Neural Comp. NEW Faster Access
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
 QUICK SEARCH:   [advanced]


     


This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Baker, S. N.
Right arrow Articles by Gerstein, G. L.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Baker, S. N.
Right arrow Articles by Gerstein, G. L.
(Neural Computation. 2001;13:1351-1377.)
© 2001 The MIT Press


Letter

Determination of Response Latency and Its Application to Normalization of Cross-Correlation Measures

Stuart N. Baker

Department of Anatomy, University of Cambridge, Cambridge CB2 3DY, U.K.

George L. Gerstein

Department of Neuroscience, University of Pennsylvania, Philadelphia, PA 19104, U.S.A.

It is often of interest experimentally to assess how synchronization between two neurons changes following a stimulus or other behaviorally relevant marker. The joint peristimulus time histogram (JPSTH) achieves this, but assumes that changes in the cells' firing rate following the stimulus are stereotyped from one sweep to the next. Erroneous results can be generated if this is not the case. We here present a method to assess whether there are variations in response latency or amplitude from sweep to sweep. We then describe how the effects of response latency variation can be mitigated by realigning sweeps to their individual latencies. Three methods of detecting response latency are presented and their performance compared on simulated data. Finally, the effect on the JPSTH of sweep realignment using detected latencies is illustrated.




This article has been cited by other articles:


Home page
J. Neurosci.Home page
A. Leblois, T. Boraud, W. Meissner, H. Bergman, and D. Hansel
Competition between feedback loops underlies normal and pathological dynamics in the basal ganglia.
J. Neurosci., March 29, 2006; 26(13): 3567 - 3583.
[Abstract] [Full Text] [PDF]


Home page
J. Neurophysiol.Home page
V. Ventura, C. Cai, and R. E. Kass
Trial-to-Trial Variability and Its Effect on Time-Varying Dependency Between Two Neurons
J Neurophysiol, October 1, 2005; 94(4): 2928 - 2939.
[Abstract] [Full Text] [PDF]


Home page
Neural Comput.Home page
V. Ventura
Testing for and Estimating Latency Effects for Poisson and Non-Poisson Spike Trains
Neural Comput., November 1, 2004; 16(11): 2323 - 2349.
[Abstract] [Full Text] [PDF]


Home page
J. Neurophysiol.Home page
K. C. Daly, G. A. Wright, and B. H. Smith
Molecular Features of Odorants Systematically Influence Slow Temporal Responses Across Clusters of Coordinated Antennal Lobe Units in the Moth Manduca sexta
J Neurophysiol, July 1, 2004; 92(1): 236 - 254.
[Abstract] [Full Text] [PDF]


Home page
Neural Comput.Home page
P. Lansky, R. Rodriguez, and L. Sacerdote
Mean Instantaneous Firing Frequency Is Always Higher Than the Firing Rate
Neural Comput., March 1, 2004; 16(3): 477 - 489.
[Abstract] [Full Text] [PDF]




HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
J COGNITIVE NEUROSCIENCE NEURAL COMPUTATION MIT PRESS JOURNALS
Copyright © 2001 by The MIT Press.