Graduate School of health and Medical Sciences

Foundational skills for Neuroimaging: Philosophy, Mathematics, and Statistics, and Other Essential Skills
Provider: Faculty of Health and Medical Sciences

Activity no.: 3472-17-00-00
	Enrollment deadline: 01/10/2017

Date and time	05.10.2017, at: 10:00 - 21.12.2017, at: 12:00
Regular seats	12
Course fee	3,600.00 kr.
Lecturers	Oliver Hulme
ECTS credits	2.40

Contact person	Oliver Hulme E-mail address: oliverh@drcmr.dk

Enrolment Handling/Course Organiser	PhD administration E-mail address: phdkursus@sund.ku.dk

Aim and content This course is free of charge for PhD students at Danish universities (except Copenhagen Business School). Special rules apply for research year students enrolled at Faculty of Health and Medical Sciences at UCPH. All other participants must pay the course fee. Anyone can apply for the course, but if you are not a PhD student, you will be placed on the waiting list for the course until enrollment deadline. After the deadline of enrollment, available seats will be allocated to students on the waiting list. Learning objectives A student who has met the objectives of the course will be able to: 1. Understand and articulate the basic philosophical assumptions of scientific methods, with particular emphasis on falsification, and theory testing, particularly as it applies to modern neuroimaging 2. Understand and apply basic mathematical tools from algebra to calculus 3. Understand and apply basic concepts in frequentist statistics, including hypothesis-testing, power, multiple linear regression 4. Understand and apply basic concepts in ”new statistics” with a greater emphasis on effect size estimation and confidence intervals, as well as Bayesian statistics, and to develop an understand of the limitations of the classical framework 5. Begin a programme of neuroimaging training equipped with most of the foundational skills necessary to learn effectively. Content This is a foundation skills course that provides many of the basic skills necessary to do neuroimaging research. Topics covered include philosophical foundations (inc. deduction, induction, falsification, inference), mathematical foundations (inc. algebra, matrices, calculus), statistical foundations (inc. Central limit theorem, hypothesis testing, power, linear regression, anova, confidence intervals & effect size estimation, and Bayesian statistics). Whilst it is contextualised and oriented towards neuroimaging problems, it does not include content on actual neuroimaging methods. Such methods are covered by the companion course Neuroimaging methods, which will be held in Spring 2018. If you are interested to learn neuroimaging it is highly recommended you take both courses. Participants Some programming experience with Matlab is essential. If you do not have this experience, it is possible to take video based coursera courses in Matlab alongside this course (in your own time). Familiarity with high school mathematics is recommended. As the course is explicitly designed for students from all backgrounds and training, no other prerequisites are required. Language English Form 12 x 2 hour lectures, with in-class exercises. Course director Oliver Hulme, Senior Researcher, Danish Research Centre for Magnetic Resonance, oliverh@drcmr.dk Teachers Oliver Hulme, Senior Researcher, Danish Research Centre for Magnetic Resonance + Teaching assistant Dates Beginning October 5th 2017, ending 21st December 2018 All lectures are Thursday mornings (all Thursdays in the perdiod included), between 10-12am Course location Danish Research Centre for Magnetic Resonance Pavillion 7 meeting room (upper floor) MR-forskning, Afs. 714 Copenhagen University Hospital Hvidovre Kettegard Allé 30 Registration Please register before October 1st 2017 Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules. Applications from other participants will be considered after the last day of enrolment. Note: All applicants are asked to submit invoice details in case of no-show, late cancellation or obligation to pay the course fee (typically non-PhD students). If you are a PhD student, your participation in the course must be in agreement with your principal supervisor.

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