Интерфейсы мозг-компьютер

Аспирантура 2020/2021

Статус: Курс по выбору

Направление: 37.06.01. Психологические науки

Кто читает: Департамент психологии

Когда читается: 2-й курс, 1 семестр

Формат изучения: без онлайн-курса

Преподаватели: Лебедев Михаил Альбертович

Язык: русский

Кредиты: 4

Контактные часы: 28

Полная версия программы учебной дисциплины

Аннотация

The course Introduction to Brain-Computer Interfaces targets PhD-students in psychology and is aimed at developing undestanding of the principles of brain-computer interfaces, including invasive and noninvasive interfaces developed using animal models and tested in humans, and the basic skills of data analysis that are necessary for reading academic literature in the field and entering the brain-computer interface community. Students will know differences between various relevant methods and types of brain-computer interfaces, strengths and limitations of different approaches, the basic data processing steps and applications.

Цель освоения дисциплины

The course aims at teaching students the following skills: 1) To get the general idea of brain-computer interfacing, the methods involved and relevant research and clinical applications 2) Acquiring basic skills in data analysis 3) Learning basic principles of brain-computer interfaces 4) Learning about different methods involved in neural data recordings and processing how to identify an appropriate method for research questions.

Планируемые результаты обучения

To name and give a brief overview of brain-computer interfaces.
To describe neural decoding methods.
To distinguish and identify in sample studies the key components of brain-computer interfaces.
To provide examples of findings in studies on brain-computer interfaces.
To explain the choice of the sequence of processing steps in brain-computer interfaces.
To suggest an appropriate approach for a given research question in the field of brain-computer interfaces.
To know the basic data processing steps and applications.
To know differences between various relevant methods and types of brain-computer interfaces, strengths and limitations of different approaches.
To describe approaches to recording neural activity.

Содержание учебной дисциплины

Topic 1.
Overview of brain-computer interfaces (BCIs). Invasive and noninvasive BCIs, data acquisition methods. Principles of decoding and major applications.
Topic 2.
An overview of brain structure and function. Basics of neurophysiology and their relationship to the design of brain-computer interfaces: neurons, synapses, glial cells, action potentials. Sensory, motor and cognitive systems of the brain.
Topic 3.
Recording methods. Sources of electrical signals in the brain when recording with implanted electrodes, EEG and ECoG.
Topic 4.
Biocompatibility and ways to improve it.
Topic 5.
Medical applications of BCIs, augmentation of brain function with BCIs.
Topic 6.
Computational models: descriptive models, mechanistic models, interpretive models.
Topic 7.
Encoding principles of the brain, representation of multiple behavioral variables by single neurons and neuronal ensembles, oscillatory neurons and brain oscillations.
Topic 8.
Brain-computer-brain interfaces. Artificial sensory feedback, sensory substitution.
Topic 9.
Data processing and analysis. Spectral methods, wavelets, machine learning, classification. Using MATLAB and Python for data analysis.
Topic 10.
Animal models: drosophila, rats, monkeys, pigs. The choice of animal model.

Элементы контроля

Homework (reading)
Class participation
Sample data analysis (both in class and homework)
Completeness of the data analysis, number and character of errors in the presented results (critical/not critical for the results), monitoring own errors
Oral project presentation
Oral presentation, 10 min; idea originality, literature search, sophistication, design details

Промежуточная аттестация

Промежуточная аттестация (I семестр)
0.1 * Class participation + 0.1 * Homework (reading) + 0.4 * Oral project presentation + 0.4 * Sample data analysis (both in class and homework)

Программа дисциплины