NAIL087: Informatics and Cognitive Science

Synopsis

This course represents an introduction into the subjects of computational neuroscience and cognitive psychology. The first semester focuses on basics of neural computation, including canonical models of neurons, architecture of cortical circuitry and its function and information processing in neural substrate. This basic knowledge is then built upon to introduce students to principles of cognition in several example systems, including vision and motor system. This course is taught by multiple experts in the respective sub-disciplines (see list of lectures below)

If you wish to gain better insight into latest developments in computational neuroscience consider joining also our Computational Neuroscience Seiminar NAIL128 running in parallel.

Requirements for passing the course

1) A computational modelling task
2) A psychological experiment
3) Written test: Required reading: Bear book, available in library, chapters 1-5.

You will get a grade for each of the three tasks, and the final grade will be calculated as the arhitmetic mean of the three partial grades. Specific info on 1 and 2 will appear here later in the semester.

Assignment

  • Data analysis homework is here.
  • Visual search experiment homework: assignment

Lecture overview and slides

This semster the course is scheduled for Thursday, from 15:40 till 18:50. First 90 minuts are in S9 and second in S1.

Date Lecture session Practical session Slides
5.10. CANCELLED CANCELLED  
12.10. Introduction (Ján Antolík) Introduction (Ján Antolík)  
19.10. Neurons biology I (Ján Antolík) Neurons biology II (Ján Antolík)  
26.10. Neurons bmodels I (Pavel Haman) Leaky integrate and fire simulations (Karolína Korvasová)  
2.11. DEANS DAY DEANS DAY  
9.11. Neurons bmodels I (Pavel Haman) Leaky integrate and fire simulations (Karolína Korvasová)  
16.11. Neural coding (Pavel Haman) Neural coding models (Karolína Korvasová)  
23.11. Cortical architecutre (Pavel Haman) Brunel network (Karolína Korvasová)  
30.11. TEST Network simulations (Karolína Korvasová)  
7.12. Visual system 1 (Ján Antolik) Semester project (Karolína Korvasová)  
14.12. fMRI and its analysis (Jaroslav Hlinka) Semester project (Karolína Korvasová)  
21.12. Machine Learning in Neuroscience (Luca Baroni) Machine Learning - excercise (Luca Baroni)  
4.1. Motor Cortex (Matej Hoffmann) Motor Cortex (Matej Hoffmann)  
11.1. Visual system 2 (Ján Antolik) Semester project (Karolína Korvasová)