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Gareth Barker

Sunderland
As seen in: Wise Men Say (Podcast), Color Research & Application, Nature, Official PlayStation Podcast, PlayStation.Blog, Frontiers, Science Magazine, Sunderland Echo, JNeurosci, Neotizen
Do loads of the things for @WiseMenSayPod.
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Articles

Reproducible human reward imaging phenotypes exhibit differential sensitivity to dopamine D2 receptor antagonism

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By Nicola Sambuco, Peter Hawkins, Pierluigi Selvaggi, Linda A. Antonucci, Alessandro Bertolino, Giuseppe Blasi, Piergiuseppe Di Palo, Luigi Grassi, Daniela Grasso, Philipp Homan, Gian Marco Leggio, Francesco Massari, Alessio Maria Monteleone, Martin Osugo, Roberta Passiatore, Alessandra Raio, Antonio Rampino, Tobias Banaschewski, Gareth Barker, Arun Bokde, Rüdiger Brühl, Sylvane Desrivières, Herta Flor, Hugh Garavan, Penny Gowland, Antoine Grigis, Andreas Heinz, Jean-Luc Martinot, Marie-Laure Paillère Martinot, Eric Artiges, Frauke Nees, Dimitri Papadopoulos Orfanos, Luise Poustka, Michael N. Smolka, Nathalie E. Holz, Nilakshi Vaidya, Henrik Walter, Robert Whelan, Gunter Schumann, IMAGEN Consortium, Oliver Howes, Mitul A Mehta, Giulio Pergola, Antonella Lupo
| Nature Verified
Abstract Human reward processing varies along cue-centric and outcome-centric axes, but the mechanistic basis of individual variation in incentive salience attribution remains incompletely characterized. Here we show, using fMRI across five cohorts (N-total = 1251; N1 = 890; N2 = 245; N3 = 34; N4 = 48; N5 = 34), two reproducible imaging phenotypes mirroring sign- and goal-tracking (ST-like, GT-like).
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Deep learning reveals a neurocomputational mechanism predicting depression risk in adolescents

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By Xin Yang, Jiaming Cao, Holly V. Moeller, Han Lu, Xiaoqian Yan, Benjamin Becker, Andreas Heinz, Barbara Sahakian, Christelle Langley, Luolong Cao, Zuo Zhang, Lauren Robinson, Nilakshi Vaidya, Jeanne M Winterer, Sinead King, Charlotte Walton, Tobias Banaschewski, Gareth Barker, Arun Bokde, Rüdiger Brühl, Herta Flor, Hugh Garavan, Penny Gowland, Antoine Grigis, Zhaoyu Zuo
| Science Magazine Verified
Abstract INTRODUCTION RESULTS DISCUSSION MATERIALS AND METHODS Acknowledgments Supplementary Materials REFERENCES Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Early detection and prevention of psychiatric disorders, particularly depression, remain as major global health challenges, yet reliable tools for identifying individuals before symptom onset are lacking.
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Brain network-based stratification of mental health disorders: design and cohort description of the STRATIFY and ESTRA studies

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By Nilakshi Vaidya, Zuo Zhang, Jeanne M Winterer, Marina Bobou, Sinead King, Lauren Robinson, Yuning Zhang, Gareth Barker, Arun Bokde, Rüdiger Brühl, Antoine Grigis, Herve Lemaitre, Frauke Nees, Dimitri Papadopoulos, Luise Poustka, Ulrike Schmidt, Julia Sinclair, Argyris Stringaris, Robert Whelan, Henrik Walter, Sylvane Desrivières, Gunter Schumann, Kofoworola Agunbiade, Georgina Keggin, Kebir Hedi, John Broulidakis, Tristam Lett
| Nature Verified
Abstract The STRATIFY (Brain Network-Based Stratification of Reinforcement-Related Disorders) and ESTRA (Eating Disorders Stratification) studies were established as harmonised “sibling” cohorts to develop a mechanistically informed framework for stratifying psychiatric disorders. Here, we describe the study design, methodology, and cohort characteristics.
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