8 results on '"Cunningham, A.C."'
Search Results
2. Measuring interoception: The phase adjustment task
- Author
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Plans, D., Ponzo, S., Morelli, D., Cairo, M., Ring, C., Keating, C.T., Cunningham, A.C., Catmur, C., Murphy, J., and Bird, G.
- Published
- 2021
- Full Text
- View/download PDF
3. Overcoming crosstalk in luminescence images of mineral grains
- Author
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Cunningham, A.C. and Clark-Balzan, L.
- Published
- 2017
- Full Text
- View/download PDF
4. Effects of copy number variations on brain structure and risk for psychiatric illness: Large-scale studies from the ENIGMA working groups on CNVs
- Author
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Sønderby, I.E., Ching, CRK, Thomopoulos, S.I., van der Meer, D., Sun, D., Villalon-Reina, J.E., Agartz, I., Amunts, K., Arango, C., Armstrong, N.J., Ayesa-Arriola, R., Bakker, G., Bassett, A.S., Boomsma, D.I., Bülow, R., Butcher, N.J., Calhoun, V.D., Caspers, S., Chow, EWC, Cichon, S., Ciufolini, S., Craig, M.C., Crespo-Facorro, B., Cunningham, A.C., Dale, A.M., Dazzan, P., de Zubicaray, G.I., Djurovic, S., Doherty, J.L., Donohoe, G., Draganski, B., Durdle, C.A., Ehrlich, S., Emanuel, B.S., Espeseth, T., Fisher, S.E., Ge, T., Glahn, D.C., Grabe, H.J., Gur, R.E., Gutman, B.A., Haavik, J., Håberg, A.K., Hansen, L.A., Hashimoto, R., Hibar, D.P., Holmes, A.J., Hottenga, J.J., Hulshoff Pol, H.E., Jalbrzikowski, M., Knowles, EEM, Kushan, L., Linden, DEJ, Liu, J., Lundervold, A.J., Martin-Brevet, S., Martínez, K., Mather, K.A., Mathias, S.R., McDonald-McGinn, D.M., McRae, A.F., Medland, S.E., Moberget, T., Modenato, C., Monereo Sánchez, J., Moreau, C.A., Mühleisen, T.W., Paus, T., Pausova, Z., Prieto, C., Ragothaman, A., Reinbold, C.S., Reis Marques, T., Repetto, G.M., Reymond, A., Roalf, D.R., Rodriguez-Herreros, B., Rucker, J.J., Sachdev, P.S., Schmitt, J.E., Schofield, P.R., Silva, A.I., Stefansson, H., Stein, D.J., Tamnes, C.K., Tordesillas-Gutiérrez, D., Ulfarsson, M.O., Vajdi, A., van 't Ent, D., van den Bree, MBM, Vassos, E., Vázquez-Bourgon, J., Vila-Rodriguez, F., Walters, G.B., Wen, W., Westlye, L.T., Wittfeld, K., Zackai, E.H., Stefánsson, K., Jacquemont, S., Thompson, P.M., Bearden, C.E., Andreassen, O.A., ENIGMA-CNV Working Group, ENIGMA 22q11.2 Deletion Syndrome Working Group, Bernard, M., Blackburn, N.B., Bøen, R., de Geus, E., de Zwarte, SMC, Forti, M.D., Frei, O., Fukunaga, M., Hehir-Kwa, J.Y., Hillegers, MHJ, Hoffmann, P., Homuth, G., Jahanshad, N., Koops, S., Kumar, K., Kikuchi, M., Le Hellard, S., Leu, C., Murray, R.M., Naerland, T., Nyberg, L., Ophoff, R.A., Pike, G.B., Sando, S.B., Shin, J., Shumskaya, E., Sisodiya, S.M., Steen, V.M., Teumer, A., Uhlmann, A., Wright, M.J., Antshel, K.M., Campbell, L.E., Crossley, N.A., Crowley, T.B., Daly, E., Fiksinski, A.M., Forsyth, J.K., Fremont, W., Goodrich-Hunsaker, N.J., Gudbrandsen, M., Jonas, R.K., Kates, W.R., Lin, A., McCabe, K.L., Moss, H., Murphy, D.G., Murphy, K.C., Owen, M.J., Ruparel, K., Simon, T.J., van Amelsvoort, T., and Vorstman, JAS
- Subjects
brain structural imaging ,copy number variant ,diffusion tensor imaging ,evolution ,genetics-first approach ,neurodevelopmental disorders ,psychiatric disorders - Abstract
The Enhancing NeuroImaging Genetics through Meta-Analysis copy number variant (ENIGMA-CNV) and 22q11.2 Deletion Syndrome Working Groups (22q-ENIGMA WGs) were created to gain insight into the involvement of genetic factors in human brain development and related cognitive, psychiatric and behavioral manifestations. To that end, the ENIGMA-CNV WG has collated CNV and magnetic resonance imaging (MRI) data from ~49,000 individuals across 38 global research sites, yielding one of the largest studies to date on the effects of CNVs on brain structures in the general population. The 22q-ENIGMA WG includes 12 international research centers that assessed over 533 individuals with a confirmed 22q11.2 deletion syndrome, 40 with 22q11.2 duplications, and 333 typically developing controls, creating the largest-ever 22q11.2 CNV neuroimaging data set. In this review, we outline the ENIGMA infrastructure and procedures for multi-site analysis of CNVs and MRI data. So far, ENIGMA has identified effects of the 22q11.2, 16p11.2 distal, 15q11.2, and 1q21.1 distal CNVs on subcortical and cortical brain structures. Each CNV is associated with differences in cognitive, neurodevelopmental and neuropsychiatric traits, with characteristic patterns of brain structural abnormalities. Evidence of gene-dosage effects on distinct brain regions also emerged, providing further insight into genotype-phenotype relationships. Taken together, these results offer a more comprehensive picture of molecular mechanisms involved in typical and atypical brain development. This "genotype-first" approach also contributes to our understanding of the etiopathogenesis of brain disorders. Finally, we outline future directions to better understand effects of CNVs on brain structure and behavior.
- Published
- 2022
5. Effects of copy number variations on brain structure and risk for psychiatric illness: Large‐scale studies from the ENIGMA working groups on CNVs
- Author
-
Sønderby, I.E., Ching, C.R.K., Thomopoulos, S.I., Meer, D., Sun, D., Villalon‐Reina, J.E., Agartz, I., Amunts, K., Arango, C., Armstrong, N.J., Ayesa‐Arriola, R., Bakker, G., Bassett, A.S., Boomsma, D.I., Bülow, R., Butcher, N.J., Calhoun, V.D., Caspers, S., Chow, E.W.C., Cichon, S., Ciufolini, S., Craig, M.C., Crespo‐Facorro, B., Cunningham, A.C., Dale, A.M., Dazzan, P., Zubicaray, G.I., Djurovic, S., Doherty, J.L., Donohoe, G., Draganski, B., Durdle, C.A., Ehrlich, S., Emanuel, B.S., Espeseth, T., Fisher, S.E., Ge, T., Glahn, D.C., Grabe, H.J., Gur, R.E., Gutman, B.A., Haavik, J., Håberg, A.K., Hansen, L.A., Hashimoto, R., Hibar, D.P., Holmes, A.J., Hottenga, J‐J, Hulshoff Pol, H.E., Jalbrzikowski, M., Knowles, E.E.M., Kushan, L., Linden, D.E.J., Liu, J., Lundervold, A.J., Martin‐Brevet, S., Martinez, K., Mather, K.A., Mathias, S.R., McDonald‐McGinn, D.M., McRae, A.F., Medland, S.E., Moberget, T., Modenato, C., Monereo Sánchez, J., Moreau, C.A., Mühleisen, T.W., Paus, T., Pausova, Z., Prieto, C., Ragothaman, A., Reinbold, C.S., Reis Marques, T., Repetto, G.M., Reymond, A., Roalf, D.R., Rodriguez‐Herreros, B., Rucker, J.J., Sachdev, P.S., Schmitt, J.E., Schofield, P.R., Silva, A.I., Stefánsson, H., Stein, D.J., Tamnes, C.K., Tordesillas‐Gutiérrez, D., Ulfarsson, M.O., Vajdi, A., Ent, D., Bree, M.B.M., Vassos, E., Vázquez‐Bourgon, J., Vila‐Rodriguez, F., Walters, G.B., Wen, W., Westlye, L.T., Wittfeld, K., Zackai, E.H., Stefánsson, K., Jacquemont, S., Thompson, P.M., Bearden, C.E., Andreassen, O.A., Sønderby, I.E., Ching, C.R.K., Thomopoulos, S.I., Meer, D., Sun, D., Villalon‐Reina, J.E., Agartz, I., Amunts, K., Arango, C., Armstrong, N.J., Ayesa‐Arriola, R., Bakker, G., Bassett, A.S., Boomsma, D.I., Bülow, R., Butcher, N.J., Calhoun, V.D., Caspers, S., Chow, E.W.C., Cichon, S., Ciufolini, S., Craig, M.C., Crespo‐Facorro, B., Cunningham, A.C., Dale, A.M., Dazzan, P., Zubicaray, G.I., Djurovic, S., Doherty, J.L., Donohoe, G., Draganski, B., Durdle, C.A., Ehrlich, S., Emanuel, B.S., Espeseth, T., Fisher, S.E., Ge, T., Glahn, D.C., Grabe, H.J., Gur, R.E., Gutman, B.A., Haavik, J., Håberg, A.K., Hansen, L.A., Hashimoto, R., Hibar, D.P., Holmes, A.J., Hottenga, J‐J, Hulshoff Pol, H.E., Jalbrzikowski, M., Knowles, E.E.M., Kushan, L., Linden, D.E.J., Liu, J., Lundervold, A.J., Martin‐Brevet, S., Martinez, K., Mather, K.A., Mathias, S.R., McDonald‐McGinn, D.M., McRae, A.F., Medland, S.E., Moberget, T., Modenato, C., Monereo Sánchez, J., Moreau, C.A., Mühleisen, T.W., Paus, T., Pausova, Z., Prieto, C., Ragothaman, A., Reinbold, C.S., Reis Marques, T., Repetto, G.M., Reymond, A., Roalf, D.R., Rodriguez‐Herreros, B., Rucker, J.J., Sachdev, P.S., Schmitt, J.E., Schofield, P.R., Silva, A.I., Stefánsson, H., Stein, D.J., Tamnes, C.K., Tordesillas‐Gutiérrez, D., Ulfarsson, M.O., Vajdi, A., Ent, D., Bree, M.B.M., Vassos, E., Vázquez‐Bourgon, J., Vila‐Rodriguez, F., Walters, G.B., Wen, W., Westlye, L.T., Wittfeld, K., Zackai, E.H., Stefánsson, K., Jacquemont, S., Thompson, P.M., Bearden, C.E., and Andreassen, O.A.
- Abstract
The Enhancing NeuroImaging Genetics through Meta‐Analysis copy number variant (ENIGMA‐CNV) and 22q11.2 Deletion Syndrome Working Groups (22q‐ENIGMA WGs) were created to gain insight into the involvement of genetic factors in human brain development and related cognitive, psychiatric and behavioral manifestations. To that end, the ENIGMA‐CNV WG has collated CNV and magnetic resonance imaging (MRI) data from ~49,000 individuals across 38 global research sites, yielding one of the largest studies to date on the effects of CNVs on brain structures in the general population. The 22q‐ENIGMA WG includes 12 international research centers that assessed over 533 individuals with a confirmed 22q11.2 deletion syndrome, 40 with 22q11.2 duplications, and 333 typically developing controls, creating the largest‐ever 22q11.2 CNV neuroimaging data set. In this review, we outline the ENIGMA infrastructure and procedures for multi‐site analysis of CNVs and MRI data. So far, ENIGMA has identified effects of the 22q11.2, 16p11.2 distal, 15q11.2, and 1q21.1 distal CNVs on subcortical and cortical brain structures. Each CNV is associated with differences in cognitive, neurodevelopmental and neuropsychiatric traits, with characteristic patterns of brain structural abnormalities. Evidence of gene‐dosage effects on distinct brain regions also emerged, providing further insight into genotype–phenotype relationships. Taken together, these results offer a more comprehensive picture of molecular mechanisms involved in typical and atypical brain development. This “genotype‐first” approach also contributes to our understanding of the etiopathogenesis of brain disorders. Finally, we outline future directions to better understand effects of CNVs on brain structure and behavior.
- Published
- 2021
6. Recurrence of Extreme Coastal Erosion in SE Australia Beyond Historical Timescales Inferred From Beach Ridge Morphostratigraphy
- Author
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Tamura, T., Oliver, T.S.N., Cunningham, A.C., Woodroffe, C.D., Tamura, T., Oliver, T.S.N., Cunningham, A.C., and Woodroffe, C.D.
- Abstract
Extreme storms present a major risk to coasts. Increasing populations worldwide, together with sea level rise, exacerbate concerns for coastal settlements, but the low frequency of extreme storms makes an assessment of risk difficult. In southeast Australia, the severest beach retreat on record relates to a series of extratropical cyclones in the 1970s, but the relatively short observational record hinders assessment of how frequent these events are. At Moruya in New South Wales, four decades of beach monitoring has provided new insights into response of beaches to extreme storms. We augment this recorded history with morphostratigraphic analysis of beach ridge evolution by using ground‐penetrating radar and optically stimulated luminescence dating. We find an episode of extreme retreat over 550 years, proving that the 1970s extreme event is a recurrent phenomenon. Our high‐precision morphostratigraphic analysis provides evidence with which to better plan coastal adaptation.
- Published
- 2019
7. Re-evaluating luminescence burial doses and bleaching of fluvial deposits using Bayesian computational statistics.
- Author
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Cunningham, A.C., Wallinga, J., Versendaal, Alice, Makaske, A., Middelkoop, H., Hobo, N., Cunningham, A.C., Wallinga, J., Versendaal, Alice, Makaske, A., Middelkoop, H., and Hobo, N.
- Abstract
The optically stimulated luminescence (OSL) signal from fluvial sediment often contains a remnant from the previous deposition cycle, leading to a partially bleached equivalent-dose distribution. Although identification of the burial dose is of primary concern, the degree of bleaching could potentially provide insights into sediment transport processes. However, comparison of bleaching between samples is complicated by sample-to-sample variation in aliquot size and luminescence sensitivity. Here we begin development of an age model to account for these effects. With measurement data from multi-grain aliquots, we use Bayesian computational statistics to estimate the burial dose and bleaching parameters of the single-grain dose distribution. We apply the model to 46 samples taken from fluvial sediment of Rhine branches in the Netherlands, and compare the results with environmental predictor variables (depositional environment, texture, sample depth, depth relative to mean water level, dose rate). Although obvious correlations with predictor variables are absent, there is some suggestion that the best-bleached samples are found close to the modern mean water level, and that the extent of bleaching has changed over the recent past. We hypothesise that sediment deposited near the transition of channel to overbank deposits receives the most sunlight exposure, due to local reworking after deposition. However, nearly all samples are inferred to have at least some well-bleached grains, suggesting that bleaching also occurs during fluvial transport.
- Published
- 2015
8. S.06.01 Copy number variations as risk and protective factors for schizophrenia in 22q11.2DS
- Author
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Van den Bree, M.B.M., primary, Cunningham, A.C., additional, and Owen, M.J., additional
- Published
- 2015
- Full Text
- View/download PDF
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