Abstract
Two techniques of non-parametric change point detection are applied to two different neuroscience datasets. In the first dataset, we show how the multivariate non-parametric change point detection can precisely estimate reaction times to input stimulation in the olfactory system using joint information of spike trains from several neurons. In the second example, we propose to analyze communication and sequence coding using change point formalism as a time segmentation of homogeneous pieces of information, revealing cues to elucidate directionality of the communication in electric fish. We are also sharing our software implementation Chapolins at GitHub.
| Original language | English (US) |
|---|---|
| Title of host publication | 2016 50th Annual Conference on Information Systems and Sciences, CISS 2016 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 545-550 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781467394574 |
| DOIs | |
| State | Published - Apr 26 2016 |
| Event | 50th Annual Conference on Information Systems and Sciences, CISS 2016 - Princeton, United States Duration: Mar 16 2016 → Mar 18 2016 |
Other
| Other | 50th Annual Conference on Information Systems and Sciences, CISS 2016 |
|---|---|
| Country | United States |
| City | Princeton |
| Period | 3/16/16 → 3/18/16 |
Keywords
- Communication
- Electric fish
- Non-parametric
- Olfaction
ASJC Scopus subject areas
- Computer Networks and Communications
- Information Systems
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Cite this
Mosqueiro, T., Strube-Bloss, M., Tuma, R., Pinto, R., Smith, B., & Huerta, R. (2016). Non-parametric change point detection for spike trains. In 2016 50th Annual Conference on Information Systems and Sciences, CISS 2016 (pp. 545-550). [7460561] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CISS.2016.7460561