NBE-E4260 - Genesis and Analysis of Brain Signals D, Lecture, 13.1.2022-14.4.2022

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Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

Students will learn an end-to-end perspective on analysis of brain signals, from neurobiological microcircuit mechanisms and electrophysiological recordings to modelling, measurement, and analysis of the signals. The students will be able to:

1. Describe basic neurobiological mechanisms governing collective neuronal activity.
2. Describe key concepts of complex dynamic systems and apply computational modelling methods to simulate these phenomena.
3. Describe and analyse the biophysical signal generation mechanisms at micro-, meso-, and macro-scale electrophysiological recordings, and interpret the measurability of specific forms and features of the neuronal activity.
4. Apply analysis methods to real and simulated data to study collective neuronal activity, design and implement new analyses, and evaluate the reliability and informativeness of the outcomes.

Credits: 5

Schedule: 13.01.2022 - 14.04.2022

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Matias Palva

Contact information for the course (applies in this implementation):

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content

  • valid for whole curriculum period:

    Neuronal oscillations and brain dynamics, electrophysiological measurement methods, neuronal modelling and time series analysis approaches, approaches to linking neurophysiological understanding with psychological/behavioral measures for functional inferences. Python-programming based exercises with simulation and analysis methods and application of the analyses to real and simulated data.

Assessment Methods and Criteria

  • valid for whole curriculum period:

    Examination. Exercises. Project work and presentation.

Workload

  • valid for whole curriculum period:

    Lectures 20-24 h and project presentations 2 h. Exercise sessions 20-24 h. Homework related to exercise sessions 20 h. Project work and preparation for project presentation 30 h. Writing learning diaries 10 h. Preparation for exam 30 h. Exam 3 h.

DETAILS

Substitutes for Courses
Prerequisites

FURTHER INFORMATION

Further Information

  • valid for whole curriculum period:

    Teaching Language : English

    Teaching Period : 2022-2023 Spring III - IV
    2023-2024 Spring III - IV

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