Abstract
The part of the primate visual cortex responsible for the recognition of objects is parcelled into about a dozen areas organized somewhat hierarchically (the region is called the ventral stream). Why are there approximately this many hierarchical levels? Here I put forth a generic information-processing hierarchical model, and show how the total number of neurons required depends on the number of hierarchical levels and on the complexity of visual objects that must be recognized. Because the recognition of written words appears to occur in a similar part of inferotemporal cortex as other visual objects, the complexity of written words may be similar to that of other visual objects for humans; for this reason, I measure the complexity of written words, and use it as an approximate estimate of the complexity more generally of visual objects. I then show that the information-processing hierarchy that accommodates visual objects of that complexity possesses the minimum number of neurons when the number of hierarchical levels is approximately 15.
Similar content being viewed by others
References
Allman J, Jeo R, Sereno M (1994) The functional organization of visual cortex in owl monkeys. In: Baer JF, Weller RE, Kakoma I (eds) Aotus: the owl monkey. Academic, Orlando, pp 287–320
Attneave F (1954) Some informational aspects of visual perception. Psychol Rev 61:183–193
Barlow HB (1961) Possible principles underlying the transformation of sensory messages. In: Rosenblith WA (eds) Sensory communication. MIT Press, Cambridge, pp 217–34
Barlow HB (1986) Why have multiple cortical areas? Vis Res 26:81–90
Boussaoud D, Ungerleider LC, Desimone R (1990) Pathways for motion analysis: cortical connections of the medial superior temporal and fundus of the superior temporal visual areas in the macaque. J Comp Neurol 296:462–495
Boussaoud D, Desimone R, Ungerleider LG (1991) Visual topography of area TEO in the macaque. J Comp Neurol 306:554–575
Cajal SR (1995) Histology of the nervous system, vol. 1. Oxford University Press, New York
Changizi MA (2001a) The economy of the shape of limbed animals. Biol Cybern 84:23–29
Changizi MA (2001b) Principles underlying mammalian neocortical scaling. Biol Cybern 84:207–215
Changizi MA (2001c) Universal scaling laws for hierarchical complexity in languages, organisms, behaviors and other combinatorial systems. J Theor Biol 211: 277–295
Changizi MA (2003a) The brain from 25,000 feet: high level explorations of brain complexity, perception, induction and vagueness. Kluwer, Dordrecht
Changizi MA (2003b) The relationship between number of muscles, behavioral repertoire, and encephalization in mammals. J Theor Biol 220:157–168
Changizi MA (2005) Scaling the brain and its connections. In: Kaas JH (eds) Evolution of nervous systems. Elsevier, Amsterdam
Changizi MA, McDannald MA, Widders D (2002) Scaling of differentiation in networks: nervous systems, organisms, ant colonies, ecosystems, businesses, universities, cities, electronic circuits, and legos. J Theor Biol 218:215–237
Changizi M, Shimojo S (2005a) Character complexity and redundancy in writing systems over human history. Proc R Soc Lond B 272:267–275
Changizi MA, Shimojo S (2005b) Parcellation and area–area connectivity as a function of neocortex size. Brain Behav Evol 66:88–98
Changizi MA, Zhang Q, Ye H, Shimojo S (2006) The structures of letters and symbols throughout human history are selected to match those found in objects in natural scenes. Am Nat (in press)
Cherniak C (1992) Local optimization of neuron arbors. Biol Cybern 66:503–510
Cherniak C (1994) Component placement optimization in the brain. J Neurosci 14:2418–2427
Cherniak C (1995) Neural component placement. Trends Neurosci 18:522–527
Cherniak C, Changizi MA, Kang D (1999) Large-scale optimization of neuron arbors. Phys Rev E 59:6001–6009
Cherniak C, Mokhtarzada Z, R-Esteban R, Changizi B (2004) Global optimization of cerebral cortex layout. Proc Nat Acad Sci 101:1081–1086
Chklovskii DB, Koulakov AA (2000) A wire length minimization approach to ocular dominance patterns in mammalian visual cortex. Physica A 284:318–334
Coogan TA, Burkhalter A (1993) Hierarchical organization of areas in rat visual cortex. J Neurosci 13:3749–3772
Cowey A (1979) Cortical maps and visual perception. The Grindley Memorial Lecture. Q J Exp Psychol 31:1–17
Cowey A (1981) Why are there so many visual areas?. In: Schmitt FO, Warden FG, Adelman G, Dennis SG (eds) The organization of the cerebral cortex. MIT Press, Cambridge, pp 395–413
Durbin R, Mitchison G (1990) A dimension reduction framework for understanding cortical maps. Nature 343:644–647
Felleman DJ, Van Essen DC (1991) Distributed hierarchical processing in the primate cerebral cortex. Cereb Cortex 1:1–47
Hasson U, Levy I, Behrmann M, Hendler T, Malach R (2002) Eccentricity bias as an organizing principle for human high-order object areas. Neuron 34:479–490
Hasson U, Harel M, Levy I, Malach R (2003) Large-scale mirror-symmetry organization of human occipito-temporal object areas. Neuron 37:1027–1041
Hilgetag CC, Grant S (2000) Uniformity, specificity and variability of corticocortical connectivity. Phil Trans R Soc Lond B 355:7–20
Hilgetag CC, O’Neill MA, Young MP (2000) Hierarchical organization of macaque and cat: cortical sensory systems explored with a novel network processor. Phil Trans R Soc Lond B 355:71–89
Jacobs RA, Jordan MI (1992) Computational consequences of a bias toward short connections. J Cogn Neurosci 4:323–336
Kaas JH (1977) Sensory representations in mammals. In: Stent GS (eds) Function and formation of neural systems. Dahlem Konferenzen, Berlin, pp 65–80
Kaas JH (1989) Why does the brain have so many visual areas?. J Cogn Neurosci 1:121–135
Kaas JH (1995) The evolution of isocortex. Brain Behav Evol 46:187–196
Kaas JH (1997a) Theories of visual cortex organization in primates. In: Rockland KS, Kaas JH, Peters A (eds) Cerebral cortex vol 12. extrastriate cortex in primates. Plenum, New York, pp 91–125
Kaas JH (1997b) Topographic maps are fundamental to sensory processing. Brain Res Bull 44:107–112
Kaas JH (2000) Why is brain size so important: design problems and solutions as neocortex gets bigger or smaller. Brain Mind 1:7–23
Kaas JH, Krubitzer LA (1991) The organization of extrastriate visual cortex. In: Dreher B, Robinson SR (eds) Neuroanatomy of the visual pathways and their development. MacMillan, London, pp 302–323
Kaas JH, Morel A (1993) Connections of visual areas of the upper temporal lobe of owl monkeys: the MT crescent and dorsal and ventral subdivisions of FST. J Neurosci 13:534–546
Klyachko VA, Stevens CF (2003) Connectivity optimization and the positioning of cortical areas. Proc Nat Acad Sci 100:7937–7941
Lewis JW, Van Essen DC (2000) Architectonic parcellation of parieto-occipital cortex and interconnected cortical regions in the macaque monkey. J Comp Neurol 428: 79–111
Lyon DC, Kaas JH (2002) Evidence for a modified V3 with dorsal and ventral halves in macaque monkeys. Neuron 33:453–461
Malach R, Levy I, Hasson U (2002) The topography of high-order human object areas. Trends Cogn Sci 6:176–184
Mead C (1989) Analog VLSI and neural systems. Addison-Wesley, Boston
Mitchison G (1991) Neuronal branching patterns and the economy of cortical wiring. Proc R Soc Lond B 245:151–158
Mitchison G (1992) Axonal trees and cortical architecture. Trends Neurosci 15:122–126
Orban G, Van Essen D, Vanduffel W (2004) Comparative mapping of higher visual areas in monkeys and humans. Trends Cogn Sci 8:315–324
Ringo JL (1991) Neuronal interconnection as a function of brain size. Brain Behav Evol 38:1–6
Rockland KS, Pandya DN (1979) Laminar origins and terminations of cortical connections of the occipital lobe in the rhesus monkey. Brain Res 179:3–20
Rolls ET, Aggelopoulos NC, Zheng F (2003) The receptive fields of inferior temporal cortex neurons in natural scenes. J Neurosci 23:339–348
Rosa MGP (1997) Visuotopic organization of primate extrastriate cortex. In: Rockland KS, Kaas JH, Peters A (eds) Cerebral cortex. vol 12. extrastriate cortex in primates. Plenum, New York, pp 127–203
Rosa MGP, Tweedale (2005) Brain maps, great and small: lessons from comparative studies of primate visual cortical organization. Phil Trans R Soc Lond B 360:665–691
Ruppin E, Schwartz EL, Yeshurun Y (1993) Examining the volume efficiency of the cortical architecture in a multi-processor network model. Biol Cybern 70:89–94
Scannell JW, Blakemore C, Young MP (1995) Analysis of connectivity in the cat cerebral cortex. J Neurosci 15:1463–1483
Sereno, Allman JM (1990) Cortical visual areas in mammals. In: Leventhal AG (eds) The neural basis of visual function, vol 4. Macmillan, London, pp 160–172
Sereno MI, Tootell RBH (2005) From monkeys to humans: what do we now know about brain homologies? Curr Opin Neurobiol 15:135–144
Shannon CE (1951) Prediction and entropy of printed English. Bell Syst Tech J 30:50–64
Simoncelli EP, Olshausen BA (2001) Natural image statistics and neural representation. Annu Rev Neurosci 24:1193–1216
Traverso S, Morchio R, Tamone G (1992) Neuronal growth and the Steiner problem. Riv Biol 85:405–418
Ullman S, Vidal-Naquet M, Sali E (2002) Visual features of intermediate complexity and their use in classification. Nat Neurosci 5:682–687
Ungerleider LG, Desimone R (1986) Cortical projections of visual area MT in the macaque. J Comp Neurol 248:190–222
Van Essen DC (1997) A tension-based theory of morphogenesis and compact wiring in the central nervous system. Nature 385:313–319
Van Essen DC (2004) Organization of visual areas in macaque and human cerebral cortex. In: Chalupa LM, Werner JS (eds) The visual neurosciences. MIT Press, Cambridge, pp 507–521
Zeki SM (2003) Improbable areas in the visual brain. Trends Neurosci 26:23–26
Van Essen DC, Maunsell JHR (1983) Hierarchical organization and the functional streams in the visual cortex. Trends Neurosci 6:370–375
Van Essen DC, Newsome WT, Maunsell JHR (1984) The visual field representation in striate cortex of the macaque monkey: asymmetries, anisotropies, and individual variability. Vis Res 24:429–448
Van Essen DC, Felleman DF, DeYoe EA, Olavarria JF, Knierim JJ (1990) Modular and hierarchical organization of extrastriate visual cortex in the macaque. Cold Spring Harb Symp Quant Biol 55: 679–696
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Changizi, M.A. The Optimal Human Ventral Stream from Estimates of the Complexity of Visual Objects. Biol Cybern 94, 415–426 (2006). https://doi.org/10.1007/s00422-006-0056-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00422-006-0056-x