15-883 Readings Archive

Selected readings:

• Albus, J. S. (1971) A theory of cerebellar function. Mathematical Biosciences, 10:25-61.

• Albus, J. S. (1975) Data storage in the Cerebellar Model Articulation Controller (CMAC). Transactions of the ASME, Journal of Dynamic Systems, Measurement, and Control, September 1975, pp. 228-233.

• Alexander, G. E. and Crutcher. M. D. (1990) Functional architecture of basal ganglia circuits: neural substrates of parallel processing. Trends in Neurosciences, 13(7):266-271.

• Amaral, D. G. (1993) Emerging principles of intrinsic hippocampal organization. Current Opinion in Neurobiology, 3:225-229.

• Apicella, P., Scarnati, E., Ljungberg, T., and Schultz, W. (1992) Neuronal activity in monkey striatum related to the expectation of predictable environmental events. Journal of Neurophysiology, 68(3):945-960.

• Barto, A., Fagg, A., Sitkoff, N., and Houk, J. (1999) A cerebellar model of timing and prediction in the control of reaching. Neural Computation, 11(3):565-594.

• Baxter, D. A. and Byrne, J. H. (1993) Learning rules from neurobiology. In D. Gardner (ed.), The Neurobiology of Neural Networks, chapter 4, pp. 71-105. MIT Press.

• Bear, M. F., Cooper, L. N., and Ebner, F. F. (1987) A physiological basis for a theory of synapse modification. Science, 237:42-48.

• Bear, M. F. (1995) Mechanism for a sliding synaptic modification threshold. Neuron, 15:1-4.

• Bliss, T. V. P. and Collingridge, G. L. (1993) A synaptic model of memory: long-term potentiation in the hippocampus. Nature, 361:31-39.

• Cherniak, C. (1990) The bounded brain: Toward quantitative neuroanatomy. J. Cog. Neurosci. 2(1):58-68.

• Churchland, P. S. and Sejnowski, T. J. (1992) The Computational Brain, chapter 3. MIT Press.

• Churchland, P.S. (1986) Neurophilosophy: Toward a Unified Science of the Mind-Brain. Chapter 2: Modern Theory of Neurons, pp 48-77. MIT Press.

• Churchland, P. S. (2002) Brain-Wise: Studies in Neurophilosophy, chapter 1, pp. 1-34. MIT Press.

• Delong, M. (2000) The basal ganglia. In E. R. Kandel, J. H. Schwartz, and T. M. Jessell (Eds.), Principles of Neural Science, 4th edition, chapter 43, pp. 853-867. New York: Elsevier.

• Crick, F. and Asanuma, C. (1986) Certain aspects of the anatomy and physiology of the cerebral cortex. In J. L. McClelland and D. E. Rumelhart (eds.), Parallel Distributed Processing: Explorations in the Microstructure of Cognition, vol. II, chapter 20, pp. 333-371. MIT Press.

• Douglas, R., Mahowald, M., and Mead, C. (1995) Neuromorphic analogue VLSI. Annual Review of Neuroscience, 18:255-281.

• A. Fagg, N. Sitkoff, A. Barto, J. Houk. (1997) Cerebellar learning for control of a two-link arm in muscle space. Proceedings of the IEEE Conference on Robotics and Automation, pp. 2638-2644.

• A. Fagg, N. Sitkoff, A. Barto, J. Houk. (1997) A model of cerebellar learning for control of arm movements using muscle synergies. Proceedings of the IEEE International Symposium on Computational Intelligence in Robotics and Automation, pp. 6-12.

• Fiala, J.C., Grossberg, S., and Bullock, D. (1996) Metabotropic glutamate receptor activation in cerebellar Purkinje cells as substrate for adaptive timing of the classically conditioned eye-blink response. Journal of Neuroscience, 16(11):3760-3774.

• Georgopoulos, A. P., Kettner, R. E., and Schwartz, A. B. (1988) Primate motor cortex and free arm movements to visual targets in three-dimensional space. II. Coding of the direction of movement by a neuronal population. Journal of Neuroscience, 8(8): 2928-2937.

• Ghez, C. and Thach, W. T. (2000) The cerebellum. In E. R. Kandel, J. H. Schwartz, and T. M. Jessell (Eds.), Principles of Neural Science, 4th edition, chapter 42, pp. 832-852. New York: Elsevier.

• Glanzman, D. L. (1995) The cellular basis of classical conditioning in Aplysia californica -it's less simple than you think. Trends in Neurosciences, 18(1):30-36.

• Glickstein, M. and Yeo, C. (1990) The cerebellum and motor learning. Journal of Cognitive Neuroscience, 2:69-80.

• Gluck, M. A. and Thompson, R. F. (1987) Modeling the neural substrates of associative learning and memory: a computational approach. Psychological Review, 94(2):176-191.

• Gluck, M.A., and Myers, C. E. (2001) Gateway to Memory, chapter 6, pp. 145-187. Cambridge, MA: MIT Press.

• Hammer, M. (1993) An identified neuron mediates the unconditioned stimulus in associative olfactory learning in honeybees. Nature, 366:59-63.

• Hasselmo, M. E. and Schnell, E. (1994) Laminar selectivity of the cholinergic suppression of synaptic transmission in rat hippocampal region CA1: computational modeling and brain slice physiology. Journal of Neuroscience, 14(6):3898-3914.

• Hasselmo, M. E., Wyble, B. P., and Wallenstein, G. V. (1996) Encoding and retrieval of episodic memories: role of cholinergic and GABAergic modulation in the hippocampus. Hippocampus, 6(6):693-708.

• Hawkins, R. D. and Kandel, E. R. (1984) Is there a cell-biological alphabet for simple forms of learning? Psychological Review, 91(3)375-391.

• Johnston, D. and Amaral, D. G. (1998) Hippocampus. In G. M. Shepherd (ed.), The Synaptic Organization of the Brain, 4th edition, chapter 11, pp. 417-458. Oxford University Press. [Read pages 417-435 and 454-458. Skim the rest if you like.]

• Jordan, M. I. (1986) An introduction to linear algebra in parallel distributed processing. In D. E. Rumelhart and J. L. McClelland (eds.), Parallel Distributed Processing: Explorations in the Microstructure of Cognition, vol. I, chapter 9, pp. 365-422. MIT Press.

• Kohonen, T., Oja, E., and Lehtiö, P. (1981) Storage and processing of information in distributed associative memory systems. In G. E. Hinton and J. A. Anderson (eds.), Parallel Models of Associative Memory, chapter 4, pp. 105-143. Lawrence Erlbaum Associates.

• Malenka, R. C. (1995) LTP and LTD: dynamic and interactive processes of synaptic plasticity. The Neuroscientist, 1(1):35-42.

• Marr, D. (1971) Simple memory: A theory for archicortex. In L. M. Vaina (ed.), From the Retina to the Neocortex: Selected papers of David Marr, pp. 59-128. Includes commentaries by D. Willshaw and B. McNaughton. Paper originally appeared in Philosophical Transactions of the Royal Society of London B, 262:23-81.

• MacPhail, E. (1993) The Neuroscience of Animal Intelligence: From the Sea Hare to the Seahorse, chapter 4, pp. 101-156. Columbia University Press.

• Medina, J.F., Garcia, K.S., Nores, W.L., Taylor, N.M., and Mauk, M.D. (2000) Timing mechanisms in the cerebellum: Testing predictions of a large-scale computer simulation. Journal of Neuroscience, 20(14):5516-5525.

• Meister, M. and Berry II, M. J. (1999) The neural code of the retina. Neuron 27:435-450.

• Miller, R. R., Barnet, R. C., and Grahame, N. J. (1995) Assessment of the Rescorla-Wagner model. Psychological Bulletin, 117(3):363-386.

• Montague, P. R., Dayan, P., Person, C., and Sejnowski, T. J. (1995) Bee foraging in uncertain environments using predictive hebbian learning. Nature, 377:725-728.

• Montague, P. R., Dayan, P., and Sejnowski, T. J. (1996) A framework for mesencephalic dopamine systems based on predictive hebbian learning. Journal of Neuroscience, 16(5);1936-1947.

• O'Reilly R. C. and McClelland, J. L. (1994) Hippocampal conjunctive encoding, storage and recall: avoiding a tradeoff. Hippocampus, 4(6):661-682.

• Pouget, A., and Sejnowski, T. J. (1996)  A model of spatial representations in parietal cortex explains hemineglect. In D. S. Touretzky, M. C. Mozer, and M. E. Hasselmo (eds.), Advances in Neural Information Processing Systems 8, pp, 10-16. Cambridge, MA: MIT Press.
• Pouget, A. and Sejnowski, T. J. (1997) Spatial transformation in the parietal cortex using basis functions. Journal of Cognitive Neuroscience, 9(2):222-237.

• Redish, A. D. and Touretzky, D. S. (1994) The reaching task: Evidence for vector subtraction in the motor system? Biological Cybernetics, 71(4): 307-317.

• Riesenhuber, M. and Poggio, T. (1999) Hierarchical models of object recognition in cortex. Nature Neuroscience, 2:1019-1025.

• Samsonovich, A. and McNaughton, B. L. (1997) Path integration and cognitive mapping in a continuous attractor neural network model. Journal of Neuroscience, 17(15):5900-5920.

• Sanger, T. D. (1994) Theoretical considerations for the analysis of population coding in motor cortex. Neural Computation, 6(1):29-37.

• Schultz, W., Apicella, P., Scarnati, E., and Ljungberg, T. (1992) Neuronal activity in monkey ventral striatum related to the expectation of reward. Journal of Neuroscience, 12(12):4595-4610.

• Schultz, W., Romo, R., Ljungberg, T., Mirenowicz, J., Hollerman, J. R., and Dickinson, A. (1995) Reward-related signals carried by dopamine neurons. In J. C. Houk, J. L. Davis, and D. G. Beiser (Eds.), Models of Information Processing in the Basal Ganglia, chapter 12, pp. 233-248.

• Sharp, P. E. (ed.) (2002) Preface to The Neural Basis of Navigation: Evidence from Single Cell Recording, pp. vii-xxiii. Kluwer Academic Publishers.

• Suri, R. E., and Schultz, W. (2001) Temporal difference model reproduces anticipatory neural activity. Neural Computation, 13(4):841-862.

• Sutton, R. S. and Barto, A. G. (1990) Time-derivative models of Pavlovian reinforcement. In M. Gabriel and J. Moore (eds.), Learning and Computational Neuroscience: Foundations of Adaptive Networks, chapter 12, pp. 497-537.

• Swindale, N. V. (1996) The development of topography in the visual cortex: a review of models. NETWORK: Computation in Neural Systems, 7(2):161-247.

• Tanaka, K. (1996) Inferotemporal cortex and object vision. Annual Review of Neuroscience, 19:109-139.

• Taube, J.S., Goodridge, J.P., Golob, E.J., Dudchenko, P.A., and Stackman, R.W. (1996) Processing the head direction cell signal: a review and commentary. Brain Research Bulletin, 40:477-486.

• Troyer, T.W. and Doupe, A.J. (2000) An associational model of birdsong sensorimotor learning I. Efference copy and the learning of song syllables. Journal of Neurophysiology, 84:1204-1223.

• Troyer, T.W. and Doupe, A.J. (2000) An associational model of birdsong sensorimotor learning II. Temporal hierarchies and the learning of song sequences. Journal of Neurophysiology, 84:1224-1239.

• Tyrrell, T. and Willshaw, D. (1992) Cerbellar cortex: its simulation and the relevance of Marr's theory. Philosophical Transaction of the Royal Society of London, Series B, 336:239-257.

• Willshaw, D. J. and Buckingham, J. T. (1990) An assessment of Marr's theory of the hippocampus as a temporary memory store. Philosophical Transactions of the Royal Society of London B, 329:205-215.

• Witter, M. P. (1993) Organization of the entorhinal-hippocampal system: a review of current anatomical data. Hippocampus, 3(special issue):33-44.

• Zipser, D., and Andersen, R. A. (1988) A back-propagation programmed network that simulates response properties of a subset of posterior parietal neurons. Nature, 331: 679-684.