Abstract
Based on elementary assumptions on the interconnectivity within a cortical macrocolumn we derive a differential equation system which models the mean neural activities of its minicolumns. A stability analysis shows a rich diversity of stationary points and sensitive behavior with respect to a parameter of inhibition. If this parameter is continuously changed, the system shows the same types of bifurcations as the macrocolumn model presented in [1] which is based on explicitly defined interconnectivity and spiking neurons. Due to this behavior the macrocolumn is able to make very sensitive decisions with respect to external input. The decision making process can be used to induce self-organization of receptive fields as is shown in [2].
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References
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Lücke, J. (2005). Dynamics of Cortical Columns – Sensitive Decision Making. 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_5
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DOI: https://doi.org/10.1007/11550822_5
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