Dismal: a spreadsheet for sequential data analysis and HCI experimentation

Dismal is a spreadsheet that works within GNU Emacs, a widely available programmable editor. Dismal has three features of particular interest to those who study behavior: (1) the ability to manipulate and align sequential data, (2) an open architecture that allows users to expand it to meet their particular needs, and (3) an instrumented and accessible interface for studies of human-computer interaction (HCI). Example uses of each of these capabilities are provided, including cognitive models that have had their sequential behavior aligned with subject’s protocols, extensions useful for teaching and doing HCI design, and studies in which keystroke logs from the timing package in Dismal have been used.     

Using partially structured attitude measures to enhance the attitude-behavior relationship

This article recalls a classic scheme for categorizing attitude measures. One particular group of measures, those that rely on respondents' interpretations of partially structured stimuli, has virtually disappeared from attitude research. An attitude measure based on respondents' interpretation of partially structured stimuli is considered. Four studies employing such a measure demonstrate that it predicts unique variance in self-reported and actual behavior, beyond that predicted by explicit and contemporary implicit measures and regardless of whether the attitude object under consideration is wrought with social desirability concerns. Implications for conceptualizing attitude measurement and attitude-behavior relations are discussed.     

A computational feature binding model of human texture perception

We present a computational model for human texture perception which assigns functional principles to the Gestalt laws of similarity and proximity. Motivated by early vision mechanisms, in the first stage, local texture features are extracted by utilizing multi-scale filtering and nonlinear spatial pooling. In the second stage, features are grouped according to the spatial feature binding model of the competitive layer model (CLM; Wersing et al. 2001). The CLM uses cooperative and competitive interactions in a recurrent network, where binding is expressed by the layer-wise coactivation of feature-representing neurons. The Gestalt law of similarity is expressed by a non-Euclidean distance measure in the abstract feature space with proximity being taken into account by a spatial component. To choose the stimulus dimensions which allow the most salient similarity-based texture segmentation, the feature similarity metrics is reduced to the directions of maximum variance. We show that our combined texture feature extraction and binding model performs segmentation in strong conformity with human perception. The examples range from classical microtextures and Brodatz textures to other classical Gestalt stimuli, which offer a new perspective on the role of texture for more abstract similarity grouping.     

A person-fit index for polytomous rasch models,latent class models,and their mixture generalizations

A normally distributed person-fit index is proposed for detecting aberrant response patterns in latent class models and mixture distribution IRT models for dichotomous and polytomous data.This article extends previous work on the null distribution of person-fit indices for the dichotomous Rasch model to a number of models for categorical data. A comparison of two different approaches to handle the skewness of the person-fit index distribution is included.Major parts of this paper were written while the first author worked at the Institute for Science Education, Kiel, Germany. Any opinions expressed in this paper are those of the authors and not necessarily of Educational Testing Service. The results presented in this paper were improved by valuable comments from J. Rost, K. Yamamoto, N.D. Verhelst, E. Bedrick and two anonymous reviewers.     

The nature and treatment of stuttering as revealed by fMRI A within- and between-group comparison

This article reviews some of our recent functional magnetic resonance imaging (fMRI) studies of stuttering. Using event-related fMRI experiments, we investigated brain activation during speech production. Results of three studies comparing persons who stutter (PWS) and persons who do not stutter (PWNS) are outlined. Their findings point to a region in the right frontal operculum (RFO) that was consistently implicated in stuttering. During overt reading and before fluency shaping therapy, PWS showed higher and more distributed neuronal activation than PWNS. Immediately after therapy differential activations were even more distributed and left sided. They extended to frontal, temporal, and parietal regions, anterior cingulate, insula, and putamen. These over-activations were slightly reduced and again more right sided two years after therapy. Left frontal deactivations remained stable over two years of observation, and therefore possibly indicate a dysfunction. After therapy, we noted higher activations in persons who stutter moderately than in those who stutter severely. These activations might reflect patterns of compensation. We discuss why these findings suggest that fluency-inducing techniques might synchronize a disturbed signal transmission between auditory, speech motor planning, and motor areas.

Educational objectives: The reader will learn about and be able to: (1) identify regions of brain activations and deactivations specific for PWS; (2) describe brain activation changes induced by fluency shaping therapy; and (3) discuss the correlation between stuttering severity and brain activation.     

On the lateralization of emotional prosody: an event-related functional MR investigation

In order to investigate the lateralization of emotional speech we recorded the brain responses to three emotional intonations in two conditions, i.e., "normal" speech and "prosodic" speech (i.e., speech with no linguistic meaning, but retaining the 'slow prosodic modulations' of speech). Participants listened to semantically neutral sentences spoken with a positive, neutral, or negative intonation in both conditions and judged how positive, negative, or neutral the intonation was on a five-point scale. Core peri-sylvian language areas, as well as some frontal and subcortical areas were activated bilaterally in the normal speech condition. In contrast, a bilateral fronto-opercular region was active when participants listened to prosodic speech. Positive and negative intonations elicited a bilateral fronto-temporal and subcortical pattern in the normal speech condition, and more frontal activation in the prosodic speech condition. The current results call into question an exclusive right hemisphere lateralization of emotional prosody and expand patient data on the functional role of the basal ganglia during the perception of emotional prosody.     

Terminal decline and cognitive performance in very old age: does cause of death matter?

Cross-sectional differences and longitudinal changes in cognitive functioning in relation to mortality across a 7-year follow-up period, with 3 times of measurement, were examined in a population-based sample of very old adults. The authors also sought to determine whether cause of death (cerebro/cardiovascular disease [CVD]; non-CVD) modified the magnitude of mortality-related cognitive deficits. Cognitive performance was indexed by tests of general cognitive ability, episodic memory, primary memory, verbal fluency, and visuospatial ability. Results indicated cross-sectional differences on all domains of functioning, with persons who would die within 3 years after baseline testing performing more poorly. Longitudinally, greater decrements were observed on all domains for persons who would die after the first follow-up period, as compared with survivors. Cause of death failed to modify the magnitude of the cross-sectional and longitudinal deficits. The pattern of results point to the general nature of this phenomenon.     

Sit-and-wait strategies in dynamic visual search

The role of memory in visual search has lately become a controversial issue. Horowitz and Wolfe (1998) observed that performance in a visual search task was little affected by whether the stimuli were static or randomly relocated every 111 ms. Because a memory-based mechanism, such as inhibition of return, would be of no use in the dynamic condition, Horowitz and Wolfe concluded that memory is likewise not involved in the static condition. However, Horowitz and Wolfe could not effectively rule out the possibility that observers adopted a different strategy in the dynamic condition than in the static condition. That is, in the dynamic condition observers may have attended to a subregion of the display and waited for the target to appear there (sit-and-wait strategy). This hypothesis is supported by experimental data showing that performance in their dynamic condition does not differ from performance in another dynamic condition in which observers are forced to adopt a sit-and-wait strategy by being presented with a limited region of the display only.     

Knowledge level learning and the power law: A soar model of skill acquisition in scheduling

Zusammenfassung. Das hier vorgestellte Modell lernt graduell, Planungsaufgaben aus der Klasse der Maschinenbelegungsprobleme (job-shop-scheduling problems) zu lösen. Mit Hilfe des Chunking-Mechanismus von Soar wird episodisches Wissen über die Belegungsreihenfolge von Aufträgen auf Maschinen memoriert. Bei der Entwicklung des Modells wurden zahlreiche qualitative (z. B. Transfereffekte) und quantitative Befunde (z. B. Bearbeitungszeiten) aus einer früheren empirischen Untersuchung berücksichtigt. In einer Validierungsstudie wurden dieselben Aufgaben von 14 Probanden und dem Modell bearbeitet. Die Passung von Simulationsdaten und empirischen Ergebnissen fiel insgesamt gut aus. Allerdings löst das Modell die Aufgaben schneller und zeigt auch einen etwas besseren Lernverlauf als die Probanden. Das Modell liefert eine Erklärung für das Rauschen, das typischerweise bei Bearbeitungszeiten zu beobachten ist: es handelt sich um erworbenes Wissen, das mehr oder weniger gut und auch unterschiedlich häufig auf neue Situationen übertragen wird. Der Lernverlauf der Probanden entspricht nur für aggregierte Daten einer Potenzfunktion (power law). Der vorgestellte Mechanismus zeigt, wie ein symbolisches Modell der Informationsverarbeitung graduelle Verhaltensänderungen generiert und wie der offensichtliche Erwerb allgemeiner Prozeduren ohne explizites Lernen von deklarativen Regeln erfolgen kann. Es wird nahegelegt, daß es sich hier um die Modellierung einer Form impliziten Lernens handelt. Summary. The model presented here gradually learns how to perform a job-shop scheduling task. It uses Soar's chunking mechanism to acquire episodic memories about the order to schedule jobs. The model was based on many qualitative (e.g., transfer effects) and quantitative (e.g., solution time) regularities found in previously collected data. The model was tested with new data where scheduling tasks were given to the model and to 14 subjects. The model generally fit these data with the restrictions that the model performs the task (in simulated time) faster than the subjects, and its performance improves somewhat more quickly than the subjects' performance. The model provides an explanation of the noise typically found in problem solving times - it is the result of learning actual pieces of knowledge that transfer more or less to new situations but rarely by an average amount. Only when the data are averaged (i.e., over subjects) does the smooth power law appear. This mechanism demonstrates how symbolic models can exhibit a gradual change in behavior and how the apparent acquisition of general procedures can be performed without resorting to explicit declarative rule generation. We suggest that this may represent a type of implicit learning.