Do Cortical Neurons Process Luminance or Contrast to Encode Surface Properties?

2006 ◽  
Vol 95 (4) ◽  
pp. 2638-2649 ◽  
Author(s):  
Tony Vladusich ◽  
Marcel P. Lucassen ◽  
Frans W. Cornelissen
Keyword(s):  
Surface Properties ◽  
Cortical Neurons ◽  
Goodness Of Fit ◽  
Information Criterion ◽  
Statistical Technique ◽  
Model Parameters ◽  
Sample Population ◽  
Individual Response ◽  
Neural Basis ◽  
The Difference

On the one hand, contrast signals provide information about surface properties, such as reflectance, and patchy illumination conditions, such as shadows. On the other hand, processing of luminance signals may provide information about global light levels, such as the difference between sunny and cloudy days. We devised models of contrast and luminance processing, using principles of logarithmic signal coding and half-wave rectification. We fit each model to individual response profiles obtained from 67 surface-responsive macaque V1 neurons in a center-surround paradigm similar to those used in human psychophysical studies. The most general forms of the luminance and contrast models explained, on average, 73 and 87% of the response variance over the sample population, respectively. We used a statistical technique, known as Akaike's information criterion, to quantify goodness of fit relative to number of model parameters, giving the relative probability of each model being correct. Luminance models, having fewer parameters than contrast models, performed substantially better in the vast majority of neurons, whereas contrast models performed similarly well in only a small minority of neurons. These results suggest that the processing of local and mean scene luminance predominates over contrast integration in surface-responsive neurons of the primary visual cortex. The sluggish dynamics of luminance-related cortical activity may provide a neural basis for the recent psychophysical demonstration that luminance information dominates brightness perception at low temporal frequencies.

scholarly journals A Comparison of Generalized Hyperbolic Distribution Models for Equity Returns

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Virginie Konlack Socgnia ◽  
Diane Wilcox
Keyword(s):  
Stock Returns ◽  
Goodness Of Fit ◽  
Temporal Stability ◽  
Information Criterion ◽  
Estimation Algorithm ◽  
Dependence Structure ◽  
Model Parameters ◽  
Distribution Models ◽  
Generalized Hyperbolic Distribution ◽  
Fit Statistics

We discuss the calibration of the univariate and multivariate generalized hyperbolic distributions, as well as their hyperbolic, variance gamma, normal inverse Gaussian, and skew Student’st-distribution subclasses for the daily log-returns of seven of the most liquid mining stocks listed on the Johannesburg Stocks Exchange. To estimate the model parameters from historic distributions, we use an expectation maximization based algorithm for the univariate case and a multicycle expectation conditional maximization estimation algorithm for the multivariate case. We assess the goodness of fit statistics using the log-likelihood, the Akaike information criterion, and the Kolmogorov-Smirnov distance. Finally, we inspect the temporal stability of parameters and note implications as criteria for distinguishing between models. To better understand the dependence structure of the stocks, we fit the MGHD and subclasses to both the stock returns and the two leading principal components derived from the price data. While the MGHD could fit both data subsets, we observed that the multivariate normality of the stock return residuals, computed by removing shared components, suggests that the departure from normality can be explained by the structure in the common factors.

Applying the Anderson-Darling Test to Suicide Clusters

Crisis ◽  
2013 ◽  
Vol 34 (6) ◽  
pp. 434-437 ◽  
Author(s):  
Donald W. MacKenzie
Keyword(s):  
Poisson Process ◽  
Goodness Of Fit ◽  
Small Samples ◽  
Massachusetts Institute Of Technology ◽  
Homogeneous Poisson Process ◽  
Cornell University ◽  
The Difference ◽  
Suicide Clusters ◽  
Institute Of Technology ◽  
Anderson Darling

Background: Suicide clusters at Cornell University and the Massachusetts Institute of Technology (MIT) prompted popular and expert speculation of suicide contagion. However, some clustering is to be expected in any random process. Aim: This work tested whether suicide clusters at these two universities differed significantly from those expected under a homogeneous Poisson process, in which suicides occur randomly and independently of one another. Method: Suicide dates were collected for MIT and Cornell for 1990–2012. The Anderson-Darling statistic was used to test the goodness-of-fit of the intervals between suicides to distribution expected under the Poisson process. Results: Suicides at MIT were consistent with the homogeneous Poisson process, while those at Cornell showed clustering inconsistent with such a process (p = .05). Conclusions: The Anderson-Darling test provides a statistically powerful means to identify suicide clustering in small samples. Practitioners can use this method to test for clustering in relevant communities. The difference in clustering behavior between the two institutions suggests that more institutions should be studied to determine the prevalence of suicide clustering in universities and its causes.

scholarly journals Relationship between Psychological Distress and Prolonged Sedentary Bouts in the Elderly: Four Period Analysis

Healthcare ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 676
Author(s):  
Yutaka Owari
Keyword(s):  
Mental Health ◽  
Psychological Distress ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Secondary Analysis ◽  
The Elderly ◽  
Sample Population ◽  
Elderly Individuals ◽  
Sedentary Bouts ◽  
Fit Index

Background: Too much sitting is associated with low mental health in elderly individuals. We clarified the relationship between psychological distress and the rate of prolonged sedentary bouts (PSBs) among the elderly over four periods. Methods: In a secondary analysis, a sample population of 68 adults aged 65 years or older in Japan was used. The following proxy variables were used: PSB (mental health) and the Kessler 6 scale; K6 scores (psychological distress). Results: Using the cross-lagged effects models, from “2016 K6” to “2017 PSB” (p = 0.004), from “2017 K6” to “2018 PSB” (p < 0.001), and from “2018 K6” to “2019 PSB” (p = 0.021) were all significant; however, the reverse were not all significant in one period. In four periods, from “2016 PSB” to “2019 K6” (p = 0.025) was significant; however, the reverse was not significant. Fit indices were obtained: χ2 = 7.641 (p = 0.182), goodness of fit index (GFI) = 0.891, comparative fit index (CFI) = 0.901, and root mean square error of approximation (RMSEA) = 0.121 in structural equation modelling. Conclusions: Psychological distress may affect the rate of PSB after one year, and the rate of PSB may affect the rate of psychological distress after three years in elderly individuals.

scholarly journals Measuring the effectiveness of catch-up MMR delivered by school nurses compared to signposting to general practice on improving MMR coverage

2020 ◽  
Vol 42 (2) ◽  
pp. 416-422 ◽  
Author(s):  
F Altinoluk-Davis ◽  
S Gray ◽  
I Bray
Keyword(s):  
General Practice ◽  
School Nurse ◽  
School Nurses ◽  
Sample Population ◽  
School Year ◽  
South Central ◽  
Chi Squared ◽  
Immunization Services ◽  
Catch Up ◽  
The Difference

Abstract Background This study assesses whether increased coverage of the measles, mumps and rubella (MMR) vaccination differs between areas where school nurses deliver catch-up MMR doses to adolescents in school settings, compared to signposting to general practice. Methods A retrospective cohort study was conducted using Child Health Information Services records within the NHS England South (South Central) commissioning boundary. The sample population included children born 1 September 2000–31 August 2001, in school year 9 during the 2014–15 academic year. Results The primary outcome findings show an increase in coverage of at least one dose of MMR by 1.6% (n = 334) in the cohort receiving catch-up MMR, compared to 0.2% (n = 12) in the cohort signposted to general practice. Over time, the difference in increase between the two cohorts was 1.4%, analysed using the chi-squared comparison of proportions test, providing strong evidence (P &lt; 0.0001) that school nurse delivery of catch-up MMR is effective at increasing coverage. The findings also suggest that school nurse delivery of catch-up MMR may benefit Black, Asian and minority ethnic children and those from more deprived backgrounds. Conclusions It is recommended that commissioners of school-aged immunization services incorporate the delivery of catch-up MMR doses in their contracts with school nurses.

Effect of elevated potassium on the ion content of mouse astrocytes and neurons

1992 ◽  
Vol 70 (S1) ◽  
pp. S263-S268 ◽  
Author(s):  
H. Steve White ◽  
Sien Yao Chow ◽  
Y. C. Yen-Chow ◽  
Dixon M. Woodbury
Keyword(s):  
Cortical Neurons ◽  
Cell Types ◽  
Mouse Cell ◽  
Ion Concentration ◽  
Cellular Heterogeneity ◽  
Resting Membrane Potential ◽  
Extracellular Potassium ◽  
Individual Response ◽  
Extracellular Potassium Concentration ◽  
The Brain

Potassium is tightly regulated within the extracellular compartment of the brain. Nonetheless, it can increase 3- to 4-fold during periods of intense seizure activity and 10- to 20-fold under certain pathological conditions such as spreading depression. Within the central nervous system, neurons and astrocytes are both affected by shifts in the extracellular concentration of potassium. Elevated potassium can lead to a redistribution of other ions (e.g., calcium, sodium, chloride, hydrogen, etc.) within the cellular compartment of the brain. Small shifts in the extracellular potassium concentration can markedly affect acid–base homeostasis, energy metabolism, and volume regulation of these two brain cells. Since normal neuronal function is tightly coupled to the ability of the surrounding glial cells to regulate ionic shifts within the brain and since both cell types can be affected by shifts in the extracellular potassium, it is important to characterize their individual response to an elevation of this ion. This review describes the results of side-by-side studies conducted on cortical neurons and astrocytes, which assessed the effect of elevated potassium on their resting membrane potential, intracellular volume, and their intracellular concentration of potassium, sodium, and chloride. The results obtained from these studies suggest that there exists a marked cellular heterogeneity between neurons and astrocytes in their response to an elevation in the extracellular potassium concentration.Key words: astrocytes, neurons, ion concentration, neuronal–glial interactions, mouse, cell culture.

LONG‐TIME RESPONSE PREDICTED BY EXACT ELASTIC RAY THEORY

Geophysics ◽  
1965 ◽  
Vol 30 (3) ◽  
pp. 363-368 ◽  
Author(s):  
T. W. Spencer
Keyword(s):  
Formal Solution ◽  
Intermediate Stage ◽  
Time Limit ◽  
Time Interval ◽  
Individual Response ◽  
Axially Symmetric ◽  
Long Time ◽  
The Difference ◽  
The Individual ◽  
Significant Figures

The formal solution for an axially symmetric radiation field in a multilayered, elastic system can be expanded in an infinite series. Each term in the series is associated with a particular raypath. It is shown that in the long‐time limit the individual response functions produced by a step input in particle velocity are given by polynomials in odd powers of the time. For rays which suffer m reflections, the degree of the polynomials is 2m+1. The total response is obtained by summing all rays which contribute in a specified time interval. When the rays are selected indiscriminately, the difference between the magnitude of the partial sum at an intermediate stage of computation and the magnitude of the correct total sum may be greater than the number of significant figures carried by the computer. A prescription is stated for arranging the rays into groups. Each group response function varies linearly in the long‐time limit and goes to zero when convolved with a physically realizable source function.

scholarly journals Comparison of growth models to describe growth from birth to 6 years in a Beninese cohort of children with repeated measurements

BMJ Open ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. e035785
Author(s):  
Shukrullah Ahmadi ◽  
Florence Bodeau-Livinec ◽  
Roméo Zoumenou ◽  
André Garcia ◽  
David Courtin ◽  
...  
Keyword(s):  
Growth Model ◽  
Goodness Of Fit ◽  
Growth Models ◽  
Information Criterion ◽  
Height Growth ◽  
Sub Saharan Africa ◽  
Individual Growth ◽  
Secondary Outcome ◽  
Growth Trajectories ◽  
Best Fitting

ObjectiveTo select a growth model that best describes individual growth trajectories of children and to present some growth characteristics of this population.SettingsParticipants were selected from a prospective cohort conducted in three health centres (Allada, Sekou and Attogon) in a semirural region of Benin, sub-Saharan Africa.ParticipantsChildren aged 0 to 6 years were recruited in a cohort study with at least two valid height and weight measurements included (n=961).Primary and secondary outcome measuresThis study compared the goodness-of-fit of three structural growth models (Jenss-Bayley, Reed and a newly adapted version of the Gompertz growth model) on longitudinal weight and height growth data of boys and girls. The goodness-of-fit of the models was assessed using residual distribution over age and compared with the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). The best-fitting model allowed estimating mean weight and height growth trajectories, individual growth and growth velocities. Underweight, stunting and wasting were also estimated at age 6 years.ResultsThe three models were able to fit well both weight and height data. The Jenss-Bayley model presented the best fit for weight and height, both in boys and girls. Mean height growth trajectories were identical in shape and direction for boys and girls while the mean weight growth curve of girls fell slightly below the curve of boys after neonatal life. Finally, 35%, 27.7% and 8% of boys; and 34%, 38.4% and 4% of girls were estimated to be underweight, wasted and stunted at age 6 years, respectively.ConclusionThe growth parameters of the best-fitting Jenss-Bayley model can be used to describe growth trajectories and study their determinants.

scholarly journals A Bayesian ensemble data assimilation to constrain model parameters and land-use carbon emissions

2018 ◽  
Vol 15 (9) ◽  
pp. 2909-2930 ◽  
Author(s):  
Sebastian Lienert ◽  
Fortunat Joos
Keyword(s):  
Land Use ◽  
Carbon Emissions ◽  
Latin Hypercube Sampling ◽  
Historical Period ◽  
Model Parameters ◽  
Dynamic Global Vegetation Model ◽  
Order Of Magnitude ◽  
The Difference ◽  
Wood Harvest ◽  
Global Vegetation

Abstract. A dynamic global vegetation model (DGVM) is applied in a probabilistic framework and benchmarking system to constrain uncertain model parameters by observations and to quantify carbon emissions from land-use and land-cover change (LULCC). Processes featured in DGVMs include parameters which are prone to substantial uncertainty. To cope with these uncertainties Latin hypercube sampling (LHS) is used to create a 1000-member perturbed parameter ensemble, which is then evaluated with a diverse set of global and spatiotemporally resolved observational constraints. We discuss the performance of the constrained ensemble and use it to formulate a new best-guess version of the model (LPX-Bern v1.4). The observationally constrained ensemble is used to investigate historical emissions due to LULCC (ELUC) and their sensitivity to model parametrization. We find a global ELUC estimate of 158 (108, 211) PgC (median and 90 % confidence interval) between 1800 and 2016. We compare ELUC to other estimates both globally and regionally. Spatial patterns are investigated and estimates of ELUC of the 10 countries with the largest contribution to the flux over the historical period are reported. We consider model versions with and without additional land-use processes (shifting cultivation and wood harvest) and find that the difference in global ELUC is on the same order of magnitude as parameter-induced uncertainty and in some cases could potentially even be offset with appropriate parameter choice.

scholarly journals Nonmonotonic Generalization Bias of Gaussian Mixture Models

2000 ◽  
Vol 12 (6) ◽  
pp. 1411-1427 ◽  
Author(s):  
Shotaro Akaho ◽  
Hilbert J. Kappen
Keyword(s):  
Symmetry Breaking ◽  
Gaussian Mixture Models ◽  
Information Criterion ◽  
Gaussian Mixture ◽  
General Tendency ◽  
Adaptive Parameters ◽  
Neural Information ◽  
The Difference ◽  
Training Error ◽  
Validation Experiments

Theories of learning and generalization hold that the generalization bias, defined as the difference between the training error and the generalization error, increases on average with the number of adaptive parameters. This article, however, shows that this general tendency is violated for a gaussian mixture model. For temperatures just below the first symmetry breaking point, the effective number of adaptive parameters increases and the generalization bias decreases. We compute the dependence of the neural information criterion on temperature around the symmetry breaking. Our results are confirmed by numerical cross-validation experiments.

scholarly journals Generalized Integrate-and-Fire Models of Neuronal Activity Approximate Spike Trains of a Detailed Model to a High Degree of Accuracy

2004 ◽  
Vol 92 (2) ◽  
pp. 959-976 ◽  
Author(s):  
Renaud Jolivet ◽  
Timothy J. Lewis ◽  
Wulfram Gerstner
Keyword(s):  
Cortical Neurons ◽  
Direct Reduction ◽  
Spike Trains ◽  
Model Parameters ◽  
Detailed Model ◽  
Fire Model ◽  
Integrate And Fire ◽  
Fire Models ◽  
Wide Range ◽  
Simple Models

We demonstrate that single-variable integrate-and-fire models can quantitatively capture the dynamics of a physiologically detailed model for fast-spiking cortical neurons. Through a systematic set of approximations, we reduce the conductance-based model to 2 variants of integrate-and-fire models. In the first variant (nonlinear integrate-and-fire model), parameters depend on the instantaneous membrane potential, whereas in the second variant, they depend on the time elapsed since the last spike [Spike Response Model (SRM)]. The direct reduction links features of the simple models to biophysical features of the full conductance-based model. To quantitatively test the predictive power of the SRM and of the nonlinear integrate-and-fire model, we compare spike trains in the simple models to those in the full conductance-based model when the models are subjected to identical randomly fluctuating input. For random current input, the simple models reproduce 70–80 percent of the spikes in the full model (with temporal precision of ±2 ms) over a wide range of firing frequencies. For random conductance injection, up to 73 percent of spikes are coincident. We also present a technique for numerically optimizing parameters in the SRM and the nonlinear integrate-and-fire model based on spike trains in the full conductance-based model. This technique can be used to tune simple models to reproduce spike trains of real neurons.

Sign in / Sign up

Export Citation Format

Share Document