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DTSTAMP:20250928T123926Z
DESCRIPTION:Schedule\n\n11:30-12:00: Registration & Coffee\n	12:00-1:00 pm: 
 Lecture\, Population Neuroimaging\, Thomas Nichols\n	1:00-1:30 pm: Lunch (f
 ree)\n	1:30-2:30 pm: Tutorial on neuroimaging meta-analysis\, Thomas Nichol
 s\n	2:30-3:00 pm: Reception & coffee\n\nAbstract\n\nBrain imaging studies h
 ave traditionally struggled to break into 3-digit sample sizes: e.g.\, a r
 ecent Functional Magnetic Resonance Imaging (fMRI) meta-analysis of emotio
 n found a median sample size of n=13. However\, we now have a growing coll
 ection studies with sample sizes with 4-\, 5- and even 6-digits. Many of t
 hese 'population neuroimaging' studies are epidemiological in nature\, try
 ing to characterise typical variation in the population to help predict he
 alth outcomes across the life span. Dr Nichols will discuss some of the ch
 allenges these studies present\, in terms of massive computational burden 
 but also in ways that they expose shortcomings of existing mass univariate
  techniques. Dr Nichols will also discuss how these datasets present intri
 guing methodological problems heretofore absent from neuroimaging statisti
 cs. For example\, the 'null hypothesis fallacy' is how H0 is never strictl
 y true\, and yet with 100\,000 subjects you'll eventually find some effect
  even if it is meaningless. This motivates work spatial confidence sets on
  meaningful effect sizes (instead of thresholding test statistic images)\,
  providing intuitive measures of spatial uncertainty.\n\nBio\n\nDr. Nichol
 s is the Professor of Neuroimaging Statistics and a Wellcome Trust Senior 
 Research Fellow in Basic Biomedical Science at the Oxford University\, Big
  Data Institute.\n\nDr Nichols is a statistician with a solitary focus on 
 modelling and inference methods for brain imaging research. He has a uniqu
 e background\, with both industrial (Director\, Modelling and Genetics\, G
 laxoSmithKline) and academic experience\, and diverse training including c
 omputer science\, cognitive neuroscience and statistics.\n\nThe focus of D
 r. Nichols work is developing modelling and inference methods for brain im
 age data. He has worked with a variety of types of data\, including Positr
 on Emission Tomography and Magneto- and Electroencephalography\, though mo
 st of his methods are motivated by Magnetic Resonance Imaging (MRI) and fu
 nctional MRI (fMRI) in particular. He has extensive experience in modellin
 g large\, complex data\, particularly known for his contributions to multi
 ple testing inference for brain imaging. He has developed methods for clin
 ical trials with imaging\, as well as methods for integrating genetic and 
 imaging data. His current research involves meta-analysis of neuroimaging 
 studies and informatics tools to make data-sharing easy and pervasive.\n\n
 \nRegister via Eventbrite - the event is free but registration is required
 .\n
DTSTART:20200121T163000Z
DTEND:20200121T200000Z
LOCATION:Jeanne Timmins Amphitheatre\, Montreal Neurological Institute\, CA
 \, QC\, Montreal\, H3A 2B4\, 3801 rue University
SUMMARY:Lecture: Modelling and inference methods for brain imaging research
URL:/hbhl/channels/event/lecture-modelling-and-inferen
 ce-methods-brain-imaging-research-304127
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