Category Archives: Research

mortest: estimates the total number of carcasses at a windfarm

Working with Aaftab Jain, we developed a estimator for total number of bird and bat carcasses at a windfarm called “mortest” and implemented it as an R package.  We are interested in estimating c, the total number of carcasses (mortalities) in a period (year). The total number of carcasses is the sum of carcasses over size classes, c = sum_s=1^S c_s. If carcasses are retained (that is, not scavenged) and searcher efficiency is perfect (every carcass is found) and every tower is searched, then each c_s would be counted perfectly. Yet, carcass scavenging by predators and searchers overlooking carcasses are a reality, making observed counts an underestimate. Furthermore, tower sampling rather than censusing is a cost-saving convenience. Our estimator of total mortality, c, weighs the estimates from different search intervals and adjusts the observed counts for scavenging, search efficiency, searchable area of each tower, and proportion of towers searched, accounting for uncertainty in these estimates using a bootstrap. The software was written by Erik Erhardt and is currently private.  Contact Aaftab Jain <> for more information for using the software.
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A simulation toolbox for fMRI data: SimTB

Update: both papers have been published, simulation toolbox and inter-subject variability. Elena Allen and I recently submitted two papers that detail a simulation toolbox for fMRI data (SimTB) and capturing inter-subject variability with group independent component analysis (ICA) using simulations. It’s been an exciting and interesting project because we can at last generate interesting and complex datasets to use as a “ground truth” to compare estimation and processing techniques.  We’ve learned a lot about the limits of some methods, as well as their robustness.  The papers will be submitted next week.  For those with MATLAB, it’s available at SimTB, a simulation toolbox for fMRI data under a model of spatiotemporal separability EB Erhardt, EA Allen, Y Wei, T Eichele, VD Calhoun. (2011)
We introduce SimTB, a MATLAB toolbox designed to simulate functional magnetic resonance imaging (fMRI) datasets under a model of spatiotemporal separability. The toolbox meets the increasing need of the fMRI community to more comprehensively understand the effects of complex processing strategies by providing a ground truth that estimation methods may be compared against. SimTB captures the fundamental structure of real data, but data generation is fully parameterized and fully controlled by the user, allowing for accurate and precise comparisons. The toolbox offers a wealth of options regarding the number and configuration of spatial sources, implementation of experimental paradigms, inclusion of tissue-specific properties, addition of noise and head movement, and much more. A straightforward data generation method and short computation time (3-10 seconds for each dataset) allow a practitioner to simulate and analyze many datasets to potentially understand a problem from many angles. Beginning MATLAB users can use the SimTB graphical user interface (GUI) to design and execute simulations while experienced users can write batch scripts to automate and customize this process. The toolbox is freely available at together with sample scripts and tutorials.
Capturing inter-subject variability with group independent component analysis of fMRI data: a simulation study EA Allen, EB Erhardt, Y Wei, T Eichele, VD Calhoun. (2011)
A key challenge in functional neuroimaging is the meaningful combination of results across subjects. Even in a sample of healthy participants, brain morphology and functional organization exhibit considerable variability, such that no two individuals have the same neural activation at the same location in response to the same stimulus. This inter-subject variability limits inferences at the group-level as average activation patterns may fail to represent the patterns seen in individuals. A promising approach to multi-subject analysis is group independent components analysis (GICA), which identities group components and reconstructs activations at the individual level. GICA has gained considerable popularity, particularly in studies where temporal response models cannot be speci ed. However, a comprehensive understanding of the performance of GICA under realistic conditions of inter-subject variability is lacking. In this study we use simulated functional magnetic resonance imaging (fMRI) data to determine the capabilities and limitations of GICA under conditions of spatial, temporal, and amplitude variability. Simulations, generated with the SimTB toolbox, address questions that commonly arise in GICA studies, such as: (1) How well can individual subject activations be estimated and when will spatial variability preclude estimation? (2) Why does component splitting occur and how is it a ected by model order? (3) How should we analyze component features to maximize sensitivity to intersubject differences? Overall, our results indicate an excellent capability of GICA to capture between-subject differences and we make a number of recommendations regarding analytic choices for application to functional imaging data.
[caption id="" align="alignnone" width="480" caption="SimTB flowchart for simulation of fMRI data"][/caption]
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VeraLight, Inc. receives Health Canada license approval

Over the last year I’ve provided statistical consulting for VeraLight, Inc., a medical device company based in Albuquerque, NM. The SCOUT DS is the first non-invasive diabetes screening system designed to provide an accurate and convenient method for screening type 2 diabetes and pre-diabetes based on the presence of advanced glycation endproducts (AGEs) biomarkers found in skin. I have been primarily responsible for demographic subgroup analysis of pre-clinical trial data and review of the analysis plan for the FDA clinical trial.  Today they announced that they have received Health Canada license approval:
ALBUQUERQUE, N.M., April 26, 2011 — VeraLight Inc., a privately held medical device company, based here, today announced its Scout DS® Device was granted a Health Canada Medical Device Licence for non-invasive diabetes screening. The easy to operate device needs no blood and does not require fasting. The patient simply places their forearm onto the portable table-top unit and a quantitative result is reported in about three minutes. … Scout DS is slated for market introduction later this year in Canada and select countries outside of the United States.
I’m really excited for them.  I imagine this product making diabetes screening a 5-minute procedure at every pharmacy drug counter.  I’m really proud of the work John, Ries, Ed, Jeff, and the rest of the group is doing to make this a reality. JULY 28, 2011 – UPDATE • VeraLight announces CE mark approval of the SCOUT DS® for non-invasive diabetes screening.  So they’ve passed Canada and Europe! AUGUST 25, 2011 – UPDATE • VeraLight announces agreement with Pear Healthcare Solutions. VeraLight and Pear Healthcare Solutions sign Canadian distribution agreement for SCOUT DS® Noninvasive Diabetes device.
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Talk: ACASA Annual meeting 2011

I’ll be giving a shortened version of my Bayesian stable isotope mixing model talk (title and abstract below) at the Albuquerque Chapter of the American Statistical Association (ACASA) annual meeting on Friday, April 29, 2011. I gave two distinct longer versions of this talk recently as part of job interview talks at St. Louis University and the University of New Mexico.  I’m looking forward to the meeting to visit with people who I’ve worked with over the last several years, organizing judging events at science fairs, and other events. A Bayesian Framework for Stable Isotope Mixing Models Erik B. Erhardt, The Mind Research Network; Edward J. Bedrick, Division of Epidemiology and Biostatistics, University of New Mexico Health Sciences Center Stable isotope sourcing is used to estimate proportional contributions of sources to a mixture, such as in the analysis of animal diets and plant nutrient use. Statistical methods for inference on the diet proportions using stable isotopes have focused on the linear mixing model. Existing frequentist methods provide inferences when the diet proportion vector can be uniquely solved for in terms of the isotope ratios. Bayesian methods apply for arbitrary numbers of isotopes and diet sources but existing models are somewhat limited as they assume that trophic fractionation or discrimination are estimated without error or that isotope ratios are uncorrelated. We present a Bayesian model for the estimation of mean diet that accounts for uncertainty in source means and discrimination and allows correlated isotope ratios. This model is easily extended to allow the diet proportion vector to depend on covariates, such as time. Two examples are used to illustrate the methodology.
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Paper published: A baseline for the multivariate comparison of resting state networks

In this paper we’ve put together a cohort of so-called “healthy normal controls” in the largest single group independent component analysis (ICA) forward model. Included in our analysis approach is a statistical methodology for performing mancova when the number of fMRI brain voxels (roughly V=60K) to test for activation differences over demographic variables is much larger than the number of subjects (N=603).  This massive project involved researchers nearly spanning our Medical Image Analysis Laboratory (MIALab), but many other investigators at the Mind Research Network (MRN).  It is a great example of what makes collaboration fun, challenging, and productive (thank you Elena, Eswar, Bill, Judith, Martin, and Srinivas). A baseline for the multivariate comparison of resting state networks Citation:Allen EA, Erhardt EB, Damaraju E, Gruner W, Segall JM, Silva RF, Havlicek M, Rachakonda S, Fries J, Kalyanam R, Michael AM, Caprihan A, Turner JA, Eichele T, Adelsheim S, Bryan AD, Bustillo J, Clark VP, Feldstein Ewing SW, Filbey F, Ford CC, Hutchison K, Jung RE, Kiehl KA, Kodituwakku P, Komesu YM, Mayer AR, Pearlson GD, Phillips JP, Sadek JR, Stevens M, Teuscher U, Thoma RJ and Calhoun VD (2011). A baseline for the multivariate comparison of resting state networks. Front. Syst. Neurosci. 5:2. doi: 10.3389/fnsys.2011.00002 Received: 16 Jun 2010; Accepted: 03 Jan 2011; Published online: 04 Feb 2011. Abstract As the size of functional and structural MRI datasets expands, it becomes increasingly important to establish a baseline from which diagnostic relevance may be determined, a processing strategy that efficiently prepares data for analysis, and a statistical approach that identifies important effects in a manner that is both robust and reproducible. In this paper, we introduce a multivariate analytic approach that optimizes sensitivity and reduces unnecessary testing. We demonstrate the utility of this mega-analytic approach by identifying the effects of age and gender on the resting state networks of 603 healthy adolescents and adults (mean age: 23.4 years, range: 12 to 71 years). Data were collected on the same scanner, preprocessed using an automated analysis pipeline based in SPM, and studied using group independent component analysis. Resting state networks were identified and evaluated in terms of three primary outcome measures: time course spectral power, spatial map intensity, and functional network connectivity. Results revealed robust effects of age on all three outcome measures, largely indicating decreases in network coherence and connectivity with increasing age. Gender effects were of smaller magnitude but suggested stronger intra-network connectivity in females and more inter-network connectivity in males, particularly with regard to sensorimotor networks. These findings, along with the analysis approach and statistical framework described here, provide a useful baseline for future investigations of brain networks in health and disease.
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Isotopic signature of photorespiration, poster

Last year David Hanson and I began collaboration continuing his study in leaf respiration.  I wrote a custom R package to process data from his tunable diode laser (TDL) and Licor devices to understand how carbon is taken up and respired by leaves.  This summer a poster presenting some of what we’ve been learning was presented by graduate student, Dianne Pater, who has been designing and running experiments. DT Pater, EB Erhardt, and DT Hanson. Isotopic signature of photorespiration. In Joint Annual Meetings of the American Society of Plant Biologists and the Canadian Society of Plant Physiologists, Montreal, CA, August 2010.
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Paper published: δ13C of soluble sugars in Tillandsia epiphytes

In a previous post I discussed this paper and how fun it was to write with Laurel.  Here I’m happy to report it’s available electronically (SpringerLink, pdf) and soon in paper. Laurel K. Goode, Erik B. Erhardt, Louis S. Santiago, Michael F. Allen.  Carbon stable isotopic composition of soluble sugars in Tillandsia epiphytes varies in response to shifts in habitat. Oecologia (2010) 163:583–590. DOI 10.1007/s00442-010-1577-5 Received: 11 March 2009 / Accepted: 25 January 2010 / Published online: 13 February 2010
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A few important areas of focus, reflecting what I’m doing and where I’m going.


Statistics for Stable Isotope applications

My vision is to be the recognized leader of statistical methods in stable isotope sourcing.  This will be accomplished through publishing papers from my dissertation work, collaborations leading to publications on methodological extensions, and giving talks in university departments and at courses and conferences.

Postdoctoral fellowship at the Mind Research Network

At the MRN my vision is to be an exceptional statistician, a valuable member of Vince Calhoun’s team, and an expert on statistical methods applying to ICA and fMRI.  This will be accomplished with thorough discussions and detailed answers to statistical inquiries, active curiosity about others’ work and how I may contribute, and careful study of existing ICA models and sound application of statistical principles. My career goals at the MRN are to develop a broad and deep knowledge of the methods for analysis of fMRI data in particular, and brain imaging data in general, to publish carefully developed extensions in well-written papers, and make contributions to others’ work.  This will be accomplished by dissecting the modeling details from published work and uncovering further details by contacting the authors, appealing to theoretical results and experimental confirmation before publicizing new methods, and helping others consider their methods, results, and interpretations.



My vision is to contribute more to the Albuquerque contra dance community and bring dance to more people, especially youth.  This will be accomplished by making opportunities for new callers, writing and calling dances, leading and participating in workshops, helping make more dance and music opportunities to bring the community together, outreach efforts to introduce dance to more people, and always collaborating with our vibrant New Mexico dance community to make it happen.
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Paper accepted: δ13C of soluble sugars in Tillandsia epiphytes vary in response to shifts in habitat

Laurel Goode, Erik Erhardt, Louis Santiago, and Michael Allen. δ13C of soluble sugars in Tillandsia epiphytes vary in response to shifts in habitat. Oecologia, Physiological ecology section, 2010. I met Laurel at SIRFER 2008 where we enjoyed a wide range of stable isotope lectures and lab experience. She first used my software, SISUS, to estimate the proportion of C3 vs CAM photosynthesis of epiphytes. Our work and friendship led to the collaboration where we thought about and developed a model for the environmental factors affecting the phothsynthetic pathways of the species studied. Abstract We studied carbon stable isotopic composition (δ13C) of bulk leaf tissue and extracted sugars of four epiphytic Tillandsia species to investigate flexibility in the use of crassulacean acid metabolism (CAM) and C3 photosynthetic pathways. Plants growing in two seasonally-dry tropical forest reserves in Mexico that differ in annual precipitation were measured during wet and dry seasons, and among secondary, mature, and wetland forest types within each site. Dry season sugars were more enriched in 13C than wet season sugars, but there was no seasonal difference in bulk tissues. Bulk tissue δ13C differed by species and by forest type, with values from open-canopied wetlands more enriched in 13C than mature or secondary forest types. The shifts within forest habitat were related to temporal and spatial changes in vapour pressure deficits (VPD). Modeling results estimate a possible 4% increase in the proportional contribution of the C3 pathway during the wet season, emphasizing that any seasonal or habitat-mediated variation in photosynthetic pathway appears to be quite moderate and within the range of isotopic effects caused by variation in stomatal conductance during assimilation through the C3 pathway and environmental variation in VPD. Carbon isotopic analysis of sugars together with bulk leaf tissue offer a useful approach for incorporating short- and long-term measurements of carbon isotope discrimination during photosynthesis.
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