Current status of the motor program: Revisited

The motor program is a concept that has had a major influence on theorizing in the field of motor control. However, there has been a lack of consensus as to what exactly is a motor program and its role in movement organization and execution. In 1994 Morris, Summers, Matyas, and Iansek concluded from a review of the application of the motor program concept in the field of physical therapy that continued use of the term may impede progress in the field. In this paper we examine what has happened to the motor program concept in the thirteen years since the previous evaluation. The review indicates that although the term is still being used in different ways, the theoretical existence of a motor program appears to be generally accepted by researchers in experimental psychology, movement science, and neurophysiology. The recent development of powerful brain imaging techniques may allow determination of whether the motor program should be regarded as a metaphorical or literal concept.     

The Relationship Between Adolescents’ Attitudes Toward Their Fathers and Loneliness: A Cross-Cultural Study

Loneliness can be regarded as an epidemic of modern society that is becoming increasingly problematic for millions of people. Adolescents are particularly susceptible to the development of this kind of emotional distress. Although many causes of loneliness can be identified, some researchers are of the opinion that it can also be attributed to unpleasant childhood experiences that result in unfulfilled needs relating to intimacy. In this research study, the relationship between loneliness and adolescents’ attitudes towards their fathers was investigated. In order to achieve this goal, information was gathered from 1068 South African respondents. Biographical questionnaires were administered and a Loneliness Scale was applied. In addition, adolescents’ attitudes towards their fathers were measured by means of a Fathers Questionnaire. Steps were taken to determine which of the independent variables, namely gender, age, race, language and socio-economic status, contributed significantly to the prediction of loneliness. In order to process the acquired information, a stepwise multiple regression analysis was conducted. The most important finding of this study is that adolescents’ attitudes towards their fathers comprise the most prominent predictor of loneliness during adolescence. The results also indicated that all of the independent variables had a statistically significant influence on loneliness.     

Net Amount of Food Affects Autoshaped Response Rate, Response Latency, and Gape Amplitude in Pigeons

The contribution of net amount of food to conditioned response strength and topography was assessed in four pigeons under autoshaping contingencies. In each session, under one baseline phase and three replication phases, three trial types were presented sequentially: One conditioned stimulus (keylight) signaled one small pellet, another signaled one large pellet, and a third signaled seven small pellets which were weight-matched to one large pellet. Five dependent variables were response rates and latencies based on the occurrence of both keyswitch closures and gapes (beak openings) and gape amplitudes. In result, net amount of food, not pellet diameter or number, affected all dependent variables. Notably, gape amplitudes elicited by the seven-small pellet keylights were larger than the gape amplutides elicited by the one-small pellet keylights even though the gape amplitudes elicited by both unconditioned stimuli (one or seven pellets) were equally small. This mismatch between conditioned and unconditioned responses is incompatible with stimulus substitution accounts but is compatible with an associative strength account. Furthermore, the changes in the dependent variables were most likely determined by Pavlovian and not by inadvertent operant contingencies. The findings demonstrate that an analysis of classical conditioning benefits from the inclusion of topographical measures.     

Fronto-parietal mirror neuron system modeling: Visuospatial transformations support imitation learning independently of imitator perspective

Although the human mirror neuron system (MNS) is critical for action observation and imitation, most MNS investigations overlook the visuospatial transformation processes that allow individuals to interpret and imitate actions observed from differing perspectives. This problem is not trivial since accurately reaching for and grasping an object requires a visuospatial transformation mechanism capable of precisely remapping fine motor skills where the observer’s and imitator’s arms and hands may have quite different orientations and sizes. Accordingly, here we describe a novel neural model to investigate the dynamics between the fronto-parietal MNS and visuospatial processes during observation and imitation of a reaching and grasping action. Our model encompasses i) the inferior frontal gyrus (IFG) and inferior parietal lobule (IPL), regions that are postulated to produce neural drive and sensory predictions, respectively; ii) the middle temporal (MT) and middle superior temporal (MST) regions that are postulated to process visual motion of a particular action; and iii) the superior parietal lobule (SPL) and intra-parietal sulcus (IPS) that are hypothesized to encode the visuospatial transformations enabling action observation/imitation based on different visuospatial viewpoints. The results reveal that when a demonstrator executes an action, an imitator can reproduce it with similar kinematics, independently of differences in anthropometry, distance, and viewpoint. As with prior empirical findings, similar model synaptic activity was observed during both action observation and execution along with the existence of both view-independent and view-dependent neural populations in the frontal MNS. Importantly, this work generates testable behavioral and neurophysiological predictions. Namely, the model predicts that i) during observation/imitation the response time increases linearly as the rotation angle of the observed action increases but remain similar when performing both clockwise and counterclockwise rotation and ii) IPL embeds essentially view-independent neurons while SPL/IPS includes both view-independent and view-dependent neurons. Overall, this work suggests that MT/MST visuomotion processes combined with the SPL/IPS allow the MNS to observe and imitate actions independently of demonstrator-imitator spatial relationships.     

Further extensions of precision medicine to behavior analysis: A demonstration using functional communication training

The potential applicability of concepts and methods of the paradigm of precision medicine to the field of applied behavior analysis is only beginning to be explored. Both precision medicine and applied behavior analysis seek to understand and classify clinical problems through identification of their causal pathways. Both aim to develop treatments directly targeting those causal pathways, which also requires an understanding of the mechanisms by which treatments produce change (treatment-action pathways). In the current study, we extend the data-analytic methods and concepts described by Hagopian et al. (2018) toward the identification of variables that predict response to functional communication training (FCT). We discuss emerging conceptual issues, including the importance of distinguishing predictive behavioral markers from predictor variables based on their purported involvement in the causal or treatment-action pathways. Making these discriminations is a complex undertaking that requires knowledge of these mechanisms and how they interact.     

Comparing variances of correlated variables

A test is proposed for the equality of the variances ofk 2 correlated variables. Pitman's test fork = 2 reduces the null hypothesis to zero correlation between their sum and their difference. Its extension, eliminating nuisance parameters by a bootstrap procedure, is valid for any correlation structure between thek normally distributed variables. A Monte Carlo study for several combinations of sample sizes and number of variables is presented, comparing the level and power of the new method with previously published tests. Some nonnormal data are included, for which the empirical level tends to be slightly higher than the nominal one. The results show that our method is close in power to the asymptotic tests which are extremely sensitive to nonnormality, yet it is robust and much more powerful than other robust tests.This research was supported by the fund for the promotion of research at the Technion.     

An alternative two stage least squares (2SLS) estimator for latent variable equations

The Maximum-likelihood estimator dominates the estimation of general structural equation models. Noniterative, equation-by-equation estimators for factor analysis have received some attention, but little has been done on such estimators for latent variable equations. I propose an alternative 2SLS estimator of the parameters in LISREL type models and contrast it with the existing ones. The new 2SLS estimator allows observed and latent variables to originate from nonnormal distributions, is consistent, has a known asymptotic covariance matrix, and is estimable with standard statistical software. Diagnostics for evaluating instrumental variables are described. An empirical example illustrates the estimator. I gratefully acknowledge support for this research from the Sociology Program of the National Science Foundation (SES-9121564) and the Center for Advanced Study in the Behavioral Sciences, Stanford, California. This paper was presented at the Interdisciplinary Consortium for Statistical Applications at Indiana University at Bloomington (March 2, 1994) and at the RMD Conference on Causal Modeling at Purdue University, West Lafayette, Indiana (March 3-5, 1994).     

A note on distributional properties of the Jöreskog-Sörbom fit indices

In introducing the LISREL model for systems of linear structural equations, Jöreskog and Sörbom proposed two goodness-of-fit indices, GFI and AGFI. Their asymptotic distributions and some statistical properties are discussed.The authors would like to acknowledge the helpful comments and suggestions from the Associate Editor and two anonymous reviewers.     

Some contributions to efficient statistics in structural models: Specification and estimation of moment structures

Current practice in structural modeling of observed continuous random variables is limited to representation systems for first and second moments (e.g., means and covariances), and to distribution theory based on multivariate normality. In psychometrics the multinormality assumption is often incorrect, so that statistical tests on parameters, or model goodness of fit, will frequently be incorrect as well. It is shown that higher order product moments yield important structural information when the distribution of variables is arbitrary. Structural representations are developed for generalizations of the Bentler-Weeks, Jöreskog-Keesling-Wiley, and factor analytic models. Some asymptotically distribution-free efficient estimators for such arbitrary structural models are developed. Limited information estimators are obtained as well. The special case of elliptical distributions that allow nonzero but equal kurtoses for variables is discussed in some detail. The argument is made that multivariate normal theory for covariance structure models should be abandoned in favor of elliptical theory, which is only slightly more difficult to apply in practice but specializes to the traditional case when normality holds. Many open research areas are described.     

The rank of reduced dispersion matrices

Psychometricians working in factor analysis and econometricians working in regression with measurement error in all variables are both interested in the rank of dispersion matrices under variation of the diagonal elements. Psychometricians concentrate on cases in which low rank can be attained, preferably rank one, the Spearman case. Econometricians cocentrate on cases in which the rank cannot be reduced below the number of variables minus one, the Frisch case. In this paper we give an extensive historial discussion of both fields, we prove the two key results in a more satisfactory and uniform way, we point out various small errors and misunderstandings, and we present a methodological comparison of factor analysis and regression on the basis of our results.Financial support by the Netherlands Organization for the Advancement of Pure Research (ZWO) is gratefully acknowledged.