- Maternal cerebellar gray matter volume is associated with daughters’ psychotic experience Hashimoto, Naoki, Michaels, Timothy I., Hancock, Roeland, Kusumi, Ichiro, and Hoeft, Fumiko Psychiatry and Clinical Neurosciences 2020
Aim A substantial portion of children and adolescents show subthreshold psychotic symptoms called psychotic experience (PE). Because PE shares its biological and environmental risk factors with psychotic spectrum disorders, parental neuroanatomical variation could reflect a heritable biological underpinning of PE that may predict an offspring’s PE. Methods A total of 94 participants from 35 families without a diagnosis of major neuropsychiatric disorders were examined, including 14 mother–daughter, 17 mother–son, 12 father–daughter, and 16 father–son dyads. An offspring’s PE was assessed with the Atypicality subscale of the Behavior Assessment System for Children – 2nd Edition, Self-Report of Personality form (BASCaty). We examined correlations between voxel-by-voxel parental gray matter volume and their offspring’s BASCaty score. Results Maternal cerebellar gray matter volume using voxel-based morphometry was positively correlated with their daughters’ BASCaty scores. The findings were significant in a more robust approach using cerebellum-specific normalization known. We did not find significant correlation between paternal gray matter volume and BASCaty scores or between offspring gray matter volumes and their BASCaty scores. Conclusion Expanding upon parent-of-origin effects in psychosis, maternal neuroanatomical variation was associated with daughters’ PE. The nature of this sex-specific intergenerational effect is unknown, but maternally transmitted genes may relate cerebellum development to PE pathogenesis.
- Variability in the analysis of a single neuroimaging dataset by many teams Botvinik-Nezer, Rotem, Holzmeister, Felix, Camerer, Colin F., Dreber, Anna, Huber, Juergen, Johannesson, Magnus, Kirchler, Michael, Iwanir, Roni, Mumford, Jeanette A., Adcock, R. Alison, Avesani, Paolo, Baczkowski, Blazej M., Bajracharya, Aahana, Bakst, Leah, Ball, Sheryl, Barilari, Marco, Bault, Nadège, Beaton, Derek, Beitner, Julia, Benoit, Roland G., Berkers, Ruud M. W. J., Bhanji, Jamil P., Biswal, Bharat B., Bobadilla-Suarez, Sebastian, Bortolini, Tiago, Bottenhorn, Katherine L., Bowring, Alexander, Braem, Senne, Brooks, Hayley R., Brudner, Emily G., Calderon, Cristian B., Camilleri, Julia A., Castrellon, Jaime J., Cecchetti, Luca, Cieslik, Edna C., Cole, Zachary J., Collignon, Olivier, Cox, Robert W., Cunningham, William A., Czoschke, Stefan, Dadi, Kamalaker, Davis, Charles P., Luca, Alberto De, Delgado, Mauricio R., Demetriou, Lysia, Dennison, Jeffrey B., Di, Xin, Dickie, Erin W., Dobryakova, Ekaterina, Donnat, Claire L., Dukart, Juergen, Duncan, Niall W., Durnez, Joke, Eed, Amr, Eickhoff, Simon B., Erhart, Andrew, Fontanesi, Laura, Fricke, G. Matthew, Fu, Shiguang, Galván, Adriana, Gau, Remi, Genon, Sarah, Glatard, Tristan, Glerean, Enrico, Goeman, Jelle J., Golowin, Sergej A. E., González-Garcı́a, Carlos, Gorgolewski, Krzysztof J., Grady, Cheryl L., Green, Mikella A., Guassi Moreira, João F., Guest, Olivia, Hakimi, Shabnam, Hamilton, J. Paul, Hancock, Roeland, Handjaras, Giacomo, Harry, Bronson B., Hawco, Colin, Herholz, Peer, Herman, Gabrielle, Heunis, Stephan, Hoffstaedter, Felix, Hogeveen, Jeremy, Holmes, Susan, Hu, Chuan-Peng, Huettel, Scott A., Hughes, Matthew E., Iacovella, Vittorio, Iordan, Alexandru D., Isager, Peder M., Isik, Ayse I., Jahn, Andrew, Johnson, Matthew R., Johnstone, Tom, Joseph, Michael J. E., Juliano, Anthony C., Kable, Joseph W., Kassinopoulos, Michalis, Koba, Cemal, Kong, Xiang-Zhen, Koscik, Timothy R., Kucukboyaci, Nuri Erkut, Kuhl, Brice A., Kupek, Sebastian, Laird, Angela R., Lamm, Claus, Langner, Robert, Lauharatanahirun, Nina, Lee, Hongmi, Lee, Sangil, Leemans, Alexander, Leo, Andrea, Lesage, Elise, Li, Flora, Li, Monica Y. C., Lim, Phui Cheng, Lintz, Evan N., Liphardt, Schuyler W., Losecaat Vermeer, Annabel B., Love, Bradley C., Mack, Michael L., Malpica, Norberto, Marins, Theo, Maumet, Camille, McDonald, Kelsey, McGuire, Joseph T., Melero, Helena, Méndez Leal, Adriana S., Meyer, Benjamin, Meyer, Kristin N., Mihai, Glad, Mitsis, Georgios D., Moll, Jorge, Nielson, Dylan M., Nilsonne, Gustav, Notter, Michael P., Olivetti, Emanuele, Onicas, Adrian I., Papale, Paolo, Patil, Kaustubh R., Peelle, Jonathan E., Pérez, Alexandre, Pischedda, Doris, Poline, Jean-Baptiste, Prystauka, Yanina, Ray, Shruti, Reuter-Lorenz, Patricia A., Reynolds, Richard C., Ricciardi, Emiliano, Rieck, Jenny R., Rodriguez-Thompson, Anais M., Romyn, Anthony, Salo, Taylor, Samanez-Larkin, Gregory R., Sanz-Morales, Emilio, Schlichting, Margaret L., Schultz, Douglas H., Shen, Qiang, Sheridan, Margaret A., Silvers, Jennifer A., Skagerlund, Kenny, Smith, Alec, Smith, David V., Sokol-Hessner, Peter, Steinkamp, Simon R., Tashjian, Sarah M., Thirion, Bertrand, Thorp, John N., Tinghög, Gustav, Tisdall, Loreen, Tompson, Steven H., Toro-Serey, Claudio, Torre Tresols, Juan Jesus, Tozzi, Leonardo, Truong, Vuong, Turella, Luca, Veer, Anna E., Verguts, Tom, Vettel, Jean M., Vijayarajah, Sagana, Vo, Khoi, Wall, Matthew B., Weeda, Wouter D., Weis, Susanne, White, David J., Wisniewski, David, Xifra-Porxas, Alba, Yearling, Emily A., Yoon, Sangsuk, Yuan, Rui, Yuen, Kenneth S. L., Zhang, Lei, Zhang, Xu, Zosky, Joshua E., Nichols, Thomas E., Poldrack, Russell A., and Schonberg, Tom Nature 2020
Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses1. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset2–5. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.
- Spoken language proficiency predicts print-speech convergence in beginning readers Marks, Rebecca A., Kovelman, Ioulia, Kepinska, Olga, Oliver, Myriam, Xia, Zhichao, Haft, Stephanie L., Zekelman, Leo, Duong, Priscilla, Uchikoshi, Yuuko, Hancock, Roeland, and Hoeft, Fumiko NeuroImage 2019
Learning to read transforms the brain, building on children’s existing capacities for language and visuospatial processing. In particular, the development of print-speech convergence, or the spatial overlap of neural regions necessary for both auditory and visual language processing, is critical for literacy acquisition. Print-speech convergence is a universal signature of proficient reading, yet the antecedents of this convergence remain unknown. Here we examine the relationship between spoken language proficiency and the emergence of the print-speech network in beginning readers (ages 5–6). Results demonstrate that children’s language proficiency, but not their early literacy skill, explains variance in their print-speech neural convergence in kindergarten. Furthermore, print-speech convergence in kindergarten predicts reading abilities one year later. These findings suggest that children’s language ability is a core mechanism guiding the neural plasticity for learning to read, and extend theoretical perspectives on language and literacy acquisition across the lifespan.
- Social Intelligence: The Adaptive Advantages of Nonverbal Communication Buck, Ross, Stifano, Stephen, Graham, Brett, Hancock, Roeland, and Allred, Ryan J 2019
- The Neurobiology of Dyslexia Kearns, Devin M, Hancock, Roeland, Hoeft, Fumiko, Pugh, Kenneth R, and Frost, Stephen J TEACHING Exceptional Children 2019
- Brain basis of cognitive resilience: Prefrontal cortex predicts better reading comprehension in relation to decoding Patael, Smadar, Farris, Emily A, Black, Jessica M, Hancock, Roeland, Gabrieli, JDE, Cutting, Laurie, and Hoeft, Fumiko PLOS ONE 2018
- Neurobiological bases of reading disability part I: Etiological investigations. Xia, Z.*, , \textbfHancock, R.*, , and Hoeft, Fumiko Language and Linguistics Compass 2017
- Neural Noise Hypothesis of Developmental Dyslexia \textbfHancock, R., , Pugh, Kenneth R, and Hoeft, Fumiko Trends in Cognitive Sciences 2017
- GABA editing with macromolecule suppression using an improved MEGA-SPECIAL sequence Gu, Meng, Hurd, Ralph, Noeske, Ralph, Baltusis, Laima, Hancock, Roeland, Sacchet, Matthew D, Gotlib, Ian H, Chin, Frederick T, and Spielman, Daniel M Magnetic Resonance in Medicine 2017
- Intergenerational transmission of reading and reading brain networks Hoeft, Fumiko, and \textbfHancock, R., 2017
- Possible roles for fronto-striatal circuits in reading disorder. \textbfHancock, R., , Richlan, Fabio, and Hoeft, Fumiko Neuroscience and Biobehavioral Reviews 2017
- Female-specific intergenerational transmission patterns of the human corticolimbic circuitry Yamagata, Bun, Murayama, Kou, Black, Jessica M, \textbfHancock, R., , Mimura, Masaru, Yang, Tony T, Reiss, Allan L, and Hoeft, Fumiko The Journal of neuroscience 2016
- Shared temporoparietal dysfunction in dyslexia and typical readers with discrepantly high IQ \textbfHancock, R., , Gabrieli, JDE, and Hoeft, F Trends in Neuroscience and Education 2016
- Processing Relative Clauses in Chinese: Evidence from Event-Related Potentials Xiaoxia, Sun, \textbfHancock, R., , Bever, Thomas G, Xiaoguang, Cheng, Schmidt, Lüder, and Seifert, Uwe Chinese Journal of Applied Linguistics 2016
- Universal brain signature of proficient reading: Evidence from four contrasting languages. Rueckl, Jay G, Paz-Alonso, Pedro M, Molfese, Peter J, Kuo, Wen-Jui, Bick, Atira, Frost, Stephen J, \textbfHancock, R., , Wu, Denise H, Mencl, William Einar, Duñabeitia, Jon Andoni, Lee, Jun-Ren, Oliver, Myriam, Zevin, Jason D, Hoeft, Fumiko, Carreiras, Manuel, Tzeng, Ovid J L, Pugh, Kenneth R, and Frost, Ram Proceedings of the National Academy of Sciences of the United States of America 2015
- U.S. Patent No 8306356B1 Bever, Thomas G, Nicholas, C D, \textbfHancock, R., , and Alcock, K W 2014
- Neuroimaging correlations of handwriting quality as children learn to read and write Gimenez, Paul, Bugescu, Nicolle, Black, Jessica, \textbfHancock, R., , Pugh, Kenneth, Nagamine, Masanori, Kutner, Emily, Mazaika, Paul, Hendren, Robert, McCandliss, Bruce, and Hoeft, Fumiko Frontiers in Human Neuroscience 2014
- White matter morphometric changes uniquely predict children’s reading acquisition. Myers, Chelsea A, Vandermosten, Maaike, Farris, Emily A, \textbfHancock, R., , Gimenez, Paul, Black, Jessica M, Casto, Brandi, Drahos, Miroslav, Tumber, Mandeep, Hendren, Robert L, Hulme, Charles, and Hoeft, Fumiko Psychological Science 2014
- The study of syntactic cycles as an experimental science \textbfHancock, R., , and Bever, Thomas G 2009
- Partitions and parameters Hancock, R., and Bever, Thomas G In 31st annual meeting of the Deutsche Gesellschaft für Sprachwissenschaft, Osnabrück, Germany.[March 4-6, 2009] 2009
- Language as ergonomic perfection Piattelli-Palmarini, Massimo, \textbfHancock, R., , and Bever, Thomas G Behavioral and Brain Sciences 2008