Rees, Geraint

Neural correlates of the ‘good life’: eudaimonic well-being is associated with insular cortex volume

Lewis, G. J., Kanai, R., Rees, G., & Bates, T. C. (2014) · Social Cognitive and Affective Neuroscience

Psychological Well-being and Life SatisfactionNeurotransmitter Receptor Influence on Behavior

Cited by 157

Primary visual cortex activation on the path of apparent motion is mediated by feedback from hMT+/V5

Sterzer, P., Haynes, J.-D., & Rees, G. (2006) · NeuroImage

Visual perception and processing mechanismsMultisensory perception and integration

Cited by 156

Atypical intrinsic neural timescale in autism

Watanabe, T., Rees, G., & Masuda, N. (2019) · eLife

Autism Spectrum Disorder ResearchFunctional Brain Connectivity Studies

Cited by 150

Larger extrastriate population receptive fields in autism spectrum disorders

Schwarzkopf, D. S., Anderson, E. J., de Haas, B., White, S. J., & Rees, G. (2014) · The Journal of Neuroscience

Autism Spectrum Disorder ResearchVisual perception and processing mechanisms

Cited by 138

The cutaneous rabbit illusion affects human primary sensory cortex somatotopically

Blankenburg, F., Ruff, C. C., Deichmann, R., Rees, G., & Driver, J. (2006) · PLoS Biology

Tactile and Sensory InteractionsMultisensory perception and integration

Cited by 131

What failure in collective decision-making tells us about metacognition

Bahrami, B., Olsen, K., Bang, D., Roepstorff, A., Rees, G., & Frith, C. (2012) · Philosophical Transactions of the Royal Society B: Biological Sciences

Visual perception and processing mechanismsMultisensory perception and integration

Cited by 118

The default network and the combination of cognitive processes that mediate self-generated thought

Axelrod, V., Rees, G., & Bar, M. (2017) · Nature Human Behaviour

Functional Brain Connectivity StudiesMind wandering and attention

Cited by 111

Extra-classical receptive field effects measured in striate cortex with fMRI

Harrison, L. M., Stephan, K. E., Rees, G., & Friston, K. J. (2007) · NeuroImage

Visual perception and processing mechanismsFace Recognition and Perception

Cited by 89

Noradrenaline blockade specifically enhances metacognitive performance

Hauser, T. U., Allen, M., Purg, N., Moutoussis, M., Rees, G., & Dolan, R. J. (2017) · eLife

Visual perception and processing mechanismsNeural and Behavioral Psychology Studies

Cited by 87

Metacognitive ability correlates with hippocampal and prefrontal microstructure

Allen, M., Glen, J. C., Müllensiefen, D., Schwarzkopf, D. S., Fardo, F., Frank, D., Callaghan, M. F., & Rees, G. (2017) · NeuroImage

Advanced Neuroimaging Techniques and ApplicationsNeural and Behavioral Psychology Studies

Cited by 85

In vivo characterization of white matter pathology in premanifest huntington's disease

Zhang, J., Gregory, S., Scahill, R. I., Durr, A., Thomas, D. L., Lehericy, S., Rees, G., Tabrizi, S. J., Zhang, H., & the TrackOn‐HD investigators (2018) · Annals of Neurology

Advanced Neuroimaging Techniques and ApplicationsGenetic Neurodegenerative Diseases

Cited by 80

A striking reduction of simple loudness adaptation in autism

Lawson, R. P., Aylward, J., White, S., & Rees, G. (2015) · Scientific Reports

Autism Spectrum Disorder ResearchHearing, Cochlea, Tinnitus, Genetics

Cited by 67

Psychosis and the Experience of Self: Brain Systems Underlying Self‐Monitoring

FRITH, C., REES, G., & FRISTON, K. (1998) · Annals of the New York Academy of Sciences

Schizophrenia research and treatmentMental Health and Psychiatry

Cited by 45

A more precise look at context in autism

Lawson, R. P., Friston, K. J., & Rees, G. (2015) · Proceedings of the National Academy of Sciences

Autism Spectrum Disorder ResearchGenetics and Neurodevelopmental Disorders

Cited by 41

Neuroanatomical correlates of visual car expertise

Gilaie-Dotan, S., Harel, A., Bentin, S., Kanai, R., & Rees, G. (2012) · NeuroImage

Visual perception and processing mechanismsFace Recognition and Perception

Cited by 36

Developing Deep Learning Continuous Risk Models for Early Adverse Event Prediction in Electronic Health Records: an AKI Case Study

Tomašev, N., Glorot, X., Rae, J. W., Zielinski, M., Askham, H., Saraiva, A., Mottram, A., Meyer, C., Ravuri, S., Protsyuk, I., et al. (2019) · Research Square

Machine Learning in HealthcareAcute Kidney Injury Research

Cited by 3