PSI068 Neuroimaging Techniques in PsychologyIstinye UniversityDegree Programs PsychologyGeneral Information For StudentsDiploma SupplementErasmus Policy StatementNational Qualifications
Psychology

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Bachelor TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF-LLL: Level 6

Course Introduction and Application Information

Course Code: PSI068
Course Name: Neuroimaging Techniques in Psychology
Semester: Fall
Course Credits:
ECTS
5
Language of instruction: Turkish
Course Condition:
Does the Course Require Work Experience?: No
Type of course: Departmental Elective
Course Level:
Bachelor TR-NQF-HE:6. Master`s Degree QF-EHEA:First Cycle EQF-LLL:6. Master`s Degree
Mode of Delivery: Face to face
Course Coordinator: Dr. Öğr. Üy. GÖKÇER ESKİKURT
Course Lecturer(s): Dr. Öğr. Ü. Gökçer Eskikurt
Course Assistants:

Course Objective and Content

Course Objectives: The aim of this course is to conceptually introduce the neuroimaging methods (MRI, fMRI, DTI, TMS, etc.) used in the field of neuroscience, as well as to enable students to design experiments in which they will use neuroimaging techniques to improve their practical skills and to enable them to analyze the data obtained from the experiments.
Course Content: An overview of the advantages and disadvantages of different neuroimaging methods will be given and discussed in order to understand what is the background information of neuroimaging methods such as MRI, fMRI, TMS, DTI, etc., which provide the opportunity to examine the neural basis underlying human behavior. In addition, in order to improve the students' ability to conduct independent research, basic analyzes will be made after sample data sets collected by different methods are passed through the preprocessing stages.

Learning Outcomes

The students who have succeeded in this course;
1) Will have theoretical knowledge about imaging methods in psychology
2) Will be able to choose the appropriate neuroimaging method for research questions
3) Will be able to collect data using neuroimaging methods effectively
4) Will be able to analyze the data collected in accordance with their hypotheses at a basic level

Course Flow Plan

Week Subject Related Preparation
1) Introducing of course and syllabus -
2) History of Neuroimaging Methods in Neuroscience -
3) Magnetic Resonance Imaging (MRI) Basics -
4) Functional Magnetic Resonance Imaging (fMRI) Basics -
5) Neuroimaging literature discussing -
6) Neuroimaging literature discussing -
7) Preprocessing of resting state fMRI data -
8) Connectivity analysis of resting state fMRI data -
9) Preprocessing of task-based fMRI data -
10) Midterm exam -
11) General linear model analysis of task-based fMRI data -
12) Connectivity analysis of task-based fMRI data -
13) Visualization of the neuroimaging data -
14) Presentation of student projects at the end of semester -
15) Submission of the written projects -

Sources

Course Notes / Textbooks: Hans Op de Beeck, Chie Nakatani - Introduction to Human Neuroimaging (2019)
References: Opensesame, MRICron, Xjview, MRIConvert, dcm2niix, Matlab yazılımları

Course - Program Learning Outcome Relationship

Course Learning Outcomes

1

2

3

4

Program Outcomes
1) Have the theoretical knowledge in major sub areas of psychology. 3 2 1 1
2) Apply psychological consepts and theories in a variety of applied settings 3 2 2 1
3) Identify and explain the cognitive, emotional and behavioral processes of human. 1 1 1 1
4) Evaluate evidence and assumptions in a scientific and critical view. 1 1 3 3
5) Collect and analyze the research data and report the findings in accordance to ethical publication rules. 1 3 3 3
6) Develop and utilize measurement tools for psychological phenomena. 1 3 3 3
7) Have the skills and abilities to follow advances in psyhology and other related sciences. 2 3 3 3
8) Have the skills and abilities to work effectively on individual and group based. 3 3 3 3
9) Have the skills and abilities to communicate in a clear and effective manner in national and international settings. 1 1 1 1
10) Behave in accordance to the professional code of ethics applied to psychology. 1 2 3 3
11) Be unprejudiced and equal to various identity groups based on such as age, gender, language, race, religion and social class in scientific and professional acitivities. 1 1 1 1
12) Have enhanced awareness of universal values as well as human and animal rights. 1 1 1 1
13) Master a foreign language at least B1 level of European Language Portfolio. 1 1 1 1
14) Master the computer softwares within information and communication technologies at least European computer driving licence. 3 3 3 3

Course - Learning Outcome Relationship

No Effect 1 Lowest 2 Average 3 Highest
       
Program Outcomes Level of Contribution
1) Have the theoretical knowledge in major sub areas of psychology. 3
2) Apply psychological consepts and theories in a variety of applied settings 3
3) Identify and explain the cognitive, emotional and behavioral processes of human. 2
4) Evaluate evidence and assumptions in a scientific and critical view. 3
5) Collect and analyze the research data and report the findings in accordance to ethical publication rules. 3
6) Develop and utilize measurement tools for psychological phenomena. 3
7) Have the skills and abilities to follow advances in psyhology and other related sciences. 2
8) Have the skills and abilities to work effectively on individual and group based. 3
9) Have the skills and abilities to communicate in a clear and effective manner in national and international settings. 1
10) Behave in accordance to the professional code of ethics applied to psychology. 2
11) Be unprejudiced and equal to various identity groups based on such as age, gender, language, race, religion and social class in scientific and professional acitivities. 1
12) Have enhanced awareness of universal values as well as human and animal rights. 1
13) Master a foreign language at least B1 level of European Language Portfolio. 1
14) Master the computer softwares within information and communication technologies at least European computer driving licence. 3

Assessment & Grading

Semester Requirements Number of Activities Level of Contribution
Project 1 % 60
Midterms 1 % 40
total % 100
PERCENTAGE OF SEMESTER WORK % 100
PERCENTAGE OF FINAL WORK %
total % 100

Workload and ECTS Credit Calculation

Activities Number of Activities Workload
Course Hours 14 28
Application 14 14
Study Hours Out of Class 14 70
Project 1 3
Total Workload 115