MSc:Neuroscience

Neuroscience

• Course name: Neuroscience
• Course number: ???

Course Characteristics

Key concepts of the class

• An introduction to modern neuroscience and neural engineering.
• Basic principles of nervous system functioning and its applications for rehabilitation, robotics and control of human brain states.

What is the purpose of this course?

This course is designed to serve an introduction to modern neuroscience and neurotechnologies. Because neuroscience is an interdisciplinary field including biological science, physics, mathematics, philosophy, and engineering, we will cover all the areas in lectures and seminars. The course goal is to make students familiar with basic principles of nervous system functioning and its applications for rehabilitation, robotics and control of human brain states. The students will learn about various methods of neuron modelling and biological bases of artificial intelligence. We will discussed the various neuroimaging methods and its applications for disease diagnostics and brain computer interfaces development. After the course the students will be able to conceptually understand the important terms and approaches of modern neuroscience and neural engineering. The theoretical introduction will be complemented by practical examples of task solving.

- What should a student remember at the end of the course?

By the end of the course, the students should be able to remember and differentiate

• Physiology and functions of neurons,
• Basic principles of realization of human cognitive abilities in the brain,
• Structure and functions of brain,
• Main brain diseases and methods of neurorehabilitation,
• Main principles of brain-computer and brain-machine interfaces.

- What should a student be able to understand at the end of the course?

By the end of the course, the students should be

• able to describe what modern neuroscience is and what a neurotechnologies might include or not include, and why, to someone not in the class
• learn about many of the features of the nervous system and body that may be useful to a specialist in artificial intelligence,
• familiar with modern computational neuroscience methods and approaches,
• learn about some of the goals of neuronal engineering and neurotechnologies and who is involved (in research and uses)

- What should a student be able to apply at the end of the course?

By the end of the course, the students should be able to ...

• Know how to construct brain-computer interfaces,
• Simulate spiking neuronal network,
• Know how to choose the neuroimaging technique depending on the required information,
• Classify different types of brain activity.

Course evaluation

Course grade breakdown

		Proposed points
Labs/seminar classes	20	50
Interim performance assessment	30	30
Exams	50	20

If necessary, please indicate freely your course’s features in terms of students’ performance assessment:

Grades range

Course grading range

		Proposed range
A. Excellent	90-100	80-100
B. Good	75-89	65-79
C. Satisfactory	60-74	50-64
D. Poor	0-59	0-49

If necessary, please indicate freely your course’s grading features: The course grades were given according to the following rules: Lab projects (2) = 50 pts, Quizzes (3) = 30 pts, Exam (1) = 20 pts.

The subject of the course is far from the materials previously studied by the students, so in many lectures it is completely new to them. Therefore the grade requirements for this course are relaxed

Resources and reference material

The course is build based on these main textbooks:

• Fundamental Neuroscience (3rd edition), Academic Press, Elsevier, 2008
• Galizia, C. Giovanni, and Pierre-Marie L. (ed.) Neurosciences-From Molecule to Behavior: an University Textbook. Springer Spektrum, 2013.

Other reference material:

• Baars, B. J., and Nicole M. G. Cognition, brain, and consciousness: Introduction to cognitive neuroscience. Academic Press, 2010.
• Nam C. S., Nijholt A., Lotte F. (ed.) Brain-Computer Interfaces Handbook: Technological and Theoretical Advances. CRC Press, 2018. .
• The review papers from Nature Neuroscience; https://www.nature.com/neuro/.

Course Sections

The main sections of the course and approximate hour distribution between them is as follows:

Course Sections

Section	Section Title	Teaching Hours
1	Introduction in Neuroscience	2
2	Computational neuroscience	20
3	Neuroanatomy and functions of brain	14
4	Cognitive neuroscience	10
5	Brain-computer interfaces	10
6	Brain diseases and neurorehabilitation	4

Section 1

Section title:

Introduction in Neuroscience.

Topics covered in this section:

• Subject of neuroscience
• History of neuroscience

What forms of evaluation were used to test students’ performance in this section?

	Yes/No
Development of individual parts of software product code	0
Homework and group projects	0
Midterm evaluation	0
Testing (written or computer based)	1
Reports	0
Essays	0
Oral polls	0
Discussions	0

Typical questions for ongoing performance evaluation within this section

1. Who got the Nobel Prize for extensive observations, descriptions, and categorizations of neurons throughout the brain? At what year?
2. Who got the Nobel Prize for discoveries regarding the functions of neurons? At what year?
3. Who and when discovered the effect of the electrical excitability of muscles and neurons?
4. Draw and explain the scheme for measuring the speed of an impulse along a nerve fiber proposed by Hermann von Helmholtz.

Test questions for final assessment in this section

1. What is a subject of neuroscience?
2. When and by whom was the neural doctrine proposed?
3. What is the essence of optogenetic imaging of neurons?

Section 2

Section title:

Computational neuroscience

Topics covered in this section:

• Functional classes of neurons
• Basic function of neurons
• Structural classes of neurons
• Glial cells
• Neuron communications and action potential
• Basic concepts of computational neuroscience
• Turning curves
• Plasticity in neuronal systems
• Mathematical model of action potential generation

What forms of evaluation were used to test students’ performance in this section?

	Yes/No
Development of individual parts of software product code	0
Homework and group projects	1
Midterm evaluation	0
Testing (written or computer based)	1
Reports	0
Essays	0
Oral polls	1
Discussions	1

Typical questions for ongoing performance evaluation within this section

1. The connection between one of the two neurons decreased by 20%, and between the other increases by 20% due to STDP. Qualitatively draw the generation of spikes of both pairs of neurons. Explain your answer.
2. Identify the type(s) or subtype(s) of neural cell performing the following functions:
   • Connecting neurons within specific regions of the central nervous system
   • Forming myelin in the motor neurons
   • Providing the appropriate ionic milieu for neurons to be able to generate action potentials
3. Draw and briefly explain voltage-clamp experiment design (aim, scheme, idea, result).
4. The persistent current through neuron membrane is determined by:
   • all channels;
   • channels that do not have inactivation gates
   • channels that have inactivation gates
   • channels that do not have activation gates
   • channels that have activation gates

Typical questions for seminar classes (labs) within this section

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1. Solve numerically the system of differential equations describing the Hodgkin-Huxley neuron model using the Runge Kutta 4th order method, analyze the correctness of choosing the time step.
2. Analyze different regimes of a neuron dynamics, plot time series and phase portraits of the signal, calculate a regime map.
3. Solve numerically the system of stochastic differential equations corresponding to the Hodgkin-Huxley neuron model with noise, analyze the influence of noise amplitude on the system dynamics.
4. Solve numerically the system of differential equations describing 2 noisy Hodgkin-Huxley neurons coupled by chemical synapses, analyze synchronization between neurons for different values of the coupling strength.
5. Numerical simulation of network of 10 Hodgkin-Huxley neurons with global topology.
6. Analyze the influence of external stimulus and noise amplitude by calculating characteristic correlation time.

Test questions for final assessment in this section

1. What are the functions of glial cells?
2. Which of the following best characterizes an action potential that occurs in a neuron?
   • Sometimes strong
   • All-or-none
   • Very rarely weak
   • Sometimes weak
3. Adaptation of a neural response to a constant stimulus? (mark all correct answers):
   • leads to decrease amplitude of spikes
   • lleads to increase neuron firing rate
   • lleads to decrease neuron firing rate
   • lleads to increase amplitude of spikes
   • lremoves the one-to-one relationship between firing rate and magnitude of the stimulus
   • lremoves the one-to-one relationship between amplitude of spikes and magnitude of the stimulus

Section 3

Section title:

Neuroanatomy and functions of brain

Topics covered in this section:

• Central and peripheral nerves systems
• Autonomic Nervous System
• Brain organization
• Invasive and non-invasive neuroimaging technics
• Structural brain connectivity
• Functional brain connectivity
• Introduction in graph theory
• A taxonomy of methods for functional connectivity detection
• Model-based and model-free methods for functional connectivity restoration
• Non-directed and directed methods for functional connectivity restoration

What forms of evaluation were used to test students’ performance in this section?

	Yes/No
Development of individual parts of software product code	0
Homework and group projects	1
Midterm evaluation	0
Testing (written or computer based)	01
Reports	0
Essays	0
Oral polls	1
Discussions	1

Typical questions for ongoing performance evaluation within this section

1. Which of the following functional connectivity recovery methods are model-free ones?
   • Recurrence measure of dependence
   • Mutual information
   • Granger causality
   • Phase locking index
   • Pierson correlation coefficient
2. The BOLD signal measures…
   • the diffusion of water molecules in the brain
   • the magnetic field excited by the post-synaptic current flow along the dendrites of pyramidal nerve cells
   • the local changes in blood oxygenation ocurring during brain activity
   • the spike activity of single nerve cells
   • the activation of various neurotransmitters during brain activity
3. How can you characterize the rich club organization pattern in network?
4. Which part of the brain is important for language comprehension?

Typical questions for seminar classes (labs) within this section

1. Use Pearson correlation and recurrence measure of dependence to estimate the connections between different EEG channels in ${\textstyle \alpha }$ (8-12 Hz) and ${\textstyle \beta }$ (15-30 Hz) frequency regions for different values of brightness intensity ${\textstyle I\in (0.1-1.0)}$, find an optimal value of ${\textstyle I}$ for each subject characterized by maximal connectivity
2. Estimate the efficiency of Pearson correlation and recurrence measure of dependence.
3. Investigate the time-dependence of the coupling strength, find an optimal value of time window for calculation of the coupling strength.
4. Use a Nonparametric Test for checking a hypothesis of achieving maximal connectivity in the found range of the optimal brightness intensity.

Test questions for final assessment in this section

1. Describe the concept of the structural and functional network of the brain. Give examples.
2. For a given functional network described by graph, calculate degree of nodes, mean shortest path, centrality.
3. Describe pros and cons of fMRI neuroimaging technics.

Section 4

Section title:

Cognitive neuroscience

Topics covered in this section:

• Neurophysiology of cognitive processes
• Brief historical tour in cognitive neuroscience
• Basic cognitive processes: sensations
• Basic cognitive processes: perceptions
• Basic cognitive processes: attention
• Basic cognitive processes: memory

What forms of evaluation were used to test students’ performance in this section?

	Yes/No
Development of individual parts of software product code	0
Homework and group projects	0
Midterm evaluation	0
Testing (written or computer based)	1
Reports	0
Essays	0
Oral polls	1
Discussions	1

Typical questions for ongoing performance evaluation within this section

1. What is Stroop effect? Repeat the Stroop’s experiment yourself
2. Draw the scheme of analysis of visual information in eye.
3. What is the difference in the processing of visual information passing through the ventral and dorsal pathways in the brain?
4. Consider the methods of cognitive neuroscience.

Test questions for final assessment in this section

1. Describe the role of the thalamo-cortical network in sensory processing.
2. What are the basic cognitive abilities you know?
3. What types of human sensation do you know?

Section 5

Section title:

Brain-computer interfaces

Topics covered in this section:

• Classification of brain-computer interfaces (BCI)
• EEG preprocessing methods for BCIs
• Brain activity pattern recognition and classification in multichannel data
• BCI applications

What forms of evaluation were used to test students’ performance in this section?

	Yes/No
Development of individual parts of software product code	0
Homework and group projects	1
Midterm evaluation	0
Testing (written or computer based)	0
Reports	1
Essays	0
Oral polls	1
Discussions	1

Typical questions for ongoing performance evaluation within this section

1. Name brain activity patterns for control commands for BCI
2. Describe the functional model of reactive BCI
3. Describe the speller based on P300 potential recognition
4. Describe the process of generation and detection of sensorimotor rhythm

Typical questions for seminar classes (labs) within this section

1. Create an artificial neural network with 31 input and 1 output neurons to work with EEG data.
2. Train the artificial neural network for recognition of EEG patterns corresponding to the human’s movement of left or right leg by half of the data.
3. Apply the trained artificial neural network to the rest of the data.
4. Estimate the accuracy of the recognition.

Test questions for final assessment in this section

1. Describe typical functional model of BCI.
2. What is difference between active and passive BCIs?.
3. Which of the following is a event-related potential?
   • Cortical potential
   • P300 evoked potential
   • Event-related synchronization/desynchronization (ERS/ERD)
   • Eye movement artefact

Section 6

Section title:

Brain diseases and neurorehabilitation

Topics covered in this section:

• Types of nervous diseases
• Epilepce
• Neurodegenerative diseases
• Stroke and impaired motor function
• Neurorehabilitation

What forms of evaluation were used to test students’ performance in this section?

	Yes/No
Development of individual parts of software product code	0
Homework and group projects	0
Midterm evaluation	0
Testing (written or computer based)	1
Reports	1
Essays	0
Oral polls	1
Discussions	1

Typical questions for ongoing performance evaluation within this section

1. Is it possible to use the brain-computer interface to treat epilepsy?
2. What are the main features of Parkinson’s disease?
3. Describe the role of modern neuroimaging techniques in the diagnosis of nervous diseases
4. Describe the main neurorehabilitation methods.

Test questions for final assessment in this section

1. How can epilepsy be diagnosed?
2. Name pros and cons of exoskeleton-based rehabilitation after stroke.
3. What are the main features of Alzheimer’s disease?