DocumentCode :
972137
Title :
The Effect of Learning on Bursting
Author :
Stegenga, Jan ; le Feber, Joost ; Marani, Enrico ; Rutten, Wim L C
Author_Institution :
Dept. of Electr. Eng., Math. & Comput. Sci. (EEMCS), Univ. of Twente, Enschede
Volume :
56
Issue :
4
fYear :
2009
fDate :
4/1/2009 12:00:00 AM
Firstpage :
1220
Lastpage :
1227
Abstract :
We have studied the effect that learning a new stimulus-response (SR) relationship had within a neuronal network cultured on a multielectrode array. For training, we applied repetitive focal electrical stimulation delivered at a low rate (Lt1/s). Stimulation was withdrawn when a desired SR success ratio was achieved. It has been shown elsewhere, and we verified that this training algorithm, named conditional repetitive stimulation (CRS), can be used to strengthen an initially weak SR. So far, it remained unclear what the role of the rest of the network during learning was. We therefore studied the effect of CRS on spontaneously occurring network bursts. To this end, we made profiles of the firing rates within network bursts. We have earlier shown that these profiles change shape on a time base of several hours during spontaneous development. We show here that profiles of summed activity, called burst profiles, changed shape at an increased rate during CRS. This suggests that the whole network was involved in making the changes necessary to incorporate the desired SR relationship. However, a local (path-specific) component to learning was also found by analyzing profiles of single-electrode-activity phase profiles. Phase profiles that were not part of the SR relationship changed far less during CRS than the phase profiles of the electrodes that were part of the SR relationship. Finally, the manner in which phase profiles changed shape varied and could not be linked to the SR relationship.
Keywords :
bioelectric phenomena; biomedical electrodes; learning (artificial intelligence); medical computing; neural nets; neurophysiology; burst profile; conditional repetitive stimulation; learning; multielectrode array; neuronal network; repetitive focal electrical stimulation; single-electrode-activity phase profile; spontaneously occurring network bursts; stimulus-response relationship; Biological neural networks; Biomedical measurements; Computer science; Delay; Electrical stimulation; Electrodes; Mathematics; Neurons; Protocols; Shape; Strontium; Testing; Cultured neuronal networks; electrical stimulation; multielectrode arrays (MEAs); synaptic plasticity; Algorithms; Animals; Animals, Newborn; Cells, Cultured; Cerebral Cortex; Electric Stimulation; Evoked Potentials; Learning; Nerve Net; Neuronal Plasticity; Pilot Projects; Rats; Rats, Wistar;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2008.2006856
Filename :
4663623
Link To Document :
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