Temporal features of spike trains in the moth antennal lobe revealed by a comparative time-frequency analysis
- Submitting institution
-
The University of Leicester
- Unit of assessment
- 12 - Engineering
- Output identifier
- 1475
- Type
- D - Journal article
- DOI
-
10.1371/journal.pone.0084037
- Title of journal
- PLoS One
- Article number
- e84037
- First page
- .
- Volume
- 9
- Issue
- 1
- ISSN
- 1932-6203
- Open access status
- Out of scope for open access requirements
- Month of publication
- January
- Year of publication
- 2014
- URL
-
-
- Supplementary information
-
https://doi.org/10.1371/journal.pone.0084037
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
8
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Being able to reliably identify statistically significant time-frequency variations in electrophysiological neural recordings taken is an important requirement to understand the brain. It describes how wavelets and combined statistical analysis may be applied to localise such features in time and rank their significance that provides a tool for neural data analysis. It’s the product of an ongoing collaboration between neuroscientists at the Max Planck Institute for Chemical Ecology, Germany and bioengineers at Leicester that we continue to apply to uncover neural mechanisms of olfactory processing in invertebrates supported by a 2.6 MEuro Future and Emerging Technologies EU RTD project (iCHEM).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
