Course Description
| Course | Code | Semester | T+P (Hour) | Credit | ECTS |
|---|---|---|---|---|---|
| FUNCTIONAL NEUROIMAGING | - | Spring Semester | 2+2 | 3 | 8 |
| Course Program |
| Prerequisites Courses | |
| Recommended Elective Courses |
| Language of Course | Turkish |
| Course Level | Third Cycle (Doctorate Degree) |
| Course Type | Elective |
| Course Coordinator | Prof.Dr. Lütfü HANOĞLU |
| Name of Lecturer(s) | Prof.Dr. Lütfü HANOĞLU, Prof.Dr. Gürkan ÖZTÜRK, Prof.Dr. Ertuğrul KILIÇ, Prof.Dr. Zübeyir BAYRAKTAROĞLU |
| Assistant(s) | |
| Aim | To provide neuroscience students with information about the basic principles of functional magnetic resonance imaging and functional near infrared beam spectroscopy techniques, their use in research and clinic, and the latest studies, learning and applying resting state fMRI analysis with FSL software tools, analyzing fNIRS data analyzes with Homer3 program. is to be learned and applied. |
| Course Content | This course contains; Introduction to Functional Neuroimaging,Fundamentals of Image Processing,Introduction to fMRI Analysis,Preprocessing of fMRI data,Spatial Normalization,Statistical Modeling,Statistical Inferences from Images ,Visualization, localization and reporting of fMRI Data,Resting State Networks,Resting State Networks 2,Human Connectome Project,Installing the Homer Program, converting the data file extension and opening the data in the program ,Preprocessing of fNIRS data in Homer ,Converting fNIRS data to numerical data in Homer Program, performing statistical analysis and visualization in Atlas Viewer program. |
| Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
| Resting state is recognized by the Functional Magnetic Resonance Imaging (fMRI) method. | 17, 19, 5, 6, 8, 9 | |
| Functional Near Infrared Ray Spectroscopy (fNIRS) recognizes the Neuroimaging technique. | 10, 16, 19, 5, 6, 8, 9 | |
| Applies resting state fMRI analysis via FSL program | 10, 16, 6, 8, 9 | |
| Applies fNIRS analysis via Homer program | 10, 11, 16, 8, 9 | |
| Comments and reports of analysis | 10, 16, 6, 9 |
| Teaching Methods: | 10: Discussion Method, 11: Demonstration Method, 16: Question - Answer Technique, 17: Experimental Technique, 19: Brainstorming Technique, 5: Cooperative Learning, 6: Experiential Learning, 8: Flipped Classroom Learning, 9: Lecture Method |
| Assessment Methods: |
Course Outline
| Order | Subjects | Preliminary Work |
|---|---|---|
| 1 | Introduction to Functional Neuroimaging | Reading the relevant sections of the Introduction to Neuroimaging Analysis book |
| 2 | Fundamentals of Image Processing | Reading the relevant sections of the Introduction to Neuroimaging Analysis book |
| 3 | Introduction to fMRI Analysis | Reading the relevant sections of the Introduction to Neuroimaging Analysis book |
| 4 | Preprocessing of fMRI data | Reading the relevant sections of the Introduction to Neuroimaging Analysis book |
| 5 | Spatial Normalization | Reading the relevant sections of the Introduction to Neuroimaging Analysis book |
| 6 | Statistical Modeling | Conducting research for analysis from the fsl course website |
| 7 | Statistical Inferences from Images | conducting research for analysis from the fsl course website |
| 8 | Visualization, localization and reporting of fMRI Data | conducting research for analysis from the fsl course website |
| 9 | Resting State Networks | Reading the literature of the last five years regarding the definition of resting state network and the studies carried out |
| 10 | Resting State Networks 2 | Reading the literature of the last five years regarding the definition of resting state network and the studies carried out |
| 11 | Human Connectome Project | Researching the human brain connectome study and reading relevant literature |
| 12 | Installing the Homer Program, converting the data file extension and opening the data in the program | Installation of MATLAB and Homer programs |
| 13 | Preprocessing of fNIRS data in Homer | Reading literature about the Homer program from the last five years |
| 14 | Converting fNIRS data to numerical data in Homer Program, performing statistical analysis and visualization in Atlas Viewer program | Reading literature about the Homer and AtlasViewer program from the last five years |
| Resources |
| Introduction to Neuroimaging Analysis, Mark Jenkinson and Michael Chappell, Oxford Neuroimaging Primers; Introduction to Resting State fMRI Functional Connectivity, Janine Bijsterbosch, Stephen M. smith, and Christian F. Beckmann, Oxford Neuroimaging Primers |
| Internet database and simulations |
Course Contribution to Program Qualifications
| Course Contribution to Program Qualifications | |||||||
| No | Program Qualification | Contribution Level | |||||
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | Has the essential knowledge about the structure and functioning of the nervous system. | X | |||||
| 2 | Knows the essential scientific questions and current research topics in neuroscience and produces hypotheses about them. | X | |||||
| 3 | Have knowledge and interpretation skills about neurodegenerative processes. | ||||||
| 4 | Know the principles of technologies for the measurement of molecular and cellular level parameters. | ||||||
| 5 | Defines the methods used in neuroscience researches. In own research area uses the required techniques without assistance, develops new methods and techniques. Designs research projects and submits them as proposals. Presents the research findings in oral or written forms and in scientific articles. | X | |||||
| 6 | Uses the communication and computer technology effectively in theoretical and practical studies. | X | |||||
| 7 | Able to present theoretical or research data orally or written in Turkish as well in English languages. | X | |||||
| 8 | Adheres to ethical values and behaves according to dynamics of social responsibility. | X | |||||
| 9 | While focusing on the basic research behaves in accordance with the principle that neuroscience research should eventually aim clinical implications and benefit. | X | |||||
| 10 | Designs and conducts scientific research, independently and within a team. Manages a research lab and establishes new ones. | X | |||||
| 11 | Evaluates all new information regarding the field and associate them based on available knowledge. | X | |||||
Assessment Methods
| Contribution Level | Absolute Evaluation | |
| Rate of Midterm Exam to Success | 50 | |
| Rate of Final Exam to Success | 50 | |
| Total | 100 | |
| ECTS / Workload Table | ||||||
| Activities | Number of | Duration(Hour) | Total Workload(Hour) | |||
| Course Hours | 14 | 2 | 28 | |||
| Guided Problem Solving | 14 | 8 | 112 | |||
| Resolution of Homework Problems and Submission as a Report | 5 | 8 | 40 | |||
| Term Project | 0 | 0 | 0 | |||
| Presentation of Project / Seminar | 0 | 0 | 0 | |||
| Quiz | 0 | 0 | 0 | |||
| Midterm Exam | 1 | 24 | 24 | |||
| General Exam | 1 | 36 | 36 | |||
| Performance Task, Maintenance Plan | 0 | 0 | 0 | |||
| Total Workload(Hour) | 240 | |||||
| Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30*=(240/30) | 8 | |||||
| ECTS of the course: 30 hours of work is counted as 1 ECTS credit. | ||||||
Detail Informations of the Course
Course Description
| Course | Code | Semester | T+P (Hour) | Credit | ECTS |
|---|---|---|---|---|---|
| FUNCTIONAL NEUROIMAGING | - | Spring Semester | 2+2 | 3 | 8 |
| Course Program |
| Prerequisites Courses | |
| Recommended Elective Courses |
| Language of Course | Turkish |
| Course Level | Third Cycle (Doctorate Degree) |
| Course Type | Elective |
| Course Coordinator | Prof.Dr. Lütfü HANOĞLU |
| Name of Lecturer(s) | Prof.Dr. Lütfü HANOĞLU, Prof.Dr. Gürkan ÖZTÜRK, Prof.Dr. Ertuğrul KILIÇ, Prof.Dr. Zübeyir BAYRAKTAROĞLU |
| Assistant(s) | |
| Aim | To provide neuroscience students with information about the basic principles of functional magnetic resonance imaging and functional near infrared beam spectroscopy techniques, their use in research and clinic, and the latest studies, learning and applying resting state fMRI analysis with FSL software tools, analyzing fNIRS data analyzes with Homer3 program. is to be learned and applied. |
| Course Content | This course contains; Introduction to Functional Neuroimaging,Fundamentals of Image Processing,Introduction to fMRI Analysis,Preprocessing of fMRI data,Spatial Normalization,Statistical Modeling,Statistical Inferences from Images ,Visualization, localization and reporting of fMRI Data,Resting State Networks,Resting State Networks 2,Human Connectome Project,Installing the Homer Program, converting the data file extension and opening the data in the program ,Preprocessing of fNIRS data in Homer ,Converting fNIRS data to numerical data in Homer Program, performing statistical analysis and visualization in Atlas Viewer program. |
| Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
| Resting state is recognized by the Functional Magnetic Resonance Imaging (fMRI) method. | 17, 19, 5, 6, 8, 9 | |
| Functional Near Infrared Ray Spectroscopy (fNIRS) recognizes the Neuroimaging technique. | 10, 16, 19, 5, 6, 8, 9 | |
| Applies resting state fMRI analysis via FSL program | 10, 16, 6, 8, 9 | |
| Applies fNIRS analysis via Homer program | 10, 11, 16, 8, 9 | |
| Comments and reports of analysis | 10, 16, 6, 9 |
| Teaching Methods: | 10: Discussion Method, 11: Demonstration Method, 16: Question - Answer Technique, 17: Experimental Technique, 19: Brainstorming Technique, 5: Cooperative Learning, 6: Experiential Learning, 8: Flipped Classroom Learning, 9: Lecture Method |
| Assessment Methods: |
Course Outline
| Order | Subjects | Preliminary Work |
|---|---|---|
| 1 | Introduction to Functional Neuroimaging | Reading the relevant sections of the Introduction to Neuroimaging Analysis book |
| 2 | Fundamentals of Image Processing | Reading the relevant sections of the Introduction to Neuroimaging Analysis book |
| 3 | Introduction to fMRI Analysis | Reading the relevant sections of the Introduction to Neuroimaging Analysis book |
| 4 | Preprocessing of fMRI data | Reading the relevant sections of the Introduction to Neuroimaging Analysis book |
| 5 | Spatial Normalization | Reading the relevant sections of the Introduction to Neuroimaging Analysis book |
| 6 | Statistical Modeling | Conducting research for analysis from the fsl course website |
| 7 | Statistical Inferences from Images | conducting research for analysis from the fsl course website |
| 8 | Visualization, localization and reporting of fMRI Data | conducting research for analysis from the fsl course website |
| 9 | Resting State Networks | Reading the literature of the last five years regarding the definition of resting state network and the studies carried out |
| 10 | Resting State Networks 2 | Reading the literature of the last five years regarding the definition of resting state network and the studies carried out |
| 11 | Human Connectome Project | Researching the human brain connectome study and reading relevant literature |
| 12 | Installing the Homer Program, converting the data file extension and opening the data in the program | Installation of MATLAB and Homer programs |
| 13 | Preprocessing of fNIRS data in Homer | Reading literature about the Homer program from the last five years |
| 14 | Converting fNIRS data to numerical data in Homer Program, performing statistical analysis and visualization in Atlas Viewer program | Reading literature about the Homer and AtlasViewer program from the last five years |
| Resources |
| Introduction to Neuroimaging Analysis, Mark Jenkinson and Michael Chappell, Oxford Neuroimaging Primers; Introduction to Resting State fMRI Functional Connectivity, Janine Bijsterbosch, Stephen M. smith, and Christian F. Beckmann, Oxford Neuroimaging Primers |
| Internet database and simulations |
Course Contribution to Program Qualifications
| Course Contribution to Program Qualifications | |||||||
| No | Program Qualification | Contribution Level | |||||
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | Has the essential knowledge about the structure and functioning of the nervous system. | X | |||||
| 2 | Knows the essential scientific questions and current research topics in neuroscience and produces hypotheses about them. | X | |||||
| 3 | Have knowledge and interpretation skills about neurodegenerative processes. | ||||||
| 4 | Know the principles of technologies for the measurement of molecular and cellular level parameters. | ||||||
| 5 | Defines the methods used in neuroscience researches. In own research area uses the required techniques without assistance, develops new methods and techniques. Designs research projects and submits them as proposals. Presents the research findings in oral or written forms and in scientific articles. | X | |||||
| 6 | Uses the communication and computer technology effectively in theoretical and practical studies. | X | |||||
| 7 | Able to present theoretical or research data orally or written in Turkish as well in English languages. | X | |||||
| 8 | Adheres to ethical values and behaves according to dynamics of social responsibility. | X | |||||
| 9 | While focusing on the basic research behaves in accordance with the principle that neuroscience research should eventually aim clinical implications and benefit. | X | |||||
| 10 | Designs and conducts scientific research, independently and within a team. Manages a research lab and establishes new ones. | X | |||||
| 11 | Evaluates all new information regarding the field and associate them based on available knowledge. | X | |||||
Assessment Methods
| Contribution Level | Absolute Evaluation | |
| Rate of Midterm Exam to Success | 50 | |
| Rate of Final Exam to Success | 50 | |
| Total | 100 | |