Бакалавриат
2025/2026
Комплексный анализ нейроданных
Статус:
Курс по выбору (Когнитивная нейробиология)
Кто читает:
Базовая кафедра Института биоорганической химии им. академиков М.М. Шемякина и Ю.А. Овчинникова РАН
Где читается:
Факультет биологии и биотехнологии
Когда читается:
4-й курс, 2, 3 модуль
Охват аудитории:
для своего кампуса
Преподаватели:
Осетрова Мария Станиславовна
Язык:
английский
Course Syllabus
Abstract
The course is designed for fourth-year undergraduate students studying cognitive neuroscience. The goal of the course is to provide students with the knowledge and skills to analyze and integrate various types of data obtained from multiple sources in neuroscience research. The course provides students with an understanding of the method of obtaining and the characteristics of various types of neurodata, and covers topics such as statistical analysis, machine learning, network analysis, and integration methods specific to the field of neuroscience.
Learning Objectives
- Equip students to understand major neuroscience data types and standards and to design defensible multimodal data integration with rigorous quality and reproducibility.
Expected Learning Outcomes
- Identify and compare major neuroscience data modalities and organize datasets with appropriate metadata using community standards (BIDS/NWB/AnnData) and FAIR/ethical principles.
- Critically evaluate data quality and published studies by detecting artifacts, biases, and confounders and assessing study design, statistical choices, and reproducibility.
- Design and justify a multimodal integration plan (feature/decision-level fusion, harmonization, validation and multiple-comparison control) and communicate interpretable conclusions in a clear, structured report.
Interim Assessment
- 2025/2026 1st module0.1 * Активность + 0.4 * Домашние задания + 0.4 * Журнальный клуб + 0.1 * Посещаемость
Bibliography
Recommended Core Bibliography
- Computational Cognitive Neuroscience - CCBY4_019 - O'Reilly, Munakata, Hazy & Frank - 2022 - Open Educational Resources: libretexts.org - https://ibooks.ru/bookshelf/390536 - 390536 - iBOOKS
- Theoretical neuroscience : computational and mathematical modeling of neural systems, Dayan, P., 2001
Recommended Additional Bibliography
- Computational neuroscience, by W. Chaovalitwongse, P. M. Pardalos, P. Xanthopoulos, 369 p., , 2010
- Naldi, G., & Nieus, T. (2018). Mathematical and Theoretical Neuroscience : Cell, Network and Data Analysis. Cham, Switzerland: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1737030
- Quantitative Neuroscience : Models, Algorithms, and Therapeutic Applications, edited by P. M. Pardalos [et. al.], 262 p., , 2004