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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

  • Ball, G, Stokes, PR, Rhodes, RA, Bose, SK, Rezek, I, Wink, A-M, Lord, L-D, Mehta, MA, Grasby, PM, Turkheimer, FE. Executive Functions and Prefrontal Cortex: A Matter of Persistence?. Frontiers in Systems Neuroscience 5: 3 2024
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  • Braga, RM, Roze, E, Ball, G, Merchant, N, Tusor, N, Arichi, T, Edwards, D, Rueckert, D, Counsell, SJ. Development of the Corticospinal and Callosal Tracts from Extremely Premature Birth up to 2 Years of Age. PLOS ONE 10(5) : e0125681 2024
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  • Adamson, CL, Alexander, B, Ball, G, Beare, R, Cheong, JLY, Spittle, AJ, Doyle, LW, Anderson, PJ, Seal, ML, Thompson, DK. Parcellation of the neonatal cortex using Surface-based Melbourne Children’s Regional Infant Brain atlases (M-CRIB-S). Scientific Reports 10(1) : 4359 2024
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  • Ball, G, Kelly, CE, Beare, R, Seal, ML. Individual variation underlying brain age estimates in typical development. 2024
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  • Arnatkevičiūtė, A, Fulcher, BD, Oldham, S, Tiego, J, Paquola, C, Gerring, Z, Aquino, K, Hawi, Z, Johnson, B, Ball, G, et al. Genetic influences on hub connectivity of the human connectome. 2024
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