MATLAB Applied to Neuronal Data

6 EC

Semester 1, period 2

5234MATN6Y

Owner Master Biomedical Sciences
Coordinator C.A. Bosman Vittini
Part of Master Biomedical Sciences, track Cognitive Neurobiology and Clinical Neurophysiology, year 1

Course manual 2016/2017

Course content

Research in contemporary neuroscience requires a solid foundation in data analysis. Data analysis in Neuroscience heavily relies on the ability to use proper software for analysis, as MATLAB. The purpose of this course is to give the students an overview of the advanced analytical techniques currently used in cognitive neuroscience, to provide computational programming skills to implement these analytical techniques using the computational software MATLAB and to use these algorithms to analyze real neuroscientific data

Study materials

Literature

  • Attaway, Stormy. Matlab: a practical introduction to programming and problem solving. Butterworth-Heinemann, 2013.

Practical training material

Software

  • http://fieldtrip.fcdonders.nl
  • http://nl.mathworks.com/

Objectives

At the end of the course, the student is able to:

  •  describe the formal aspects of basic and advanced methods of statistical inference testing
  •  actively judge what type of different analytical methodologies can be used in different neuroscientific problems
  •  use basic programming MATLAB tools to analysis neuronal data
  •  apply MATLAB programming tools and being able to solve problems based on these learning objectives
  •  understand MATLAB code programmed by others to analyze neuronal data

Teaching methods

  • Lecture
  • Computer lab session/practical training
  • Self-study
  • Supervision/feedback meeting
  • Seminar

Learning activities

Activity

Number of hours

Computerpracticum

56

Hoorcollege

18

Tentamen

2

Vragenuur

2

Werkcollege

 6

Zelfstudie

78

Attendance

The programme does not have requirements concerning attendance (OER-B).


Additional requirements for this course:

Assessment

Item and weight Details Remarks

Final grade

40%

Tentamen

Must be ≥ 6

60%

Report Assignments

Must be ≥ 6Assignments are required to be delivered in due time to obtain a proper grade

Inspection of assessed work

The manner of inspection will be communicated via the digitial learning environment.

Assignments

Report Computer Practical LFP Analyses

  • A report about the activities developed during the first week of the course

Report Computer Practical Spike Analyses

  • A report about the activities developed during the second week of the course

Report Computer Practical Calcium Imaging

  • A report about the activities developed during the third week of the course

Onderstaande opdrachten komen aan bod in deze cursus:

  •    Naam opdracht 1 : beschrijving 2
  •    Naam opdracht 2 : beschrijving 1
  •    ....

Fraud and plagiarism

Dit vak hanteert de algemene ‘Fraude- en plagiaatregeling’ van de UvA. Onder plagiaat of fraude wordt verstaan het overschrijven van het werk van een medestudent dan wel het kopiëren van wetenschappelijke bronnen (uit bijvoorbeeld boeken en tijdschriften en van het Internet) zonder daarbij de bron te vermelden. Uiteraard is plagiaat verboden. Hier wordt nauwkeurig op gecontroleerd en streng tegen opgetreden. Bij verdenking van plagiaat wordt de examencommissie van de opleiding ingeschakeld. Wanneer de examencommissie overtuigd is dat er plagiaat gepleegd is dan kan dit maximaal leiden tot een uitsluiting van al het onderwijs van de opleiding voor een heel kalenderjaar. Zie voor meer informatie over het fraude- en plagiaatreglement van de Universiteit van Amsterdam.www.uva.nl/plagiaat

Course structure

Weeknummer Onderwerpen Studiestof
1
2
3
4
5
6
7
8

Additional information

Prior basic programming courses during bachelor (MATLAB, C++ or R) is desirable (not required)

Contact information

Coordinator

  • C.A. Bosman Vittini