Artificial Minds for Intelligent Systems - AMIS

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Computational Cognitive Science


Computational cognitive science
AIL087, 2/2 (6 credits)
Cyril Brom, Jiří Lukavský, Kamil Vlček

This course gives an introduction into computational neuroscience and cognitive psychology. We will study neuronal networks at the levels of synapses, individual synapses and neural circuits, taking into consideration also psychological point of view. The main part of the course will cover perceptional theories and memory systems. More in English... More in Czech...

Schedule 2016/2017

regular, winter term: Thu, S9, start: 15:40; end: 18:50

13.10. Cyril Brom
20.10. Jiri Lukavsky
27.10. Jiri Lukavsky
3.11. Cyril Brom
10.11. Cyril Brom
17.11. no lecture
24.11. Cyril Brom (till 17:10); Filip Dechterenko — seminar (from 17:20)
1.12. Jiri Lukavsky
8.12. Cyril Brom test (till 17:10); Filip Dechterenko — seminar (from 17:20)
15.12. Jiri Lukavsky
22.12. no lecture
5.1. Cyril Brom (till 17:10); Filip Dechterenko — seminar (from 17:20)
12.1. Cyril Brom

Exams 2016/2017

Winter term 2016/17

1) A computational modelling task
2) A psychological experiment
3) Participation in a psychological experiment
4) Written test: Required reading: Bear, ch. 1 - 5

A computational modelling task

TO BE Announced

A psychological experiment

TO BE Announced

Participation in a psychological experiment

a) If you participated in an experiment in courses Human-like artificial agents, Computer games development or Computational Cognitive Sciences (in the past), please, email Cyril Brom no latter than 24th October 2016

b) Otherwise:

You have to attend an experiment related to cognitive psychology (and pedagogy). The experiment concerns itself with learning about a certain process from multimedia learning materials (i.e., computerized learning materials). The experiment will include filling in questionnaires and knowledge tests regarding the process you will study. The details (such as the topic of the process) will be given to you at the beginning of the experiment.

The experiment has two parts roughly three weeks apart and you have to attend both of them. The first one is around 105 min long, the second one up to 45 min long. There will be many dates during the term offered you for participation in the experiment, but the last dates will be around the end of November (as concerns the experiment's first part). This means: do not hesitate :) For the first part you must sign up via orsee system of the Labels laboratory (deadline 24th Oct 2016). Most of the terms (95%) will be during mornings. For the second part, you will receive special dates via email. When registering, please check “experimenty v laboratoři”. After that you will start receiving weekly invitations via e-mails and you will sign up for a particular date via the link in the invitation.

One of the goals of this activity is to demonstrate you how such experiments look like. There will be a final lecture about the experiment in the summer term (after the experiment's end) explaining you all the details and results.

Students from different faculties can also attend the experiment.

a) you must not be sleepy at the beginning of the experiment or drunk
b) you must not be in stress (e.g., hurrying up for a train)
c) you should not talk to other students (i.e., possible participants) about details of the experiment (i.e., no spoilers)
d) if you are sick, please do not come; unsign from the date instead
e) if you cannot attend a date you already signed up for, please unsign as soon as possible; otherwise, you'll be blocking the slot to others

Summer term 2016/17

To be announced.

Exams 2014/2015

Winter term 2014/15

1) A computational model task
2) A psychological experiment
3) Participation in a psychological experiment
4) Written test: Required reading: Bear, ch. 1 - 5, 7, 8, 12, 13, 1st part of 14 (pp. 452 — 464); Highly recommended reading: "KokkoKap1"; Izkikevich, ch. 1, 2 (web, "IzhikKap2"); Ijspeert et al. 2007

Psychological experiment 2014/15

Your task is to collect data for a small experiment (Simon's effect) and report the results. The instructions contain assignment details and useful links. Send the report and data before deadline to Jiří Lukavský.

Deadline: 7 days before final exam

Swimmy 2014/15

Your task is to solve Swimmy circuit and write up the results. Swimmy will be assigned on the second practicum. Materials for Swimmy can by found here
Send me the solution on email filip tečka dechterenko na gmail tečka com

Deadline: 7 days before final exam

Summer term 2014/15

1) Experiment participation (TODO: Filip Dechterenko)
2) Paper presentation (May)
3) Oral exams (two chapters from teh Bear's book, ch. 8 — 24)

Syllabus — 2014/15


Introduction to cognitive science

Methods and perspectives in cognitive science, research projects examples. Brief history of cognitive psychology.

Psychological theories of vision

2 lectures

Sensory organs, theories of color vision, psychophysics, eyetracking.
Theories of vision (pattern/object recognition), space perception cues, Gestalt, Marr, Biedermann, Gibson theories.

Strongly recommended reading:
Eysenck & Keane, chap. 2, 3, 4

Supplementary materials
Seeing blood vessels in your eye
Motion aftereffect example
Biological motion demo


Important experimental paradigms of attention, visual attention, auditory attention, eye movements, visual search, multiple object tracking. Theories of attention (Broadbent, Deutsch, Treisman, FIT, Kahneman).

Strongly recommended reading:
Sternberg, ch. 2
Bear, ch. 21

Psychological theories of memory

Atkinson & Shiffrin, Baddeley model. Mental representation of knowledge. Episodic memory. Autobiographic memory. Excellent memory performance.
Implicit and explicit processes, examples. Implicit/explicit/automatic processing and consciousness. Artificial grammars.

Strongly recommended reading:
Eysenck & Keane chap. 8
Sternberg, chap. 5, 6, 7
Bear, chap. 24, 25
Cleeremans, Axel (2006) Conscious and unconscious cognition: A graded, dynamic perspective. International Journal of Psychology

Decision making, problem solving

Prefrontal cortex, tests of executive functions. P. Cage. Problem solving, insight. Judgement and decision making. Probability judgements and Bayes theorem. Framing, heuristics.

Strongly recommended reading:
Eysenck & Keane, chap.17
Sternberg, ch. 11

Optional reading:
Sternberg, ch. 12
Bear, ch. 24
Rougier NP: Prefrontal cortex and flexible cognitive control: Rules without symbols. PNAS Vol. 102, No. 20: 7338-7343 (2005)

Neurobiology: single neuron, coupled neurons


2 lectures

Cyril Brom:
A bit of history, anatomy of a neuron, membrane potential, action potencial, synaptic transmition, receptors, neurotransmiters, Gray I, II, EPSP, IPSP, Dale, ionotropic vs. metabotropic receptors, microcircuits, Nernst eq.

Strongly recommended reading:
Kokko, ch. 1 ("KokkoKap1")
Bear, chap. 2, 3, 4, 5
Useful animations

Optional reading:
Bear, chap. 1

Optional video and animations:
Giant squid axon
Neuronal mechanisms
Nice slides

Mathematical models of a single neuron

3 lectures

Cyril Brom:
Ionic conductance, Leaky integrate & fire, Quadratic integrate & fire, Hodgkin & Huxley, linear cable model, Izhikevich's model. Blue brain project.

Strongly recommended reading:
Bear, chap. 2, 3, 4, 5
Izkikevich, ch. 1, 2 (web, "IzhikKap2")

Optional reading:
Koch, chap. 1.1, 1.2, 1.4, 6.1, 6.2 (or the whole chap. 1, 2, 6)
Shepherd, ch. 1
Bower & Beeman, chap. 4
Dayan & Abbott, chap. 5
The Blue Blue Brain Project. Markram, Henry. Nat. Rev. Neurosci., Feb2006, Vol. 7 Issue 2, p153-160
Izhikevich, 2004
Dayan & Abbott, chap. 5
Koch, chap. 1, 2, 6

Low-level motor system

3 lectures

Cyril Brom:
Organization of the motor system. Reflexes, central pattern generators, motor programs. The oculomotor system (horizontal saccades). Hexapod robots. Lampery robots.

Strongly recommended reading:

Bear, 12, 13, 1st part of 14 (pp. 452 — 464)
Ijspeert et al.: From Swimming to Walking with a Salamander Robot Driven by a Spinal Cord Model. Science 315, 1416 (2007)

Optional Reading:

Frasca et al.: Bio-inspired emergent control of locomotion systems. World Scientific, 2004
Raibert, M. H.: Legged Robots That Balance, MIT Press, 1986 ("LeggedRobots_ch1", "LeggedRobots_ch2")

Neurobiology: large-scale circuits, networks; research methods

Neural coding

1 lecture

Rate-code vs. spike-code, encoding/decoding, population coding, tuning-curves, small-worlds, architecture of the neocortex

Supplementary material (in Czech)

Optional reading:
Dayan & Abbott, chap. 1, 5, 6


Karel Blahna, FgU CSAV

Required reading:

Bear, chap. 7

Optional reading:

Bear, chap. 15, 16

Brain research methodology

Kamil Vlček, FgU CSAV

Intra/extracellular recording, EEG, evoked potentials, MRI, fMRI, PET, lesioning, double dissociation, transcranial magnetic resonance

Optional reading:
TR10: Neuron Control by Emily Singer. In: Technology Review, Monday, March 12, 2007


Introduction to behavioral science

Eva Landová, PrF UK:

Behaviorism, etology; FAP, imprinting, appetitive & consumatory behavior
Conditioning; stimulus-response, operant conditioning; trace-conditioning, delay-conditioning, fear-conditioning, eye-blinking paradigm, (non-)match-to-sample,...

Strongly recommended reading:

Sweatt, chap. 1 ("")
Hopson: Behavioral Game Design

Optional reading:

Sweatt, chap. 2
Kokko, chap. 2 - 4

Neurobiological perspective of learning

Cyril Brom:
Molecular mechanisms of learning; LTP, LTD, Habituation, sensitisation, conditioning. NMDA vs. AMPA receptors.

Strongly recommended reading:

Bear, ch. 24, 25
Kendel E & al.: The Molecular Biology of Memory Storage: A Dialogue Between Genes and Synapses. Science 294, 2001: pp. 1030 - 1038

Optional reading:

Bear, ch. 23
Abbott, ch. 7, 8, 9
Sahand, Wesbrook: The circuit of fear, Nature, Vol. 454, 2008, pp. 589-590 ("Fear")

Visual systems of the brain, computational models of vision

Low-level vision

2 lectures

Cyril Brom

The retina, the LGN, the V1; descriptive models of receptive fields (Gabor filters etc.), learning in V1, LISSOM model.

Strongly recommended reading:

Bear, chap. 9, 10

Optional reading:

Bear, chap. 21
Koch II, chap. 4
Dayan & Abbott, chap. 2
O'Reilly, chap. 8
Bednar, chap. 4 - 6
Superior collisulus 1 2
Gazzaniga, chap. 20
Lettvin et al.: What the frog's eye tells the frog's brain

Other materials:

Poster, Video

Higher visual areas

1 lecture

Cyril Brom

V2, V4, MT, FFA, IT, PP; dorsal vs. ventral stream; working memory in the occipital cortex; binding problem; hierarchical models detecting complex features.

Strongly recommended reading:

Bear, chap. 10

Optional reading:

Pasternak & Greenlee: Working memory in primate sensory systems. Nature Reviews Neuroscience, Vol. 6, Feb. 2005, pp. 97-107
DiCarlo & Cox: Untangling invariant object recognition. Trends in Cognitive Sciences. Vol., 11, No. 8, pp. 333 - 341
Hummel: Complementary solutions to the binding problem in vision: Implications for shape perception and object recognition. Visual Cognition, 8, 2001, 489-517
Riesenhuber & Poggio: Hierarchical models of object recognition in cortex. Nature Neuroscience, Vol. 2, No. 11, 1999, pp. 1019 — 1025
Ullman & Epshtein: Visual Classification by a Hierarchy of Extended Fragments. TODO, 2006
Koch II, chap. 8
O'Reilly, chap. 8
Visiontrain materials 2007
Tsunoda et al.: Complex objects are represented in macaque inferotemporal cortex by the combination of feature columns. Nature Neursocience. Vol. 4, No. 8, 2001, pp. 832--838

Higher motor systems

Cyril Brom

Proprioception. Motor, premotor, supplementary motor cortex. Cerebellum (purkinje cells, granule cells, climbing fiebers, parallel fibers; function, Marr's hypothesis). Basal ganglia (gross organisation; go / no-go pathways; function; Parkinson disease; b.g. learning vs. hippocampus learning).

Strongly recommended reading:

Bear, 13, 14

Optional reading:

Eichenbaum, ch. 13
Frank, MJ: Dynamic Dopamine Modulation in the Basal Ganglia: A Neurocomputational Account of Cognitive Deficits in Medicated and Nonmedicated Parkinsonism. Jn Cog Neurosci 17:1, pp. 51-72 (2005)
Girard et al., Contracting model of the basal ganglia. Proc. of Modelling Natural Action Selection. 69-76 (2005)
O'Reilly, RC: Biologically Based Computational Models of High-Level Cognition. Science, Vol. 314, 6 Oct 2006

Spatial cognition

Navigation and episodic-like memory - animals

Tereza Nekovářová, FGÚ

Subjective vs. objective space. Place cells, grid cells, head direction cells. Types of maze experiments. Episodic-like memory.

Strongly recommended reading:

Jeffery (ed.): Introduction. In: The Neurobiology of Spatial Behaviour. Oxford Uni Press (2003) pp. x — xxxi
Etienne & Jeffery: Path Integration in mammals, Hippocampus 14: 180-192 (2004)

Navigation - humans

Kamil Vlček, FGÚ

Allocentric vs. egocentric representation, landmarks, dead-reckoning, cognitive maps, view-dep. representation, VR experiments.

Strongly recommended reading:

Wang & Spelke: Comparative approaches to human navigation. In (Jeffery, ed.): The Neurobiology of Spatial Behaviour. Oxford Uni Press (2003) pp. 119 — 143

Computational models of hippocampus I

2 lectures

Cyril Brom

Anatomy of hippocampus (trisynaptic circuit, DG, CA3, CA1), episodic memory models (simple attractor networks, single events vs. episodes), catastrophic forgetting (dual-net architecture), consolidation, "hippocampal pointers".

Strongly recommended reading:

Bear, ch. 24, 25
Rolls et al.: A unified model of spatial and episodic memory. Proc. R. Soc. Lond. B, 269, pp. 1087 - 1093, 2002
French, R.M.: Catastrophic Forgetting in Connectionist Networks: Causes, Cosequences and Solutions. In: Trends in Cognitive Sciences, 3(4) (1999)

Optional reading:

Lisman: Relating Hippocampal Circuitry to Function: Recall of Memory Sequences by Reciprocal Dentate-CA3 Interactions. Neuron Vol. 22, pp. 233-242, 1999
O'Reilly: chap. 9
McClelland et al.: Why there are complementary learning systems in the hippocampus and neocortex: Insights from the success and failures of connectionist models of learning and memory. Psychological Review Vol. 102, No. 3, pp. 419 - 457, 1995
Samsonovich & Ascoli: A simple neural network model of the hippocampus suggesting its pathfinding role in episodic memory retrieval. In: Learning & Memory, 12, pp. 193-208. 2005
Quiroga et al.: Invariant visual representation by single neurons in the human brain. Nature Vol. 435, June 2005, pp. 1102 — 1107

Computational models of hippocampus III

2 lectures

Head-direction cells models, basic place-cell models (BV cells, multi-chart architecture), grid cell models.

Strongly recommended reading:

Bear, ch. 24, 25
Hafting et al.: Microstructure of a spatial map in the enthorinal cortex. Nature, Vol. 436, 11 Aug 2005, pp 801--806
McNaughton et al.: Path integration and the neural basis of the 'cognitive map'. Nature Reviews neurosci, Vol. 7. Aug. 2006, pp. 663-678

Optional reading:

Solstad et al.: From grid cells to place cells: A mathematical model. Hippocampus, 16, pp. 1026-1031, 2006
Zhang: Representation of Spatial Orientation by the Intrinsic Dynamics of the Head-Direction Cell Ensemble: A Theory. The Journal of Neurosci. 16(6). pp 2112-2126 (1996)
Eichenbaum et al.: The Hippocampus, Memory, and Place Cells: Is It Spatial Memory or a Memory Space? Neuron, Vol. 23, June, 1999, pp 209--226
Fuhs & Touretzky: A Spin Glass Model of Path Integration in Rat Medial Enthorinal Cortex. The Journal of Neurosci. 26(16), pp. 4266-4276, 2006
Nakazawa et al.: NMDA receptors, place cells and hippocampal spatial memory. Nature Reviews Neurosci. Vol. 5, May 2004, pp. 361 --372
Samsonovich & McNaughton: Path Integration and Cognitive Mapping in a Continuous Attractor Neural Network Model. The Journal of Neurosci. 17(15). pp 5900-5920 (1997)
Wills et al.: Attractor Dynamics in the Hippocampal Representation of the Local Environment. Science, Vol. 308, 6 May 2005, pp. 873 — 876
Leutgeb et al.: Independent Codes for Spatial and Episodic Memory in Hippocampal Neuronal Ensembles. Science, Vol. 309, 22 July 2005, pp. 619 --623



The NEURON tutorial

1 lecture
Rudolf Kadlec
10.11. 19:00 SW1

Basics of NEURON simulator, mathematical model used by NEURON, working towards HH model of neuron

Neuron homepage

Tutorial 1
Tutorial 2
Lecture 1


2 lectures
Rudolf Kadlec

1st lecture
24.11. 19:00 SW1

Pattern generators, specifying the task, learning how to use Swimmy
Lecture slides, tutorial and the simulator.
Read chapter 4.1 from SwimmyTutorial2Week.pdf, it provides hints how the circuit could work.

Date to be decided
Check of progress of the work on circuit solution.

The EMERGENT tutorial & abstract neural models


Exams 2010/2011

Winter term 2010/11


1) Swimmy
2) A psychological experiment
3) Participation in a psychological experiment
4) Homework — reading
5) Oral exams: Required reading: Bear, ch. 1 - 5, 7, 8, 12, 13, 1st part of 14 (pp. 452 — 464); "KokkoKap1"; Izkikevich, ch. 1, 2 (web, "IzhikKap2"); Ijspeert et al. 2007


1) A psychological experiment
2) Participation in a psychological experiment
4) Homework — reading
3) Oral exams: Required reading: Bear, ch. 1 - 5, 7, 8, 12, 13, 1st part of 14 (pp. 452 — 464); "KokkoKap1"; Strongly recommended reading: Sterberg, ch. 2 — 7, 11, 12 (or equivalent in Eysenck & Keane)

Psychological experiment

Updated information for Winter term 2010/11:
This assignement is part of exams for all students of Mathematical-Physical faculty. Students of other faculties should either do this assignement or, if they are not familiar with statistics, contact the lecturer for other one (collect data, vizualize the data in Excel - similarly to the chart described in slides and write the report using only chart and means for each condition in the Results section).

Deadline: 23.1.2011

experiment scripts, slides and reading materials


Swimmy Lecture slides, tutorial and the simulator. Students not present at this practicum will solve circuit "swmD".


I have received the homework from the following students:

Kovarova, Majer, Konarova, Stibor, Paciskova, Patek, Preisler, Mika, Skvarek, Dobroucky, Culikova, Bjackova, Sudoma, Vykouk, Podloucky, Pascenko, Toth, Hanus, Horacek, Maslowski, Brunetto, Vondrakova, Sejnoha, Dzurenko, Kolombo, Cerny, Smid, Dechterenko, Horacek, Vodrazka, Popelova, Nohejl, Krajicek, Tomek, Sotak, Policar

All texts were of high or acceptable quality.

Summer term 2010/11

Every student is required to read a paper on a (randomly) assigned topic and prepare 3-6 slides that would introduce in 10 minutes his/her topic to others during a panel (see below). The papers given individually.

Couples of students will have the same topic — students with a same topic will form a team. Students from one team are encouraged to prepare their slides together.

Students from one team will present their topic together to all other students during a panel. There will be one panel on each topic. Each panel will start with a 10 minut presentation of the topic using the prepared slides by a randomly chosen member of the group. Hence, each student must be ready to give this short introduction. Then, a panel discussion will follow for about 15 minutes. Questions will be given by the lector as well as other students. No questions will be known in advance.

Presentations during the panel will constitute 60% of the students evaluations. Each team will be evaluated together! The 40% will be written exam.

The action starts: NOT KNOWN YET.

Schedule & Information for students — 2010/11

In the summer term, lectures take place in S10, Tuesday at 15.40.

Extra lectures:

Fri 15th April, 14:00, S11: Hippocampus


Fri 25th March, 12:20, SW1: Computational models of visual cortex
Fri 29th April, 12:20, SW1: Computational model of hippocampus


Bear et al.: Neuroscience: Exploring the Brain, Third Edition
O'Reilly & Munakata: Computational Explorations in Cognitive Neuroscience
Shepherd (ed.): The Synaptic Organization of the Brain, Fifth Edition
Koch: Biophysics of Computation: Information Processing in Single Neuron
Koch II: The Quest for Consciousness: A Neurobiological Approach
Dayan & Abbott: Theoretical Neuroscience - Ask the lecturer for the copy of the book.
Gazzaniga (ed.): The Cognitive Neurosciences III: Third Edition
Miikkulainen, Bednar, Choe, and Sirosh: Computational Maps in the Visual Cortex - Ask the lecturer for the copy of the book.
Bower & Beeman: The book of Genesis
Gerstner & Kistler: Spiking Neuron Models
Eichenbaum & Cohen: From Conditioning to Conscious Recollection: Memory Systems of the Brain
Sternberg, R.: Kognitivní psychologie, Portál, 2002 (in Czech)
Veselovský, Z.: Etologie : biologie chování zvířat. Praha : Academia, 2005 (in Czech)
Cruse, H.: Neural Networks as Cybernetic Systems
Izhiklevich EM: Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting. The MIT Press, 2007
Kokko H: Modelling For Field Biologists: and Other Interesting People. Cambridge University Press (2007)

Useful web resources

NEURONS - animations of action potential and membrane processes
GENESIS - a book & a simulator
Catacomb - a simulator
Brian - a simulator
MOOSE - a simulator
Krasnow/L-Neuron tools
Interactive Educational Media for the Neural and Cognitive Sciences
Igor Farkas' slides on Neurocomputing
INCF - various resources
neuroMorpho - 3D models of reconstructed neurons
Neurodatabase - data
Cell centred database - data, visualisations
Neuroscience information framework - data, visualisations - visualised slices
Van Essen Lab - tools & data
Karolinska hospital - 3D demos
Caenorhadbitis elegans - atlas
Drosophila CNS
Flybrain - Drosophila brain atlas
Topographica & LISSOM — tools
ModelDB — models database
Adaptive Resonance Theory
Allen Reference Atlas


In the years 2009-11, extensions to the lecture were supported by the project CZ.2.17/3.1.00/31162, which is financed by by the European Social Fund.

Prague & EU: We invest into your future!

Created by: cyril last modification: Wednesday 19 of October, 2016 [20:34:23 UTC] by cyril

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