Global, Voxel and Cluster Tests, by Theory and Permutation, for a Difference Between Two Groups of Structural MR Images of the Brain. - Edward T. Bullmore; John Suckling; Stephan Overmeyer; Sophia Rabe-Hesketh; Eric Taylor; Michael J. Brammer (IEEE Trans. Medical Imaging, 1999)

A Functional Magnetic Resonance Imaging Study of Overt Letter Verbal Fluency Using a Clustered Acquisition Sequence: Greater Anterior Cingulate Activation with Increased Task Demand. - Cynthia H. Y. Fu; Kevin Morgan; John Suckling; Steven C. R. Williams; Christopher Andrew; Goparlen N. Vythelingum; Philip K. McGuire (NeuroImage, 2002)

Effects of Verbal Working Memory Load on Corticocortical Connectivity Modeled by Path Analysis of Functional Magnetic Resonance Imaging Data. - Garry Honey; Cynthia H. Y. Fu; Jieun Kim; Michael J. Brammer; T. J. Croudace; John Suckling; E. M. Pich; Steven C. R. Williams; Edward T. Bullmore (NeuroImage, 2002)

GABAergic inhibitory mechanisms for repetition-adaptivity in large-scale brain systems. - C. M. E. Stephenson; John Suckling; Sharon Dirckx; C. Ooi; P. J. McKenna; R. Bisbrown-Chippendale; R. W. Kerwin; John D. Pickard; Edward T. Bullmore (NeuroImage, 2003)

Fractional Gaussian noise, functional MRI and Alzheimer's disease. - Voichita Maxim; Levent Sendur; Jalal Fadili; John Suckling; Rebecca L. Gould; Robert J. Howard; Ed Bullmore (NeuroImage, 2005)

Variable precision registration via wavelets: Optimal spatial scales for inter-subject registration of functional MRI. - John Suckling; Christopher J. Long; Christina Triantafyllou; Michael J. Brammer; Edward T. Bullmore (NeuroImage, 2006)

Frequency based mutual information measures between clusters of brain regions in functional magnetic resonance imaging. - Raymond Salvador; Angel Martinez-Perez; Edith Pomarol-Clotet; Salvador Sarró; John Suckling; Edward T. Bullmore (NeuroImage, 2007)

Resampling methods for improved wavelet-based multiple hypothesis testing of parametric maps in functional MRI. - Levent Sendur; John Suckling; Brandon J. Whitcher; Ed Bullmore (NeuroImage, 2007)

Modulation of the fractal properties of low frequency endogenous brain oscillations in functional MRI by a working memory task. - Anna Barnes; Garry Honey; Alle Meije Wink; Edward T. Bullmore; John Suckling (IJCNN, 2008)

Standardized structural magnetic resonance imaging in multicentre studies using quantitative T1 and T2 imaging at 1.5 T. - Sean C. L. Deoni; Steven C. R. Williams; Peter Jezzard; John Suckling; Declan G. M. Murphy; Derek K. Jones (NeuroImage, 2008)

CamBAfx: workflow design, implementation and application for neuroimaging. - Cinly Ooi; Edward T. Bullmore; Alle Meije Wink; Levent Sendur; Anna Barnes; Sophie Achard; John Aspden; Sanja Abbott; Shigang Yue; Manfred G. Kitzbichler; David Meunier; Voichita Maxim; et al. (Frontiers Neuroinformatics, 2009)

Generic aspects of complexity in brain imaging data and other biological systems. - Ed Bullmore; Anna Barnes; Danielle S. Bassett; Alex Fornito; Manfred G. Kitzbichler; David Meunier; John Suckling (NeuroImage, 2009)

Shared Neural Circuits for Mentalizing about the Self and Others. - Michael V. Lombardo; Bhismadev Chakrabarti; Edward T. Bullmore; Sally J. Wheelwright; Susan A. Sadek; John Suckling; Simon Baron-Cohen (J. Cogn. Neurosci., 2010)

A comparison of permutation and parametric testing for between group effective connectivity differences using DCM. - Nia Goulden; Shane McKie; John Suckling; Stephen Ross Williams; Ian Muir Anderson; John Francis William Deakin; Rebecca Elliott (NeuroImage, 2010)

Assessment of the impact of the scanner-related factors on brain morphometry analysis with Brainvisa. - Mahsa Shokouhi; Anna Barnes; John Suckling; Thomas W. J. Moorhead; David Brennan; Dominic Job; G. Katherine S. Lymer; Paola Dazzan; Tiago Reis Marques; Clare E. Mackay; Shane McKie; Steven C. R. Williams; et al. (BMC Medical Imaging, 2011)

Intrinsic Curvature: a Marker of Millimeter-Scale Tangential cortico-Cortical Connectivity? - Lisa Ronan; Rudolph Pienaar; Guy B. Williams; Edward T. Bullmore; Tim J. Crow; Neil Roberts; Peter B. Jones; John Suckling; Paul C. Fletcher (Int. J. Neural Syst., 2011)

Sample Size Estimation for Comparing Parameters Using Dynamic Causal Modeling. - Nia Goulden; Rebecca Elliott; John Suckling; Stephen Ross Williams; John Francis William Deakin; Shane McKie (Brain Connect., 2012)

Multifractal characterisation of electrocardiographic RR and QT time-series before and after progressive exercise. - M. J. Lewis; A. L. Short; John Suckling (Comput. Methods Programs Biomed., 2012)

Neuregulin-1 genotype is associated with structural differences in the normal human brain. - Anna Barnes; Matti Isohanni; Jennifer H. Barnett; Olli Pietiläinen; Juha Veijola; Jouko Miettunen; Tiina Paunio; Päivikki Tanskanen; Khanum Ridler; John Suckling; Edward T. Bullmore; Peter B. Jones; et al. (NeuroImage, 2012)

Individual differences in brain structure underpin empathizing-systemizing cognitive styles in male adults. - Meng-Chuan Lai; Michael V. Lombardo; Bhismadev Chakrabarti; Christine Ecker; Susan A. Sadek; Sally J. Wheelwright; Declan G. M. Murphy; John Suckling; Edward T. Bullmore; Simon Baron-Cohen (NeuroImage, 2012)

Consistency and interpretation of changes in millimeter-scale cortical intrinsic curvature across three independent datasets in schizophrenia. - Lisa Ronan; Natalie L. Voets; Morgan G. Hough; Clare E. Mackay; Neil Roberts; John Suckling; Edward T. Bullmore; Anthony James; Paul C. Fletcher (NeuroImage, 2012)

Identifying endophenotypes of autism: a multivariate approach. - Fermín Segovia; Rosemary Holt; Michael D. Spencer; Juan Manuel Górriz; Javier Ramírez 001; Carlos García Puntonet; Christophe Phillips; Lindsay Chura; Simon Baron-Cohen; John Suckling (Frontiers Comput. Neurosci., 2014)

Structural neuroimaging correlates of allelic variation of the BDNF val66met polymorphism. - Natalie J. Forde; Lisa Ronan; John Suckling; Cathy Scanlon; Simon Neary; Laurena Holleran; Alexander Leemans; Roger Tait; Catarina Rua; Paul C. Fletcher; Ben Jeurissen; Chris M. Dodds; et al. (NeuroImage, 2014)

A wavelet method for modeling and despiking motion artifacts from resting-state fMRI time series. - Ameera X. Patel; Prantik Kundu; Mikail Rubinov; P. Simon Jones; Petra E. Vértes; Karen D. Ersche; John Suckling; Edward T. Bullmore (NeuroImage, 2014)

A Winding Road: Alzheimer's Disease Increases Circuitous Functional Connectivity Pathways. - John Suckling; Tiago Simas; Shayanti Chattopadhyay; Roger Tait; Li Su 002; Guy B. Williams; James B. Rowe; John T. O'Brien (Frontiers Comput. Neurosci., 2015)

Multivariate and repeated measures (MRM): A new toolbox for dependent and multimodal group-level neuroimaging data. - Martyn McFarquhar; Shane McKie; Richard Emsley; John Suckling; Rebecca Elliott; Stephen Ross Williams (NeuroImage, 2016)

Corrigendum to "Multivariate and repeated measures (MRM): A new toolbox for dependent and multimodal group-level neuroimaging data" [NeuroImage 132 (2016) 373-389]. - Martyn McFarquhar; Shane McKie; Richard Emsley; John Suckling; Rebecca Elliott; Stephen Ross Williams (NeuroImage, 2016)

Case-Based Statistical Learning: A Non-Parametric Implementation With a Conditional-Error Rate SVM. - Juan Manuel Górriz; Javier Ramírez 001; John Suckling; Ignacio Álvarez Illán; Andrés Ortiz García; Francisco Jesús Martínez-Murcia; Fermín Segovia; Diego Salas-Gonzalez; Shuihua Wang (IEEE Access, 2017)

A semi-supervised learning approach for model selection based on class-hypothesis testing. - Juan Manuel Górriz; Javier Ramírez 001; John Suckling; Francisco Jesús Martínez-Murcia; Ignacio Álvarez; Fermín Segovia; Andrés Ortiz 001; Diego Salas-Gonzalez; Diego Castillo-Barnes; Carlos García Puntonet (Expert Syst. Appl., 2017)

Deep Learning on Brain Images in Autism: What Do Large Samples Reveal of Its Complexity? - Matthew Leming; John Suckling (IWINAC (1), 2019)

A Machine Learning Approach to Reveal the NeuroPhenotypes of Autisms. - Juan Manuel Górriz; Javier Ramírez 001; Fermín Segovia; Francisco Jesús Martínez-Murcia; Meng-Chuan Lai; Michael V. Lombardo; Simon Baron-Cohen; John Suckling (Int. J. Neural Syst., 2019)

Normative pathways in the functional connectome. - Matthew Leming; Li Su 002; Shayanti Chattopadhyay; John Suckling (NeuroImage, 2019)

On the computation of distribution-free performance bounds: Application to small sample sizes in neuroimaging. - Juan Manuel Górriz; Javier Ramírez 001; MRC AIMS Consortium; John Suckling (Pattern Recognit., 2019)

Stochastic encoding of graphs in deep learning allows for complex analysis of gender classification in resting-state and task functional brain networks from the UK Biobank. - Matthew Leming; John Suckling (CoRR, 2020)

Single-participant structural connectivity matrices lead to greater accuracy in classification of participants than function in autism in MRI. - Matthew Leming; Simon Baron-Cohen; John Suckling (CoRR, 2020)

A connection between the pattern classification problem and the General Linear Model for statistical inference. - Juan Manuel Górriz; John Suckling (CoRR, 2020)

Ensemble Deep Learning on Large, Mixed-Site fMRI Datasets in Autism and Other Tasks. - Matthew Leming; Juan Manuel Górriz; John Suckling (Int. J. Neural Syst., 2020)

Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications. - Juan Manuel Górriz; Javier Ramírez 001; Andrés Ortiz 001; Francisco Jesús Martínez-Murcia; Fermín Segovia; John Suckling; Matthew Leming; Yu-Dong Zhang 001; José Ramón Álvarez Sánchez; Guido Bologna; María Paula Bonomini; Fernando E. Casado; et al. (Neurocomputing, 2020)

Granger causality-based information fusion applied to electrical measurements from power transformers. - Jacob Rodriguez-Rivero; Javier Ramírez 001; Francisco Jesús Martínez-Murcia; Fermín Segovia; Andrés Ortiz 001; Diego Salas-Gonzalez; Diego Castillo-Barnes; Ignacio Álvarez Illán; Carlos García Puntonet; Carmen Jimenez-Mesa; F. J. Leiva; S. Carillo; et al. (Inf. Fusion, 2020)

Deep Learning in current Neuroimaging: a multivariate approach with power and type I error control but arguable generalization ability. - Carmen Jimenez-Mesa; Javier Ramírez 001; John Suckling; Jonathan Vöglein; Johannes Levin; Juan Manuel Górriz; Alzheimer's Disease Neuroimaging Initiative; Dominantly Inherited Alzheimer Network (DIAN) (CoRR, 2021)

Statistical Agnostic Mapping: A framework in neuroimaging based on concentration inequalities. - Juan Manuel Górriz; Carmen Jimenez-Mesa; Rafael Romero-Garcia; Fermín Segovia; Javier Ramírez 001; Diego Castillo-Barnes; Francisco Jesús Martínez-Murcia; Andrés Ortiz 001; Diego Salas-Gonzalez; Ignacio Álvarez Illán; Carlos García Puntonet; David López-García; et al. (Inf. Fusion, 2021)

Deep learning for sex classification in resting-state and task functional brain networks from the UK Biobank. - Matthew Leming; John Suckling (NeuroImage, 2021)

A hypothesis-driven method based on machine learning for neuroimaging data analysis. - Juan Manuel Górriz; Rubén Martín-Clemente; Carlos García Puntonet; Andrés Ortiz 001; Javier Ramírez 001; John Suckling (Neurocomputing, 2022)

A Connection Between Pattern Classification by Machine Learning and Statistical Inference With the General Linear Model. - J. M. Górriz; Carmen Jimenez-Mesa; Fermín Segovia; Javier Ramírez 001; John Suckling (IEEE J. Biomed. Health Informatics, 2022)

Inferring the Individual Psychopathologic Deficits With Structural Connectivity in a Longitudinal Cohort of Schizophrenia. - Yi Sun 008; Zhe Zhang 029; Ioannis Kakkos; George K. Matsopoulos; Jingjia Yuan; John Suckling; Luoyi Xu; Shuxia Cao; Wenjuan Chen; Xingyue Hu; Tao Li; Kang Sim; et al. (IEEE J. Biomed. Health Informatics, 2022)

A 3D explainability framework to uncover learning patterns and crucial sub-regions in variable sulci recognition. - Michail Mamalakis; Héloïse de Vareilles; Atheer AI-Manea; Samantha C. Mitchell; Ingrid Agartz; Lynn Egeland Morch-Johnsen; Jane R. Garrison; Jon S. Simons; Pietro Lio; John Suckling; Graham K. Murray (CoRR, 2023)

A non-parametric statistical inference framework for Deep Learning in current neuroimaging. - Carmen Jimenez-Mesa; Javier Ramírez 001; John Suckling; Jonathan Vöglein; Johannes Levin; Juan Manuel Górriz (Inf. Fusion, 2023)

HUMANISE: Human-Inspired Smart Management, towards a Healthy and Safe Industrial Collaborative Robotics. - Karmele López de Ipiña; Jon Iradi; Elsa Fernández; Pilar M. Calvo; Damien Sallé; Anujan Poologaindran; Ivan Villaverde; Paul Daelman; Emilio Sánchez; Catalina Requejo; John Suckling (Sensors, 2023)

Genome-wide association study of cerebellar white matter microstructure and genetic overlap with common brain disorders. - Bang-Sheng Wu; Yi-Jun Ge; Wei Zhang 056; Shi-Dong Chen; Shitong Xiang; Ya-Ru Zhang; Ya-Nan Ou; Yu-Chao Jiang; Lan Tan; Wei Cheng 002; John Suckling; Jianfeng Feng; et al. (NeuroImage, 2023)

Computational approaches to Explainable Artificial Intelligence: Advances in theory, applications and trends. - J. M. Górriz; I. Álvarez Illán; Agustín Álvarez-Marquina; Juan Eloy Arco; Martin Atzmüller; F. Ballarini; Emilia I. Barakova; Guido Bologna; María Paula Bonomini; Germán Castellanos-Domínguez; Diego Castillo-Barnes; S. B. Cho; et al. (Inf. Fusion, 2023)

Is K-fold cross validation the best model selection method for Machine Learning? - Juan Manuel Górriz; Fermín Segovia; Javier Ramírez 001; Andrés Ortiz 001; John Suckling (CoRR, 2024)

Statistical Agnostic Regression: a machine learning method to validate regression models. - Juan Manuel Górriz; J. Ramirez; Fermín Segovia; Francisco Jesús Martínez-Murcia; Carmen Jiménez-Mesa; John Suckling (CoRR, 2024)

Solving the enigma: Deriving optimal explanations of deep networks. - Michail Mamalakis; Antonios Mamalakis; Ingrid Agartz; Lynn Egeland Mørch-Johnsen; Graham K. Murray; John Suckling; Pietro Lio (CoRR, 2024)

Contrastive-Adversarial and Diffusion: Exploring pre-training and fine-tuning strategies for sulcal identification. - Michail Mamalakis; Héloïse de Vareilles; Shun-Chin Jim Wu; Ingrid Agartz; Lynn Egeland Mørch-Johnsen; Jane R. Garrison; Jon S. Simons; Pietro Lio; John Suckling; Graham K. Murray (CoRR, 2024)

The Explanation Necessity for Healthcare AI. - Michail Mamalakis; Héloïse de Vareilles; Graham K. Murray; Pietro Lio; John Suckling (CoRR, 2024)

Solving the enigma: Enhancing faithfulness and comprehensibility in explanations of deep networks. - Michail Mamalakis; Antonios Mamalakis; Ingrid Agartz; Lynn Egeland Mørch-Johnsen; Graham K. Murray; John Suckling; Pietro Lio (AI Open, 2025)

Uncovering Neuroimaging Biomarkers of Brain Tumor Surgery with AI-Driven Methods. - Carmen Jimenez-Mesa; Yizhou Wan; Guilio Sansone; Francisco Jesús Martínez-Murcia; Javier Ramírez 001; Pietro Lio; Juan Manuel Górriz; Stephen J. Price; John Suckling; Michail Mamalakis (CoRR, 2025)