Event Abstract Back to Event Efficient spike encoding for mapping visual receptive fields A standard way to understand spike-encoding principles by which neurons represent and process information in stimuli is through neural coding analysis. Three spike-encoding methods are commonly used to relate quantitatively neural spiking activity to the features of putative stimuli: Wiener-Volterra kernel (WVK), the spike-triggered average (STA), and the point process generalized linear model (GLM). In a visual receptive field mapping study, we compared the performance of these three spike coding approaches in estimating receptive field sizes and orientation tuning of 251 V1 neurons recorded from two adult monkeys during a fixation period in response to a moving bar. The GLM consisted of two formulations of the conditional intensity function for a point process characterization of the neural spiking activity: one with a stimulus-only component and one with both stimulus and spike history components. The GLM fit is implemented efficiently in MATLAB using a maximum likelihood principle. Goodness-of-fit of spike encoding methods was assessed using cross-validation with Kolmogorov-Smirnov (KS) tests in light of the time-rescaling theorem. Spike coding accuracy and reliability are evaluated for each model in predicting the individual neurons? spiking activity for every moving bar direction (4016 models in total, for 251 neurons,16 different directions, and 9 trials per direction). The GLM that considered spike history of up to 35 ms accurately predicted neuronal spiking activity (95% confidence intervals for the one-sample KS test) with a performance of 97.0% (3895/4016) for the training data, and 96.5% (3876/4016) for the test data. If the spike history was not considered, then the performance dropped to 73.1% in the training and 71.3% in the testing data. In contrast, the WVK and the STA predicted spiking activity poorly, achieving the accuracy rates of 24.2% and 44.5% for the test data, respectively. In our findings, the receptive field size estimates obtained from the GLM (with and without history), WVK, and STA were comparable using a standard 1/e criterion; however, using a new criterion based on the 95% confidence bound of the rate estimate, the RF size estimates from WVK and STA are greatly underestimated, whereas the estimation bias can be avoided if employing the new criterion from the GLM estimate. We also found that in orientation tuning, compared to the GLM estimate, the results from the WVK and the STA were underestimated on average by a factor of 0.45. Qualitative comparisons between three spike-coding methods reveal their links and differences. The main reason for using the STA and WVF approaches is their apparent simplicity. However, our experimental analyses suggest that more accurate spike prediction as well as more reliable estimates of receptive field size and orientation tuning can be computed using GLM. We believe these findings provide valuable insights in mapping visual receptive fields using efficient spike encoding analysis. Acknowledgments: Research was funded by an European Union grant EU-04330 (to G.P.) and US NIH grants DP1 OD003646-01, MH59733-07, and HL084501-01(to E.N.B.). Conference: Computational and systems neuroscience 2009, Salt Lake City, UT, United States, 26 Feb - 3 Mar, 2009. Presentation Type: Oral Presentation Topic: Oral Presentations Citation: (2009). Efficient spike encoding for mapping visual receptive fields. Front. Syst. Neurosci. Conference Abstract: Computational and systems neuroscience 2009. doi: 10.3389/conf.neuro.06.2009.03.086 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 02 Feb 2009; Published Online: 02 Feb 2009. Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Google Google Scholar PubMed Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.