Recovery of Sequential and Non Sequential Memories with a Neural Mass Model

Filippo Cona, Mauro Ursino

Abstract

A neural model for the recovery of learnt patterns is presented. The model simulates the theta-gamma activity associated to memory recall. Two versions of the model are described: the first can learn generic patterns without a given order, while the second learns patterns in a specific sequence. The latter has been implemented to overcome the limited recovery capacity of the former. The network is trained using Hebbian and anti-Hebbian paradigms, and exploits excitatory and inhibitory mutual synapses. The results show that autoassociative memories for storage and recovery of multiple patterns can be built using biologically inspired models which simulate brain rhythms, and that the model which learns sequences can recover much more patterns.

References

  1. Bartos, M., Vida, I., Frotscher, M., Meyer, A., Monyer, H., Geiger, J. R. P. and Jonas, P., (2002). Fast synaptic inhibition promotes synchronized gamma oscillations in hippocampal interneuron networks. Proceedings of the National Academy of Sciences of the United States of America, 99(20), 13222-13227.
  2. Bartos, M., Vida, I. and Jonas, P., (2007). Synaptic mechanisms of synchronized gamma oscillations in inhibitory interneuron networks. Nature Reviews Neuroscience, 8(1), 45-56.
  3. Bikbaev, A. and Manahan-Vaughan, D., (2008). Relationship of hippocampal theta and gamma oscillations to potentiation of synaptic transmission. Frontiers in Neuroscience, 2(1), 56-63.
  4. Canolty, R. T., Edwards, E., Dalal, S. S., Soltani, M., Nagarajan, S. S., Kirsch, H. E., Berger, M. S., Barbaro, N. M. and Knight, R. T., (2006). High gamma power is phase-locked to theta oscillations in human neocortex. Science, 313(5793), 1626-1628.
  5. Cona, F., Zavaglia, M. and Ursino, M., (2012). Binding and segmentation via a neural mass model trained with hebbian and anti-hebbian mechanisms. International Journal of Neural Systems, 22(02), 1-20.
  6. Cowan, N., (2000). The magical number 4 in short-term memory: A reconsideration of mental storage capacity. Behavioral and Brain Sciences, 24(01), 87-185.
  7. Doesburg, S. M., Green, J. J., McDonald, J. J. and Ward, L. M., (2009). Rhythms of consciousness: binocular rivalry reveals large-scale oscillatory network dynamics mediating visual perception. PLoS ONE, 4(7), e6142.
  8. Lisman, J., (2005). The theta/gamma discrete phase code occuring during the hippocampal phase precession may be a more general brain coding scheme. Hippocampus, 15(7), 913-922.
  9. von der Malsburg, C. and Buhmann, J., (1992). Sensory segmentation with coupled neural oscillators. Biological Cybernetics, 67(3), 233-242.
  10. Miller, G. A., (1956). The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychological Review, 63(2), 81-97.
  11. Singer, W., (1999). Neuronal synchrony: a versatile code for the definition of relations. Neuron, 24, 49-65.
  12. Ursino, M., La Cara, G. E. and Sarti, A., (2003). Binding and segmentation of multiple objects through neural oscillators inhibited by contour information. Biological Cybernetics, 89(1), 56-70.
  13. Ursino, M., Cona, F. and Zavaglia, M., (2010). The generation of rhythms within a cortical region: Analysis of a neural mass model. NeuroImage, 52(3), 1080-1094.
  14. Ursino, M., Magosso, E. and Cuppini, C., (2009). Recognition of abstract objects via neural oscillators: Interaction among topological organization, associative memory and gamma band synchronization. IEEE Transactions on Neural Networks, 20(2), 316- 335.
  15. Varela, F., Lachaux, J. P., Rodriguez, E. and Martinerie, J., (2001). The brainweb: Phase synchronization and large-scale integration. Nature Reviews Neuroscience, 2(4), 229-239.
  16. Wang, D., Buhmann, J. and von der Malsburg, C., (1990). Pattern segmentation in associative memory. Neural Computation, 2(1), 94-106.
  17. Wang, D. and Terman, D., (1997). Image segmentation based on oscillatory correlation. Neural Computation, 9(4), 805-836.
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Paper Citation


in Harvard Style

Cona F. and Ursino M. (2012). Recovery of Sequential and Non Sequential Memories with a Neural Mass Model . In Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2012) ISBN 978-989-8565-33-4, pages 547-551. DOI: 10.5220/0004154005470551


in Bibtex Style

@conference{ncta12,
author={Filippo Cona and Mauro Ursino},
title={Recovery of Sequential and Non Sequential Memories with a Neural Mass Model},
booktitle={Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2012)},
year={2012},
pages={547-551},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004154005470551},
isbn={978-989-8565-33-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: NCTA, (IJCCI 2012)
TI - Recovery of Sequential and Non Sequential Memories with a Neural Mass Model
SN - 978-989-8565-33-4
AU - Cona F.
AU - Ursino M.
PY - 2012
SP - 547
EP - 551
DO - 10.5220/0004154005470551