Effects of differences between stimuli, responses, and reinforcer rates on conditional discrimination performance

In a discrete-trial conditional discrimination procedure, 4 pigeons obtained food reinforcers by pecking a key with a short latency on trials signaled by one stimulus and by pecking the same key with a long latency on trials signaled by a second stimulus. The physical difference between the two stimuli and the temporal separation between the latency values required for reinforcement were varied factorially over four sets of conditions, and the ratio of reinforcer rates for short and long latencies was varied within each set of conditions. Stimulus discrimination varied directly with both stimulus and response differences and was unaffected by the reinforcer ratio. Sensitivity to reinforcement, estimated by generalized-matching-law fits to the data within each set of conditions, varied directly with the response difference but inversely with the stimulus difference arranged between sets of conditions. Because variations in stimulus differences, response differences, and reinforcer differences did not have equivalent effects, these findings question the functional equivalence of the three terms of the discriminated operant: antecedent stimuli, behavior, and consequences.     

Analyzing sequential categorical data: Individual variation in markov chains

Markov chains are probabilistic models for sequences of categorical events, with applications throughout scientific psychology. This paper provides a method for anlayzing data consisting of event sequences and covariate observations. It is assumed that each sequence is a Markov process characterized by a distinct transition probability matrix. The objective is to use the covariate data to explain differences between individuals in the transition probability matrices characterizing their sequential data. The elements of the transition probability matrices are written as functions of a vector of latent variables, with variation in the latent variables explained through a multivariate regression on the covariates. The regression is estimated using the EM algorithm, and requires the numerical calculation of a multivariate integral. An example using simulated cognitive developmental data is presented, which shows that the estimation of individual variation in the parameters of a probability model may have substantial theoretical importance, even when individual differences are not the focus of the investigator's concerns.Research contributing to this article was supported by B.R.S. Subgrant 5-35345 from the University of Virginia. I thank the DADA Group, Bill Fabricius, Don Hartmann, William Griffin, Jack McArdle, Ivo Molenaar, Ronald Schoenberg, Simon Tavaré, and several anonymous reviewers for their discussion of these points.     

A NOTE ON TRANSFER OF STIMULUS CONTROL IN THE DELAYED-CUE PROCEDURE: FACILITATION BY AN OVERT DIFFERENTIAL RESPONSE

This case study describes initially unsuccessful attempts to use the delayed-cue procedure to teach conditional discriminations to an individual with moderate mental retardation. The task was matching printed-word comparison stimuli to dictated-name sample stimuli. In three experiments, the subject typically waited for the delayed cue unless differential responses to the dictated samples (repeating the sample names) were required. Hence, the study provides an example of a way to make the delayed-cue method more effective. The stimulus control bases for the results are discussed.     

Formation of transitivity in conditional matching to sample by pigeons

Four homing pigeons were trained over 5 months in a zero-delay, “arbitrary” matching-to-sample procedure with sample and comparison stimuli presented on any of three response keys. Birds were also required to complete a fixed-ratio 10 requirement on both sample and comparison stimuli to terminate their presentation. The procedure resulted in the establishment of relations that were not specifically trained and that can be characterized by the property of transitivity in a stimulus equivalence context. This result was in contrast with the findings obtained from most previous research with nonhuman subjects.     

Neurobehavioral deficits,adolescent traumatic brain injury,and transition to college

Outcome following traumatic brain injury (TBI) has been frequently evaluated for adults, although there has been minimal research on adolescents with TBI. It has been argued that TBI sequelae may be more difficult for adolescents to adjust to given developmental changes in physical (puberty), interpersonal (self-concept), and environmental domains (transition to college). In addition, it is commonly acknowledged that moderator variables such as psychiatric history, family functioning, substance use, and sexuality impact functional outcome following TBI, although it is often difficult to objectively evaluate these variables. The current study examined relationships among TBI-related deficits, moderator variables, and academic outcomes for six adolescents transitioning to college. The findings suggest that it may not be appropriate to predict functional outcome based solely on objective neuropsychological results. However, moderator variables appear to have a more direct relationship with outcome, depending on the moderator variable and the individual.     

Detachment and defeasibility in deontic logic

The purpose of the paper is to present a logical framework that allow to formalize a kind of prima facie duties, defeasible conditional duties, indefeasible conditional duties and actual (indefeasible) duties, as well as to show their logical interconnections.     

CONDITIONAL DISCRIMINATION VS. MATCHING TO SAMPLE: AN EXPANSION OF THE TESTING PARADIGM

A subject's performance under a conditional-discrimination procedure defines conditional relations between stimuli: “If A1, then B1; if A2, then B2.” The procedure may also generate matching to sample. If so, the stimuli will be related not only by conditionality, but by equivalence: A1 and B1 will become equivalent members of one stimulus class, A2 and B2 of another. One paradigm for testing whether a conditional-discrimination procedure has generated equivalence relations uses three sets of stimuli, A, B, and C, three stimuli per set. Subjects learn to select Set-B and Set-C comparisons conditionally upon Set-A samples. Having been explicitly taught six sample-comparison relations, A1B1, A1C1, A2B2, A2C2, A3B3, and A3C3, subjects prove immediately capable of matching the B- and C-stimuli; six new relations emerge (B1C1, B2C2, B3C3, C1B1, C2B2, C3B3). The 12 stimulus relations, six taught and six emergent, define the existence of three three-member stimulus classes, A1B1C1, A2B2C2, and A3B3C3. This paradigm was expanded by introducing three more stimuli (Set D), and teaching eight children not only the AB and AC relations but DC relations also—selecting Set-C comparisons conditionally upon Set-D samples. Six of the children proved immediately capable of matching the B- and D-stimuli to each other. By selecting appropriate Set-B comparisons conditionally upon Set-D samples, and Set-D comparisons conditionally upon Set-B samples, they demonstrated the existence of three four-member stimulus classes, A1B1C1D1, A2B2C2D2, and A3B3C3D3. These larger classes were confirmed by the subjects' success with the prerequisite lower-level conditional relations; they were also able to select Set-D comparisons conditionally upon samples from Sets A and C, and to do the BC and CB matching that defined the original three-member classes. Adding the three DC relations therefore generated 12 more, three each in BD, DB, AD, and CD. Enlarging each class by one member brought about a disproportionate increase in the number of emergent relations. Ancillary oral naming tests suggested that the subject's application of the same name to each stimulus was neither necessary nor sufficient to establish classes of equivalent stimuli.     

The polyserial correlation coefficient

The polyserial and point polyserial correlations are discussed as generalizations of the biserial and point biserial correlations. The relationship between the polyserial and point polyserial correlation is derived. The maximum likelihood estimator of the polyserial correlation is compared with a two-step estimator and with a computationally convenient ad hoc estimator. All three estimators perform reasonably well in a Monte Carlo simulation. Some practical applications of the polyserial correlation are described.By coincidence, the first author and the second and third authors learned that they were working independently on closely related problems and, consequently, decided to write a jointly authored paper.