Reading for Computational Neuroscience course
After completing the thesis process, the student….
- Knows concepts of theoretical neuroscience and contemporary models of mammalian brain structure and function; understands benefit of model-based experimental neuroscience; learns prominent neural simulation platforms; learns the basics of multidimensional data analysis; knows likely application in clinical medicine
- The aim is to evoke interest in the field to target further self-learning towards relevant individual application area.
Exam will be arranged on November 9th and a possibility for re-examination will be provided in November-December.
Thematic seminar meetings as listed below, including preceding review article as preparatory material, lecture (45 min) and seminar-type discussion (45 min)
-history, motivation, aim, clinical potential
Modeling neural function
-models for synapse, membrane, cell and systems
Simulating neural systems
-simulation platforms (NEST, NEURON, Brian2) and their strengths and weaknesses
Analyzing high-dimensional data
-introduction to relevant statistics and math for bioscientists
-PCA, ICA, GLM, deep learning
Software and hardware implementation of the models
-restrictions and potential of distinct computer platforms, brain-computer interface, embedded systems
-motivation, platforms, comparative neurobiology
Computational neurology and psychiatry
-introduction to human brain as an organ and as a network
-epilepsy, schizophrenia models, simulation platform: the Virtual Brain
Course completion methods (3 credits):
- Pre-reading before the course: review articles on course topics (provided at the course Moodle page)
- Lectures during October 22-23, 2018
- Exam on a later specified date.
Evaluation 0-5, exam, activity in seminars, seminar presentations
- Seminar meetings/lectures (compulsory participation)
- Course, review articles, book exam
- The course consists of approximately 20h of contact teaching and 100 h of independent studying.
Simo Vanni, other teachers: Juha Voipio, Jugoslava Acimovic (Tampere University of Technology), Marja-Leena Linne (Tampere University of Technology), Linda Henriksson (Aalto University)