Philip Reiss

• PhD
• Professor at University of Haifa

The glutamatergic modulator ketamine is associated with changes in sleep, depression, and suicidal ideation (SI). This study sought to evaluate differences in arousal-related sleep metrics between 36 individuals with treatment-resistant major depression (TRD) and 25 healthy volunteers (HVs). It also sought to determine whether ketamine normalizes a...

The main diagnostic criteria for major depressive disorder (MDD) are consistent experiences of high levels of negative emotions and low levels of positive emotions. Therefore, modification of these emotions is essential in the treatment of MDD. In the current study, we harnessed a computational approach to explore whether experiencing negative emot...

The starting point for much of multivariate analysis (MVA) is an $n\times p$ data matrix whose $n$ rows represent observations and whose $p$ columns represent variables. Some multivariate data sets, however, may be best conceptualized not as $n$ discrete $p$-variate observations, but as $p$ curves or functions defined on a common time interval. We...

In many psychological studies, in particular those conducted by experience sampling, mental states are measured repeatedly for each participant. Such a design allows for regression models that separate between‐ from within‐person, or trait‐like from state‐like, components of association between two variables. But these models are typically designed...

In many psychological studies, in particular those conducted by experience sampling, mental states are measured repeatedly for each participant. Such a design allows for regression models that separate between- from within-person, or trait-like from state-like, components of association between two variables. But these models are typically designed...

Graphical tests assess whether a function of interest departs from an envelope of functions generated under a simulated null distribution. This approach originated in spatial statistics, but has recently gained some popularity in functional data analysis. Whereas such envelope tests examine deviation from a functional null distribution in an omnibu...

The intraclass correlation coefficient (ICC) is a classical index of measurement reliability. With the advent of new and complex types of data for which the ICC is not defined, there is a need for new ways to assess reliability. To meet this need, we propose a new distance‐based intraclass correlation coefficient (dbICC), defined in terms of arbitr...

Time is among the most important yet mysterious aspects of experience. We investigated everyday mental time travel, especially into the future. Two community samples, contacted at random points for three (Study 1; 6,686 reports) and 14 days (Study 2; 2,361 reports), reported on their most recent thought. Both studies found that thoughts about the p...

Time is among the most important yet mysterious aspects of experience. We investigated everyday mental time travel, especially into the future. Two community samples, contacted at random points for 3 (Study 1; 6,686 reports) and 14 days (Study 2; 2,361 reports), reported on their most recent thought. Both studies found that thoughts about the prese...

The intraclass correlation coefficient (ICC) is a classical index of measurement reliability. With the advent of new and complex types of data for which the ICC is not defined, there is a need for new ways to assess reliability. To meet this need, we propose a new distance-based intraclass correlation coefficient (dbICC), defined in terms of arbitr...

Graphical tests assess whether a function of interest departs from an envelope of functions generated under a simulated null distribution. This approach originated in spatial statistics, but has recently gained some popularity in functional data analysis. Whereas such envelope tests examine deviation from a functional null distribution in an omnibu...

Functional principal component analysis for sparse longitudinal data usually proceeds by first smoothing the covariance surface, and then obtaining an eigendecomposition of the associated covariance operator. Here we consider the use of penalized tensor product splines for the initial smoothing step. Drawing on a result regarding finite-rank symmet...

The problem of dividing an estate among creditors, when their claims total more than the value of the estate, was posed in the Talmud and has been analyzed in the game theory literature. Here we reveal a close connection between schemes for estate division and linear regression solution paths obtained by least angle regression or by the lasso. We f...

We propose a novel approach to the analysis of synchronized three-dimensional motion in dyads. Motion recorded at high time resolution, as with a gaming device, is preprocessed in each of the three spatial dimensions by spline smoothing. Synchrony is then defined, at each time point, as the cosine between the two individuals’ estimated velocity vec...

Motivated by studies of the development of the human cerebral cortex, we consider the estimation of a mean growth trajectory and the relative merits of cross-sectional and longitudinal data for that task. We define a class of relative efficiencies that compare function estimates in terms of aggregate variance of a parametric function estimate. Thes...

In the fields of neuroimaging and genetics, a key goal is testing the association of a single outcome with a very high-dimensional imaging or genetic variable. Often, summary measures of the high-dimensional variable are created to sequentially test and localize the association with the outcome. In some cases, the results for summary measures are s...

In the fields of neuroimaging and genetics, a key goal is testing the association of a single outcome with a very high-dimensional imaging or genetic variable. Often, summary measures of the high-dimensional variable are created to sequentially test and localize the association with the outcome. In some cases, the results for summary measures are s...

We extend the notion of an influence or hat matrix to regression with functional responses and scalar predictors. For responses depending linearly on a set of predictors, our definition is shown to reduce to the conventional influence matrix for linear models. The pointwise degrees of freedom, the trace of the pointwise influence matrix, are shown...

Many modern neuroimaging studies acquire large spatial images of the brain observed sequentially over time. Such data are often stored in the forms of matrices. To model these matrix-variate data we introduce a class of separable processes using explicit latent process modeling. To account for the size and two-way structure of the data, we extend p...

Parametric and semi-parametric inference for massively parallel models, i.e., a large number of models with common design matrix, as often occurs with brain imaging data

A number of classical approaches to nonparametric regression have recently been extended to the case of functional predictors. This article introduces a new method of this type, which extends intermediate-rank penalized smoothing to scalar-on-function regression. In the proposed method, which we call principal coordinate ridge regression, one regre...

Background: Social anxiety disorder (SAD) typically onsets in adolescence and is associated with multiple impairments. Despite promising clinical interventions, most socially anxious adolescents remain untreated. To address this clinical neglect, we developed a school-based, 12-week group intervention for youth with SAD, Skills for Academic and So...

Objective: Diffusion tensor imaging (DTI) can identify structural connectivity alterations in attention-deficit/hyperactivity disorder (ADHD). Most ADHD DTI studies have concentrated on regional differences in fractional anisotropy (FA) despite its limited sensitivity to complex white matter architecture and increasing evidence of global brain dif...

Recent years have seen an explosion of activity in the field of functional data analysis (FDA), in which curves, spectra, images and so on are considered as basic functional data units. A central problem in FDA is how to fit regression models with scalar responses and functional data points as predictors. We review some of the main approaches to th...

An increasingly important goal of psychiatry is the use of brain imaging data to develop predictive models. Here we present two contributions to statistical methodology for this purpose. First, we propose and compare a set of wavelet-domain procedures for fitting generalized linear models with scalar responses and image predictors: sparse variants...

An increasingly important goal of psychiatry is the use of brain imaging data to develop predictive models. Here we present two contributions to statistical methodology for this purpose. First, we propose and compare a set of wavelet-domain procedures for fitting generalized linear models with scalar responses and image predictors: sparse variants...

To date, only one study has examined test-retest reliability of resting state fMRI (R-fMRI) in children, none in clinical developing groups. Here, we assessed short-term test-retest reliability in a sample of 46 children (11-17.9 years) with attention-deficit/hyperactivity disorder (ADHD) and 57 typically developing children (TDC). Our primary test...

The "ten ironic rules for statistical reviewers" presented by [Friston(2012)] prompted a rebuttal by Friston (2013), which was followed by a rejoinder by [Friston(2013)]. A key issue left unresolved in this discussion is the use of cross-validation to test the significance of predictive analyses. This note discusses the role that cross-validation-b...

We propose a novel method for neurodevelopmental brain mapping that displays how an individual's values for a quantity of interest compare with age-specific norms. By estimating smoothly age-varying distributions at a set of brain regions of interest, we derive age-dependent region-wise quantile ranks for a given individual, which can be presented...

This paper studies estimation of a smooth function $f(t,s)$ when we are given functional responses of the form $f(t,\cdot)$ + error, but scientific interest centers on the collection of functions $f(\cdot,s)$ for different $s$. The motivation comes from studies of human brain development, in which $t$ denotes age whereas $s$ refers to brain locatio...

Background: The 'New Forest Parenting Package' (NFPP), an 8-week home-based intervention for parents of preschoolers with attention-deficit/hyperactivity disorder (ADHD), fosters constructive parenting to target ADHD-related dysfunctions in attention and impulse control. Although NFPP has improved parent and laboratory measures of ADHD in communit...

Testing the independence between two random variables $x$ and $y$ is an important problem in statistics and machine learning, where the kernel-based tests of independence is focused to address the study of dependence recently. The advantage of the kernel framework rests on its flexibility in choice of kernel. The Hilbert-Schmidt Independence Criter...

Background Schizophrenia is a disorder of brain connectivity and altered neurodevelopmental processes. Cross-sectional case-control studies in different age groups have suggested that deficits in cortical thickness in childhood-onset schizophrenia may normalize over time, suggesting a disorder-related difference in cortical growth trajectories. Me...

This article presents novel sequential methods of sample coordination appropriate for a repeated survey, with a stratified design and simple random sampling without replacement (SRSWOR) selection within each stratum, when the composition or definition of strata changes. Such changes could be the result of updating the frame for births, deaths, or t...

Many techniques of functional data analysis require choosing a measure of distance between functions, with the most common choice being L2 distance. In this article we show that using a weighted L2 distance, with a judiciously chosen weight function, can improve the performance of various statistical methods for functional data, including k-medoids...

The identification of phenotypic associations in high-dimensional brain connectivity data represents the next frontier in the neuroimaging connectomics era. Exploration of brain- phenotype relationships remains limited by statistical approaches that are computationally intensive, depend on a priori hypotheses, or require stringent correction for mu...

We propose a penalized spline approach to performing large numbers of parallel non-parametric analyses of either of two types: restricted likelihood ratio tests of a parametric regression model versus a general smooth alternative, and nonparametric regression. Compared with naïvely performing each analysis in turn, our techniques reduce computation...

Diffusion tensor imaging (DTI) measures water diffusion within white matter, allowing for in vivo quantification of brain pathways. These pathways often subserve specific functions, and impairment of those functions is often associated with imaging abnormalities. As a method for predicting clinical disability from DTI images, we propose a hierarchi...

One of the cognitive changes associated with Alzheimer's disease is a diminution of the primacy effect, i.e., the tendency toward better recall of items studied early on a list compared with the rest. We examined whether learning and recall of primacy words predicted subsequent cognitive decline in 204 elderly subjects who were non-demented and cog...

Social anxiety disorder is highly prevalent in adolescence, persistent into adulthood, and associated with multiple impairments. Despite the development of efficacious treatments for socially anxious youth, few affected adolescents receive such treatment. This study examined service use in a sample of high school students (n = 1,574), as well as pr...

When a linear model is chosen by searching for the best subset among a set of candidate predictors, a fixed penalty such as that imposed by the Akaike information criterion may penalize model complexity inadequately, leading to biased model selection. We study resampling-based information criteria that aim to overcome this problem through improved...

The National Institute of Mental Health strategic plan for advancing psychiatric neuroscience calls for an acceleration of discovery and the delineation of developmental trajectories for risk and resilience across the lifespan. To attain these objectives, sufficiently powered datasets with broad and deep phenotypic characterization, state-of-the-ar...

Adaptive false discovery rate (FDR) procedures, which offer greater power than the original FDR procedure of Benjamini and Hochberg, are often applied to statistical maps of the brain. When a large proportion of the null hypotheses are false, as in the case of widespread effects such as cortical thinning throughout much of the brain, adaptive FDR m...

In linear regression with functional predictors and scalar responses, it may be advantageous, particularly if the function is thought to contain features at many scales, to restrict the coefficient function to the span of a wavelet basis, thereby converting the problem into one of variable selection. If the coefficient function is sparsely represen...

Modern data-rich analyses may call for fitting a large number of nonparametric quantile regressions. For example, growth charts may be constructed for each of a collection of variables, to identify those for which individuals with a disorder tend to fall in the tails of their age-specific distribution; such variables might serve as developmental bi...

Volumetric studies have reported relatively decreased cortical thickness and gray matter volumes in adults with attention-deficit/hyperactivity disorder (ADHD) whose childhood status was retrospectively recalled. We present, to our knowledge, the first prospective study combining cortical thickness and voxel-based morphometry in adults diagnosed as...

Background: Children and adolescents who seek medical treatment for persistent physical distress often suffer from co-occurring anxiety disorders. Treatment options for this impaired population are limited. This study tests the feasibility and potential efficacy of a cognitive-behavioral intervention targeting pain and anxiety for youth with impai...

Regression models for functional responses and scalar predictors are often fitted by means of basis functions, with quadratic roughness penalties applied to avoid overfitting. The fitting approach described by Ramsay and Silverman in the 1990s amounts to a penalized ordinary least squares (P-OLS) estimator of the coefficient functions. We recast th...

Poor recruitment and high attrition may invalidate results of research studies. This paper describes successful recruitment and retention strategies in a school-based substance use prevention trial and explores factors associated with intervention attendance and retention. A total of 384 parent-child dyads from 15 schools in the New York Metropolit...

Permutation tests based on distances among multivariate observations have found many applications in the biological sciences. Two major testing frameworks of this kind are multiresponse permutation procedures and pseudo-F tests arising from a distance-based extension of multivariate analysis of variance. In this article, we derive conditions under...

Functional connectivity (FC) analyses of resting-state fMRI data allow for the mapping of large-scale functional networks, and provide a novel means of examining the impact of dopaminergic challenge. Here, using a double-blind, placebo-controlled design, we examined the effect of L-dopa, a dopamine precursor, on striatal resting-state FC in 19 heal...

Electrophysiological studies have long demonstrated a high degree of correlated activity between the left and right hemispheres, however little is known about regional variation in this interhemispheric coordination. Whereas cognitive models and neuroanatomical evidence suggest differences in coordination across primary sensory-motor cortices versu...

Functional principal component regression (FPCR) is a promising new method for regressing scalar outcomes on functional predictors. In this article, we present a theoretical justification for the use of principal components in functional regression. FPCR is then extended in two directions: from linear to the generalized linear modeling, and from un...

Background: Converging lines of evidence support models of autism spectrum disorders (ASD) as developmental dysconnection syndromes, characterized by increased short-range connectivity and reduced long-range connectivity in the brain. Initially based on findings of white matter abnormalities during development, such models have gained support from...

Spline-based approaches to non-parametric and semiparametric regression, as well as to regression of scalar outcomes on functional predictors, entail choosing a parameter controlling the extent to which roughness of the fitted function is penalized. We demonstrate that the equations determining two popular methods for smoothing parameter selection,...

Human cerebral development is remarkably protracted. Although microstructural processes of neuronal maturation remain accessible only to morphometric post-mortem studies, neuroimaging tools permit the examination of macrostructural aspects of brain development. The analysis of resting-state functional connectivity (FC) offers novel possibilities fo...

Increased intra-subject response time standard deviations (RT-SD) discriminate children with attention-deficit/hyperactivity disorder (ADHD) from healthy control subjects. The RT-SD is averaged over time; thus it does not provide information about the temporal structure of RT variability. We previously hypothesized that such increased variability m...

Regression of a scalar response on signal predictors, such as near-infrared (NIR) spectra of chemical samples, presents a major challenge when, as is typically the case, the dimension of the signals far exceeds their number. Most solutions to this problem reduce the dimension of the predictors either by regressing on components [e.g., principal com...

In survey sampling there is often a need to coordinate the selection of pairs of samples drawn from two overlapping populations so as to maximize or minimize their expected overlap, subject to constraints on the marginal probabilities determined by the respective designs. For instance, maximizing the expected overlap between repeated samples can st...

Thesis (Ph. D.)--Columbia University, 2006. Includes bibliographical references (leaves 136-150). Department: Biostatistics.

Only the metopic suture normally fuses during early childhood; all other cranial sutures normally fuse much later in life. Despite this, metopic synostosis is one of the least common forms of craniosynostosis. The temporal sequence of normal physiologic metopic suture fusion remains undefined and controversial. Therefore, diagnosis of metopic synos...

To evaluate dissemination of the Agency for Health Care Policy and Research (AHCPR) Smoking cessation clinical practice guideline in community health centres. Pre- and post-trial. Fourteen community health centres in Rhode Island. Provider performance was assessed with 1798 and 1591 patient contacts, in pre-post cross sectional consecutive samples,...

ABSTRACT Weview,the problem,of maximizing,or minimizing the expected overlap of two,surveys as a transportation problem,(TP) and give simple selection algorithms for solving it. We compare our method,with the sequential SRSWOR for positive and negative coordination, the method of collocated samples and the PRN method with full-stratum rotation. KEY...

Little is known about the influence of personal and practice-level factors on physicians' dietary counseling practices. Primary care physicians (n = 130) were surveyed regarding the frequency that they "ask" patients about their diet, "assess" patients' reasons for and against dietary changes, "advise" patients to eat less fat and more fiber, "assi...

The rate of macrolide resistance among Streptococcus pneumoniae is increasing, but some investigators have questioned its clinical relevance. We conducted a matched case-control study of patients with bacteremic pneumococcal infection at 4 hospitals to determine whether development of breakthrough bacteremia during macrolide treatment was related t...

Individuals treated for cancer often experience higher levels of emotional distress than the general population. Previous research has shown that exercise can have an ameliorating effect on these problems. This 12-month prospective longitudinal study investigated mood, quality of life, cancer-related symptoms, and exercise behavior of 69 women who...

Novel systemic treatments are needed in pancreatic cancer. The authors sought to establish the frequency of overexpression of the HER-2/neu oncogene in patients with pancreatic adenocarcinoma to determine the potential role of trastuzumab (Herceptin) as a therapeutic agent in this disease. Tumor specimens from patients with pancreatic adenocarcinom...

Several results are presented concerning mean busy periods and mean busy cycles for certain general classes of queuing systems with bulk arrivals. These results lead to methods of estimating mean busy period and cycle length from Monte Carlo simulations. Using data from simulations, we compare these estimation methods with a more straightforward te...

How much noise must be added to a voter model (in the sense of Liggett (1997)) to render it ergodic? A partial answer is obtained by studying algebraic conditions on the flip rates associated with cancellative duality. It is shown that spontaneous births and deaths must both attain a certain threshold for cancellative duality to occur. The threshol...

When a linear model is chosen by searching among a large set of candidate models, a fixed penalty such as that imposed by the Akaike information criterion may penalize complexity inadequately, and hence favor overfitted models. We study resampling-based information criteria that aim to overcome this problem, including a bootstrapping approach and a...

Functional connectivity of an individual human brain is often studied by acquiring a resting-state functional magnetic resonance imaging scan, and mapping the correlation of each voxel's BOLD time series with that of a seed region. As large collections of such maps become available, including multisite data sets, there is an increasing need for way...