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1.  A Hierarchical Adaptive Approach to Optimal Experimental Design 
Neural computation  2014;26(11):2465-2492.
Experimentation is at the core of research in the behavioral and neural sciences, yet observations can be expensive and time-consuming to acquire (e.g., MRI scans, responses from infant participants). A major interest of researchers is designing experiments that lead to maximal accumulation of information about the phenomenon under study with the fewest possible number of observations. In addressing this challenge, statisticians have developed adaptive design optimization methods. This letter introduces a hierarchical Bayes extension of adaptive design optimization that provides a judicious way to exploit two complementary schemes of inference (with past and future data) to achieve even greater accuracy and efficiency in information gain. We demonstrate the method in a simulation experiment in the field of visual perception.
doi:10.1162/NECO_a_00654
PMCID: PMC4275799  PMID: 25149697
2.  Discriminating Among Probability Weighting Functions Using Adaptive Design Optimization 
Journal of risk and uncertainty  2013;47(3):255-289.
Probability weighting functions relate objective probabilities and their subjective weights, and play a central role in modeling choices under risk within cumulative prospect theory. While several different parametric forms have been proposed, their qualitative similarities make it challenging to discriminate among them empirically. In this paper, we use both simulation and choice experiments to investigate the extent to which different parametric forms of the probability weighting function can be discriminated using adaptive design optimization, a computer-based methodology that identifies and exploits model differences for the purpose of model discrimination. The simulation experiments show that the correct (data-generating) form can be conclusively discriminated from its competitors. The results of an empirical experiment reveal heterogeneity between participants in terms of the functional form, with two models (Prelec-2, Linear in Log Odds) emerging as the most common best-fitting models. The findings shed light on assumptions underlying these models.
doi:10.1007/s11166-013-9179-3
PMCID: PMC3895409  PMID: 24453406
3.  How Do PDP Models Learn Quasiregularity? 
Psychological review  2013;120(4):903-916.
Parallel Distributed Processing (PDP) models have had a profound impact on the study of cognition. One domain in which they have been particularly influential is quasiregular learning, in which mastery requires both learning regularities that capture the majority of the structure in the input plus learning exceptions that violate the regularities. How PDP models learn quasiregularity is still not well understood. Small- and large-scale analyses of a feedforward, three-layer network were carried out to address two fundamental issues about network functioning: how the model can learn both regularities and exceptions without sacrificing generalizability; and the nature of the hidden representation that makes this learning possible. Results show that capacity-limited learning pressures the network to form componential representations, which ensures good generalizability. Small and highly local perturbations of this representational system allow exceptions to be learned while minimally disrupting generalizability. Theoretical and methodological implications of the findings are discussed.
doi:10.1037/a0034195
PMCID: PMC4029953  PMID: 24015955
PDP model; quasiregularity; network analysis; hidden representation
4.  Human Capital Investment and the Gender Division of Labor in a Brawn-Based Economy 
The American economic review  2012;102(7):3531-3560.
We use a model of human capital investment and activity choice to explain facts describing gender differentials in the levels and returns to human capital investments. These include the higher return to and level of schooling, the small effect of healthiness on wages, and the large effect of healthiness on schooling for females relative to males. The model incorporates gender differences in the level and responsiveness of brawn to nutrition in a Roy-economy setting in which activities reward skill and brawn differentially. Empirical evidence from rural Bangladesh provides support for the model and the importance of the distribution of brawn.
doi:10.1257/aer.102.7.3531
PMCID: PMC4140409  PMID: 25152536
Brawn; health; schooling; gender
5.  A Tutorial on Adaptive Design Optimization 
Experimentation is ubiquitous in the field of psychology and fundamental to the advancement of its science, and one of the biggest challenges for researchers is designing experiments that can conclusively discriminate the theoretical hypotheses or models under investigation. The recognition of this challenge has led to the development of sophisticated statistical methods that aid in the design of experiments and that are within the reach of everyday experimental scientists. This tutorial paper introduces the reader to an implementable experimentation methodology, dubbed Adaptive Design Optimization, that can help scientists to conduct “smart” experiments that are maximally informative and highly efficient, which in turn should accelerate scientific discovery in psychology and beyond.
doi:10.1016/j.jmp.2013.05.005
PMCID: PMC3755632  PMID: 23997275
6.  Gunfight at the NOT OK Corral: Reply to “High Noon for Microfinance” by Duvendack and Palmer-Jones (Uncut version) 
The journal of development studies  2012;48(12):1886-1891.
The paper “High Noon for Microfinance Impact Evaluations” by Duvendack and Palmer-Jones replicates the papers of Chemin (2008) and Pitt and Khandker (1998) that estimate the impact of microfinance in Bangladesh. My paper replicates the Duvendack and Palmer-Jones replication and finds so many serious errors in their code and misrepresentations of the methods described in their paper that I conclude that their results are spurious and provide no evidence about the validity of either the papers of Chemin or Pitt and Khandker or on the effectiveness of microfinance.
doi:10.1080/00220388.2012.727563
PMCID: PMC4019335  PMID: 24833807
7.  Optimal Decision Stimuli for Risky Choice Experiments: An Adaptive Approach 
Management science  2013;59(2):358-375.
Collecting data to discriminate between models of risky choice requires careful selection of decision stimuli. Models of decision making aim to predict decisions across a wide range of possible stimuli, but practical limitations force experimenters to select only a handful of them for actual testing. Some stimuli are more diagnostic between models than others, so the choice of stimuli is critical. This paper provides the theoretical background and a methodological framework for adaptive selection of optimal stimuli for discriminating among models of risky choice. The approach, called Adaptive Design Optimization (ADO), adapts the stimulus in each experimental trial based on the results of the preceding trials. We demonstrate the validity of the approach with simulation studies aiming to discriminate Expected Utility, Weighted Expected Utility, Original Prospect Theory, and Cumulative Prospect Theory models.
doi:10.1287/mnsc.1120.1558
PMCID: PMC3924862  PMID: 24532856
experimental design; active learning; choice under risk; model discrimination
8.  Visual context due to speech-reading suppresses the auditory response to acoustic interruptions in speech 
Speech reading enhances auditory perception in noise. One means by which this perceptual facilitation comes about is through information from visual networks reinforcing the encoding of the congruent speech signal by ignoring interfering acoustic signals. We tested this hypothesis neurophysiologically by acquiring EEG while individuals listened to words with a fixed portion of each word replaced by white noise. Congruent (meaningful) or incongruent (reversed frames) mouth movements accompanied the words. Individuals judged whether they heard the words as continuous (illusion) or interrupted (illusion failure) through the noise. We hypothesized that congruent, as opposed to incongruent, mouth movements should further enhance illusory perception by suppressing the auditory cortex's response to interruption onsets and offsets. Indeed, we found that the N1 auditory evoked potential (AEP) to noise onsets and offsets was reduced when individuals experienced the illusion during congruent, but not incongruent, audiovisual streams. This N1 inhibitory effect was most prominent at noise offsets, suggesting that visual influences on auditory perception are instigated to a greater extent during noisy periods. These findings suggest that visual context due to speech-reading disengages (inhibits) neural processes associated with interfering sounds (e.g., noisy interruptions) during speech perception.
doi:10.3389/fnins.2014.00173
PMCID: PMC4078912  PMID: 25053937
audiovisual integration; auditory evoked potentials; degraded speech; illusory filling-in; phonemic restoration
9.  How does context play a part in splitting words apart? Production and perception of word boundaries in casual speech 
Journal of memory and language  2012;66(4):509-529.
Four experiments examined listeners’ segmentation of ambiguous schwa-initial sequences (e.g., a long vs. along) in casual speech, where acoustic cues can be unclear, possibly increasing reliance on contextual information to resolve the ambiguity. In Experiment 1, acoustic analyses of talkers’ productions showed that the one-word and two-word versions were produced almost identically, regardless of the preceding sentential context (biased or neutral). These tokens were then used in three listening experiments, whose results confirmed the lack of local acoustic cues for disambiguating the interpretation, and the dominance of sentential context in parsing. Findings speak to the H&H theory of speech production (Lindblom, 1990), demonstrate that context alone guides parsing when acoustic cues to word boundaries are absent, and demonstrate how knowledge of how talkers speak can contribute to an understanding of how words are segmented.
doi:10.1016/j.jml.2011.12.007
PMCID: PMC3480226  PMID: 23105169
Word segmentation; Casual speech; Speech production; Speech perception
10.  Exploring the role of exposure frequency in recognizing pronunciation variants 
Journal of phonetics  2011;39(3):304-311.
Words can be pronounced in multiple ways in casual speech. Corpus analyses of the frequency with which these pronunciation variants occur (e.g., Patterson & Connine, 2001) show that typically, one pronunciation variant tends to predominate; this raises the question of whether variant recognition is aligned with exposure frequency. We explored this issue in words containing one of four phonological contexts, each of which favors one of four surface realizations of word-medial /t/: [t], [ʔ], [ɾ], or a deleted variant. The frequencies of the four realizations in all four contexts were estimated for a set of words in a production experiment. Recognition of all pronunciation variants was then measured in a lexical decision experiment. Overall, the data suggest that listeners are sensitive to variant frequency: Word classification rates closely paralleled production frequency. The exceptions to this were [t] realizations (i.e., canonical pronunciations of the words), a finding which confirms other results in the literature and indicates that factors other than exposure frequency affect word recognition.
doi:10.1016/j.wocn.2010.07.004
PMCID: PMC3150572  PMID: 21822340
11.  Model discrimination through adaptive experimentation 
Psychonomic bulletin & review  2011;18(1):204-210.
An ideal experiment is one in which data collection is efficient and the results are maximally informative. This standard can be difficult to achieve because of uncertainties about the consequences of design decisions. We demonstrate the success of a Bayesian adaptive method (adaptive design optimization, ADO) in optimizing design decisions when comparing models of the time course of forgetting. Across a series of testing stages, ADO intelligently adapts the retention interval in order to maximally discriminate power and exponential models. Compared with two different control (non-adaptive) methods, ADO distinguishes the models decisively, with the results unambiguously favoring the power model. Analyses suggest that ADO’s success is due in part to its flexibility in adjusting to individual differences. This implementation of ADO serves as an important first step in assessing its applicability and usefulness to psychology.
doi:10.3758/s13423-010-0030-4
PMCID: PMC3289091  PMID: 21327352
Retention; Active learning; Model discrimination; Experimental design; Adaptive testing
12.  How are pronunciation variants of spoken words recognized? A test of generalization to newly learned words 
Journal of memory and language  2009;61(1):19-36.
One account of how pronunciation variants of spoken words (center-> “senner” or “sennah”) are recognized is that sublexical processes use information about variation in the same phonological environments to recover the intended segments (Gaskell & Marslen-Wilson, 1998). The present study tests the limits of this phonological inference account by examining how listeners process for the first time a pronunciation variant of a newly learned word. Recognition of such a variant should occur as long as it possesses the phonological structure that legitimizes the variation. Experiments 1 and 2 identify a phonological environment that satisfies the conditions necessary for a phonological inference mechanism to be operational. Using a word-learning paradigm, Experiments 3 through 5 show that inference alone is not sufficient for generalization but could facilitate it, and that one condition that leads to generalization is meaningful exposure to the variant in an overheard conversation, demonstrating that lexical processing is necessary for variant recognition.
doi:10.1016/j.jml.2009.02.005
PMCID: PMC2706522  PMID: 20161243
spoken word recognition; variant recognition; phonological inference; /t/ deletion
13.  The strength and time course of lexical activation of pronunciation variants 
Spoken words undergo frequent and often predictable variation in pronunciation. One form of variation is medial /t/ deletion, in which words like center and cantaloupe are pronounced without acoustic cues indicative of syllable-initial /t/. Three experiments examined the consequences of this missing phonetic information on lexical activation. In Experiments 1, the Ganong (1980) paradigm was used to measure the strength of activation of /t/-deleted variants, comparing labeling and response time results with their citation counterparts. Phonemic restoration was used in Experiment 2 to generalize the results. In the final experiment, Experiment 1 was replicated with a large number of trials so that the time course of activation could be mapped. Results show lexical influences on labeling begin sooner and reach a higher level for the citation than the /t/-deleted variant, although the overall shapes of their activation profiles are similar.
doi:10.1037/a0013160
PMCID: PMC2690714  PMID: 19485698
14.  Optimal Experimental Design for Model Discrimination 
Psychological review  2009;116(3):499-518.
Models of a psychological process can be difficult to discriminate experimentally because it is not easy to determine the values of the critical design variables (e.g., presentation schedule, stimulus structure) that will be most informative in differentiating them. Recent developments in sampling-based search methods in statistics make it possible to determine these values, and thereby identify an optimal experimental design. After describing the method, it is demonstrated in two content areas in cognitive psychology in which models are highly competitive: retention (i.e., forgetting) and categorization. The optimal design is compared with the quality of designs used in the literature. The findings demonstrate that design optimization has the potential to increase the informativeness of the experimental method.
doi:10.1037/a0016104
PMCID: PMC2743521  PMID: 19618983
15.  Evaluation and Comparison of Computational Models 
Methods in enzymology  2009;454:287-304.
Computational models are powerful tools that can enhance the understanding of scientific phenomena. The enterprise of modeling is most productive when the reasons underlying the adequacy of a model, and possibly its superiority to other models, are understood. This chapter begins with an overview of the main criteria that must be considered in model evaluation and selection, in particular explaining why generalizability is the preferred criterion for model selection. This is followed by a review of measures of generalizability. The final section demonstrates the use of five versatile and easy-to-use selection methods for choosing between two mathematical models of protein folding.
doi:10.1016/S0076-6879(08)03811-1
PMCID: PMC2704205  PMID: 19216931
16.  Modeling the word recognition data of Vitevitch and Luce (1998): Is it ARTful? 
Psychonomic bulletin & review  2007;14(3):442-448.
Vitevitch and Luce (1998) showed that the probability with which phonemes co-occur in the language (phonotactic probability) affects the speed with which words and nonwords are named. Words with high phonotactic probabilities between phonemes were named more slowly than words with low probabilities, whereas with nonwords, just the opposite was found. To reproduce this reversal in performance, a model would seem to require not merely sublexical representations, but sublexical representations that are relatively independent of lexical representations. ARTphone (Grossberg, Boardman, & Cohen, 1997) is designed to meet these requirements. In this study, we used a technique called parameter space partitioning to analyze ARTphone’s behavior and to learn if it can mimic human behavior and, if so, to understand how. To perform best, differences in sublexical node probabilities must be amplified relative to lexical node probabilities to offset the additional source of inhibition from top-down masking) that is found at the sublexical level.
PMCID: PMC2603571  PMID: 17874585
17.  FTIR Microspectroscopy Coupled with Two-Class Discrimination Segregates Markers Responsible for Inter- and Intra-Category Variance in Exfoliative Cervical Cytology 
Biomarker insights  2008;3:179-189.
Infrared (IR) absorbance of cellular biomolecules generates a vibrational spectrum, which can be exploited as a “biochemical fingerprint” of a particular cell type. Biomolecules absorb in the mid-IR (2–20 μm) and Fourier-transform infrared (FTIR) microspectroscopy applied to discriminate different cell types (exfoliative cervical cytology collected into buffered fixative solution) was evaluated. This consisted of cervical cytology free of atypia (i.e. normal; n = 60), specimens categorised as containing low-grade changes (i.e. CIN1 or LSIL; n = 60) and a further cohort designated as high-grade (CIN2/3 or HSIL; n = 60). IR spectral analysis was coupled with principal component analysis (PCA), with or without subsequent linear discriminant analysis (LDA), to determine if normal versus low-grade versus high-grade exfoliative cytology could be segregated. With increasing severity of atypia, decreases in absorbance intensity were observable throughout the 1,500 cm−1 to 1,100 cm−1 spectral region; this included proteins (1,460 cm−1), glycoproteins (1,380 cm−1), amide III (1,260 cm−1), asymmetric (νas) PO2− (1,225 cm−1) and carbohydrates (1,155 cm−1). In contrast, symmetric (νs) PO2− (1,080 cm−1) appeared to have an elevated intensity in high-grade cytology. Inter-category variance was associated with protein and DNA conformational changes whereas glycogen status strongly influenced intra-category. Multivariate data reduction of IR spectra using PCA with LDA maximises inter-category variance whilst reducing the influence of intra-class variation towards an objective approach to class cervical cytology based on a biochemical profile.
PMCID: PMC2493409  PMID: 18677422
biomarker; cervical cytology; Fourier-transform infrared microspectroscopy; high-grade; low-grade; principal component analysis
18.  Does response scaling cause the generalized context model to mimic a prototype model? 
Psychonomic bulletin & review  2007;14(6):1043-1050.
Smith and Minda (1998, 2002) argued that the response scaling parameter γ in the exemplar-based generalized context model (GCM) makes the model unnecessarily complex and allows it to mimic the behavior of a prototype model. We evaluated this criticism in two ways. First, we estimated the complexity of the GCM with and without the γ parameter and also compared its complexity to that of a prototype model. Next, we assessed the extent to which the models mimic each other, using two experimental designs (Nosofsky & Zaki, 2002, Experiment 3; Smith & Minda, 1998, Experiment 2), chosen because these designs are thought to differ in the degree to which they can discriminate the models. The results show that γ can increase the complexity of the GCM, but this complexity does not necessarily allow mimicry. Furthermore, if statistical model selection methods such as minimum description length are adopted as the measure of model performance, the models will be highly discriminable, irrespective of design.
PMCID: PMC2430630  PMID: 18229473
19.  Analytic Expressions for the BCDMEM Model of Recognition Memory 
We introduce a Fourier Transformation technique that enables one to derive closed-form expressions of performance measures (e.g., hit and false alarm rates) of simulation-based models of recognition memory. Application of the technique is demonstrated using the bind cue decide model of episodic memory (BCDMEM; Dennis & Humphreys, 2001). In addition to reducing the time required to test the model, which for models like BCDMEM can be excessive, asymptotic expressions of the measures reveal heretofore unknown properties of the model, such as model predictions being dependent on vector length.
doi:10.1016/j.jmp.2007.02.001
PMCID: PMC2031849  PMID: 18516213
Recognition Memory; Cognitive Modeling; Fourier Transformation; Signal Detection Theory
20.  FTIR Microspectroscopy Coupled with Two-Class Discrimination Segregates Markers Responsible for Inter- and Intra-Category Variance in Exfoliative Cervical Cytology 
Biomarker Insights  2008;3:179-189.
Infrared (IR) absorbance of cellular biomolecules generates a vibrational spectrum, which can be exploited as a “biochemical fingerprint” of a particular cell type. Biomolecules absorb in the mid-IR (2–20 μm) and Fourier-transform infrared (FTIR) microspectroscopy applied to discriminate different cell types (exfoliative cervical cytology collected into buffered fixative solution) was evaluated. This consisted of cervical cytology free of atypia (i.e. normal; n = 60), specimens categorised as containing low-grade changes (i.e. CIN1 or LSIL; n = 60) and a further cohort designated as high-grade (CIN2/3 or HSIL; n = 60). IR spectral analysis was coupled with principal component analysis (PCA), with or without subsequent linear discriminant analysis (LDA), to determine if normal versus low-grade versus high-grade exfoliative cytology could be segregated. With increasing severity of atypia, decreases in absorbance intensity were observable throughout the 1,500 cm−1 to 1,100 cm−1 spectral region; this included proteins (1,460 cm−1), glycoproteins (1,380 cm−1), amide III (1,260 cm−1), asymmetric (νas) PO2− (1,225 cm−1) and carbohydrates (1,155 cm−1). In contrast, symmetric (νs) PO2− (1,080 cm−1) appeared to have an elevated intensity in high-grade cytology. Inter-category variance was associated with protein and DNA conformational changes whereas glycogen status strongly influenced intra-category. Multivariate data reduction of IR spectra using PCA with LDA maximises inter-category variance whilst reducing the influence of intra-class variation towards an objective approach to class cervical cytology based on a biochemical profile.
PMCID: PMC2493409  PMID: 18677422
biomarker; cervical cytology; Fourier-transform infrared microspectroscopy; high-grade; low-grade; principal component analysis

Results 1-20 (20)