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Biologically Inspired Intelligent Systems

Biologically Inspired Intelligent Systems. Lecture 1 Dr. Roger S. Gaborski Tuesday / Thursday: 10:00am-11:50am Room: GOL (70)- 3455. Where to Find Me. Office: 70 – 3647 Office Hours: Tuesday noon-2pm* Unless otherwise noted My lab 70-3400 Email: rsg@cs.rit.edu.

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Biologically Inspired Intelligent Systems

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  1. Biologically Inspired Intelligent Systems Lecture 1 Dr. Roger S. Gaborski Tuesday / Thursday: 10:00am-11:50am Room: GOL (70)- 3455

  2. Where to Find Me • Office: 70 – 3647 • Office Hours: Tuesday noon-2pm* • Unless otherwise noted • My lab 70-3400 • Email: rsg@cs.rit.edu

  3. How will the course be run? • Combination of Lecture and Discussion • Lecture notes supplemented with material from the Internet • Downloadable textbook for computational algorithm. • Reading Assignments -Internet websites and journal articles • Programming Homework Assignments in MATLAB • Quizzes, in-Class Assignments and Exams • Research Paper

  4. Course Webpage • www.cs.rit.edu/~rsg • For MATLAB tutorial - Register at: http://www.mathworks.com/academia/student_center/tutorials/launchpad.html • Do I need to know • Biology? • Chemistry? • Electrical Engineering? • Differential Equations?

  5. Why Study Biological Systems?(primate brains, insect anatomy and behavior, such as, ants, bees, fireflies) • Gain insight for designing systems • Vision systems • Use biological processes as a model for developing computational systems • Apply biological genetic processes to develop algorithms, such as, computational genetic algorithms and evolutionary strategies

  6. Why Study Biological Systems? continued • Use biological behavior to develop algorithms to solve problems • Search algorithms based on firefly or bee behavior • Develop artificial life algorithms • Gain insight into complex information processing in living organisms • Gain a better understanding of structural form that could be applied in robotics

  7. Course Outline:Brain Structure and Function • How is the brain organized? • How are major functions implemented? • How is information processed? • How can we develop of algorithms inspired by brain processes and operation • Such as: • Vision system • Computational models influenced by brain processes

  8. A Few Basic Ideas:Brain Model (Paul MacLean) • Three major components have evolved: • Reptilian Complex • Limbic System • Neocortex • All layers interact • http://www.buffalostate.edu/orgs/bcp/brainbasics/triune.html

  9. Brain Model (Paul MacLean) • Reptilian Complex • Brain stem and cerebellum • Physical survival and maintenance of the body • Automatic behaviors

  10. Brain Model (Paul MacLean) • Limbic System • Centers for emotion • Memory

  11. Brain Model (Paul MacLean) • Neocortex • Outer portion of the brain • Responsible for: • Language • Logical Thinking • Planning • Sensory processing

  12. Four Major Lobes http://www.scientificpsychic.com/workbook/chapter5.htm

  13. What Each Lobe Does • Frontal Lobe • Higher mental processes • Longer term memories that are not task related • Parietal Lobe • Integrates sensory information from different modalities

  14. What Each Lobe Does,continued • Occipital Lobe • Visual processing • Temporal Lobe • Auditory perception (hearing, speech)

  15. Are there locations in the brain that are more responsive to face images or images of houses?

  16. Where Do We Recognize Faces? • Fusiform Gyrus (located in temporal lobe) is responsible for: • Face recognition • More responsive to faces, less responsive to stimuli containing objects, scenes and houses

  17. Recognition of Scenes • Parahippocampal place area (PPA) • Subregion of the parahippocampal cortex • Encoding and Recognition of scenes • Area becomes active when individual views images of landscapes, cityscapes or places

  18. Also, Fusiform Gyrus • Fusiform Gyrus also responsible for: • Word recognition • “Visual Word Formation Area” – groups of letters are joined into integrated visual percepts • Within 250 ms we can recognize a word in script of print, regardless of font and size • With-in category classification • Processing color information

  19. REFERENCES: • “The visual word form area: expertise for reading in the fusiform gyrus” • Bruce D. McCandliss, Laurent Cohen and Stanislas Dehaene • TRENDS in Cognitive SciencesVol.7 No.7 July 2003 • “Culture differences in neural processing of faces and houses in the ventral visual cortex” • Joshua O. S. Goh, Eric D. Leshikar, Bradley P. Sutton, Jiat Chow Tan Sam K. Y. Sim, Andrew C. Hebrank, and Denise C. Park • Social Cognitive and Affective Neuroscience, 2010 • “The Parahippocampal Place Area Responds Preferentially to High Spatial Frequencies in Humans and Monkeys” • Reza Rajimehr, Kathryn J. Devaney, Natalia Y. Bilenko, Jeremy C. Young, Roger B. H. Tootell • PLOS Biology (open access journal)

  20. How are computations performed in the brain? • NEURONS :Basic Computational component of the brain

  21. Real Neurons www.alanturing.net/

  22. How Do Real Neurons ‘Operate’ ? http://ei.cs.vt.edu/~history/NEURLNET.HTML

  23. Simple Model

  24. Question? • How does information get to the brain?

  25. How does information get to the brain? • Receptors • Modalities: Light, Smell, Tastes, Sounds, Touch • Cellular structures that transform physical information into electrical impulses

  26. Functional Organization, continued • Information from sensors in the head are carried by the cranial nerves to the brain • Information from the body is carried by peripheral nerves to the spinal column and then by the axons in the spinal column

  27. Cranial Nerves http://www.gwc.maricopa.edu/class/bio201/cn/cranial.htm

  28. Cranial Nerves http://www.gwc.maricopa.edu/class/bio201/cn/cranial.htm

  29. Primary Areas for Each Modality • There are primary areas in the cortex for each perception modality • Information from each modality is sent to a specific region of the cortex • Damage to these areas results in loss (partial or complete) of that modality

  30. Example – Visual Cortex http://thebrain.mcgill.ca/

  31. Other Functions • Memory • Planning • Problem Solving

  32. Computational Neuroscience • Major focus  development and evaluation of models • Use computers because complexity of models make analytical analysis intractable, but analytical studies can provide deeper insight into features of models and the reasons behind numerical findings

  33. Computational Neuroscience-2 • Develop and test hypotheses about functional mechanisms of the brain Speculate how The brain does Something Develop hypotheses Realize model Test against experimental data Evaluate analytically Or numerically

  34. Levels of OrganizationWhich level do we want to investigate? Adapted from “The Computational Brain,” Churchland and Sejnowski

  35. Levels of Implementation • Neuron level • Design individual neuron models • Design individual ‘circuits’ • Train networks of neurons • Evolve Networks • Function level • Algorithmic implementation of functions (hearing, vision, etc) • Abstract level • AI techniques

  36. Evolutionary Algorithms • Genetic Algorithms • Evolutionary Strategies • Firefly Algorithm • Fuzzy Inference Systems

  37. Genetic Algorithm Population of potential solutions Select parents Crossover parents over to produce children Possibly mutate children coeff1a coeff2a coeff3a coeff4a coeff5a Parent 1 coeff1b coeff2b coeff3b coeff4b coeff5b Parent 2 Crossover point coeff1a coeff2a coeff3b coeff4b coeff5b Child 1 coeff1b coeff2b coeff3a coeff4a coeff5a Child 2

  38. Genetic Algorithm Possibly mutate children. For example, Coefficients coeff2a and coeff1b are modified by adding a random number to the original value coeff1a coeff2a coeff3b coeff4b coeff5b Child 1 coeff1b coeff2b coeff3a coeff4a coeff5a Child 2

  39. ASSIGNMENT: Watch the following videos before next Tuesday’s class: • Brain Anatomy and Functions http://www.youtube.com/watch?v=HVGlfcP3ATI&feature=related • Be able to locate and describe the function of the following areas: • Cerebrum • Brain Stem • Cerebellum • Frontal lobe • Parietal lobe • Occipital lobe • Temporal lobe 

  40. VIDEO • Carl Sagan on Human Brain http://www.youtube.com/watch?v=5SHc67Hep48&NR=1&feature=fvwp • Be able to locate and describe the function of the following areas: • Reptilian Complex • Limbic System • Neocortex • Left Hemisphere • Right Hemisphere (how does the function differ from the left?) • What structure connects the left and right hemispheres • Who is Carl Sagan?

  41. VIDEO • How the Body Works : The Regions of the Brain http://www.youtube.com/watch?v=g6KpIrKCDwg&feature=related • What are the three major functional and anatomical parts of the brain? • Which components of the brain make up each part? • What are the functions of each component? • What is the Corpus Callosum

  42. Study the material on the following website: • http://serendip.brynmawr.edu/bb/kinser/Home1.html

  43. YouTube video: “Building the Brain: From Simplicity to Complexity” • http://www.youtube.com/watch?v=qY829SnAm5M • Brain Development • http://www.youtube.com/watch?v=FugrcVhi2tg&feature=relmfu • Grey Matters series, UCtelevision

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