Abstract
We investigated the effect of reciprocal connections in a network of modules of simulated spiking neurons. The neural activity is recorded by means of virtual electrodes and EEG-like signals, called electrochipograms (EChG), are analyzed by time- and frequency-domain methods. Bio-inspired processes in the circuits drive the build-up of auto-associative links within each module, which generate an areal activity, recorded by EChG, that reflect the changes in the corresponding functional connectivity within and between neuronal modules. We found that circuits with short inter-layer reciprocal projections exhibited enhanced response as to the stimulus, as to the inner-activity and long inter-layer projections make circuit exhibit non-coherent behavior. We show evidence that all networks of modules are able to process and maintain patterns of activity associated with the stimulus after its offset.
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Shaposhnyk, V., Villa, A.E.P. (2012). An Effect of Short and Long Reciprocal Projections on Evolution of Hierarchical Neural Networks. In: Villa, A.E.P., Duch, W., Érdi, P., Masulli, F., Palm, G. (eds) Artificial Neural Networks and Machine Learning – ICANN 2012. ICANN 2012. Lecture Notes in Computer Science, vol 7552. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33269-2_47
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DOI: https://doi.org/10.1007/978-3-642-33269-2_47
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