karl, Lange, Thomas, Lee, Phil, Levendovszky, Swati Rane, Limperopoulos, Catherine, Liu, Feng, Lloyd, William, Lythgoe, David J, Machizawa, Maro G, MacMillan, Erin L, Maddock, Richard J, Manzhurtsev, Andrei V, Martinez-Gudino, María L, Miller, Jack J, Mirzakhanian, Heline, Moreno-Ortega, Marta, Mullins, Paul G, Nakajima, Shinichiro, Near, Jamie, Noeske, Ralph, Nordhøy, Wibeke, Oeltzschner, Georg, Osorio-Duran, Raul, Otaduy, Maria CG, Pasaye, Erick H, Peeters, Ronald, Peltier, Scott J, Pilatus, Ulrich, Polomac, Nenad, Porges, Eric C, Pradhan, Subechhya, Prisciandaro, James Joseph, Puts, Nicolaas A, Rae, Caroline D, Reyes-Madrigal, Francisco, Roberts, Timothy PL, Robertson, Caroline E, Rosenberg, Jens T, Rotaru, Diana-Georgiana, O'Gorman Tuura, Ruth L, Saleh, Muhammad G, Sandberg, Kristian, Sangill, Ryan, and Schembri, Keith

Subjects
3T, Frequency drift, Magnetic resonance spectroscopy, Multi-site, Multi-vendor, Press, Brain, Data Analysis, Databases, Factual, Humans, Magnetic Resonance Imaging, Magnetic Resonance Spectroscopy, Clinical Research, Biomedical Imaging, Neurology & Neurosurgery, Medical and Health Sciences, Psychology and Cognitive Sciences
Abstract

PurposeHeating of gradient coils and passive shim components is a common cause of instability in the B0 field, especially when gradient intensive sequences are used. The aim of the study was to set a benchmark for typical drift encountered during MR spectroscopy (MRS) to assess the need for real-time field-frequency locking on MRI scanners by comparing field drift data from a large number of sites.MethodA standardized protocol was developed for 80 participating sites using 99 3T MR scanners from 3 major vendors. Phantom water signals were acquired before and after an EPI sequence. The protocol consisted of: minimal preparatory imaging; a short pre-fMRI PRESS; a ten-minute fMRI acquisition; and a long post-fMRI PRESS acquisition. Both pre- and post-fMRI PRESS were non-water suppressed. Real-time frequency stabilization/adjustment was switched off when appropriate. Sixty scanners repeated the protocol for a second dataset. In addition, a three-hour post-fMRI MRS acquisition was performed at one site to observe change of gradient temperature and drift rate. Spectral analysis was performed using MATLAB. Frequency drift in pre-fMRI PRESS data were compared with the first 5:20 minutes and the full 30:00 minutes of data after fMRI. Median (interquartile range) drifts were measured and showed in violin plot. Paired t-tests were performed to compare frequency drift pre- and post-fMRI. A simulated in vivo spectrum was generated using FID-A to visualize the effect of the observed frequency drifts. The simulated spectrum was convolved with the frequency trace for the most extreme cases. Impacts of frequency drifts on NAA and GABA were also simulated as a function of linear drift. Data from the repeated protocol were compared with the corresponding first dataset using Pearson's and intraclass correlation coefficients (ICC).ResultsOf the data collected from 99 scanners, 4 were excluded due to various reasons. Thus, data from 95 scanners were ultimately analyzed. For the first 5:20 min (64 transients), median (interquartile range) drift was 0.44 (1.29) Hz before fMRI and 0.83 (1.29) Hz after. This increased to 3.15 (4.02) Hz for the full 30 min (360 transients) run. Average drift rates were 0.29 Hz/min before fMRI and 0.43 Hz/min after. Paired t-tests indicated that drift increased after fMRI, as expected (p < 0.05). Simulated spectra convolved with the frequency drift showed that the intensity of the NAA singlet was reduced by up to 26%, 44 % and 18% for GE, Philips and Siemens scanners after fMRI, respectively. ICCs indicated good agreement between datasets acquired on separate days. The single site long acquisition showed drift rate was reduced to 0.03 Hz/min approximately three hours after fMRI.DiscussionThis study analyzed frequency drift data from 95 3T MRI scanners. Median levels of drift were relatively low (5-min average under 1 Hz), but the most extreme cases suffered from higher levels of drift. The extent of drift varied across scanners which both linear and nonlinear drifts were observed.

Published
2021

7. Frequency drift in MR spectroscopy at 3T

Author

Hui, Steve C.N., Mikkelsen, Mark, Zöllner, Helge J., Ahluwalia, Vishwadeep, Alcauter, Sarael, Baltusis, Laima, Barany, Deborah A., Barlow, Laura R., Becker, Robert, Berman, Jeffrey I., Berrington, Adam, Bhattacharyya, Pallab K., Blicher, Jakob Udby, Bogner, Wolfgang, Brown, Mark S., Calhoun, Vince D., Castillo, Ryan, Cecil, Kim M., Choi, Yeo Bi, Chu, Winnie C.W., Clarke, William T., Craven, Alexander R., Cuypers, Koen, Dacko, Michael, de la Fuente-Sandoval, Camilo, Desmond, Patricia, Domagalik, Aleksandra, Dumont, Julien, Duncan, Niall W., Dydak, Ulrike, Dyke, Katherine, Edmondson, David A., Ende, Gabriele, Ersland, Lars, Evans, C. John, Fermin, Alan S.R., Ferretti, Antonio, Fillmer, Ariane, Gong, Tao, Greenhouse, Ian, Grist, James T., Gu, Meng, Harris, Ashley D., Hat, Katarzyna, Heba, Stefanie, Heckova, Eva, Hegarty, John P., II, Heise, Kirstin-Friederike, Honda, Shiori, Jacobson, Aaron, Jansen, Jacobus F.A., Jenkins, Christopher W., Johnston, Stephen J., Juchem, Christoph, Kangarlu, Alayar, Kerr, Adam B., Landheer, Karl, Lange, Thomas, Lee, Phil, Levendovszky, Swati Rane, Limperopoulos, Catherine, Liu, Feng, Lloyd, William, Lythgoe, David J., Machizawa, Maro G., MacMillan, Erin L., Maddock, Richard J., Manzhurtsev, Andrei V., Martinez-Gudino, María L., Miller, Jack J., Mirzakhanian, Heline, Moreno-Ortega, Marta, Mullins, Paul G., Nakajima, Shinichiro, Near, Jamie, Noeske, Ralph, Nordhøy, Wibeke, Oeltzschner, Georg, Osorio-Duran, Raul, Otaduy, Maria C.G., Pasaye, Erick H., Peeters, Ronald, Peltier, Scott J., Pilatus, Ulrich, Polomac, Nenad, Porges, Eric C., Pradhan, Subechhya, Prisciandaro, James Joseph, Puts, Nicolaas A, Rae, Caroline D., Reyes-Madrigal, Francisco, Roberts, Timothy P.L., Robertson, Caroline E., Rosenberg, Jens T., Rotaru, Diana-Georgiana, O'Gorman Tuura, Ruth L, Saleh, Muhammad G., Sandberg, Kristian, Sangill, Ryan, Schembri, Keith, Schrantee, Anouk, Semenova, Natalia A., Singel, Debra, Sitnikov, Rouslan, Smith, Jolinda, Song, Yulu, Stark, Craig, Stoffers, Diederick, Swinnen, Stephan P., Tain, Rongwen, Tanase, Costin, Tapper, Sofie, Tegenthoff, Martin, Thiel, Thomas, Thioux, Marc, Truong, Peter, van Dijk, Pim, Vella, Nolan, Vidyasagar, Rishma, Vovk, Andrej, Wang, Guangbin, Westlye, Lars T., Wilbur, Timothy K., Willoughby, William R., Wilson, Martin, Wittsack, Hans-Jörg, Woods, Adam J., Wu, Yen-Chien, Xu, Junqian, Lopez, Maria Yanez, Yeung, David K.W., Zhao, Qun, Zhou, Xiaopeng, Zupan, Gasper, and Edden, Richard A.E.

Published
2021
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8. Brain Age Prediction Reveals Aberrant Brain White Matter in Schizophrenia and Bipolar Disorder: A Multisample Diffusion Tensor Imaging Study

Author

Farde, L., Flyckt, L., Engberg, G., Erhardt, S., Fatouros-Bergman, H., Cervenka, S., Schwieler, L., Piehl, F., Agartz, I., Collste, K., Victorsson, P., Malmqvist, A., Hedberg, M., Orhan, F., Sellgren, C., Tønnesen, Siren, Kaufmann, Tobias, de Lange, Ann-Marie G., Richard, Geneviève, Doan, Nhat Trung, Alnæs, Dag, van der Meer, Dennis, Rokicki, Jaroslav, Moberget, Torgeir, Maximov, Ivan I., Agartz, Ingrid, Aminoff, Sofie R., Beck, Dani, Barch, Deanna M., Beresniewicz, Justyna, Cervenka, Simon, Fatouros-Bergman, Helena, Craven, Alexander R., Flyckt, Lena, Gurholt, Tiril P., Haukvik, Unn K., Hugdahl, Kenneth, Johnsen, Erik, Jönsson, Erik G., Kolskår, Knut K., Kroken, Rune Andreas, Lagerberg, Trine V., Løberg, Else-Marie, Nordvik, Jan Egil, Sanders, Anne-Marthe, Ulrichsen, Kristine, Andreassen, Ole A., and Westlye, Lars T.

Published
2020
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11. Big GABA II: Water-referenced edited MR spectroscopy at 25 research sites

Author

Mikkelsen, Mark, Rimbault, Daniel L., Barker, Peter B., Bhattacharyya, Pallab K., Brix, Maiken K., Buur, Pieter F., Cecil, Kim M., Chan, Kimberly L., Chen, David Y.-T., Craven, Alexander R., Cuypers, Koen, Dacko, Michael, Duncan, Niall W., Dydak, Ulrike, Edmondson, David A., Ende, Gabriele, Ersland, Lars, Forbes, Megan A., Gao, Fei, Greenhouse, Ian, Harris, Ashley D., He, Naying, Heba, Stefanie, Hoggard, Nigel, Hsu, Tun-Wei, Jansen, Jacobus F.A., Kangarlu, Alayar, Lange, Thomas, Lebel, R. Marc, Li, Yan, Lin, Chien-Yuan E., Liou, Jy-Kang, Lirng, Jiing-Feng, Liu, Feng, Long, Joanna R., Ma, Ruoyun, Maes, Celine, Moreno-Ortega, Marta, Murray, Scott O., Noah, Sean, Noeske, Ralph, Noseworthy, Michael D., Oeltzschner, Georg, Porges, Eric C., Prisciandaro, James J., Puts, Nicolaas A.J., Roberts, Timothy P.L., Sack, Markus, Sailasuta, Napapon, Saleh, Muhammad G., Schallmo, Michael-Paul, Simard, Nicholas, Stoffers, Diederick, Swinnen, Stephan P., Tegenthoff, Martin, Truong, Peter, Wang, Guangbin, Wilkinson, Iain D., Wittsack, Hans-Jörg, Woods, Adam J., Xu, Hongmin, Yan, Fuhua, Zhang, Chencheng, Zipunnikov, Vadim, Zöllner, Helge J., and Edden, Richard A.E.

Published
2019
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13. GABA, glutamatergic dynamics and BOLD contrast assessed concurrently using functional MRS during a cognitive task.

Author

Craven, Alexander R., Dwyer, Gerard, Ersland, Lars, Kazimierczak, Katarzyna, Noeske, Ralph, Sandøy, Lydia Brunvoll, Johnsen, Erik, and Hugdahl, Kenneth

Subjects
GABA, FUNCTIONAL magnetic resonance imaging, OXYGEN in the blood, CINGULATE cortex, TASK performance
Abstract

A recurring issue in functional neuroimaging is how to link task‐driven haemodynamic blood oxygen level dependent functional MRI (BOLD‐fMRI) responses to underlying neurochemistry at the synaptic level. Glutamate and γ‐aminobutyric acid (GABA), the major excitatory and inhibitory neurotransmitters respectively, are typically measured with MRS sequences separately from fMRI, in the absence of a task. The present study aims to resolve this disconnect, developing acquisition and processing techniques to simultaneously assess GABA, glutamate and glutamine (Glx) and BOLD in relation to a cognitive task, at 3 T. Healthy subjects (N = 81) performed a cognitive task (Eriksen flanker), which was presented visually in a task‐OFF, task‐ON block design, with individual event onset timing jittered with respect to the MRS readout. fMRS data were acquired from the medial anterior cingulate cortex during task performance, using an adapted MEGA‐PRESS implementation incorporating unsuppressed water‐reference signals at a regular interval. These allowed for continuous assessment of BOLD activation, through T2*‐related changes in water linewidth. BOLD‐fMRI data were additionally acquired. A novel linear model was used to extract modelled metabolite spectra associated with discrete functional stimuli, building on well established processing and quantification tools. Behavioural outcomes from the flanker task, and activation patterns from the BOLD‐fMRI sequence, were as expected from the literature. BOLD response assessed through fMRS showed a significant correlation with fMRI, specific to the fMRS‐targeted region of interest; fMRS‐assessed BOLD additionally correlated with lengthening of response time in the incongruent flanker condition. While no significant task‐related changes were observed for GABA+, a significant increase in measured Glx levels (~8.8%) was found between task‐OFF and task‐ON periods. These findings verify the efficacy of our protocol and analysis pipelines for the simultaneous assessment of metabolite dynamics and BOLD. As well as establishing a robust basis for further work using these techniques, we also identify a number of clear directions for further refinement in future studies. [ABSTRACT FROM AUTHOR]

Published
2024
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15. Neurobiological mechanisms of ECT and TMS treatment in depression. Study protocol of a multimodal magnetic resonance investigation

Author

Frid, Leila Marie, primary, Kessler, Ute, additional, Ousdal, Olga-Therese, additional, Hammar, Åsa, additional, Haavik, Jan, additional, Riemer, Frank, additional, Hirnstein, Marco, additional, Ersland, Lars, additional, Erchinger, Vera Jane, additional, Ronold, Eivind Haga, additional, Nygaard, Gyrid, additional, Jakobsen, Petter, additional, Craven, Alexander R, additional, Osnes, Berge, additional, Alisauskiene, Renata, additional, Bartsch, Hauke, additional, Hellard, Stephanie Le, additional, Stavrum, Anne-Kristin, additional, Oedegaard, Ketil J, additional, and Oltedal, Leif, additional

Published
2023
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23. Big GABA: Edited MR spectroscopy at 24 research sites

Author

Mikkelsen, Mark, Barker, Peter B., Bhattacharyya, Pallab K., Brix, Maiken K., Buur, Pieter F., Cecil, Kim M., Chan, Kimberly L., Chen, David Y.-T., Craven, Alexander R., Cuypers, Koen, Dacko, Michael, Duncan, Niall W., Dydak, Ulrike, Edmondson, David A., Ende, Gabriele, Ersland, Lars, Gao, Fei, Greenhouse, Ian, Harris, Ashley D., He, Naying, Heba, Stefanie, Hoggard, Nigel, Hsu, Tun-Wei, Jansen, Jacobus F.A., Kangarlu, Alayar, Lange, Thomas, Lebel, R. Marc, Li, Yan, Lin, Chien-Yuan E., Liou, Jy-Kang, Lirng, Jiing-Feng, Liu, Feng, Ma, Ruoyun, Maes, Celine, Moreno-Ortega, Marta, Murray, Scott O., Noah, Sean, Noeske, Ralph, Noseworthy, Michael D., Oeltzschner, Georg, Prisciandaro, James J., Puts, Nicolaas A.J., Roberts, Timothy P.L., Sack, Markus, Sailasuta, Napapon, Saleh, Muhammad G., Schallmo, Michael-Paul, Simard, Nicholas, Swinnen, Stephan P., Tegenthoff, Martin, Truong, Peter, Wang, Guangbin, Wilkinson, Iain D., Wittsack, Hans-Jörg, Xu, Hongmin, Yan, Fuhua, Zhang, Chencheng, Zipunnikov, Vadim, Zöllner, Helge J., and Edden, Richard A.E.

Published
2017
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24. The intra‐individual reliability of 1H‐MRS measurement in the anterior cingulate cortex across 1 year.

Author

Wang, Meng‐Yun, Korbmacher, Max, Eikeland, Rune, Craven, Alexander R., and Specht, Karsten

Subjects
CINGULATE cortex, NUCLEAR magnetic resonance spectroscopy, GABA, NEURAL development, GLUTAMATE receptors
Abstract

Magnetic resonance spectroscopy (MRS) is the primary method that can measure the levels of metabolites in the brain in vivo. To achieve its potential in clinical usage, the reliability of the measurement requires further articulation. Although there are many studies that investigate the reliability of gamma‐aminobutyric acid (GABA), comparatively few studies have investigated the reliability of other brain metabolites, such as glutamate (Glu), N‐acetyl‐aspartate (NAA), creatine (Cr), phosphocreatine (PCr), or myo‐inositol (mI), which all play a significant role in brain development and functions. In addition, previous studies which predominately used only two measurements (two data points) failed to provide the details of the time effect (e.g., time‐of‐day) on MRS measurement within subjects. Therefore, in this study, MRS data located in the anterior cingulate cortex (ACC) were repeatedly recorded across 1 year leading to at least 25 sessions for each subject with the aim of exploring the variability of other metabolites by using the index coefficient of variability (CV); the smaller the CV, the more reliable the measurements. We found that the metabolites of NAA, tNAA, and tCr showed the smallest CVs (between 1.43% and 4.90%), and the metabolites of Glu, Glx, mI, and tCho showed modest CVs (between 4.26% and 7.89%). Furthermore, we found that the concentration reference of the ratio to water results in smaller CVs compared to the ratio to tCr. In addition, we did not find any time‐of‐day effect on the MRS measurements. Collectively, the results of this study indicate that the MRS measurement is reasonably reliable in quantifying the levels of metabolites. [ABSTRACT FROM AUTHOR]

Published
2024
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28. Neural Activation in the Ventromedial Prefrontal Cortex Precedes Conscious Experience of Being in or Out of a Transient Hallucinatory State

Author

Hugdahl, Kenneth, primary, Craven, Alexander R, additional, Johnsen, Erik, additional, Ersland, Lars, additional, Stoyanov, Drozdstoy, additional, Kandilarova, Sevdalina, additional, Brunvoll Sandøy, Lydia, additional, Kroken, Rune A, additional, Løberg, Else-Marie, additional, and Sommer, Iris E, additional

Published
2022
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29. Comparison of seven modelling algorithms for GABA-edited (1)H-MRS: Evaluation of data from 20 sites, with: FSL-MRS, Gannet, jMRUI (AMARES, QUEST), LCModel, Osprey and Tarquin

Author

Craven, Alexander R., Bhattacharyya, Pallab K., Clarke, William T., Dydak, Ulrike, Edden, Richard A. E., Ersland, Lars, Mandal, Pravat K., Mikkelsen, Mark, Murdoch, James B., Near, Jamie, Rideaux, Reuben, Shukla, Deepika, Wang, Min, Wilson, Martin, Zöllner, Helge J., Hugdahl, Kenneth, and Oeltzschner, Georg

Subjects
Magnetic Resonance Spectroscopy, Proton Magnetic Resonance Spectroscopy, Brain, Humans, Reproducibility of Results, Article, Algorithms, gamma-Aminobutyric Acid
Abstract

Edited MRS sequences are widely used for studying γ-aminobutyric acid (GABA) in the human brain. Several algorithms are available for modelling these data, deriving metabolite concentration estimates through peak fitting or a linear combination of basis spectra. The present study compares seven such algorithms, using data obtained in a large multisite study. GABA-edited (GABA+, TE = 68 ms MEGA-PRESS) data from 222 subjects at 20 sites were processed via a standardised pipeline, before modelling with FSL-MRS, Gannet, AMARES, QUEST, LCModel, Osprey and Tarquin, using standardised vendor-specific basis sets (for GE, Philips and Siemens) where appropriate. After referencing metabolite estimates (to water or creatine), systematic differences in scale were observed between datasets acquired on different vendors' hardware, presenting across algorithms. Scale differences across algorithms were also observed. Using the correlation between metabolite estimates and voxel tissue fraction as a benchmark, most algorithms were found to be similarly effective in detecting differences in GABA+. An interclass correlation across all algorithms showed single-rater consistency for GABA+ estimates of around 0.38, indicating moderate agreement. Upon inclusion of a basis set component explicitly modelling the macromolecule signal underlying the observed 3.0 ppm GABA peaks, single-rater consistency improved to 0.44. Correlation between discrete pairs of algorithms varied, and was concerningly weak in some cases. Our findings highlight the need for consensus on appropriate modelling parameters across different algorithms, and for detailed reporting of the parameters adopted in individual studies to ensure reproducibility and meaningful comparison of outcomes between different studies.

Published
2022

30. Virtual ontogeny of cortical growth preceding mental illness

Author

German Research Foundation, University of Münster, National Health and Medical Research Council (Australia), University of Cape Town, National Research Foundation (South Africa), Swinburne University of Technology, Jack Brockhoff Foundation, University of Melbourne, Barbara Dicker Brain Sciences Foundation, Rebecca L. Cooper Medical Research Foundation, Society for Mental Health Research (Australia), Swedish Research Council, Swedish Foundation for Strategic Research, Swedish Brain Foundation, Health Research Board (Ireland), Russian Foundation for Basic Research, University of Zurich, Pratt Foundation, Ramsay Health Care, Viertel Charitable Foundation, Schizophrenia Research Institute (Australia), European Commission, Australian Research Council, Instituto de Salud Carlos III, National Institute for Health and Care Research (US), National Institute for Health Research (UK), Ministry of Health of the Czech Republic, Bill & Melinda Gates Foundation, South African Medical Research Council, Carnegie Corporation of New York, Wellcome Trust, Medical Research Council (UK), Medical Research Scotland, Netherlands Organization for Scientific Research, Ambrogi, Sonia [0000-0002-2897-358X], Banaschewski, Tobias [0000-0003-4595-1144], Bandeira, Cibele Edom [0000-0003-0681-1309], Cupertino, Renata [0000-0002-3452-0632], Calderoni, Sara [0000-0002-6250-5739], Cannon, Dara [0000-0001-7378-3411], Carr, Vaughan [0000-0002-8907-5804], Chew, Qian Hui [0000-0003-0969-7994], Coghill, David [0000-0003-3017-9737], Cullen, Kathryn [0000-0001-9631-3770], Dahl, Andreas [0000-0002-8097-2082], Epstein, Jeffery [0000-0003-3464-5256], Foran, William [0000-0001-7491-9798], Fortea, Lydia [0000-0001-6778-2316], Fuentes-Claramonte, Paola [0000-0002-1428-7976], Fullerton, Janice M. [0000-0003-4014-4490], Furlong, Lisa [0000-0001-6196-4565], Gallagher, Louise [0000-0001-9462-2836], Gao, Si [0000-0002-4473-1142], Gotlib, Ian [0000-0002-3622-3199], Haavik, Jan [0000-0001-7865-2808], Henskens, Frans [0000-0003-2358-5630], Hilland, Eva [0000-0002-7102-8372], Hoekstra, Pieter J [0000-0001-7260-4119], Howells, Fleur M [0000-0001-9759-2556], Ipser, Jonathan [0000-0003-1272-0032], Jørgensen, Jes Kristian [0000-0001-9133-1670], Karantonis, James A. [0000-0003-2281-0912], Lawrie, Stephen [0000-0002-2444-5675], Patel, Yash, Shin, Jean, Abé, Christoph, Agartz, Ingrid, Alloza, Clara, Alnæs, Dag, Ambrogi, Sonia, Antonucci, Linda A., Arango, Celso, Arolt, Volker, Auzias, Guillaume, Gruber, Oliver, Haavik, Jan, McDonald, Colm, Hahn, Tim, Harrison, Ben J., Heindel, Walter, Henskens, Frans, Heslenfeld, Dirk J., Hilland, Eva, King, Joseph A., Vernooij, Meike W., Hoekstra, Pieter J., Hohmann, Sarah, Holz, Nathalie, Howells, Fleur M., McIntosh, Andrew, Ipser, Jonathan C., Meinert, Susanne, Hoogman, Martine, Kircher, Tilo, Kochunov, Peter, Vieta, Eduard, Koopowitz, Sheri-Michelle, Landén, Mikael, Landrø, Nils Inge, Lawrie, Stephen, Michie, Patricia T., Ayesa Arriola, Rosa, Mitchell, Philip, Moreno-Alcázar, Ana, Franke, Barbara, Mowry, Bryan, Bau, Claiton H. D., Muratori, Filippo, Nabulsi, Leila, Nenadić, Igor, O'Gorman Tuura, Ruth, Oosterlaan, Jaap, Overs, Bronwyn, Pantelis, Christos, Banaj, Nerisa, Parellada, Mara, van Rooij, Daan, Vilarroya, Oscar, Pariente, Jose C., Pauli, Paul, Pergola, Giulio, Piarulli, Francesco Maria, Picon, Felipe, Piras, Fabrizio, Pomarol-Clotet, Edith, Pretus, Clara, Quidé, Yann, Banaschewski, Tobias, Weickert, Cynthia, Buitelaar, Jan, Radua, Joaquim, Ramos-Quiroga, J. Antoni, Rasser, Paul E., Reif, Andreas, Retico, Alessandra, Roberts, Gloria, Rossell, Susan, Rovaris, Diego Luiz, Rubia, Katya, Weickert, Thomas, Sacchet, Matthew, Ching, Christopher R. K., Bandeira, Cibele, Salavert, Josep, Salvador, Raymond, Sarró, Salvador, Sawa, Akira, Schall, Ulrich, Scott, Rodney, Selvaggi, Pierluigi, Westlye, Lars T., Silk, Tim, Sim, Kang, Andreassen, Ole A., Skoch, Antonin, Başgöze, Zeynep, Spalletta, Gianfranco, Spaniel, Filip, Stein, Dan J., Steinsträter, Olaf, Stolicyn, Aleks, Whalley, Heather, Takayanagi, Yoichiro, Tamm, Leanne, Tavares, Maria, Pozzi, Elena, Teumer, Alexander, Thiel, Katharina, Cupertino, Renata Basso, Thomopoulos, Sophia I., Tomecek, David, Tomyshev, Alexander S., Willinger, David, Tordesillas-Gutiérrez, Diana, Tosetti, Michela, Uhlmann, Anne, Van Rheenen, Tamsyn, Veltman, Dick, Vázquez-Bourgon, Javier, Schmaal, Lianne, Jahanshad, Neda, Winter, Alexandra, Wittfeld, Katharina, Yang, Tony T., Yoncheva, Yuliya, Bauer, Jochen, Zijlmans, Jendé L., Baumeister, Sarah, Lebedeva, Irina, van Erp, Theo G. M., Turner, Jessica, Jakobi, Babette, Castellanos, F. Xavier, Pausova, Zdenka, Thompson, Paul, Paus, Tomas, Bernardoni, Fabio, Bertolino, Alessandro, Bonnin, Caterina Del Mar, Brandeis, Daniel, Luna, Beatriz, Brem, Silvia, Jansen, Andreas, Bruggemann, Jason, Bülow, Robin, Bustillo, Juan R., Calderoni, Sara, Calvo, Rosa, Canales-Rodríguez, Erick J., Cannon, Dara M., Carmona, Susanna, Carr, Vaughan J., Lundervold, Astri J., Janssen, Joost, Catts, Stanley V., Chenji, Sneha, Chew, Qian Hui, Coghill, David, Connolly, Colm G., Conzelmann, Annette, Craven, Alexander R., Crespo-Facorro, Benedicto, Cullen, Kathryn, Dahl, Andreas, Jonassen, Rune, MacMaster, Frank P., Dannlowski, Udo, Davey, Christopher G., Deruelle, Christine, Díaz-Caneja, Covadonga M., Dohm, Katharina, Ehrlich, Stefan, Epstein, Jeffery, Erwin-Grabner, Tracy, Eyler, Lisa T., Kaiser, Anna, Fedor, Jennifer, Maglanoc, Luigi A., Fitzgerald, Jacqueline, Foran, William, Ford, Judith M., Fortea, Lydia, Fuentes-Claramonte, Paola, Fullerton, Janice, Furlong, Lisa, Gallagher, Louise, Kaleda, Vasiliy, Gao, Bingchen, Gao, Si, Mathalon, Daniel H., Goikolea, Jose M., Gotlib, Ian, Goya-Maldonado, Roberto, Grabe, Hans J., Green, Melissa, Grevet, Eugenio H., Groenewold, Nynke A., Karantonis, James, Grotegerd, Dominik., German Research Foundation, University of Münster, National Health and Medical Research Council (Australia), University of Cape Town, National Research Foundation (South Africa), Swinburne University of Technology, Jack Brockhoff Foundation, University of Melbourne, Barbara Dicker Brain Sciences Foundation, Rebecca L. Cooper Medical Research Foundation, Society for Mental Health Research (Australia), Swedish Research Council, Swedish Foundation for Strategic Research, Swedish Brain Foundation, Health Research Board (Ireland), Russian Foundation for Basic Research, University of Zurich, Pratt Foundation, Ramsay Health Care, Viertel Charitable Foundation, Schizophrenia Research Institute (Australia), European Commission, Australian Research Council, Instituto de Salud Carlos III, National Institute for Health and Care Research (US), National Institute for Health Research (UK), Ministry of Health of the Czech Republic, Bill & Melinda Gates Foundation, South African Medical Research Council, Carnegie Corporation of New York, Wellcome Trust, Medical Research Council (UK), Medical Research Scotland, Netherlands Organization for Scientific Research, Ambrogi, Sonia [0000-0002-2897-358X], Banaschewski, Tobias [0000-0003-4595-1144], Bandeira, Cibele Edom [0000-0003-0681-1309], Cupertino, Renata [0000-0002-3452-0632], Calderoni, Sara [0000-0002-6250-5739], Cannon, Dara [0000-0001-7378-3411], Carr, Vaughan [0000-0002-8907-5804], Chew, Qian Hui [0000-0003-0969-7994], Coghill, David [0000-0003-3017-9737], Cullen, Kathryn [0000-0001-9631-3770], Dahl, Andreas [0000-0002-8097-2082], Epstein, Jeffery [0000-0003-3464-5256], Foran, William [0000-0001-7491-9798], Fortea, Lydia [0000-0001-6778-2316], Fuentes-Claramonte, Paola [0000-0002-1428-7976], Fullerton, Janice M. [0000-0003-4014-4490], Furlong, Lisa [0000-0001-6196-4565], Gallagher, Louise [0000-0001-9462-2836], Gao, Si [0000-0002-4473-1142], Gotlib, Ian [0000-0002-3622-3199], Haavik, Jan [0000-0001-7865-2808], Henskens, Frans [0000-0003-2358-5630], Hilland, Eva [0000-0002-7102-8372], Hoekstra, Pieter J [0000-0001-7260-4119], Howells, Fleur M [0000-0001-9759-2556], Ipser, Jonathan [0000-0003-1272-0032], Jørgensen, Jes Kristian [0000-0001-9133-1670], Karantonis, James A. [0000-0003-2281-0912], Lawrie, Stephen [0000-0002-2444-5675], Patel, Yash, Shin, Jean, Abé, Christoph, Agartz, Ingrid, Alloza, Clara, Alnæs, Dag, Ambrogi, Sonia, Antonucci, Linda A., Arango, Celso, Arolt, Volker, Auzias, Guillaume, Gruber, Oliver, Haavik, Jan, McDonald, Colm, Hahn, Tim, Harrison, Ben J., Heindel, Walter, Henskens, Frans, Heslenfeld, Dirk J., Hilland, Eva, King, Joseph A., Vernooij, Meike W., Hoekstra, Pieter J., Hohmann, Sarah, Holz, Nathalie, Howells, Fleur M., McIntosh, Andrew, Ipser, Jonathan C., Meinert, Susanne, Hoogman, Martine, Kircher, Tilo, Kochunov, Peter, Vieta, Eduard, Koopowitz, Sheri-Michelle, Landén, Mikael, Landrø, Nils Inge, Lawrie, Stephen, Michie, Patricia T., Ayesa Arriola, Rosa, Mitchell, Philip, Moreno-Alcázar, Ana, Franke, Barbara, Mowry, Bryan, Bau, Claiton H. D., Muratori, Filippo, Nabulsi, Leila, Nenadić, Igor, O'Gorman Tuura, Ruth, Oosterlaan, Jaap, Overs, Bronwyn, Pantelis, Christos, Banaj, Nerisa, Parellada, Mara, van Rooij, Daan, Vilarroya, Oscar, Pariente, Jose C., Pauli, Paul, Pergola, Giulio, Piarulli, Francesco Maria, Picon, Felipe, Piras, Fabrizio, Pomarol-Clotet, Edith, Pretus, Clara, Quidé, Yann, Banaschewski, Tobias, Weickert, Cynthia, Buitelaar, Jan, Radua, Joaquim, Ramos-Quiroga, J. Antoni, Rasser, Paul E., Reif, Andreas, Retico, Alessandra, Roberts, Gloria, Rossell, Susan, Rovaris, Diego Luiz, Rubia, Katya, Weickert, Thomas, Sacchet, Matthew, Ching, Christopher R. K., Bandeira, Cibele, Salavert, Josep, Salvador, Raymond, Sarró, Salvador, Sawa, Akira, Schall, Ulrich, Scott, Rodney, Selvaggi, Pierluigi, Westlye, Lars T., Silk, Tim, Sim, Kang, Andreassen, Ole A., Skoch, Antonin, Başgöze, Zeynep, Spalletta, Gianfranco, Spaniel, Filip, Stein, Dan J., Steinsträter, Olaf, Stolicyn, Aleks, Whalley, Heather, Takayanagi, Yoichiro, Tamm, Leanne, Tavares, Maria, Pozzi, Elena, Teumer, Alexander, Thiel, Katharina, Cupertino, Renata Basso, Thomopoulos, Sophia I., Tomecek, David, Tomyshev, Alexander S., Willinger, David, Tordesillas-Gutiérrez, Diana, Tosetti, Michela, Uhlmann, Anne, Van Rheenen, Tamsyn, Veltman, Dick, Vázquez-Bourgon, Javier, Schmaal, Lianne, Jahanshad, Neda, Winter, Alexandra, Wittfeld, Katharina, Yang, Tony T., Yoncheva, Yuliya, Bauer, Jochen, Zijlmans, Jendé L., Baumeister, Sarah, Lebedeva, Irina, van Erp, Theo G. M., Turner, Jessica, Jakobi, Babette, Castellanos, F. Xavier, Pausova, Zdenka, Thompson, Paul, Paus, Tomas, Bernardoni, Fabio, Bertolino, Alessandro, Bonnin, Caterina Del Mar, Brandeis, Daniel, Luna, Beatriz, Brem, Silvia, Jansen, Andreas, Bruggemann, Jason, Bülow, Robin, Bustillo, Juan R., Calderoni, Sara, Calvo, Rosa, Canales-Rodríguez, Erick J., Cannon, Dara M., Carmona, Susanna, Carr, Vaughan J., Lundervold, Astri J., Janssen, Joost, Catts, Stanley V., Chenji, Sneha, Chew, Qian Hui, Coghill, David, Connolly, Colm G., Conzelmann, Annette, Craven, Alexander R., Crespo-Facorro, Benedicto, Cullen, Kathryn, Dahl, Andreas, Jonassen, Rune, MacMaster, Frank P., Dannlowski, Udo, Davey, Christopher G., Deruelle, Christine, Díaz-Caneja, Covadonga M., Dohm, Katharina, Ehrlich, Stefan, Epstein, Jeffery, Erwin-Grabner, Tracy, Eyler, Lisa T., Kaiser, Anna, Fedor, Jennifer, Maglanoc, Luigi A., Fitzgerald, Jacqueline, Foran, William, Ford, Judith M., Fortea, Lydia, Fuentes-Claramonte, Paola, Fullerton, Janice, Furlong, Lisa, Gallagher, Louise, Kaleda, Vasiliy, Gao, Bingchen, Gao, Si, Mathalon, Daniel H., Goikolea, Jose M., Gotlib, Ian, Goya-Maldonado, Roberto, Grabe, Hans J., Green, Melissa, Grevet, Eugenio H., Groenewold, Nynke A., Karantonis, James, and Grotegerd, Dominik.

Abstract

[Background]: Morphology of the human cerebral cortex differs across psychiatric disorders, with neurobiology and developmental origins mostly undetermined. Deviations in the tangential growth of the cerebral cortex during pre/perinatal periods may be reflected in individual variations in cortical surface area later in life., [Methods]: Interregional profiles of group differences in surface area between cases and controls were generated using T1-weighted magnetic resonance imaging from 27,359 individuals including those with attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, schizophrenia, and high general psychopathology (through the Child Behavior Checklist). Similarity of interregional profiles of group differences in surface area and prenatal cell-specific gene expression was assessed., [Results]: Across the 11 cortical regions, group differences in cortical area for attention-deficit/hyperactivity disorder, schizophrenia, and Child Behavior Checklist were dominant in multimodal association cortices. The same interregional profiles were also associated with interregional profiles of (prenatal) gene expression specific to proliferative cells, namely radial glia and intermediate progenitor cells (greater expression, larger difference), as well as differentiated cells, namely excitatory neurons and endothelial and mural cells (greater expression, smaller difference). Finally, these cell types were implicated in known pre/perinatal risk factors for psychosis. Genes coexpressed with radial glia were enriched with genes implicated in congenital abnormalities, birth weight, hypoxia, and starvation. Genes coexpressed with endothelial and mural genes were enriched with genes associated with maternal hypertension and preterm birth., [Conclusions]: Our findings support a neurodevelopmental model of vulnerability to mental illness whereby prenatal risk factors acting through cell-specific processes lead to deviations from typical brain development during pregnancy.

Published
2022

31. Neural Activation in the Ventromedial Prefrontal Cortex Precedes Conscious Experience of Being in or out of a Transient Hallucinatory State.

Author

Hugdahl, Kenneth, Craven, Alexander R, Johnsen, Erik, Ersland, Lars, Stoyanov, Drozdstoy, Kandilarova, Sevdalina, Sandøy, Lydia Brunvoll, Kroken, Rune A, Løberg, Else-Marie, and Sommer, Iris E C

Subjects
HALLUCINATIONS, PREFRONTAL cortex, EVOKED potentials (Electrophysiology), LARGE-scale brain networks, SCHIZOPHRENIA, AUDITORY perception, TRANSCRANIAL magnetic stimulation, MAGNETIC resonance imaging, WORD deafness, COMPARATIVE studies, RESEARCH funding, TIME series analysis, NEURORADIOLOGY
Abstract

Background and Hypotheses Auditory verbal hallucinations (AVHs) is not only a common symptom in schizophrenia but also observed in individuals in the general population. Despite extensive research, AVHs are poorly understood, especially their underlying neuronal architecture. Neuroimaging methods have been used to identify brain areas and networks that are activated during hallucinations. A characteristic feature of AVHs is, however, that they fluctuate over time, with varying frequencies of starts and stops. An unanswered question is, therefore, what neuronal events co-occur with the initiation and inhibition of an AVH episode. Study Design We investigated brain activation with fMRI in 66 individuals who experienced multiple AVH-episodes while in the scanner. We extracted time-series fMRI-data and monitored changes second-by-second from 10 s before to 15 s after participants indicated the start and stop of an episode, respectively, by pressing a hand-held response-button. Study Results We found a region in the ventromedial prefrontal cortex (VMPFC) which showed a significant increase in activation initiated a few seconds before participants indicated the start of an episode, and a corresponding decrease in activation initiated a few seconds before the end of an episode. Conclusions The consistent increase and decrease in activation in this area in advance of the consciously experienced presence or absence of the "voice" imply that this region may act as a switch in turning episodes on and off. The activation is unlikely to be confounded by motor responses. The findings could have clinical implications for brain stimulation treatments, like transcranial magnetic stimulation. [ABSTRACT FROM AUTHOR]

Published
2023
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32. The NADPARK study: A randomized phase I trial of nicotinamide riboside supplementation in Parkinson’s disease

Author

Brakedal, Brage, Dölle, Christian, Riemer, Frank, Ma, Yilong, Nido, Gonzalo S., Skeie, Geir Olve, Craven, Alexander R., Schwarzlmüller, Thomas, Brekke, Njål, Diab, Joseph, Sverkeli, Lars, Skjeie, Vivian, Varhaug, Kristin, Tysnes, Ole-Bjørn, Peng, Shichun, Haugarvoll, Kristoffer, Ziegler, Mathias, Grüner, Renate, Eidelberg, David, and Tzoulis, Charalampos

Published
2022
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33. Comparison of seven modelling algorithms for γ‐aminobutyric acid–edited proton magnetic resonance spectroscopy

Author

Craven, Alexander R., primary, Bhattacharyya, Pallab K., additional, Clarke, William T., additional, Dydak, Ulrike, additional, Edden, Richard A. E., additional, Ersland, Lars, additional, Mandal, Pravat K., additional, Mikkelsen, Mark, additional, Murdoch, James B., additional, Near, Jamie, additional, Rideaux, Reuben, additional, Shukla, Deepika, additional, Wang, Min, additional, Wilson, Martin, additional, Zöllner, Helge J., additional, Hugdahl, Kenneth, additional, and Oeltzschner, Georg, additional

Published
2022
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35. Negative valence of hallucinatory voices as predictor of cortical glutamatergic metabolite levels in schizophrenia patients

Author

Hjelmervik, Helene, primary, Craven, Alexander R., additional, Johnsen, Erik, additional, Kompus, Kristiina, additional, Bless, Josef J., additional, Sinkeviciute, Igne, additional, Kroken, Rune A., additional, Løberg, Else‐Marie, additional, Ersland, Lars, additional, Grüner, Renate, additional, Sommer, Iris E., additional, and Hugdahl, Kenneth, additional

Published
2021
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36. Comparison of seven modelling algorithms for GABA-edited 1H-MRS

Author

Craven, Alexander R., primary, Bhattacharyya, Pallab K., additional, Clarke, William T., additional, Dydak, Ulrike, additional, Edden, Richard A. E., additional, Ersland, Lars, additional, Mandal, Pravat K., additional, Mikkelsen, Mark, additional, Murdoch, James B., additional, Near, Jamie, additional, Rideaux, Reuben, additional, Shukla, Deepika, additional, Wang, Min, additional, Wilson, Martin, additional, Zöllner, Helge, additional, Hugdahl, Kenneth, additional, and Oeltzschner, Georg, additional

Published
2021
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37. Frequency Drift in MR Spectroscopy at 3T

Author

Hui, Steve C N, Mikkelsen, Mark, Zöllner, Helge J, Ahluwalia, Vishwadeep, Alcauter, Sarael, Baltusis, Laima, Barany, Deborah A, Barlow, Laura R, Becker, Robert, Berman, Jeffrey I, Berrington, Adam, Bhattacharyya, Pallab K, Blicher, Jakob Udby, Bogner, Wolfgang, Brown, Mark S, Calhoun, Vince D, Castillo, Ryan, Cecil, Kim M, Choi, Yeo Bi, Chu, Winnie C W, Clarke, William T, Craven, Alexander R, Cuypers, Koen, Dacko, Michael, de la Fuente-Sandoval, Camilo, Desmond, Patricia, Domagalik, Aleksandra, Dumont, Julien, Duncan, Niall W, Dydak, Ulrike, Dyke, Katherine, Edmondson, David A, Ende, Gabriele, Ersland, Lars, Evans, C John, Fermin, Alan S R, Ferretti, Antonio, Fillmer, Ariane, Gong, Tao, Greenhouse, Ian, Grist, James T, Gu, Meng, Harris, Ashley D, Hat, Katarzyna, Heba, Stefanie, Heckova, Eva, Hegarty, John P, Heise, Kirstin-Friederike, Jacobson, Aaron, Jansen, Jacobus F A, Jenkins, Christopher W, Johnston, Stephen J, Juchem, Christoph, Kangarlu, Alayar, Kerr, Adam B, Landheer, Karl, Lange, Thomas, Lee, Phil, Levendovszky, Swati Rane, Limperopoulos, Catherine, Liu, Feng, Lloyd, William, Lythgoe, David J, Machizawa, Maro G, MacMillan, Erin L, Maddock, Richard J, Manzhurtsev, Andrei V, Martinez-Gudino, María L, Miller, Jack J, Mirzakhanian, Heline, Moreno-Ortega, Marta, Mullins, Paul G, Near, Jamie, Noeske, Ralph, Nordhøy, Wibeke, Oeltzschner, Georg, Osorio-Duran, Raul, Otaduy, Maria C G, Pasaye, Erick H, Peeters, Ronald, Peltier, Scott J, Pilatus, Ulrich, Polomac, Nenad, Porges, Eric C, Pradhan, Subechhya, Prisciandaro, James Joseph, Puts, Nicolaas A, Rae, Caroline D, Reyes-Madrigal, Francisco, Roberts, Timothy P L, Robertson, Caroline E, Rosenberg, Jens T, Rotaru, Diana-Georgiana, O'Gorman Tuura, Ruth L, Saleh, Muhammad G, Sandberg, Kristian, Sangill, Ryan, Schembri, Keith, Schrantee, Anouk, Semenova, Natalia A, Singel, Debra, Sitnikov, Rouslan, Smith, Jolinda, Song, Yulu, Stark, Craig, Stoffers, Diederick, Swinnen, Stephan P, Tain, Rongwen, Tanase, Costin, Tapper, Sofie, Tegenthoff, Martin, Thiel, Thomas, Thioux, Marc, Truong, Peter, van Dijk, Pim, Vella, Nolan, Vidyasagar, Rishma, Vovk, Andrej, Wang, Guangbin, Westlye, Lars T, Wilbur, Timothy K, Willoughby, William R, Wilson, Martin, Wittsack, Hans-Jörg, Woods, Adam J, Wu, Yen-Chien, Xu, Junqian, Lopez, Maria Yanez, Yeung, David K W, Zhao, Qun, Zhou, Xiaopeng, Zupan, Gasper, Edden, Richard A E, Hui, Steve C N, Mikkelsen, Mark, Zöllner, Helge J, Ahluwalia, Vishwadeep, Alcauter, Sarael, Baltusis, Laima, Barany, Deborah A, Barlow, Laura R, Becker, Robert, Berman, Jeffrey I, Berrington, Adam, Bhattacharyya, Pallab K, Blicher, Jakob Udby, Bogner, Wolfgang, Brown, Mark S, Calhoun, Vince D, Castillo, Ryan, Cecil, Kim M, Choi, Yeo Bi, Chu, Winnie C W, Clarke, William T, Craven, Alexander R, Cuypers, Koen, Dacko, Michael, de la Fuente-Sandoval, Camilo, Desmond, Patricia, Domagalik, Aleksandra, Dumont, Julien, Duncan, Niall W, Dydak, Ulrike, Dyke, Katherine, Edmondson, David A, Ende, Gabriele, Ersland, Lars, Evans, C John, Fermin, Alan S R, Ferretti, Antonio, Fillmer, Ariane, Gong, Tao, Greenhouse, Ian, Grist, James T, Gu, Meng, Harris, Ashley D, Hat, Katarzyna, Heba, Stefanie, Heckova, Eva, Hegarty, John P, Heise, Kirstin-Friederike, Jacobson, Aaron, Jansen, Jacobus F A, Jenkins, Christopher W, Johnston, Stephen J, Juchem, Christoph, Kangarlu, Alayar, Kerr, Adam B, Landheer, Karl, Lange, Thomas, Lee, Phil, Levendovszky, Swati Rane, Limperopoulos, Catherine, Liu, Feng, Lloyd, William, Lythgoe, David J, Machizawa, Maro G, MacMillan, Erin L, Maddock, Richard J, Manzhurtsev, Andrei V, Martinez-Gudino, María L, Miller, Jack J, Mirzakhanian, Heline, Moreno-Ortega, Marta, Mullins, Paul G, Near, Jamie, Noeske, Ralph, Nordhøy, Wibeke, Oeltzschner, Georg, Osorio-Duran, Raul, Otaduy, Maria C G, Pasaye, Erick H, Peeters, Ronald, Peltier, Scott J, Pilatus, Ulrich, Polomac, Nenad, Porges, Eric C, Pradhan, Subechhya, Prisciandaro, James Joseph, Puts, Nicolaas A, Rae, Caroline D, Reyes-Madrigal, Francisco, Roberts, Timothy P L, Robertson, Caroline E, Rosenberg, Jens T, Rotaru, Diana-Georgiana, O'Gorman Tuura, Ruth L, Saleh, Muhammad G, Sandberg, Kristian, Sangill, Ryan, Schembri, Keith, Schrantee, Anouk, Semenova, Natalia A, Singel, Debra, Sitnikov, Rouslan, Smith, Jolinda, Song, Yulu, Stark, Craig, Stoffers, Diederick, Swinnen, Stephan P, Tain, Rongwen, Tanase, Costin, Tapper, Sofie, Tegenthoff, Martin, Thiel, Thomas, Thioux, Marc, Truong, Peter, van Dijk, Pim, Vella, Nolan, Vidyasagar, Rishma, Vovk, Andrej, Wang, Guangbin, Westlye, Lars T, Wilbur, Timothy K, Willoughby, William R, Wilson, Martin, Wittsack, Hans-Jörg, Woods, Adam J, Wu, Yen-Chien, Xu, Junqian, Lopez, Maria Yanez, Yeung, David K W, Zhao, Qun, Zhou, Xiaopeng, Zupan, Gasper, and Edden, Richard A E

Abstract

PURPOSE: Heating of gradient coils and passive shim components is a common cause of instability in the B0 field, especially when gradient intensive sequences are used. The aim of the study was to set a benchmark for typical drift encountered during MR spectroscopy (MRS) to assess the need for real-time field-frequency locking on MRI scanners by comparing field drift data from a large number of sites.METHOD: A standardized protocol was developed for 80 participating sites using 99 3T MR scanners from 3 major vendors. Phantom water signals were acquired before and after an EPI sequence. The protocol consisted of: minimal preparatory imaging; a short pre-fMRI PRESS; a ten-minute fMRI acquisition; and a long post-fMRI PRESS acquisition. Both pre- and post-fMRI PRESS were non-water suppressed. Real-time frequency stabilization/adjustment was switched off when appropriate. Sixty scanners repeated the protocol for a second dataset. In addition, a three-hour post-fMRI MRS acquisition was performed at one site to observe change of gradient temperature and drift rate. Spectral analysis was performed using MATLAB. Frequency drift in pre-fMRI PRESS data were compared with the first 5:20 minutes and the full 30:00 minutes of data after fMRI. Median (interquartile range) drifts were measured and showed in violin plot. Paired t-tests were performed to compare frequency drift pre- and post-fMRI. A simulated in vivo spectrum was generated using FID-A to visualize the effect of the observed frequency drifts. The simulated spectrum was convolved with the frequency trace for the most extreme cases. Impacts of frequency drifts on NAA and GABA were also simulated as a function of linear drift. Data from the repeated protocol were compared with the corresponding first dataset using Pearson's and intraclass correlation coefficients (ICC).RESULTS: Of the data collected from 99 scanners, 4 were excluded due to various reasons. Thus, data from 95 scanners were ultimately anal

Published
2021

40. Brain Age Prediction Reveals Aberrant Brain White Matter in Schizophrenia and Bipolar Disorder : A Multisample Diffusion Tensor Imaging Study

Author

Tønnesen, Siren, Kaufmann, Tobias, de Lange, Ann-Marie G, Richard, Geneviève, Doan, Nhat Trung, Alnæs, Dag, van der Meer, Dennis, Rokicki, Jaroslav, Moberget, Torgeir, Maximov, Ivan I, Agartz, Ingrid, Aminoff, Sofie R, Beck, Dani, Barch, Deanna M, Beresniewicz, Justyna, Cervenka, Simon, Fatouros-Bergman, Helena, Craven, Alexander R, Flyckt, Lena, Gurholt, Tiril P, Haukvik, Unn K, Hugdahl, Kenneth, Johnsen, Erik, Jönsson, Erik G, Kolskår, Knut K, Kroken, Rune Andreas, Lagerberg, Trine V, Løberg, Else-Marie, Nordvik, Jan Egil, Sanders, Anne-Marthe, Ulrichsen, Kristine, Andreassen, Ole A, Westlye, Lars T, Tønnesen, Siren, Kaufmann, Tobias, de Lange, Ann-Marie G, Richard, Geneviève, Doan, Nhat Trung, Alnæs, Dag, van der Meer, Dennis, Rokicki, Jaroslav, Moberget, Torgeir, Maximov, Ivan I, Agartz, Ingrid, Aminoff, Sofie R, Beck, Dani, Barch, Deanna M, Beresniewicz, Justyna, Cervenka, Simon, Fatouros-Bergman, Helena, Craven, Alexander R, Flyckt, Lena, Gurholt, Tiril P, Haukvik, Unn K, Hugdahl, Kenneth, Johnsen, Erik, Jönsson, Erik G, Kolskår, Knut K, Kroken, Rune Andreas, Lagerberg, Trine V, Løberg, Else-Marie, Nordvik, Jan Egil, Sanders, Anne-Marthe, Ulrichsen, Kristine, Andreassen, Ole A, and Westlye, Lars T

Abstract

BACKGROUND: Schizophrenia (SZ) and bipolar disorder (BD) share substantial neurodevelopmental components affecting brain maturation and architecture. This necessitates a dynamic lifespan perspective in which brain aberrations are inferred from deviations from expected lifespan trajectories. We applied machine learning to diffusion tensor imaging (DTI) indices of white matter structure and organization to estimate and compare brain age between patients with SZ, patients with BD, and healthy control (HC) subjects across 10 cohorts. METHODS: We trained 6 cross-validated models using different combinations of DTI data from 927 HC subjects (18-94 years of age) and applied the models to the test sets including 648 patients with SZ (18-66 years of age), 185 patients with BD (18-64 years of age), and 990 HC subjects (17-68 years of age), estimating the brain age for each participant. Group differences were assessed using linear models, accounting for age, sex, and scanner. A meta-analytic framework was applied to assess the heterogeneity and generalizability of the results. RESULTS: Tenfold cross-validation revealed high accuracy for all models. Compared with HC subjects, the model including all feature sets significantly overestimated the age of patients with SZ (Cohen's d = -0.29) and patients with BD (Cohen's d = 0.18), with similar effects for the other models. The meta-analysis converged on the same findings. Fractional anisotropy-based models showed larger group differences than the models based on other DTI-derived metrics. CONCLUSIONS: Brain age prediction based on DTI provides informative and robust proxies for brain white matter integrity. Our results further suggest that white matter aberrations in SZ and BD primarily consist of anatomically distributed deviations from expected lifespan trajectories that generalize across cohorts and scanners.

Published
2020
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41. Comparison of Multivendor Single-Voxel MR Spectroscopy Data Acquired in Healthy Brain at 26 Sites

Author

Považan, Michal, Mikkelsen, Mark, Berrington, Adam, Bhattacharyya, Pallab K, Brix, Maiken K, Buur, Pieter F, Cecil, Kim M, Chan, Kimberly L, Chen, David Y T, Craven, Alexander R, Cuypers, Koen, Dacko, Michael, Duncan, Niall W, Dydak, Ulrike, Edmondson, David A, Ende, Gabriele, Ersland, Lars, Forbes, Megan A, Gao, Fei, Greenhouse, Ian, Harris, Ashley D, He, Naying, Heba, Stefanie, Hoggard, Nigel, Hsu, Tun-Wei, Jansen, Jacobus F A, Kangarlu, Alayar, Lange, Thomas, Lebel, R Marc, Li, Yan, Lin, Chien-Yuan E, Liou, Jy-Kang, Lirng, Jiing-Feng, Liu, Feng, Long, Joanna R, Ma, Ruoyun, Maes, Celine, Moreno-Ortega, Marta, Murray, Scott O, Noah, Sean, Noeske, Ralph, Noseworthy, Michael D, Oeltzschner, Georg, Porges, Eric C, Prisciandaro, James J, Puts, Nicolaas A J, Roberts, Timothy P L, Sack, Markus, Sailasuta, Napapon, Saleh, Muhammad G, Schallmo, Michael-Paul, Simard, Nicholas, Stoffers, Diederick, Swinnen, Stephan P, Tegenthoff, Martin, Truong, Peter, Wang, Guangbin, Wilkinson, Iain D, Wittsack, Hans-Jörg, Woods, Adam J, Xu, Hongmin, Yan, Fuhua, Zhang, Chencheng, Zipunnikov, Vadim, Zöllner, Helge J, Edden, Richard A E, Barker, Peter B, Považan, Michal, Mikkelsen, Mark, Berrington, Adam, Bhattacharyya, Pallab K, Brix, Maiken K, Buur, Pieter F, Cecil, Kim M, Chan, Kimberly L, Chen, David Y T, Craven, Alexander R, Cuypers, Koen, Dacko, Michael, Duncan, Niall W, Dydak, Ulrike, Edmondson, David A, Ende, Gabriele, Ersland, Lars, Forbes, Megan A, Gao, Fei, Greenhouse, Ian, Harris, Ashley D, He, Naying, Heba, Stefanie, Hoggard, Nigel, Hsu, Tun-Wei, Jansen, Jacobus F A, Kangarlu, Alayar, Lange, Thomas, Lebel, R Marc, Li, Yan, Lin, Chien-Yuan E, Liou, Jy-Kang, Lirng, Jiing-Feng, Liu, Feng, Long, Joanna R, Ma, Ruoyun, Maes, Celine, Moreno-Ortega, Marta, Murray, Scott O, Noah, Sean, Noeske, Ralph, Noseworthy, Michael D, Oeltzschner, Georg, Porges, Eric C, Prisciandaro, James J, Puts, Nicolaas A J, Roberts, Timothy P L, Sack, Markus, Sailasuta, Napapon, Saleh, Muhammad G, Schallmo, Michael-Paul, Simard, Nicholas, Stoffers, Diederick, Swinnen, Stephan P, Tegenthoff, Martin, Truong, Peter, Wang, Guangbin, Wilkinson, Iain D, Wittsack, Hans-Jörg, Woods, Adam J, Xu, Hongmin, Yan, Fuhua, Zhang, Chencheng, Zipunnikov, Vadim, Zöllner, Helge J, Edden, Richard A E, and Barker, Peter B

Abstract

Background The hardware and software differences between MR vendors and individual sites influence the quantification of MR spectroscopy data. An analysis of a large data set may help to better understand sources of the total variance in quantified metabolite levels. Purpose To compare multisite quantitative brain MR spectroscopy data acquired in healthy participants at 26 sites by using the vendor-supplied single-voxel point-resolved spectroscopy (PRESS) sequence. Materials and Methods An MR spectroscopy protocol to acquire short-echo-time PRESS data from the midparietal region of the brain was disseminated to 26 research sites operating 3.0-T MR scanners from three different vendors. In this prospective study, healthy participants were scanned between July 2016 and December 2017. Data were analyzed by using software with simulated basis sets customized for each vendor implementation. The proportion of total variance attributed to vendor-, site-, and participant-related effects was estimated by using a linear mixed-effects model. P values were derived through parametric bootstrapping of the linear mixed-effects models (denoted Pboot). Results In total, 296 participants (mean age, 26 years ± 4.6; 155 women and 141 men) were scanned. Good-quality data were recorded from all sites, as evidenced by a consistent linewidth of N-acetylaspartate (range, 4.4-5.0 Hz), signal-to-noise ratio (range, 174-289), and low Cramér-Rao lower bounds (≤5%) for all of the major metabolites. Among the major metabolites, no vendor effects were found for levels of myo-inositol (Pboot > .90), N-acetylaspartate and N-acetylaspartylglutamate (Pboot = .13), or glutamate and glutamine (Pboot = .11). Among the smaller resonances, no vendor effects were found for ascorbate (Pboot = .08), aspartate (Pboot > .90), glutathione (Pboot > .90), or lactate (Pboot = .28). Conclusion Multisite multivendor single-voxel MR spectroscopy studies performed at 3.0 T can yield results that are coheren

Published
2020

43. Brain Age Prediction Reveals Aberrant Brain White Matter in Schizophrenia and Bipolar Disorder: A Multisample Diffusion Tensor Imaging Study

Author

Tønnesen, Siren, primary, Kaufmann, Tobias, additional, de Lange, Ann-Marie G., additional, Richard, Geneviève, additional, Doan, Nhat Trung, additional, Alnæs, Dag, additional, van der Meer, Dennis, additional, Rokicki, Jaroslav, additional, Moberget, Torgeir, additional, Maximov, Ivan I., additional, Agartz, Ingrid, additional, Aminoff, Sofie R., additional, Beck, Dani, additional, Barch, Deanna M., additional, Beresniewicz, Justyna, additional, Cervenka, Simon, additional, Fatouros-Bergman, Helena, additional, Craven, Alexander R., additional, Flyckt, Lena, additional, Gurholt, Tiril P., additional, Haukvik, Unn K., additional, Hugdahl, Kenneth, additional, Johnsen, Erik, additional, Jönsson, Erik G., additional, Kolskår, Knut K., additional, Kroken, Rune Andreas, additional, Lagerberg, Trine V., additional, Løberg, Else-Marie, additional, Nordvik, Jan Egil, additional, Sanders, Anne-Marthe, additional, Ulrichsen, Kristine, additional, Andreassen, Ole A., additional, Westlye, Lars T., additional, Farde, L., additional, Flyckt, L., additional, Engberg, G., additional, Erhardt, S., additional, Fatouros-Bergman, H., additional, Cervenka, S., additional, Schwieler, L., additional, Piehl, F., additional, Agartz, I., additional, Collste, K., additional, Victorsson, P., additional, Malmqvist, A., additional, Hedberg, M., additional, Orhan, F., additional, and Sellgren, C., additional

Published
2020
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47. Comparison of Multivendor Single-Voxel MR Spectroscopy Data Acquired in Healthy Brain at 26 Sites

Author

Považan, Michal, primary, Mikkelsen, Mark, additional, Berrington, Adam, additional, Bhattacharyya, Pallab K., additional, Brix, Maiken K., additional, Buur, Pieter F., additional, Cecil, Kim M., additional, Chan, Kimberly L., additional, Chen, David Y.T., additional, Craven, Alexander R., additional, Cuypers, Koen, additional, Dacko, Michael, additional, Duncan, Niall W., additional, Dydak, Ulrike, additional, Edmondson, David A., additional, Ende, Gabriele, additional, Ersland, Lars, additional, Forbes, Megan A., additional, Gao, Fei, additional, Greenhouse, Ian, additional, Harris, Ashley D., additional, He, Naying, additional, Heba, Stefanie, additional, Hoggard, Nigel, additional, Hsu, Tun-Wei, additional, Jansen, Jacobus F. A., additional, Kangarlu, Alayar, additional, Lange, Thomas, additional, Lebel, R. Marc, additional, Li, Yan, additional, Lin, Chien-Yuan E., additional, Liou, Jy-Kang, additional, Lirng, Jiing-Feng, additional, Liu, Feng, additional, Long, Joanna R., additional, Ma, Ruoyun, additional, Maes, Celine, additional, Moreno-Ortega, Marta, additional, Murray, Scott O., additional, Noah, Sean, additional, Noeske, Ralph, additional, Noseworthy, Michael D., additional, Oeltzschner, Georg, additional, Porges, Eric C., additional, Prisciandaro, James J., additional, Puts, Nicolaas A. J., additional, Roberts, Timothy P. L., additional, Sack, Markus, additional, Sailasuta, Napapon, additional, Saleh, Muhammad G., additional, Schallmo, Michael-Paul, additional, Simard, Nicholas, additional, Stoffers, Diederick, additional, Swinnen, Stephan P., additional, Tegenthoff, Martin, additional, Truong, Peter, additional, Wang, Guangbin, additional, Wilkinson, Iain D., additional, Wittsack, Hans-Jörg, additional, Woods, Adam J., additional, Xu, Hongmin, additional, Yan, Fuhua, additional, Zhang, Chencheng, additional, Zipunnikov, Vadim, additional, Zöllner, Helge J., additional, Edden, Richard A.E., additional, and Barker, Peter B., additional

Published
2020
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50. Negative valence of hallucinatory voices as predictor of cortical glutamatergic metabolite levels in schizophrenia patients.

Author

Hjelmervik, Helene, Craven, Alexander R., Johnsen, Erik, Kompus, Kristiina, Bless, Josef J., Sinkeviciute, Igne, Kroken, Rune A., Løberg, Else‐Marie, Ersland, Lars, Grüner, Renate, Sommer, Iris E., and Hugdahl, Kenneth

Subjects
*EMOTIONAL experience, *TEMPORAL lobe, *AUDITORY hallucinations, *PEOPLE with schizophrenia, *EXCITATORY amino acid agents, *NUCLEAR magnetic resonance spectroscopy, *PREFRONTAL cortex
Abstract

Objectives: Negative emotional valence of auditory verbal hallucinations (AVHs) in schizophrenia can be a source of distress and is considered a strong predictor of illness severity. Previous studies have found glutamate to mediate AVH severity in frontal and temporal brain regions, however, they do not specifically address emotional valence of AVH. The role of glutamate for the experience of negative‐ versus positive emotional valence of AVH is therefore unknown and was investigated in the current study. Methods: Using magnetic resonance spectroscopy (MRS), 37 schizophrenia patients had Glx (glutamate+glutamine) measured in the left superior temporal gyrus (STG), and additionally in the anterior cingulate cortex (ACC) and the right STG, or in the left inferior frontal gyrus (IFG). Self‐reported emotional valence in AVH was measured with the Beliefs About Voices Questionnaire (BAVQ‐R). Results: Results from linear mixed models showed that negative emotional valence was associated with reduced Glx levels across all four measured brain regions in the frontal and temporal lobe. More specifically, voices that were experienced to be omnipotent (p = 0.04) and that the patients attempted to resist (p = 0.04) were related to lower Glx levels. Follow‐up analysis of the latter showed that voices that evoked emotional resistance (i.e., fear, sadness, anger), rather than behavioral resistance, was a significant predictor of reduced glutamate (p = 0.02). Conclusion: The findings could indicate aberrant glutamatergic signaling, or increased NMDA‐receptor hypoactivity in patients who experience their voices to be more emotionally negative. Overall, the study provides support for the glutamate hypothesis of schizophrenia. [ABSTRACT FROM AUTHOR]

Published
2022
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