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Regular version of the site

Research Seminar "Cognitive Sciences"

2019/2020
Academic Year
ENG
Instruction in English
8
ECTS credits
Course type:
Compulsory course
When:
2 year, 1-3 module

Instructors

Course Syllabus

Abstract

The present program establishes minimum demands of students’ knowledge and skills, and determines content of the course. The present syllabus is aimed at department teaching the course, their teaching assistants, and students of the Master of Science program 37.04.01 «Cognitive sciences and technologies: from neuron to cognition».
Learning Objectives

Learning Objectives

  • Know information for career design
  • Discuss logic, probability, and statistics to understand their relation with students' research projects.
  • Understand issues of science in society
  • Learn analysis and interpretation of neurophysiological data
Expected Learning Outcomes

Expected Learning Outcomes

  • Learn to consider their practical career plans before/after getting degree
  • Learn to present and discuss their own research projects
  • Learn to understand, present and discuss results
  • Learn to plan and work on their own research projects independently.
  • Learn to consider and discuss current issues of empirical science: replication crisis, publication bias, and research misconduct.
  • Learn to consider and discuss roles of science in society.
  • Be confident with the theoretical basis of the analysis of neurophysiological data
  • Be able to implement basic analysis pipeline on EEG/MEG data
  • Be able to understand, present and discuss results
Course Contents

Course Contents

  • Career design
    Possible careers after a master program: industry, a PhD school in Russia or in a foreign country. Materials of an application. How to write motivation letters. Who can be references and can write recommendation letters.
  • Logic, Probability, and Statistics
    Fallacies in logic, in probability, and in statistics. Sophism
  • Science in society
    Science and Pseudo-science. The demarcation problem, Publication bias, Replication crisis. Scientific discussion.
  • Introduction to EEG/MEG data analysis
    Data reading, preprocessing and visualization in the temporal and spectral domain. Sensor space and source space representation. Connectivity analysis and cross-frequency coupling.Multi-unit activity and local filed potential in humans. Technology, methodologies and achievements in cognitive and clinical neuroscience. Contribution of clinical neurophysiology to epilepsy surgery. State of the art of diagnostic tools.
Assessment Elements

Assessment Elements

  • non-blocking Home assignment
    1 home assignment around the end of the 1st module. Its weight in grading is 0.3. The 1st-retake of a home assignment is evaluated in the same way as the original assignment. The 2nd-retake of the assignment comes with 20% of penalty on its score. Namely, its score is first computed in the same way as the original assignment and then the computed score is multiplied by 0.8.
  • non-blocking Essay
    1 essay around the end of the 2nd module. Its weight in grading is 0.4. The 1st-retake of the essay is evaluated in the same way as the original essay. The 2nd-retake of the essay comes with 20% of penalty on its score. Namely, its score is first computed in the same way as the original essay and then the computed score is multiplied by 0.8.
  • non-blocking Short oral presentation
    1 short oral presentation in the 2nd module. Its weight in grading is 0.3. The 1st-retake of a presentation is evaluated in the same way as the original presentation. The 2nd-retake of the presentation comes with 20% of penalty on its score. Namely, its score is first computed in the same way as the original presentation and then the computed score is multiplied by 0.8.
  • non-blocking Writing test
    A writing test at the end of the 3rd module; This score (Gx) will be integrated with grades of the 1st-year Research Seminar (G1) and of the 2nd-year Research Seminar (G2) as follows: 0.1*Gx + 0.504*G1 + 0.396*G2. The 1st-retake of a test is evaluated in the same way as the original assignment. The 2nd-retake of the test comes with 20% of penalty on its score. Namely, its score is first computed in the same way as the original test and then the computed score is multiplied by 0.8. Экзамен проводится в письменной форме (тест по материалам курса). Экзамен проводится на платформе Zoom (https://www.zoom.us/). Компьютер студента должен удовлетворять требованиям: наличие рабочей камеры и микрофона, поддержка Zoom. Для участия в экзамене студент обязан: поставить на аватар свою фотографию, явиться на экзамен согласно точному расписанию, при ответе включить камеру и микрофон. Во время экзамена студентам запрещено: выключать камеру, пользоваться конспектами и подсказками. Кратковременным нарушением связи во время экзамена считается нарушение связи менее минуты. Долговременным нарушением связи во время экзамена считается нарушение длиной в минуту и более. При долговременном нарушении связи студент не может продолжить участие в экзамене.Экзамен проводится в письменной форме (тест по материалам курса). Экзамен проводится на платформе Zoom (https://www.zoom.us/). Компьютер студента должен удовлетворять требованиям: наличие рабочей камеры и микрофона, поддержка Zoom. Для участия в экзамене студент обязан: поставить на аватар свою фотографию, явиться на экзамен согласно точному расписанию, при ответе включить камеру и микрофон. Во время экзамена студентам запрещено: выключать камеру, пользоваться конспектами и подсказками. Кратковременным нарушением связи во время экзамена считается нарушение связи менее минуты. Долговременным нарушением связи во время экзамена считается нарушение длиной в минуту и более. При долговременном нарушении связи студент не может продолжить участие в экзамене.
Interim Assessment

Interim Assessment

  • Interim assessment (3 module)
    0.4 * Essay + 0.3 * Home assignment + 0.3 * Short oral presentation
Bibliography

Bibliography

Recommended Core Bibliography

  • Donald L. Schomer, & Fernando Lopes da Silva. (2012). Niedermeyer’s Electroencephalography : Basic Principles, Clinical Applications, and Related Fields. [N.p.]: LWW. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=2017668
  • Reinhart, A. (2015). Statistics Done Wrong : The Woefully Complete Guide. San Francisco: No Starch Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=984483

Recommended Additional Bibliography

  • Cohen, M. X. (2014). Analyzing Neural Time Series Data : Theory and Practice. Cambridge, Massachusetts: The MIT Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=689432
  • Lakatos, I., Feyerabend, P., & Motterlini, M. (1999). For and Against Method : Including Lakatos’s Lectures on Scientific Method and the Lakatos-Feyerabend Correspondence. Chicago: University of Chicago Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=351279