Atif G. Hashmi, Mikko H. Lipasti


We describe a cortical architecture inspired by the structural and functional properties of the cortical columns distributed and hierarchically organized throughout the mammalian neocortex. This results in a model which is both computationally efficient and biologically plausible. The strength and robustness of our cortical architecture is ascribed to its distributed and uniformly structured processing units and their local update rules. Since our architecture avoids complexities involved in modeling individual neurons and their synaptic connections, we can study other interesting neocortical properties like independent feature detection, feedback, plasticity, invariant representation, etc. with ease. Using feedback, plasticity, object permanence, and temporal associations, our architecture creates invariant representations for various similar patterns occurring within its receptive field. We trained and tested our cortical architecture using a subset of handwritten digit images obtained from the MNIST database. Our initial results show that our architecture uses unsupervised feedforward processing as well as supervised feedback processing to differentiate handwritten digits from one another and at the same time pools variations of the same digit together to generate invariant representations.


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Paper Citation

in Harvard Style

G. Hashmi A. and H. Lipasti M. (2010). DISCOVERING CORTICAL ALGORITHMS . In Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICNC, (IJCCI 2010) ISBN 978-989-8425-32-4, pages 196-204. DOI: 10.5220/0003079301960204

in Bibtex Style

author={Atif G. Hashmi and Mikko H. Lipasti},
booktitle={Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICNC, (IJCCI 2010)},

in EndNote Style

JO - Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICNC, (IJCCI 2010)
SN - 978-989-8425-32-4
AU - G. Hashmi A.
AU - H. Lipasti M.
PY - 2010
SP - 196
EP - 204
DO - 10.5220/0003079301960204