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SPRING 07 ARCHIVE Readings

The reading material for this course is drawn from a variety of sources, including book chapters, review articles, journal articles and conference proceedings. There are no required textbooks.

You can expect to have about 30 pages of reading material per week. All reading material will be available in PDF format. You'll need to enter the course ID and PASSWORD to access the PDF files.

Weekly reading lists

Week 1: Jan 16, 18 -- introduction and overview

  1. Hawking S (1994?) Life in the Universe (5 pp)
    Text of a public lecture by physicist Stephen Hawking on the emergence of intelligent life in the universe, and some provocative speculations about what the future might hold.
  2. Belew RK (1991) Artificial life: A constructive lower bound for artificial intelligence. IEEE Expert, 6(1):8-15 (8 pp)
    artificial life research, Alife as a lower bound on AI, centrality of evolution, modeling the environment, computational ethology.
  3. Crist E (2002) The inner life of earthworms: Darwin's argument and its implications. In Bekoff M, Allen C and Burghardt G (eds) The Cognitive Animal. MIT Press. pp. 3-8 (6 pp).
    assessing animal intelligence/cognition; observing behavior in the animal's natural environment; interpretation of behavior.
Additional resources (optional):
  1. Web article on earthworm biology and ecology
    short and interesting.

Week 2: Jan 23, 25 -- behavior without a nervous system; bacterial chemotaxis

  1. Dusenbery DB (1996) Life at Small Scale. Scientific American Library. Chapter 1, Invisible Organisms, pp 2-17 (16 pp).
    intro to microbes, basic problems faced by microbes, diffusion processes, evolutionary history, food chains, hunting and farming life styles in the micro world
  2. Jurica MS, Stoddard BL (1998) Mind your Bs and Rs: Bacterial Chemotaxis, signal transduction, and protein recognition" Structure 6:809-813 (5 pp)
    bacterial chemotaxis, signaling pathway, coupling of sensor to effector elements
  3. Zupanc GKH (2004) Behavioral Neurobiology: An Integrative Approach. Oxford Press. 80-88 (9 pp)
    classification of orienting movements; orienting behavior without a nervous system; cellular mechanisms of taxis behavior in paramecians.
Additional resources (optional):
  1. Benhamou S, Bovet P (1989) How animals use their environment: a new look at kinesis. Anim Behav 38: 375-383 (9 pp)
    how simple sensory-motor coupling can give rise to adaptive behavior (spending more time in 'favorable' parts of the environment)
  2. Dusenbery DB (1996) Life at Small Scale. Chapter 4, Navigating Through a Chemical Sea, pp. 64-89, (26 pp)
    sensing environmental change, choosing a response, sensory adaptation, a cyanobacterium's strategy for finding light, simultaneous sampling, sequential sampling, avoiding obstacles
  3. Spiro P A, Parkinson JS, and Othmer HG (1997) A model of excitation and adaptation in bacterial chemotaxis. Proc. Natl. Acad. Sci. USA 94:7263-7268 (6 pp)
    a detailed biochemical model of the signaling pathway for bacterial chemotaxis

Week 3: Jan 30, Feb 01 -- sensory information processing

  1. Braitenberg V (1984) Vehicles: Experiments in Synthetic Psychology. MIT Press. pp. 1-14 (14 pp)
    Introduction; Vehicle 1: Getting Around; Vehicle 2: Fear and Aggression; Vehicle 3: Love.
  2. Dusenbery DB (1996) Information is where you find it. Biol. Bull. 191:124-128 (5 pp)
    Information from a biological perspective. Informational versus causal agents; 3 information processing pathways operating on different timescales: genome (evolutionary times), memory (lifetime), sensory (current state). Example of informational processing: thermotaxis in root-knot nematodes.
  3. Cariani P. (1991) Some epistemological implications of devices which construct their own sensors and effectors. In: Varela F, Bourgine P eds. Towards a practice of autonomous systems. Cambridge, MA: MIT Press, 484-493 (10 pp)
    A philosophical consideration of relationships between sensation, action, internal processing, and the external environment. Explores implications for agents (biological and artificial) that can evolve new sensors, new effectors, and new information processing strategies.
Additional resources (optional):
  1. Kung C. (2005) A possible unifying principle for mechanosensation. Nature 436: 647-654.
    The senses of sight, smell and taste share a common molecular basis: the binding of a ligand to a G-protein-coupled receptor. But the mechanical senses of touch and hearing have proved harder nuts to crack and their molecular mechanisms are not yet clear. Work showing that mechanosensitive ion channels in bacteria are capable of sensing forces directly from the lipid bilayer may have provided an important clue.

Week 4: Feb 06, 08 -- simple nervous systems; C. elegans chemotaxis

  1. Braitenberg V (1984) Vehicles: Experiments in Synthetic Psychology. pp. 15-25 (11 pp)
    Vehicle 4: Values and Special Tastes; nonlinearity, instincts; Vehicle 5: Logic. "Law of uphill analysis and downhill invention", threshold devices.
  2. Ferree TC, Lockery SR (1999) Computational rules for chemotaxis in the nematode C. elegans. J Comput Neurosci 6:263-277 (15 pp)
    a neural model of chemotaxis; computing temporal derivatives using network dynamics
  3. Allman JM (2000) Evolving brains. Chapter 4, Eyes, Noses and Brains, pp. 63-83 (21 pp)
    Cambrian explosion, predator-prey arms race, early evolution of eyes, chordates, the rise of vertebrates, gene duplications create a keen sense of smell, tectum: an ancient map, origin of the cerebellum, myelin: a crucial vertebrate innovation, cephalopds: the second great pinnacle of brain evolution
Additional resources (optional):
  1. Douglas SJ, Dawson-Scully K, Sokolowski MB (2005) The neurogenetics and evolution of food-related behaviour. Trends Neurosci .28: 644-652.
    Recent review of the neural and genetic components that contribute to the regulation of food-related behaviour in invertebrates, with emphasis on mechanisms that are conserved throughout various taxa.

Week 5: Feb 13, 15 -- modulation of behavior; motor patterns (Exam I on Thu)

  1. Hills T, Brockie PJ, Maricq AV (2004) Dopamine and glutamate control area-restricted search behavior in Caenorhabditis elegans. J Neurosci 24:1217-1225 (9 pp)
    modulation of chemotaxis behavior
  2. Beer R, Chiel J, Sterling L (1991) An artificial insect. American Scientist, 79:444-452 (9 pp)
    A computer simulated cockroach with 78 model neurons and 156 synapses.
Additional resources (optional):
  1. Beer RD and Chiel HJ (1991) The neural basis of behavioral choice in an artificial insect. In J. Meyer and S. Wilson (Eds.), From Animals to Animats: Proceedings of the Conference on Simulation of Adaptive Behavior. MIT Press. pp. 247-254 (8 pp)
    More details on action-selection mechanisms in Beer's artificial insect.
  2. Braitenberg V (1984) Vehicles: Experiments in Synthetic Psychology. MIT Press. pp. 26-28 (3 pp)
    Vehicle 6: Selection, the Impersonal Engineer;

Week 6: Feb 20, 22 -- action selection, control architectures

  1. Prescott TJ, Redgrave P, Gurney K (1999) Layered control architectures in robots and vertebrates. Adaptive Behavior, 7, 99-127 (29 pp).
    Overview of hierarchical control strategies; Brooks' subsumption architecture; hierarchical organization of rat defense system; role of the basal ganglia in action selection.

Week 7: Feb 27, Mar 01 -- vertebrate neuroethology

  1. Carew TJ (2000) Behavioral Neurobiology, Chapter 4, Feature Analysis in Toads. 95-119 (25 pp) A popular vertebrate neuroethological model system for addressing issues of feature detection, classification and action selection.
  2. Dennett DC (1987) Eliminate the Middletoad! Behavioral and Brain Sciences 10, 372-374 (HTML VERSION). Zombie toads, middletoads, brains, minds, and consciousness :-)

Week 8: Mar 06, 08 -- TBA (Tournament I on Thu)

  1. Carew TJ (2000) Behavioral Neurobiology, Chapter 9, Associative Learning in Honeybees. 271-300 (30 pp)
    Overview of honeybee foraging and why learning is important.
Additional resources (optional):
  1. Montague PR, Dayan P, Person C, Sejnowski TJ (1995) Bee foraging in uncertain environments using predictive Hebbian learning. Nature 377:725-728 (4 pp)
    Simulation of bee foraging that incorporates a biologically plausible learning mechanism.
  2. Hammer M, Menzel R (1995) Learning and memory in the honeybee. J Neurosci 15:1617-1630 (14 pp)
    review article on neural basis of associative learning

Week 9: Mar 13, 15 -- circadian rhythms (Exam II on Thu)

  1. Shettleworth SJ (1998) Timing and Counting. In: Cognition, Evolution and Behavior. Oxford Press. pp. 333-337 (5 pp)
    Intro to circadian rhythms
  2. Braitenberg V (1984) Vehicles: Experiments in Synthetic Psychology. MIT Press. pp. 29-49 (21 pp)
    Vehicle 7: Concepts. Vehicle 8: Space, Things, Movements; Vehicle 9: Shapes.

SPRING BREAK: Mar 19-23

Week 10: Mar 27, 29 -- active sensing; memory systems

  1. Braitenberg V (1984) Vehicles: Experiments in Synthetic Psychology. pp. 50-61 (12 pp)
    Vehicle 10: Getting Ideas; Vehicle 11: Rules and Regularities.
  2. Squire LR (2004) Memory systems of the brain: A brief history and current perspective. Neurobiol Learn Mem 82:171-177 (7 pp.)
    overview of memory subtypes and memory systems
  3. Clayton NS, Bussey TJ, Dickinson A (2003) Can animals recall the past and plan for the future? Nat Rev Neurosci 4:685-691 (7 pp.)
    episodic memory in animals; food-caching in birds

Week 11: Apr 03, 05 -- communication

  1. Dennett DC (1998) Out of the Armchair and into the Field. In: Brainchildren: Essays on Designing Minds by DC Dennett. MIT Press. pp. 289-306 (18 pp).
    vocal communication in vervet monkeys
  2. Goss S, Aron S, Deneubourg JL, Pasteels JM (1989) Self-organized shortcuts in the Argentine ant. Naturwissenschaften 76, 579-581 (3 pp).
    geometric cues help distinguish inbound vs outbound directions
  3. Jackson DE, Holcombe M, Ratnieks FLW (2004) Trail geometry gives polarity to ant foraging networks. Nature 432:907-909 (3 pp).
    collectively, ants can find the shortest route to a food resource

Week 12: Apr 10, 12 -- emotions; spatial navigation

  1. Aube M and Senteni A (1996) What are emotions for? Commitments management and regulation within animals/animats encounters. In From Animals to Animats 4 : Proc. Fourth Intl. Conf. on Simulation of Adaptive Behavior, MIT Press, pp. 264-271 (8 pp)
    emotions as a mechanism for resource management in multi-agent systems
  2. Wehner R (2003) Desert ant navigation: how miniature brains solve complex tasks. J. Comp. Physiol. A 189: 579-588 (10 pp). desert ants head straight back to their nest after a circuitous outbound foraging trek...find out how they do it.
  3. Ekstrom AD, Kahana MJ, Caplan JB, et al. (2003) Cellular networks underlying human spatial navigation. Nature 425: 184-187. (4 pp) neural recordings from human subjects (!) provide evidence that human spatial navigation is based on cells that respond at specific locations (place cells) and cells that respond to views of landmarks.

Week 13: Apr 17, 19 - Braitenberg revisited (Exam III on Thursday)

  1. Braitenberg V (1984) Vehicles: Experiments in Synthetic Psychology. pp. 62-83 (22 pp)
    Vehicle 12: Trains of Thought; Vehicle 13: Foresight; Vehicle 14: Egotism and Optimism.

Week 14: Apr 24, 26 - applications (Tournament II on Thursday)

  1. Mussa-Ivaldi FA, Miller LE(2003) Brain-machine interfaces: computational demands and clinical needs meet basic neuroscience. Trends Neurosci 26:329-334 (6 pp.)
    establishing functional connections between brains and computers