Biological Cybernetics

, Volume 65, Issue 2, pp 135–145 | Cite as

On the computational architecture of the neocortex

I. The role of the thalamo-cortical loop
  • D. Mumford


This paper proposes that each area of the cortex carries on its calculations with the active participation of a nucleus in the thalamus with which it is reciprocally and topographically connected. Each cortical area is responsible for maintaining and updating the organism's knowledge of a specific aspect of the world, ranging from low level raw data to high level abstract representations, and involving interpreting stimuli and generating actions. In doing this, it will draw on multiple sources of expertise, learned from experience, creating multiple, often conflicting, hypotheses which are integrated by the action of the thalamic neurons and then sent back to the standard input layer of the cortex. Thus this nucleus plays the role of an ‘active blackboard’ on which the current best reconstruction of some aspect of the world is always displayed. Evidence for this theory is reviewed and experimental tests are proposed. A sequel to this paper will discuss the cortico-cortical loops and propose quite different computational roles for them.


Experimental Test Cortical Area Multiple Source Active Participation Input Layer 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. Bender DB (1981) Retinotopic organization of the macaque pulvinar. J Neurophys 46:672–693Google Scholar
  2. Blinkov SM, Glazer II (1968) The human brain in figures and tables. Basic Books, New YorkGoogle Scholar
  3. Bransford J, Barclay JB, Franks J (1972) Sentence memory: a constructure vs. interpretive approach. Cogn Psychol 3:193–209Google Scholar
  4. Brodal A (1981) Neurological anatomy. Oxford University Press, OxfordGoogle Scholar
  5. Cherniak C (1990) The bounded brain. J Cogn Neurosci 2:58–68Google Scholar
  6. Clark J, Yuille A (1990) Data fusion for sensory information processing systems. Kluwer Academic Press, AmsterdamGoogle Scholar
  7. Crick F (1984) Function of the thalamic reticular complex: the searchlight hypothesis. Proc Natl Acad Sci 81:4586–4590Google Scholar
  8. Erman LD, Hayes-Roth F, Lesser VR, Reddy R (1980) The HEARSAY-II speech understanding system. Comput Surv 12:213–253Google Scholar
  9. Evarts EV (1973) Motor cortex reflexes associated with learned movement. Science 179:501–503Google Scholar
  10. Felleman DJ, Van Essen DC (1991) Distributed hierarchical processing in primate cerebral cortex. Cerebral Cortex: (to be published)Google Scholar
  11. Gemba H, Hashimoto S, Sasaki K (1981) Cortical field potentials preceding visually initiated hand movements in monkeys. Exp Brain Res 42:435–441Google Scholar
  12. Georgopoulos AP, Lurito JT, Petrides M, Schwartz AB, Massey JT (1989) Mental rotation of the neuronal population vector. Science 243:234–236Google Scholar
  13. Graybiel AM, Berson DM (1981) Families of related cortical areas in the extrastriate visual system. In: Cortical sensory organization, vol 2. Humana Press, Clifton, NJ, pp 103–120Google Scholar
  14. Harth E (1983) Windows on the mind. Quill, New YorkGoogle Scholar
  15. Harth E, Unnikrishnan KP, Pandya AS (1987) The inversion of sensory processing by feedback pathways: a model of visual cognitive functions. Science 1987:184–187Google Scholar
  16. Jahnsen H, Llinas R (1984) Electrophysiological properties of guineapig thalamic neurons: an in vitro study. J Physiol London 349:205–247Google Scholar
  17. Jones EB (1985) The thalamus. Plenum Press, New YorkGoogle Scholar
  18. Lindsey P, Norman D (1977) Human information processing. Academic Press, New YorkGoogle Scholar
  19. Luria AR (1969) Higher cognitive functions in man, 2nd edn. Moscow University Press, Moscow (English edn 1980, Basic Books, New York)Google Scholar
  20. Marr D (1982) Vision. Freeman, San FranciscoGoogle Scholar
  21. Minsky M (1975) A framework for representing knowledge. In: Winston P (ed) The psychology of computer vision. McGraw-Hill, New YorkGoogle Scholar
  22. Mjolness E, Gindi G, Anandan P (1988) Optimization in model matching and perceptual organization. Research report YaleU/ DCS/RR-634Google Scholar
  23. Ojemann G (1983) Brain organization for language from the perspective of electrical stimulation mapping. Behav Brain Sci 2:189–206Google Scholar
  24. Rockel AJ, Hiorns RW, Powell TPS (1980) The basic uniformity in structure of the neocortex. Brain 103:221–244Google Scholar
  25. Selfridge O (1959) Pandemonium: a paradigm for learning. In: Symposium on the Mechanization of Thought Processes. HM Stationary Office, LondonGoogle Scholar
  26. Shepherd G (1990) The synaptic organization of the brain, 3rd edn. Oxford University Press, Oxford.Google Scholar
  27. Sherman SM, Koch C (1986) The control of retinogeniculate transmission in the mammalian lateral geniculate nucleus. Exp Brain Res 63:1–20Google Scholar
  28. Steriade M, Llinas RR (1988) The functional states of the thalamus and the associated neuronal interplay. Physiol Rev 68:649–742Google Scholar
  29. Steriade M, Domich L, Oakson G (1986) Reticularis thalami neurons revisited: activity changes during shifts in states of vigilance. J Neurosci 6:68–81Google Scholar
  30. Treisman A (1988) Features and objects. Q J Exp Psychol 40A:1988Google Scholar
  31. Ullman S (1984) Visual routines. Cognition 18:97–159Google Scholar
  32. Van der Heydt R, Peterhans E (1989) Cortical contour mechanisms and geometrical illusions. In: Lam DM, Gilbert CD (eds) Neural mechanisms of visual perception. Gulf, Houston, TexasGoogle Scholar
  33. Weller RE, Kaas JH (1981) Cortical and subcortical connections of visual cortex in primates. In: Cortical sensory organization, vol 2. Humana Press, Clifton, NJ, pp 121–156Google Scholar
  34. Winston P (1975) Learning structural descriptions from examples. In: Winston (ed) The psychology of computer vision. McGraw-Hill, New YorkGoogle Scholar

Copyright information

© Springer-Verlag 1991

Authors and Affiliations

  • D. Mumford
    • 1
  1. 1.Mathematics DepartmentHarvard UniversityCambridgeUSA

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