The standard general linear model (GLM) for rapid event-related fMRI design protocols typically ignores reduction in hemodynamic responses in successive stimuli in a train due to incomplete recovery from the preceding stimuli. To capture this adaptation effect, we incorporate a region-specific adaptation model into GLM. The model quantifies the rate of adaptation across brain regions, which is ...

This paper studies the assortment optimization problem under the General Luce Model (GLM), a discrete choice introduced by Echenique and Saito (2015) that generalizes the standard multinomial logit model (MNL). The GLM does not satisfy the Independence of Irrelevant Alternatives (IIA) property but it ensures that each product has an intrinsic utility and uses a dominance relation between produc...

Airbnb has been increasingly gaining popularity since 2008 due to its low prices and direct interactions with the local community. This paper employed a general linear model (GLM) and a geographically weighted regression (GWR) model to identify the key factors affecting Airbnb listing prices using data sets of 794 samples of Airbnb listings of business units in Metro Nashville, Tennessee. The r...

Within functional magnetic resonance imaging (fMRI), the use of the traditional general linear model (GLM) based analysis methods is often restricted to strictly controlled research setups requiring a parametric activation model. Instead, Inter-Subject Correlation (ISC) method is based on voxel-wise correlation between the time series of the subjects, which makes it completely non-parametric an...

To understand neural activity, two broad categories of models exist: statistical and dynamical. While statistical models possess rigorous methods for parameter estimation and goodness-of-fit assessment, dynamical models provide mechanistic insight. In general, these two categories of models are separately applied; understanding the relationships between these modeling approaches remains an area...

introduction: a fixed hemodynamic response function (hrf) is commonly used for functional magnetic resonance imaging (fmri) analysis. however, hrf may vary from region to region and subject to subject. we investigated the effect of locally estimated hrf (in functionally homogenous parcels) on activation detection sensitivity in a heroin cue reactivity study. methods: we proposed a novel explora...

General linear model (GLM) is a standard and widely used fMRI analysis tool. It enables the detection of hypothesis-driven brain activations. In contrast, Independent Component Analysis (ICA) is a powerful technique, which enables the detection of data-driven spatially independent networks. Hybrid approaches that combine and take advantage of GLM and ICA have been proposed. Yet the choice of th...

To validate the usefulness of a model-based analysis approach according to the general linear model (GLM) for functional near-infrared spectroscopy (fNIRS) data, a rapid event-related paradigm with an unpredictable stimulus sequence was applied to 15 healthy subjects. A parametric design was chosen wherein four differently graded contrasts of a flickering checkerboard were presented, allowing d...