UKN: Intro to Cognitive and Neural Science /
Úvod do kognitívnych a neurálnych vied
(Merged with MTL: MATLAB and neurocognition and VKN: Computational and cognitive neuroscience)
Institute of computer science, Faculty of Science
UPJŠ Košice
Winter semester 2024
Lecturer: Norbert Kopčo, Perception and cognition laboratory, norbert.kopco@upjs.sk, Jesenná 5, room T2.16, tel. 234 2450
Teaching assistants (TA): UKN Myroslav Fedorenko myroslav.fedorenko@student.upjs.sk, VKN: Udbhav Singhal udbhav.singhal@student.upjs.sk, Jesenná 5, PCL lab (4th floor). Support: Peter Loksa peter.loksa@upjs.sk.
Lectures: Tue 15:20 – 16:15 via Skype or in person in SJ0S15
Labs: Mon 12:45-14:15 SA1C0 (classrooms with Matlab available for individual use also on: Wed 9:50-11:20 sa1c0 AND 13:30-15:00 sa1c05). With the exception of the initial lab sessions and written exams, the labs will be in the form of individual consultations (or, upon agreement with TAs).
NEWS AND UPDATES (for old updates, scroll to the end of page)
2024/11/18
– Lecture #10 is now online. We will start by catching up on Lecture 9. (We will meet in person, but skype connection will also work.)
– Assignment 3 is now published. It is due today (after extending it by a week).
– Assignment 4 is now published. Due next Monday (week 11).
– Project will be due on Monday in week 12.
– Final exam will be in week 14 during the lab.
Class contents
Overview of the anatomy, physiology and cognitive processes in the human brain and mind. Description of neural centers and mechanisms underlying some cortical functions (e.g., visual, auditory and sensorimotor cortex, learning and memory). Basic physiological, psychophysical and computational methods used in neuroscience with emphasis on the application of computational methods in neurophysiological measurements and in the imaging of brain activity (e.g. magnetic resonance). Technical applications of neuroscience research.
Prerequisites
– basics of biology, chemistry, physics
– linear algebra and differential equations
– knowledge of MATLAB or OCTAVE or willingness to learn
Class philosophy and student’s work
The emphasis will be on individual work during the semester. Attendance at lectures is very important (and will be monitored using an attendance sheet). Students’ work in the labs will involve several assignments which the students will work out individually or in small groups. Submitted assignments will be graded and will constitute a part of the final grade. During the semester there will be two compulsory written exams, one in the middle (midterm exam) and one at the end of the semester (final exam). Another requirement is to work on a project (essay, model, small experiment). Based on the points obtained by a student for the assignments, project and written exams, a final overall grade will be proposed after the final exam on the final week of classes. Those who want to improve their grade will have an opportunity to sign up for an additional exam (assuming they passed the course / ak dostali zápočet).
Grading
Contribution of the individual tasks to the final grade:
– active participation at the lectures 6%
– assignments 20% (5 assignments, 4% each)
– project 14% (not compulsory for MTL)
– midterm exam 30%
– final exam 30%
– extra: 5% of the grade can be earned by the participation on the experiments in the Perception and cognition lab. We will keep you informed about the options.
Penalty in grading and ethics
The number of points earned for assignments and projects is reduced by 20% of the maximum value for the assignment/project with each week of delay (i.e., you do not have to bother at all after 5 weeks). Delay begins to count on the day following the labs during which the assignment / project was supposed to be submitted. Each assignment, project, and essay should reflect the work and knowledge of the person who is stated as the author. Questions from the assignments / labs will also appear in the written exams. You can work in groups (up to 2 people) for the assignments, but I expect that everyone who is listed in the assignment as the author actually participated on it. The contribution of the assignments to the final grade is relatively low because I would like each of you (or each group) to try to work on it so that I can give you a feedback on your work (instead of you sending me a copy of the worked-out assignment that you took from someone else without knowing what was there). At random, I will review how the assignment was done for all who are stated as the authors. And if I find that an author does not know how something was done in the assignment, it could mean losing up to 20% of the overall grade for the whole group (i.e., including those who actually did the assignment and can explain how it was done). Once again, I emphasize that the goal is that everyone, not just one person from the group, should do the work on the assignment. Also, I want to motivate those who have completed the assignment to not provide it to others for copying.
Literature
(some texts are available in the electronic form in this folder, accessible with the password mentioned at the lecture)
Primary source of information are the PDF slides of lectures and the book (in Slovak)
Kopčo Norbert (2011) Výpočtová neuroveda (Úvod do modelovania neurofyziologických a behaviorálnych dát), Vydavateľ: Technická univerzita v Košiciach. (abbreviation KVN)
Additional sources:
Gazzaniga M. (ed.): The New Cognitive Neurosciences. 2nd ed. MIT Press. 1999 (available electronically – upon request. Alternatively, for $15 you can get 5-days access and download whichever of more than 400 books available on CogNet. Printed version of the book is in my office)
Purves et al.: Neuroscience. 2nd ed., Sinauer Associates, 1991 (available in fulltext electronically. It is not possible to orient in the book from the contents but you can view the contents and then search for the title of the chapter)
Dayan P and LF Abbott: Theoretical Neuroscience – Computational and Mathematical Modeling of Neural Systems. MIT Press, 2001 (further referred to as TN, available electronically)
Gerstner et al.: Neuronal Dynamics: From single neurons to networks and models of cognition. Camb Univ Press 2014 (free online).
Stillings et al.: Cognitive Science: An Introduction, 2nd ed., MIT Press, 1995 (referred to as CSAI, available electronically)
Wilson RA a FC Keil: The MIT Encyclopedia of the Cognitive Sciences. MIT Press, 1999 (MITECS available electronically)
Rybár J, Beňušková Ľ a Kvasnička V: Kognitívne vedy. Kalligram, 2002 (referred to as RKV, the copy is in my office)
Posner, M: Foundations of Cognitive Science. MIT Press, 1989 (the copy is in my office)
Kandel ER, Schwartz JH a TM Jessell: Principles of Neural Science. McGraw -Hill, 2000 (the copy is in my office)
Novák M, Faber J a O Kufudaki: Neuronové sítě a informační systémy živých organismů. Grada, 1993 (referred to as NS, available electronically)
Marek Dobeš: Základy neuropsychológie.(available electronically)
Levine DS: Introduction to neural and cognitive modeling. Lawrence Erlbaum 1991 (the copy is in my office)
Hertz J, Krogh A and Palmer RG: Introduction to the theory of neural computation. Addison-Wesley 1991 (HKP, the copy is in my office)
Kopčo Norbert (2011) Výpočtová a kognitívna neuroveda (Návody na cvičenia), Vydavateľ: Technická univerzita v Košiciach.
Kvasnička V and Clementis L (2014) Kognitívna veda v kontexte informatických vied. Slovenská technická univerzita v Bratislave
Projects
Detailed information regarding projects can be found here.
Schedule and grading:
Week 5: Approved topic of the project (20% of the grade). Each group will write what topic they have chosen and what sources they plan to use. Only when I approve the topic you can work on it.
Week 12: project submitted (80% of the grade)
Schedule of lectures:
Week 1: 17.9. Introduction to neuroscience and cognitive science (slides in PDF EN; SK; animations/demos mentioned in the lectures are available in protected folder)
Structure of the class and requirements, What is neuroscience, What is cognitive psychology and cognitive science,
What is computational neuroscience and neural modeling, Examples of neural models at different levels
Literature: KVN (Chapter 1 Introduction, possibly also Chapter 2), TN (Preface), Preface to RKV, Chapter by M. Dobeš about Cognitive psychology, CSAI chapter 1 (possibly also chapters 2 a 3)
Week 2: 24.9. Overview of the anatomy and of the functions of central nervous system (CNS) (slides in PDF EN, SK)
Overview of the anatomy, functions and historical theories about CNS funtioning. Introduction to mathematical methods of modeling of neurophysiological data.
Literature: KVN (Chapters 2,3), NS (pages 19-35, 142-150), PNS (Chapters 1 and 19),
R. Wessel, C. Koch, F. Gabbiani (1996) Coding of time-varying electric field amplitude modulations in a wave-type electric fish. J Neurophysiol 75:2280-93 (1996),
Daugman J (2001) “Brain metaphor and brain theory.”
Additional literature:
Web book Neuroscience: The Organization of the Nervous System, Neural Systems, The Subdivisions of the Central Nervous System
PNS (Chapter 1 The brain and behavior and 19 Integration of sensory and motor function)
Hubel DH and Wiesel TN (1959) Receptive fields of single neurones in the cat’s striate cortex. The Journal of Physiology 148, 574–591
DENISE GELLENE David Hubel, Nobel-Winning Scientist, Dies at 87, New York Times
Week 3: 1.10. Methods of study in neuroscience. Sensory, motor and association brain areas. (slides in PDF EN, SK)
Literature: NS (Chapter 1 Mozek a metody zkoumani…)
Videos from the celebration of the 25th anniversary of the introduction of fMRI in cognitive neuroscience in 2016 containing also an explanation of the method
Videos of Visual Cognitive Disordes shown in lecture from Bob Rafal
Week 4: 8.10. Neuron: Anatomy and types, action potential (slides in PDF EN, SK)
Literatúra: KVN (Chapter 4)
Additional literature: D. Johnston and S. Miao-Sin Wu, Foundations of Cellular Neurophysiology, Chapter 2, The MIT Press (1995)
Week 5: 15.10. Neuron: Models of activation of neuron, Spreading of signals in neuron (slides in PDF EN, SK)
Literature: TN (Chapters 5.2, 5.3, 5.5, 5.8).
Week 6: 22.10. Neuron: neural coding, synaptic transmission (slides in PDF EN, SK)
Vyskočil (2001) Pomalý synaptický přenos Vesmír (80), 13-15
lectures by Christof Koch about neural coding ( local copy, non-functional original source)
Week 7: 29.10. Synaptic plasticity – neural basis of learning and memory (slides in PDF EN, SK)
PNS chapters 64,65. Knudsen EI (2002) Instructed learning in the auditory localization pathway of the barn owl. Nature 417: 322-328
Wilson RA a FC Keil (1999) The MIT Encyclopedia of the Cognitive Sciences. Keywords: „Memory”, “Memory: Animal Studies”, “Memory: Human Neurophysiology” a „Hippocampus“
Jedlicka P, Benuskova L, Macakova J, Ostatnikova D (2002) Molekulove mechanizmy ucenia a pamati. In: Hulin I (ed) Patofyziologia, 6. vydanie. Slovak Academic Press (SAP), s.r.o, Bratislava, pp. 1183-1199.
Kelemen E, Pašťalková E (2000) O studiu paměti u lidí a zvířat Prostorová orientace u potkanů jako model pro studium paměti u savců. Vesmír.
Youtube lecture of Jennifer Groh: Space and Memory from online course The Brain and Space
Week 8: 5.11. Psychology of memory and learning (slides in PDF EN, SK)
Gluck MA, Myers CE (2000) Gateway to Memory. MIT Press. Chapter 2: Introduction
Corkin, S. (2002) What’s new with the amnesic patient H.M.? Nature Reviews Neuroscience 3, 153-160.
Articles related to current controversy about patient H.M.: New York Times, reaction of MIT BCS.
Christopher Nolan (2000) Memento. Quite interesting (action) movie about the man suffering from anterograde amnesia (he will lose the ability to remember anything new in long term)
Week 9: 12.11. Hearing and auditory cognition (slides in PDF EN, SK)
Literature: Grantham, D.W. (1995). Spatial hearing and related phenomena. In B.C.J. Moore (ed.), Hearing. Academic: London, pp. 297-345
Hartman, W.M. (1999) How We Localize Sound. Physics Today.
Fechner GT (1860) Elements of psychophysics
Wilson RA a FC Keil (1999) The MIT Encyclopedia of the Cognitive Sciences. Keywords: „Auditory physiology:, „Audition“
Supplementary links:
Video introduction to auditory research our lab
Deutch D (2020) Musical Illusions and Phantom Words. Video presented at 2020 meeting of LA chapter of Acoustical Society of America.
Dr. William Brownell- ‘From Sound to Action Potentials – A Tour of the Inner Ear’ Association for Research in Otolaryngology seminar (abstract).
Auditory mailing-list’s list of CDs and webs with auditory demonstrations and illusions.
We have several demo CDs in the lab:
1. Brian Moore’s book Perceptual consequences of cochlear damage,
2. Diana Deutsch Musical Illusions And_Paradoxes,
3. Duda Auditory localization demonstrations,
4. Houtsma_Auditory_demonstrations (some available here)
Week 10: 19.11. Sight and vision: Introduction. Perception of brightness, contours, color. BCS/FCS model. Perception of size and distance. (slides in PDF EN, SK)
Literature: CSAI chapters 12.1, 12.3, 12.5
Web: Flash demo with series of visual illusions and explanations what they tell us about processing of visual information in the brain (from University in Bangore, original link), Large collection of visual illusions IllusionWorks
Grossberg, S. and Todorovic, D. (1988). Neural dynamics of 1-D and 2-D brightness perception: A unified model of classical and recent phenomena.Perception & Psychophysics, 43, 241-277
Week 11: 26.11. Attention (slides in PDF EN, SK)
Literature: Pashler HE (1997) Psychology of Attention. MIT Press. Chapter 1: Introduction. Chapter 2: Selective attention.
Behrmann, M. & Haimson, C. (1999) The cognitive neuroscience of visual attention. Curr Opin Neurobiol 9, 158-63
Parasuraman R (2000) The Attentive Brain. Kapitola 1: The attentive brain: Issues and prospects. MIT Press.
Michael Posner on the anatomy of attentional networks – a historical perspective (Youtube video)
Kopčo, N, A Ler, and B Shinn-Cunningham (2001). “Effect of auditory cuing on azimuthal localization accuracy,” J. Acoust. Soc. Am. 109(5), 2377 ( poster in PDF)
Zatorre RJ, Mondor TA and Evans AC (1999) Auditory Attention to Space and Frequency Activates Similar Cerebral Systems. NeuroImage 10:544-554
James W. (1890) The Principles of Psychology. Chapter 11: Attention.
Lavanya Viswanathan and Ennio Mingolla Attention in Depth
Rensink’s demos of the „change blindness“ effect
Phylishin Z (2000) Situating vision in the world. Trends in Cognitive Sciences. 4(5):197-207.
Web: Demos of visual attention from Visual Attention Lab at Rutgers.
DVD demos in the lab: Visual Awareness Demonstrations from Dan Simons lab
Week 12: 3.12. Language, psycholinguistics, production and perception of speech. (slides in PDF EN, SK)
Literature: CSAI chapter 6, MITECS keywords Speech processing, RKN chapter 4.
Gick B & Derrick D Aero-tactile integration in speech perception. Nature 462, 502-504.
Week 13 : 10.12. Crossmodal interactions (hearing, vision, touch). (slides in PDF EN, SK)
Literature:
Web: Seeing through Sound.
Bor et al. (2014) Adults Can Be Trained to Acquire Synesthetic Experiences. Nature Scientific Reports, 4, Article number: 7089
Talk: Amedi A (2022) Healing the brain via Multisensory technologies and using these technologies to better understand the brain
Additional literature: Our paper about crossmodal interactions / ventriloquism effect in humans and apes:
Kopco, N, I-F Lin, BG Shinn-Cunningham, and JM Groh (2009). Reference frame of the ventriloquism aftereffect. Journal of Neuroscience, 29(44):13809-13814
Kopčo N, Lokša P, Lin I-F, Groh J, Shinn-Cunningham B (2019). Hemisphere-Specific Properties of the Ventriloquism Aftereffect. Journal of the Acoustical Society of America, 146, EL177 doi.org/10.1121/1.5123176
Week 14: 18.12. Other topics of study of brain and mind (consciousness, emotions, motivation, decision making, reasoning)
Literature: Keyword Emotions from Purves et al.: Neuroscience.
PICARD, R. W. (1997) Affective Computing. The MIT Press.
Chapter by M. Dobeš about Cognitive psychology
Week 14: 21.12. individually videolecture by Daniel Dennett “From Bacteria to Bach and Back” 30.10.2017 in Prague
Schedule of labs
Week 1: Introduction to Matlab: obtain Matlab from UPJS Matlab page, Matlab Onramp (also see Getting Started videos or Get started web; or see resources in Useful links)
Week 2: Assignment 1 (sk) (info related to assignment 1 is here) (SK), to be submitted by the beginning of the labs in week 4), convolution in Matlab , linear regression
Week 3: discussion related to projects – description of electronic sources;
Week 4: work on project; submit the assignment 1
Week 5: assignment 2 (sk) (to be submitted by the beginning of the labs in week 7); submit the project proposal;
Week 6: work on assignment 2
Week 7: work on the project, submit the assignment 2, assignment 3 (sk) (to be submitted by the beginning of the labs in week 9)
Week 8: written exam 1,
Week 9: submit the assignment 3, assignment 4 (sk) (to be submitted by the beginning of the labs in week 11)
Week 10: work on project and assignment 4
Week 11: submit assignment 4; assignment 5 (sk) (Intro to tests of significance) (to be submitted by week 13)
Week 12: submit the project;
Week 13: submit assignment 5
Week 14: written exam 2, final grades
Useful links (if you find other useful links, you can send them to me)
World organizations: Cognitive neuroscience society, Cognitive science society, Society for neuroscience, Human Brain Mapping, auditory and multimodal: Association for research in otolaryngology, Acoustical Society of America, European Acoustics Association, International Multisensory Research Forum
Slovak/czech/central-european related links: Cognitive science at UKom (+ http://www.meicogsci.eu/ with Vienna / BP / Ljublana), Neuroscience at Neurobio institute at SAV KE (also at Institute of social sciences and Institute of expermental physics) KE, Conference Cognition and artificial life, http://cognitivescience.cz/, Society for cognitive science and philosophy.
Neuroscience in general: facts and figures, more facts, biophysics, Nobel prizes, simulator of Goldmann’s equation, electrophysiology,
Hearing: EarLab
Vision: spatiotemporal receptive fields in LGN and V1, sensitivity to orientation
Neuroanatomy: 3D anatomy of the brain, brain museum, brain anatomy
Modeling: overview of the simulation software, Genesis, The Virtual Brain, Two Ears
Guide to MATLAB/ OCTAVE (free software compatible with MATLAB): interactive introduction to MATLAB Onramp (click on the image in the section “Learn Interactively”), original documentation, video Getting started, short intro in czech language, from MIT in english.
Mathematics: statistics (in slovak), MathWorld, Numerical recipes
Language hints: Short dictionary of slovak language, Medical dictionary (in czech), English-czech medical dictionary (not always available)
Interviews and popularization lectures: Fresh Air with Oliver Sacks (author of the book The man who mistook his wife for a hat)
OLDER NEWS
2024/9/15
– Welcome to the new semester. Please, read carefully the contents of this web – it will serve as the default mode of communication between the teaching staff and the students of the Intro to Cognitive and Nerual Science class (including Matlab and neurocognition and Computational and cognitive Neuroscience – these three courses will be merged). The class will be held in Slovak or English (depending on the number of international students) but the lectures, labs, assignments, and exams are also offered in Slovak and the students can choose in which language they work during the semester. The class webpage is in English. However, there is a Slovak version of the class webpage and the lecture slides in case you prefer to follow it in Slovak (note that not all the information must be up to date on the Slovak web). The students will be allowed to take exams in Slovak or in English, and they can communicate with us in either language (however, note that the teaching assistants are international).
– UKN, MTL and VKN will be merged mainly because too few students signed up for each of the classes.
– Lectures in UKN will mostly take place via skype using this link https://join.skype.com/j43AfhdHOTsa . UKN students are required to attend them – we will track attendance. VKN students will study the lectures individually. They can attend the lab with the UKN students or individually. Students taking MTL are encouraged to join the lectures so that they get background for their assignments. However, the MTL students are not expected to learn the contents of the lectures and they will only be tested from the lab assignments.
– Lecture slides in PDF are now published online in the Schedule of Lectures list below (password will be provided via email and at lecture).
– Lab1 will take place on Monday (UKN) – it will cover intro to Matlab (to obtain matlab see http://upjs.sk/matlab ). It will be covered by Peter Lokša peter.loksa@upjs.sk as the official TAs are traveling. Look for an email from Peter about the location.
– alternate date/time: it is better if the lectures precede the labs. So, let us move the labs to the Wednesday 9:50 or 13:30 where we have time for MTL and VKN (alternatively, we can swap lectures and labs). We’ll discuss this during the lecture.
2024/9/17
– We agreed on the UKN lab to be on Mondays at 12:45 – 14:15 in SA1C0. The VKN lab will separate only for consultations with the TA and for the exams on Wednesdays at 13:30. MTL lab will be with UKN.
2024/9/23
– Lecture #2 is now online. We will start tomorrow by finishing lecture #1, and then #2.
– Assignment #1 is now published. It was discussed in yesterday’s lab.
– Next lab topic will be introduction to projects and work with scientific literature/databases.
2024/9/30
– Lecture #3 is now online.
– Assignment #1 is now published, it is due in Week 4 (on the day of the lab by 23:59).
– During the next lab you should be working on your project definition and proposal (proposal to be submitted in Week 5). Details at https://pcl.upjs.sk/unv_project_eng/
2024/10/7
– Lecture #4 is now online. Tomorrow, we’ll start by finishing up lecture #3.
– Assignment #1 was due yesterday (on the day of the lab by 23:59). Email the assignments to TA Myroslav Fedorenko (in addition to kogneuro@gmail.com)
– Assignment #2 is published. But, the intro will only be given during Lecture #5. So, during the next lab you should be working on your project definition and proposal (proposal to be submitted in Week 5). Details at https://pcl.upjs.sk/unv_project_eng/
2024/10/14
– Lecture #5 is now online.
– Assignment #1 was will be graded soon.
– Assignment #2 is published, due in week 7. The intro will only be given during Lecture #5 and you can consult it with the TA during the next lab.
– Project proposals are due today (i.e., on the day of the lab by 23:59). Email them to me, TA, or kogneuro@gmail.com. Details at https://pcl.upjs.sk/unv_project_eng/
2024/10/10
– Please, inform us if you find any links that are not working (I just updated two links in the Projects section that didn’t work)
– Also the Nobel Prize in chemistry goes to AI research https://www.euronews.com/next/2024/10/09/nobel-prize-in-chemistry-awarded-to-david-baker-demis-hassabis-and-john-jumper-for-work-on
2024/10/8
– AI pioneers John Hopfield and Geoffrey Hinton win Nobel Prize in physics https://www.euronews.com/next/2024/10/08/john-hopfield-and-geoffrey-hinton-win-nobel-prize-in-physics-for-work-on-neural-networks
2024/10/7
– Lecture #4 is now online. Tomorrow, we’ll start by finishing up lecture #3.
– Assignment #1 was due yesterday (on the day of the lab by 23:59). Email the assignments to TA Myroslav Fedorenko (in addition to kogneuro@gmail.com)
– Assignment #2 is published. But, the intro will only be given during Lecture #5. So, during the next lab you should be working on your project definition and proposal (proposal to be submitted in Week 5). Details at https://pcl.upjs.sk/unv_project_eng/
– Lecture #6 is now online.
– Assignment #1 was will be graded soon.
– Assignment #2 is published, due next week.
– Project proposals are due today (i.e., on the day of the lab by 23:59). Email them to me, TA, or kogneuro@gmail.com. Details at https://pcl.upjs.sk/unv_project_eng/
– Midterm exam during the lab in week 8. It will cover lectures 1 – 7 and assignments 1 & 2.
– Assignment 3 will be published next week, but intro will be given in Lecture 7 (and 8). So, next lab is mostly to work on your project.
2024/10/28
– Lecture #7 is now online. Tomorrow we will finish Lecture #6 and hopefully also go through Lecture #7.
– Assignment #1 has been graded. See email with the link to your grades.
– Assignment #2 is due today, by midnight.
– Assignment 3 is now published, intro will be given in Lecture 7 (and 8). It is due in week 9.
– Midterm exam during the NEXT lab in week 8. It will cover lectures 1 – 7 and assignments 1 & 2. The format is a written exam with duration of 90 minutes, consisting of multiple questions. E.g., you will be asked to write answers to questions about a topic from a specific lecture (like “Name the brain areas involved in language processing”) or from the assignments.
2024/11/4
– Lecture #8 is now online.
– Assignment #2 will be graded soon.
– Assignment 3 is now published. Intro will be given in Lecture 8. It is due in week 9.
– Assignment 4 is now published. Intro will be given in Lecture 9.
– Midterm exam will be graded soon. For now no additional exam is planned for the ones who did not prepare for the exam. But, you will have a chance to prepare for the final exam. And, you can get 5 points credit for participation in experiments.
– Lectures #9 and 10 will be in person. Skype will be only available if necessary.
2024/11/10
– Lecture #9 is now online. (It will take place in person.)
– Assignment #2 will be graded soon.
– Assignment 3 is now published. Intro will be given in Lecture 8. It is due this Monday.
– Assignment 4 is now published. Intro will be given in Lecture 9.
– Midterm exam is now graded. You can see your grade in the excel sheet at the link I shared before. As mentioned before, for now no additional exam is planned for the ones who did not prepare for the exam. But, you will have a chance to prepare for the final exam. And, you can get 5 points credit for participation in experiments.
– Lectures #9 and 10 will be in person. Skype will be only available if necessary.