    Course module   SOWDGCN12  Category   MA (Master)  Language of instruction   English  Offered by   Radboud University; Faculty of Social Sciences; Cognitive Neuroscience;  Lecturer(s)     Academic year   2022   Period   SEM1  (05/09/2022 to 27/01/2023) 
 Starting block   SEM1  
 Course mode   fulltime  
 Remark   Please note: if you do not yet have a master's registration, you are not yet registered for the tests for this course. 
 Remarks     Registration using OSIRIS   Yes  Course open to students from other faculties   No  Preregistration   No  Waiting list   No  Placement procedure    
     
Any science becomes more mathematical as it matures. Also the field of cognitive neuroscience applies advanced mathematical techniques to investigate the psychological, computational, and neuroscientific bases of human cognition and behaviour.
The data considered in cognitive neuroscience studies are typically of a considerable complexity: multiple timeseries of haemodynamic responses recorded in numerous voxels (fMRI, PET) or electrophysiological activity recorded through many electrode channels (EEG) or sensors (MEG). Both the acquisition and analysis of such data rely on sometimes pretty sophisticated quantitative techniques. Also, increasingly, models for the neurocognitive processes underlying these data are specified at a quantitative level.
Consequently, for a basic understanding of data acquisition, analysis and modelling, some minimum amount of mathematical 'literacy' is required. The aim of this course is to provide (or refresh) such a minimal background. Both technical detail and mathematical rigor will be bypassed; instead, focus is on familiarizing the student with the basic mathematical concepts and tools to be encountered in the other courses of the master's programme and possibly to be applied in the secondyear research training.
The course also contains numerous exercises with applications of math in the broad field of cognitive neuroscience.



The course will start with general mathematics at –or at least not going far beyond a sound secondary school level. Topics here include: (review of) standard functions (algebraic, exponential, logarithmic, trigonometric), differentiation and function extrema, partial derivatives and multidimensional function extrema, integration. Later, more specific topics appear: introduction to differential equations, introduction to complex numbers, to the ideas of Fourier analysis, and to the basics of vector and matrix algebra.

    

 Assumed previous knowledgeThis course is for CNS students only. NonCNS students can contact Ellen Janssen (e.janssen@donders.ru.nl) or Arno Koning ( a.koning@donders.ru.nl) 
   Required materialsBlackboardAdditional book chapters plus reader supplied through Brightspace 


Recommended materialsBookApplied Calculus (4th Ed.) by HughesHallett, Gleason, Lock, Flath, et al. 
 BookLinear Algebra (Schaum’s outlines, 4th edition) by Lipschutz and Lipson. Chapters 1 and 2 are used for an introduction to vectors and matrices. 


Instructional modesAssignmentsAttendance Mandatory   Yes 
RemarkDiscussion of reading assignments and exercises to be prepared at home.
 DiscussionAttendance Mandatory   Yes 
 LectureAttendance Mandatory   Yes 

 TestsOpenquestion examTest weight   1 
Test type   Exam 
Opportunities   Block SEM1, Block SEM1 
RemarkNOTE: enrollment for a course automatically registers you for its exam. For participating in the retake, register again.
 Openquestion examTest weight   1 
Test type   Exam 
Opportunities   Block SEM1, Block SEM1 


  
 
 