חישוביות וקוגניציה א' 06118
“Men ought to know that from nothing else but thence [from the brain] come joys, delights, laughter and sports, and sorrows, griefs, despondency, and lamentations. And by this, in an special manner, we acquire wisdom and knowledge, and see and hear, and know what are foul and what are fair, what are bad and what are good, what are sweet and what unsavory.” Hippocrates, 460BC-370BC
What are the questions?
5.What is a neuronal map, how does it arise, and what is it good for? 6.What is the role of top-down connections? 8.What is the origin and functional properties of irregular activity? 11. What is the formal computation in early vision? 12. Are neurons adapted for specific computations? 13. How can neural systems compute in the time domain 14. How common are neural codes? 15. How does the hearing system perform auditory scene analysis? 22. Do qualia, metaphor, language, and abstract thought emerge from synesthesia, 23. What are the neural correlates of consciousness?
What are the challenges? The brain operates on multiple temporal and spatial scales (sec) sound localization Barn owl Ormia ochracea (fly) humans spike persistent activity protein synthesis protein turnover lifetime memories
What are the challenges? The brain operates on multiple temporal and spatial scales (m) ionic channel synapse soma of neuron fMRI resolution length of axon hypercolumn vesicle
The approach Proper level of abstraction Mathematical models
Mechanistic vs. normative questions 5.What is a neuronal map, how does it arise, and what is it good for? 6.What is the role of top-down connections? 8.What is the origin and functional properties of irregular activity? 11. What is the formal computation in early vision? 12. Are neurons adapted for specific computations? 13. How can neural systems compute in the time domain 14. How common are neural codes? 15. How does the hearing system perform auditory scene analysis? 22. Do qualia, metaphor, language, and abstract thought emerge from synesthesia, 23. What are the neural correlates of consciousness?
The approach Mechanistic models (‘how’ questions) Functional models (‘why’ questions’)
Syllabus Computation and Cognition A: Dynamics of neural networks Multistability Oscillations Associative memory Supervised learning Binary perceptron Linear perceptron Back-Propagation Unsupervised learning PCA Clustering Reinforcement learning
Syllabus Computation and Cognition B: Search algorithms Games Reinforcement learning Probabilistic models of Cognition Motor control
מטרות הקורס חישוביות וקוגניציה הקניית כלים חישוביים ותיאורטיים
חישוביות וקוגניציה א' מרצה : יונתן לוינשטיין מתרגל : איתמר לרנר
דרישות פורמליות (לא מחייב) נוכחות בכיתה ( לא פחות מ 50 %~ מהשעורים ) תרגילים יינתנו לשבועיים חובת הגשה 5/6 הגשת תרגילים בזמן ! ( 5 - נקודות לכל יום איחור ) 30 % מהציון הסופי בחינת סיום מחברות פתוחות 70 % מהציון