Abstract
We present a system of differential equations which abstractly models neural dynamics and synaptic plasticity of a cortical macrocolumn. The equations assume inhibitory coupling between minicolumn activities and Hebbian type synaptic plasticity of afferents to the minicolumns. If input in the form of activity patterns is presented, self-organization of receptive fields (RFs) of the minicolumns is induced. Self-organization is shown to appropriately classify input patterns or to extract basic constituents form input patterns consisting of superpositions of subpatterns. The latter is demonstrated using the bars benchmark test. The dynamics was motivated by the more explicit model suggested in [1] but represents a much compacter, continuous, and easier to analyze dynamic description.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Lücke, J., von der Malsburg, C.: Rapid processing and unsupervised learning in a model of the cortical macrocolumn. Neural Computation 16, 501–533 (2004)
Mountcastle, V.B.: The columnar organization of the neocortex. Brain 120, 701–722 (1997)
Buxhoeveden, D.P., Casanova, M.F.: The minicolumn and evolution of the brain. Brain, Behavior and Evolution 60, 125–151 (2002)
Favorov, O.V., Diamond, M.: Demonstration of discrete place-defined columns, segregates, in cat SI. Journal of Comparative Neurology 298, 97–112 (1990)
Schmidt, K.E., Kim, D.S., Singer, W., Bonhoeffer, T., Löwel, S.: Functional specificity of long-range intrinsic and interhemispheric connections in the visual cortex of strabismic cats. Journal of Neuroscience 17, 5480–5492 (1997)
Lücke, J.: Dynamics of cortical columns – sensitive decision making. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds.) ICANN 2005. LNCS, vol. 3696, pp. 25–30. Springer, Heidelberg (2005)
Földiák, P.: Forming sparse representations by local anti-Hebbian learning. Biological Cybernetics 64, 165–170 (1990)
Lücke, J.: Hierarchical self-organization of minicolumnar receptive fields. Neural Networks, Special Issue ‘New Developments in Self-Organizing Systems’ 17/8–9, 1377–1389 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lücke, J., Bouecke, J.D. (2005). Dynamics of Cortical Columns – Self-organization of Receptive Fields. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds) Artificial Neural Networks: Biological Inspirations – ICANN 2005. ICANN 2005. Lecture Notes in Computer Science, vol 3696. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550822_6
Download citation
DOI: https://doi.org/10.1007/11550822_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28752-0
Online ISBN: 978-3-540-28754-4
eBook Packages: Computer ScienceComputer Science (R0)