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Language of Instruction
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English
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Level of Course Unit
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Master's Degree
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Department / Program
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ELECTRICAL AND COMPUTER ENGINEERING
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Type of Program
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Formal Education
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Type of Course Unit
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Elective
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Course Delivery Method
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Face To Face
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Objectives of the Course
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Detailed coverage of mathematical methods of brain dynamic; experience of analysis of brain dynamics at the different levels of cortical hierarchy; experience of modeling of neurons and neuron populations; introduction to quantitative EEG analysis.
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Course Content
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Human brain. Neurons: Methods of Brain Dinamics (BD). Hierarchic approach to the models of BD.
Mathematical neurons vs biological neurons.
Phenomenological models in BD. Spiking of neuron: Spike-generation of neurons and after-spike neuron reaction. Hodgkin-Huxley equations. 2D ODE spiking models for the membrane potential. Input stimulation.
Bursting of neuron: Classification of bursting. Discrete-time approach to bursting. Continuous-time model for bursting.
‘Quantum’ models in BD and concepts of ‘quantum neuron’.
Network models in BD: Structural characterization of brain networks. Types of brain connectivity. Clustering. Random graph models. Statistical network models for brain. ‘Brain temperature’.
Hierarchic models in BD: K-model family. Interacting neural populations with different topology. Excitatory and inhibitory links. Chaotic BD. Attractors in the brain.
Continuous (‘condensed matter’) models in BD: Umezawa class of models and ‘corticons’. Long-range collective modes in the brain. ‘Quantization’ of the collective modes.
Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI): Introduction to the methods of quantitative EEG (qEEG).
Searching for a time hierarchy in brain: Codes in brain.
Searching for a macroscopic spatial hierarchy in brain: Geometric approaches. Topology.
Models of BD for some diseases: Epilepsy, autism.
Control methods in BD.
Perspectives of BD.
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Course Methods and Techniques
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Students are obliged to refrain from acts that they know or, under the circumstances, have reason to believe, will impair the integrity of the university or others. Violations of academic integrity include, but are not limited to, cheating, plagiarism, unauthorized multiple submissions or copying and using somebody else’s paper/assignment.
Any of these violations will be investigated by the discipline committee and may cause expulsion of the student from the University.
Students are expected to attend all asynchronous / synchronous times. Student absences in excess of 3 weeks (4 or more) of synchronous times will result in automatic failure in the course. It is your responsibility to come to class on time.
Students with medical reports, you need to submit the paperwork to your deanship of faculty in 5 days following the last day of the sick leave. (refer to: Section 27 at https://goo.gl/HbPM2y). Absence due to medical reasons cannot exceed 2 weeks.
It is the responsibility of each student to keep track of how you are doing on class participation by checking with the instructor several times during the semester.
For a detailed description of AGU attendance policy, please refer to the website at https://goo.gl/HbPM2y section 25.
Students are obliged to refrain from acts that they know or, under the circumstances, have reason to believe, will impair the integrity of the university or others. Violations of academic integrity include, but are not limited to, cheating, plagiarism, unauthorized multiple submissions or copying and using somebody else’s paper/assignment.
Any of these violations will be investigated by the discipline committee and may cause expulsion of the student from the University.
Students are expected to attend all asynchronous / synchronous times. Student absences in excess of 3 weeks (4 or more) of synchronous times will result in automatic failure in the course. It is your responsibility to come to class on time.
Students with medical reports, you need to submit the paperwork to your deanship of faculty in 5 days following the last day of the sick leave. (refer to: Section 27 at https://goo.gl/HbPM2y). Absence due to medical reasons cannot exceed 2 weeks.
It is the responsibility of each student to keep track of how you are doing on class participation by checking with the instructor several times during the semester.
For a detailed description of AGU attendance policy, please refer to the website at https://goo.gl/HbPM2y section 25.
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Prerequisites and co-requisities
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None
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Course Coordinator
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Associate Prof.Dr. SERGEY BORISENOK sergey.borisenok@agu.edu.tr
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Name of Lecturers
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None
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Assistants
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None
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Work Placement(s)
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No
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Recommended or Required Reading
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Resources
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Human brain. Neurons: Methods of Brain Dinamics (BD). Hierarchic approach to the models of BD. (LO1)
Mathematical neurons vs biological neurons. (LO2)
Phenomenological models in BD. Spiking of neuron: Spike-generation of neurons and after-spike neuron reaction. Hodgkin-Huxley equations. 2D ODE spiking models for the membrane potential. Input stimulation. (LO1, LO2)
Bursting of neuron: Classification of bursting. Discrete-time approach to bursting. Continuous-time model for bursting. (LO1, LO2)
‘Quantum’ models in BD and concepts of ‘quantum neuron’. (LO1, LO2)
Network models in BD: Structural characterization of brain networks. Types of brain connectivity. Clustering. Random graph models. Statistical network models for brain. ‘Brain temperature’. (LO3)
Hierarchic models in BD: K-model family. Interacting neural populations with different topology. Excitatory and inhibitory links. Chaotic BD. Attractors in the brain. (LO3, LO5)
Continuous (‘condensed matter’) models in BD: Umezawa class of models and ‘corticons’. Long-range collective modes in the brain. ‘Quantization’ of the collective modes. (LO1, LO3)
Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI): Introduction to the methods of quantitative EEG (qEEG). (LO4)
Searching for a time hierarchy in brain: Codes in brain. (LO4, LO5)
Searching for a macroscopic spatial hierarchy in brain: Geometric approaches. Topology. (LO4)
Models of BD for some diseases: Epilepsy, autism. (LO4, LO6)
Control methods in BD. (LO5, LO6)
Perspectives of BD. (LO4, LO5, LO6)
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