Fikret E. Kapucu

According to our database1, Fikret E. Kapucu authored at least 11 papers between 2012 and 2020.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

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Bibliography

2020
Corrigendum: Spectral Entropy Based Neuronal Network Synchronization Analysis Based on Microelectrode Array Measurements.
Frontiers Comput. Neurosci., 2020

2017
Network-Wide Adaptive Burst Detection Depicts Neuronal Activity with Improved Accuracy.
Frontiers Comput. Neurosci., 2017

On electrophysiological signal complexity during biological neuronal network development and maturation.
Proceedings of the 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017

2016
Methods to Enhance Information Extraction from Microelectrode Array Measurements of Neuronal Networks.
PhD thesis, 2016

Spectral Entropy Based Neuronal Network Synchronization Analysis Based on Microelectrode Array Measurements.
Frontiers Comput. Neurosci., 2016

Automatic objective thresholding to detect neuronal action potentials.
Proceedings of the 24th European Signal Processing Conference, 2016

Analyzing the feasibility of time correlated spectral entropy for the assessment of neuronal synchrony.
Proceedings of the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2016

2015
On the threshold based neuronal spike detection, and an objective criterion for setting the threshold.
Proceedings of the 7th International IEEE/EMBS Conference on Neural Engineering, 2015

A fast stimulability screening protocol for neuronal cultures on microelectrode arrays.
Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2015

Quantification and automatized adaptive detection of in vivo and in vitro neuronal bursts based on signal complexity.
Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2015

2012
Burst analysis tool for developing neuronal networks exhibiting highly varying action potential dynamics.
Frontiers Comput. Neurosci., 2012


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