Author(s)
Content
Video Abstract (AI generated) (01:29) Paper Preprint Data/CodePoint process generalized linear models (GLMs) provide a powerful tool for characterizing the coding properties of neural populations. Spline basis functions are often used in point process GLMs, when the relationship between the spiking and driving signals are nonlinear, but common choices for the structure of these spline bases often lead to loss of statistical power and numerical instability when the signals that influence spiking are bounded above or below. In particular, history dependent spike train models often suffer these issues at times immediately following a previous spike. This can make inferences related to refractoriness and bursting activity more challenging. Here, we propose a modified set of spline basis functions that assumes a flat derivative at the endpoints and show that this limits the uncertainty and numerical issues associated with cardinal splines. We illustrate the application of this modified basis to the problem of simultaneously estimating the place field and history dependent properties of a set of neurons from the CA1 region of rat hippocampus, and compare it with the other commonly used basis functions. We have made code available in MATLAB to implement spike train regression using these modified basis functions. ### Competing Interest Statement The authors have declared no competing interest.
More Projects
Loren Frank
13 views • 2 years ago
Global Immunotalks
390 views • 3 years ago
Laurel Yohe
2 views • 2 years ago
Global Immunotalks
130 views • 3 years ago
Jignesh H. Parmar
0 views • 2 years ago
Winston A. Haynes
0 views • 2 years ago
Noam Mazor
0 views • 2 years ago
Global Immunotalks
182 views • 3 years ago
Cem Yuksel
345 views • 2 years ago
Oscar Gonzalez-Recio
3 views • 2 years ago
Please pick a style:
Uri T Eden. (2021, Nov 8).Efficient Spline Regression for Neural Spiking Data[Video]. Scitok. https://scitok.com/project/p/78cb90c5
Sarmashghi Mehrad. "Efficient Spline Regression for Neural Spiking Data" Scitok, uploaded by T Eden Uri, 8 Nov, 2021, https://scitok.com/project/p78cb90c5
Uri T Eden. "Efficient Spline Regression for Neural Spiking Data" Scitok. (Nov 8, 2021). https://scitok.com/project/p/78cb90c5
Uri T Eden (Nov 8, 2021). Efficient Spline Regression for Neural Spiking Data Scitok. https://scitok.com/project/p/78cb90c5
Uri T Eden. Efficient Spline Regression for Neural Spiking Data[video]. 2021 Nov 8. https://scitok.com/project/p/78cb90c5
@online{al2006link, title={ Efficient Spline Regression for Neural Spiking Data }, author={ T Eden, Uri }, organization={Scitok}, month={ Nov }, day={ 8 }, year={ 2021 }, url = {https://scitok.com/project/p/78cb90c5}, }