Mrs Sonya Foley

2025

• Harrison, J. R. et al. 2025. White matter microstructure in mid- to late adulthood is influenced by pathway-stratified polygenic risk for Alzheimer’s disease. Frontiers in Neuroscience 19 1638503. (10.3389/fnins.2025.1638503)
• McNabb, C. B. et al. 2025. Controlled antenatal thyroid screening study III: effects of gestational thyroid status on brain microstructure. The Journal of Clinical Endocrinology & Metabolism 110 (12), pp.3322-3330. (10.1210/clinem/dgaf277)

2024

• Kerestes, R. et al., 2024. Patterns of subregional cerebellar atrophy across epilepsy syndromes: An ENIGMA‐Epilepsy study. Epilepsia 65 (4), pp.1072-1091. (10.1111/epi.17881)

2023

• Harrison, J. R. et al. 2023. Pathway-specific polygenic scores for Alzheimer's disease are associated with changes in brain structure in younger and older adults. Brain Communications 5 (5) fcad229. (10.1093/braincomms/fcad229)
• Messaritaki, E. et al. 2023. Increased structural connectivity in high schizotypy. Network Neuroscience 7 (1), pp.213-233. (10.1162/netn_a_00279)

2022

• Altmann, A. et al., 2022. A systems-level analysis highlights microglial activation as a modifying factor in common epilepsies. Neuropathology and Applied Neurobiology 48 (1) e12758. (10.1111/nan.12758)
• Larivière, S. et al., 2022. Structural network alterations in focal and generalized epilepsy assessed in a worldwide ENIGMA study follow axes of epilepsy risk gene expression. Nature Communications 13 (1) 4320. (10.1038/s41467-022-31730-5)
• Lopez, S. M. et al., 2022. Event‐based modeling in temporal lobe epilepsy demonstrates progressive atrophy from cross‐sectional data. Epilepsia 63 (8), pp.2081-2095. (10.1111/epi.17316)
• Mirza-Davies, A. et al. 2022. The impact of genetic risk for Alzheimer’s disease on the structural brain networks of young adults. Frontiers in Neuroscience 16 987677. (10.3389/fnins.2022.987677)
• Park, B. et al., 2022. Topographic divergence of atypical cortical asymmetry and atrophy patterns in temporal lobe epilepsy. Brain 145 (4), pp.1285-1298. (10.1093/brain/awab417)
• Zwarte, S. M. C. et al., 2022. Intelligence, educational attainment, and brain structure in those at familial high-risk for schizophrenia or bipolar disorder. Human Brain Mapping 43 (1), pp.414-430. (10.1002/hbm.25206)

2021

• Dimitriadis, S. I. et al. 2021. Genetic risk for schizophrenia is associated with altered visually-induced gamma band activity: evidence from a population sample stratified polygenic risk. Translational Psychiatry 11 592. (10.1038/s41398-021-01678-z)
• Messaritaki, E. et al. 2021. Predicting MEG resting-state functional connectivity using microstructural information. Network Neuroscience 5 (2), pp.477-504. (10.1162/netn_a_00187)

2020

• Dima, D. C. et al. 2020. Electrophysiological network alterations in adults with copy number variants associated with high neurodevelopmental risk. Translational Psychiatry 10 324. (10.1038/s41398-020-00998-w)
• Grasby, K. L. et al., 2020. The genetic architecture of the human cerebral cortex. Science 367 (6484) eaay6690. (10.1126/science.aay6690)
• Han, L. K. M. et al., 2020. Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group. Molecular Psychiatry 26 , pp.5124-5139. (10.1038/s41380-020-0754-0)
• Hatton, S. N. et al., 2020. White matter abnormalities across different epilepsy syndromes in adults: an ENIGMA-epilepsy study. Brain 143 (8), pp.2454-2473. (10.1093/brain/awaa200)
• Larivière, S. et al., 2020. Network-based atrophy modeling in the common epilepsies: a worldwide ENIGMA study. Science Advances 6 (47) eabc6457. (10.1126/sciadv.abc6457)
• Nunes, A. et al., 2020. Using structural MRI to identify bipolar disorders - 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group. Molecular Psychiatry 25 , pp.2130-2143. (10.1038/s41380-018-0228-9)

2019

• Favre, P. et al., 2019. Widespread white matter microstructural abnormalities in bipolar disorder: Evidence from mega- and meta-analyses across 3,033 individuals. Neuropsychopharmacology 44 , pp.2285-2293. (10.1038/s41386-019-0485-6)
• Favre, P. et al., 2019. Widespread white matter microstructural abnormalities in bipolar disorder: evidence from mega- and meta-analyses across 3033 individuals. Neuropsychopharmacology 44 , pp.2285-2293. (10.1038/s41386-019-0485-6)

2018

• Foley, S. F. et al. 2018. Fractional anisotropy of the uncinate fasciculus and cingulum in bipolar disorder type I, type II, their unaffected siblings and healthy controls. British Journal of Psychiatry 213 (3), pp.548-554. (10.1192/bjp.2018.101)
• Whelan, C. D. et al., 2018. Structural brain abnormalities in the common epilepsies assessed in a worldwide ENIGMA study. Brain 141 (2), pp.391-408. (10.1093/brain/awx341)
• Whittaker, J. R. et al. 2018. The functional connectivity between the nucleus accumbens and the ventromedial prefrontal cortex as an endophenotype for bipolar disorder. Biological Psychiatry 84 (11), pp.803-809. (10.1016/j.biopsych.2018.07.023)

2017

• Foley, S. F. et al. 2017. Multimodal brain imaging reveals structural differences in Alzheimer's disease polygenic risk carriers: A study in healthy young adults. Biological Psychiatry 81 (2), pp.154-161. (10.1016/j.biopsych.2016.02.033)
• Metzler-Baddeley, C. et al. 2017. Dynamics of white matter plasticity underlying working memory training: Multi-modal evidence from diffusion MRI and relaxometry. Journal of Cognitive Neuroscience 29 (9), pp.1509-1520. (10.1162/jocn_a_01127)
• Zacharopoulos, G. et al. 2017. Nonlinear associations between human values and neuroanatomy. Social Neuroscience 12 (6), pp.673-684. (10.1080/17470919.2016.1229215)

2016

• Caeyenberghs, K. et al., 2016. Dynamics of the human structural connectome underlying working memory training. Journal of Neuroscience 36 (14), pp.4056-4066. (10.1523/JNEUROSCI.1973-15.2016)
• Lancaster, T. et al. 2016. CACNA1C risk variant is associated with increased amygdala volume. European Archives of Psychiatry and Clinical Neuroscience 266 (3), pp.269-275. (10.1007/s00406-015-0609-x)
• Metzler-Baddeley, C. et al. 2016. Longitudinal data on cortical thickness before and after working memory training. Data in Brief 7 , pp.1143-1147. (10.1016/j.dib.2016.03.090)
• Metzler-Baddeley, C. et al. 2016. Task complexity and location specific changes of cortical thickness in executive and salience networks after working memory training. NeuroImage 130 , pp.48-62. (10.1016/j.neuroimage.2016.01.007)

2015

• Caseras, X. et al. 2015. Association between genetic risk scoring for schizophrenia and bipolar disorder with regional subcortical volumes. Translational Psychiatry 5 e692. (10.1038/tp.2015.195)