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Details

Role Senior Research Fellow
Research area Clinical Sciences

Contact

Available for student supervision
Studying brain development from the time of birth, through childhood and into adolescence.

Dr Ball's research combines Magnetic Resonance Imaging, bioinformatics and state-of-the-art machine learning models to discover the patterns that underlie typical brain development and identify the mechanisms that can lead to common neurodevelopmental disorders such as autism or ADHD. He is particularly interested in the impact of preterm birth on early brain development, and the long-term effects of early life adversity on a child's cognitive and functional outcomes.

Other aspects of Dr Ball's research program focus on the application of machine learning to identify abnormal movement patterns in infants at risk of developing cerebral palsy, the characterisation of pathological tissue types in paediatric brain tumour and modelling of structural connectivity networks in the brain.

Available projects include:
- Mapping cortical networks in the developing brain
- Modelling infant movements using video capture
- Combining neuroimaging and transcriptomics to model cortical development
Studying brain development from the time of birth, through childhood and into adolescence.

Dr Ball's research combines Magnetic Resonance Imaging, bioinformatics and state-of-the-art machine learning models to discover the patterns that underlie...
Studying brain development from the time of birth, through childhood and into adolescence.

Dr Ball's research combines Magnetic Resonance Imaging, bioinformatics and state-of-the-art machine learning models to discover the patterns that underlie typical brain development and identify the mechanisms that can lead to common neurodevelopmental disorders such as autism or ADHD. He is particularly interested in the impact of preterm birth on early brain development, and the long-term effects of early life adversity on a child's cognitive and functional outcomes.

Other aspects of Dr Ball's research program focus on the application of machine learning to identify abnormal movement patterns in infants at risk of developing cerebral palsy, the characterisation of pathological tissue types in paediatric brain tumour and modelling of structural connectivity networks in the brain.

Available projects include:
- Mapping cortical networks in the developing brain
- Modelling infant movements using video capture
- Combining neuroimaging and transcriptomics to model cortical development

Top Publications

  • Cusack, R, Ball, G, Smyser, CD, Dehaene-Lambertz, G. A neural window on the emergence of cognition. Annals of the New York Academy of Sciences 1369(1) : 7 -23 2016
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  • Lumsden, DE, Ashmore, J, Ball, G, Charles-Edwards, G, Selway, R, Ashkan, K, Lin, J-P. Fractional anisotropy in children with dystonia or spasticity correlates with the selection for DBS or ITB movement disorder surgery. Neuroradiology 58(4) : 401 -408 2016
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  • Chung, AW, Schirmer, MD, Krishna, ML, Ball, G, Aljabar, P, Edwards, AD, Montana, G. Characterising brain network topologies: a dynamic analysis approach using heat kernels. 2016
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  • Karolis, VR, Froudist-Walsh, S, Brittain, PJ, Kroll, J, Ball, G, Edwards, AD, Dell'Acqua, F, Williams, SC, Murray, RM, Nosarti, C. Reinforcement of the Brain's Rich-Club Architecture Following Early Neurodevelopmental Disruption Caused by Very Preterm Birth. Cerebral Cortex 26(3) : 1322 -1335 2016
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  • Estrin, GL, Kyriakopoulou, V, Makropoulos, A, Ball, G, Kuhendran, L, Chew, A, Hagberg, B, Martinez-Biarge, M, Allsop, J, Fox, M, et al. Altered white matter and cortical structure in neonates with antenatally diagnosed isolated ventriculomegaly. NeuroImage Clinical 11: 139 -148 2016
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