scholarly journals Efficient spline regression for neural spiking data

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0258321
Author(s):  
Mehrad Sarmashghi ◽  
Shantanu P. Jadhav ◽  
Uri Eden
Keyword(s):  
Spike Train ◽  
Point Process ◽  
Statistical Power ◽  
Linear Models ◽  
Basis Functions ◽  
Ca1 Region ◽  
Neural Spiking ◽  
Spline Basis ◽  
Cardinal Splines ◽  
The Relationship

Point 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.

scholarly journals Efficient Spline Regression for Neural Spiking Data

2020 ◽  
Author(s):  
Mehrad Sarmashghi ◽  
Shantanu P Jadhav ◽  
Uri Eden
Keyword(s):  
Spike Train ◽  
Point Process ◽  
Statistical Power ◽  
Linear Models ◽  
Basis Functions ◽  
Ca1 Region ◽  
Neural Spiking ◽  
Spline Basis ◽  
Cardinal Splines ◽  
The Relationship

AbstractPoint 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.

scholarly journals The Relationships Between Serum DHEA-S and AMH Levels in Infertile Women: A Retrospective Cross-Sectional Study

2021 ◽  
Vol 10 (6) ◽  
pp. 1211
Author(s):  
Li-Te Lin ◽  
Kuan-Hao Tsui
Keyword(s):  
Generalized Linear Models ◽  
Large Scale ◽  
Linear Models ◽  
Positive Association ◽  
Cross Sectional Study ◽  
Dehydroepiandrosterone Sulphate ◽  
Sectional Study ◽  
Cross Sectional ◽  
Infertile Women ◽  
The Relationship

The relationship between serum dehydroepiandrosterone sulphate (DHEA-S) and anti-Mullerian hormone (AMH) levels has not been fully established. Therefore, we performed a large-scale cross-sectional study to investigate the association between serum DHEA-S and AMH levels. The study included a total of 2155 infertile women aged 20 to 46 years who were divided into four quartile groups (Q1 to Q4) based on serum DHEA-S levels. We found that there was a weak positive association between serum DHEA-S and AMH levels in infertile women (r = 0.190, p < 0.001). After adjusting for potential confounders, serum DHEA-S levels positively correlated with serum AMH levels in infertile women (β = 0.103, p < 0.001). Infertile women in the highest DHEA-S quartile category (Q4) showed significantly higher serum AMH levels (p < 0.001) compared with women in the lowest DHEA-S quartile category (Q1). The serum AMH levels significantly increased across increasing DHEA-S quartile categories in infertile women (p = 0.014) using generalized linear models after adjustment for potential confounders. Our data show that serum DHEA-S levels are positively associated with serum AMH levels.

scholarly journals Relationship between Cycling Infrastructure and Transportation Cycling in a Small Urban Area

2021 ◽  
Vol 1 (1) ◽  
pp. 99-112
Author(s):  
Richard Larouche ◽  
Nimesh Patel ◽  
Jennifer L. Copeland
Keyword(s):  
Generalized Linear Models ◽  
Qualitative Data ◽  
Linear Models ◽  
The Other ◽  
Small City ◽  
The Road ◽  
The Past ◽  
Low Prevalence ◽  
The Relationship

The role of infrastructure in encouraging transportation cycling in smaller cities with a low prevalence of cycling remains unclear. To investigate the relationship between the presence of infrastructure and transportation cycling in a small city (Lethbridge, AB, Canada), we interviewed 246 adults along a recently-constructed bicycle boulevard and two comparison streets with no recent changes in cycling infrastructure. One comparison street had a separate multi-use path and the other had no cycling infrastructure. Questions addressed time spent cycling in the past week and 2 years prior and potential socio-demographic and psychosocial correlates of cycling, including safety concerns. Finally, we asked participants what could be done to make cycling safer and more attractive. We examined predictors of cycling using gender-stratified generalized linear models. Women interviewed along the street with a separate path reported cycling more than women on the other streets. A more favorable attitude towards cycling and greater habit strength were associated with more cycling in both men and women. Qualitative data revealed generally positive views about the bicycle boulevard, a need for education about sharing the road and for better cycling infrastructure in general. Our results suggest that, even in smaller cities, cycling infrastructure may encourage cycling, especially among women.

scholarly journals Predicting Rates of Inbreeding in Populations Undergoing Selection

Genetics ◽  
2000 ◽  
Vol 154 (4) ◽  
pp. 1851-1864 ◽  
Author(s):  
John A Woolliams ◽  
Piter Bijma
Keyword(s):  
Overlapping Generations ◽  
Linear Models ◽  
Selection Process ◽  
Correction Term ◽  
Random Mating ◽  
Nonrandom Mating ◽  
Selection Processes ◽  
Genetic Contributions ◽  
The Relationship

AbstractTractable forms of predicting rates of inbreeding (ΔF) in selected populations with general indices, nonrandom mating, and overlapping generations were developed, with the principal results assuming a period of equilibrium in the selection process. An existing theorem concerning the relationship between squared long-term genetic contributions and rates of inbreeding was extended to nonrandom mating and to overlapping generations. ΔF was shown to be ~¼(1 − ω) times the expected sum of squared lifetime contributions, where ω is the deviation from Hardy-Weinberg proportions. This relationship cannot be used for prediction since it is based upon observed quantities. Therefore, the relationship was further developed to express ΔF in terms of expected long-term contributions that are conditional on a set of selective advantages that relate the selection processes in two consecutive generations and are predictable quantities. With random mating, if selected family sizes are assumed to be independent Poisson variables then the expected long-term contribution could be substituted for the observed, providing ¼ (since ω = 0) was increased to ½. Established theory was used to provide a correction term to account for deviations from the Poisson assumptions. The equations were successfully applied, using simple linear models, to the problem of predicting ΔF with sib indices in discrete generations since previously published solutions had proved complex.

scholarly journals Bayonet-shaped language development in autism with regression: a retrospective study

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
David Gagnon ◽  
Abderrahim Zeribi ◽  
Élise Douard ◽  
Valérie Courchesne ◽  
Borja Rodríguez-Herreros ◽  
...  
Keyword(s):  
Language Development ◽  
Linear Models ◽  
Autism Spectrum ◽  
Early Language ◽  
Verbal Iq ◽  
Logistic Regression Models ◽  
Language Level ◽  
Language Outcome ◽  
Almost All ◽  
The Relationship

Abstract Background Language delay is one of the major referral criteria for an autism evaluation. Once an autism spectrum diagnosis is established, the language prognosis is among the main parental concerns. Early language regression (ELR) is observed by 10–50% of parents but its relevance to late language level and socio-communicative ability is uncertain. This study aimed to establish the predictive value of ELR on the progression of language development and socio-communicative outcomes to guide clinicians in addressing parents’ concerns at the time of diagnosis. Methods We used socio-communicative, language, and cognitive data of 2,047 autism spectrum participants from the Simons Simplex Collection, aged 4–18 years (mean = 9 years; SD = 3.6). Cox proportional hazard and logistic regression models were used to evaluate the effect of ELR on language milestones and the probability of using complex and flexible language, as defined by the choice of ADOS module at enrollment. Linear models were then used to evaluate the relationship of ELR and non-verbal IQ with socio-communicative and language levels. Results ELR is associated with earlier language milestones but delayed attainment of fluent, complex, and flexible language. However, this language outcome can be expected for almost all autistic children without intellectual disability at 18 years of age. It is mostly influenced by non-verbal IQ, not ELR. The language and socio-communicative level of participants with flexible language, as measured by the Vineland and ADOS socio-communicative subscales, was not affected by ELR. Limitations This study is based on a relatively coarse measure of ultimate language level and relies on retrospective reporting of early language milestones and ELR. It does not prospectively document the age at which language catches up, the relationship between ELR and other behavioral areas of regression, nor the effects of intervention. Conclusions For autistic individuals with ELR and a normal level of non-verbal intelligence, language development follows a “bayonet shape” trajectory: early first words followed by regression, a plateau with limited progress, and then language catch up.

scholarly journals Gender Differences in Phytoestrogens and the Relationship with Speed of Processing in Older Adults: A Cross-Sectional Analysis of NHANES, 1999–2002

Nutrients ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1780 ◽  
Author(s):  
Alwerdt ◽  
Patterson ◽  
Sliwinski
Keyword(s):  
Older Adults ◽  
Gender Differences ◽  
Cognitive Aging ◽  
Linear Models ◽  
Speed Of Processing ◽  
Cross Sectional ◽  
Health And Nutrition ◽  
Performance Results ◽  
Sectional Analysis ◽  
The Relationship

Sex hormone changes in adults are known to play a part in aging, including cognitive aging. Dietary intake of phytoestrogens can mimic estrogenic effects on brain function. Since sex hormones differ between genders, it is important to examine gender differences in the phytoestrogen–cognition association. Therefore, the goal of this study is to examine the relationship between urinary phytoestrogens and speed of processing (SOP) and the variation of the association between genders in older adults. Participants were drawn from the 1999–2002 National Health and Nutrition Examination Survey and included 354 individuals aged 65–85 years old. General linear models (GLMs) were used to test for significant gender differences in the relationship between phytoestrogens and SOP. Results from the GLMs showed significant gender differences in the relationship between genistein and SOP. Higher levels of genistein were associated with better SOP in women. This relationship was reversed in men: higher genistein levels were associated with worse performance. Results indicate that there are distinct gender differences in the relationship between genistein and SOP. These results emphasize the importance of considering gender differences when devising dietary and pharmacologic interventions that target phytoestrogens to improve brain health.

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