Skip to content

Code for the publication: Välkki IA, Lenk K, Mikkonen JE, Kapucu FE and Hyttinen JAK (2017) Network-Wide Adaptive Burst Detection Depicts Neuronal Activity with Improved Accuracy. Front. Comput. Neurosci. 11:40. doi: 10.3389/fncom.2017.00040

License

Notifications You must be signed in to change notification settings

kerstinlenk/NetworkWideAdaptiveBurstDetection

Repository files navigation

NetworkWideAdaptiveBurstDetection

The network-wide adaptive burst depection algorithm can detect bursts (cascades of action potentials) in neuronal activity, typically measured with in vitro multielectrode arrays. The algorithm is implemented in Matlab.

The repository includes the code for the publication: Välkki IA, Lenk K, Mikkonen JE, Kapucu FE and Hyttinen JAK (2017) Network-Wide Adaptive Burst Detection Depicts Neuronal Activity with Improved Accuracy. Front. Comput. Neurosci. 11:40. doi: 10.3389/fncom.2017.00040

Author

  • Inkeri Välkki

Contributors

  • Kerstin Lenk
  • Emre Kapucu

Citation

DOI

@article{Valkki2017,
author = {V{\"{a}}lkki, Inkeri A. and Lenk, Kerstin and Mikkonen, Jarno E. and Kapucu, Fikret E. and Hyttinen, Jari A. K.},
doi = {10.3389/fncom.2017.00040},
issn = {1662-5188},
journal = {Frontiers in Computational Neuroscience},
number = 40,
pages = {1--14},
title = {{Network-Wide Adaptive Burst Detection Depicts Neuronal Activity with Improved Accuracy}},
url = {http://journal.frontiersin.org/article/10.3389/fncom.2017.00040/full},
volume = {11},
year = {2017}
}

Derivative of CMA algorithm

The algorithm is a derivative of the cumulative moving average (CMA) algorithm published in Kapucu FE, Tanskanen JA, Mikkonen JE, Ylä-Outinen L, Narkilahti S, Hyttinen JAK (2012) Burst analysis tool for developing neuronal networks exhibiting highly varying action potential dynamics. Front. Comput. Neurosci. 6:38. doi: 10.3389/fncom.2012.00038

Requirements

MATLAB (tested with versions 2017-2019b)

Usage

See Manual.docx

License information

The network-wide adaptive burst depection algorithm is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

The code is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.

About

Code for the publication: Välkki IA, Lenk K, Mikkonen JE, Kapucu FE and Hyttinen JAK (2017) Network-Wide Adaptive Burst Detection Depicts Neuronal Activity with Improved Accuracy. Front. Comput. Neurosci. 11:40. doi: 10.3389/fncom.2017.00040

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages