The problem of perfect predictors in statistical spike train models

Towards statistical summaries of spike train data.

Statistical inference has an important role in analysis of neural spike trains. While current approaches are mostly model-based, and designed for capturing the temporal evolution of the underlying stochastic processes, we focus on a data-driven approach where statistics are defined and computed in function spaces where individual spike trains are viewed as points. The first contribution of this...

Predicting Spike Train Responses of Neuron Models Predicting Spike Train Responses of Neuron Models

It is shown how neural spike train responses can be predicted by truncated Wiener series and by LN-cascade models. To prove the capability of these methods we test them on spike trains which have been generated by model neurons. The agreement of the approximated responses and the neuron response to known stimuli is analysed quantitatively by calculating least mean square errors and rates of coi...

the problem of divine hiddenness

این رساله به مساله احتجاب الهی و مشکلات برهان مبتنی بر این مساله میپردازد. مساله احتجاب الهی مساله ای به قدمت ادیان است که به طور خاصی در مورد ادیان ابراهیمی اهمیت پیدا میکند. در ادیان ابراهیمی با توجه به تعالی خداوند و در عین حال خالقیت و حضور او و سخن گفتن و ارتباط شهودی او با بعضی از انسانهای ساکن زمین مساله ای پدید میاید با پرسشهایی از قبیل اینکه چرا ارتباط مستقیم ویا حداقل ارتباط وافی به ب...

Predicting spike train responses of neuron models

Correcting for the sampling bias problem in spike train information measures abbreviated title: Bias in spike train information measures

Acknowledgments We are grateful to S.N. Baker for organizing the EPSRCfunded Newcastle workshop on Spike Train Analysis, which inspired the writing of this review. We thank M. Diamond and E. Arabzadeh for sharing their data, and P.E. Latham, L. Paninski and J.D. Victor for useful discussions and insightful comments. Our research was supported by Pfizer Global Development (SP,RS), EPSRC EP/C0108...