An interactive tool for visualization of spike train synchronization.
A number of studies have examined the synchronization of central and peripheral spike trains by applying signal analysis techniques in the time and frequency domains. These analyses can reveal the presence of one or more common neural inputs that produce synchronization. However, synchronization measurements can fluctuate significantly due to the inherent variability of neural discharges and a finite data record length. Moreover, the effect of these natural variations is further compounded by the number of parameters available for calculating coherence in the frequency domain and the number of indices used to quantify short-term synchronization (STS) in the time domain. The computational tool presented here provides the user with an interactive environment that dynamically calculates and displays spike train properties along with STS and coherence indices to show how these factors interact. It is intended for a broad range of users, from those who are new to synchronization to experienced researchers who want to develop more meaningful and effective computational and experimental studies. To ensure this freely available tool meets the needs of all users, there are two versions. The first is a stand-alone version for educational use that can run on any computer. The second version can be modified and expanded by researchers who want to explore more in-depth questions about synchronization. Therefore, the distribution and use of this tool should both improve the understanding of fundamental spike train synchronization dynamics and produce more efficient and meaningful synchronization studies.
Terry
Kevin
K
Kessler Foundation Research Center, 1199 Pleasant Valley Way, W. Orange, NJ 07052, USA. kterry@kesslerfoundation.org
D000200:Action Potentials / Q000502:physiology*; D000465:Algorithms; D002490:Central Nervous System / Q000502:physiology; D003198:Computer Simulation / Q000592:standards; D003344:Cortical Synchronization; D004594:Electrophysiology / Q000379:methods*; D006801:Humans; D009474:Neurons / Q000502:physiology*; D010363:Pattern Recognition, Automated / Q000379:methods; D012815:Signal Processing, Computer-Assisted; D012984:Software / Q000592:standards*; D014584:User-Computer Interface