التفاصيل البيبلوغرافية
| العنوان: |
Development and Validation of a Spike Detection and Classification Algorithm Aimed at Implementation on Hardware Devices |
| المؤلفون: |
E. Biffi, D. Ghezzi, A. Pedrocchi, G. Ferrigno |
| بيانات النشر: |
Computational Intelligence and Neuroscience |
| سنة النشر: |
2010 |
| المجموعة: |
Hindawi Publishing Corporation |
| الوصف: |
Neurons cultured in vitro on MicroElectrode Array (MEA) devices connect to each other, forming a network. To study electrophysiological activity and long term plasticity effects, long period recording and spike sorter methods are needed. Therefore, on-line and real time analysis, optimization of memory use and data transmission rate improvement become necessary. We developed an algorithm for amplitude-threshold spikes detection, whose performances were verified with (a) statistical analysis on both simulated and real signal and (b) Big O Notation. Moreover, we developed a PCA-hierarchical classifier, evaluated on simulated and real signal. Finally we proposed a spike detection hardware design on FPGA, whose feasibility was verified in terms of CLBs number, memory occupation and temporal requirements; once realized, it will be able to execute on-line detection and real time waveform analysis, reducing data storage problems. |
| نوع الوثيقة: |
article in journal/newspaper |
| اللغة: |
English |
| العلاقة: |
https://doi.org/10.1155/2010/659050Test |
| DOI: |
10.1155/2010/659050 |
| الإتاحة: |
https://doi.org/10.1155/2010/659050Test |
| حقوق: |
Copyright © 2010 E. Biffi et al. |
| رقم الانضمام: |
edsbas.5D258B03 |
| قاعدة البيانات: |
BASE |
