Shaw’s stored information as a quantitative measure of sequential structure

In this paper, we describe a method to study the sequential structure in interevent times. The technique uses the stored information of an iterative map developed by-Shaw (1984). The stored information is a quantitative measure of the sequential organization or predictability in data. This paper discusses the concept of stored information and provides a FORTRAN routineto compute the stored information of interevent time data. Several synthetic data sets with known sequential structures are examined. Finally, we present some initial results from computing the stored information of experimental interresponse time data.     

Methodological improvements to a Procedure for Rapidly Establishing Steady-State Behavior

We performed three experiments to improve the quality and retention of data obtained from a Procedure for Rapidly Establishing Steady-State Behavior (PRESS-B; Klapes et al., 2020). In Experiment 1, 120 participants worked on nine concurrent random-interval random-interval (conc RI RI) schedules and were assigned to four conditions of varying changeover delay (COD) length. The 0.5-s COD condition group exhibited the fewest instances of exclusive reinforcer acquisition. Importantly, this group did not differ in generalized matching law (GML) fit quality from the other groups. In Experiment 2, 60 participants worked on nine conc RI RI schedules with a wider range of scheduled reinforcement rate ratios than was used in Experiment 1. Participants showed dramatic reductions in exclusive reinforcer acquisition. Experiment 3 entailed a replication of Experiment 2 wherein blackout periods were implemented between the schedule presentations and each schedule remained in operation until at least one reinforcer was acquired on each alternative. GML fit quality was slightly more consistent in Experiment 3 than in the previous experiments. Thus, these results suggest that future PRESS-B studies should implement a shorter COD, a wider and richer scheduled reinforcement rate ratio range, and brief blackouts between schedule presentations for optimal data quality and retention.     

On the current status of the evolutionary theory of behavior dynamics

The evolutionary theory of behavior dynamics is a complexity theory that instantiates the Darwinian principles of selection, reproduction, and mutation in a genetic algorithm. The algorithm is used to animate artificial organisms that behave continuously in time and can be placed in any experimental environment. The present paper is an update on the status of the theory. It includes a summary of the evidence supporting the theory, a list of the theory's untested predictions, and a discussion of how the algorithmic operations of the theory may correspond to material reality. Based on the evidence reviewed here, the evolutionary theory appears to be a strong candidate for a comprehensive theory of adaptive behavior.     

Impaired discriminative fear-conditioning resulting from elevated fear responding to learned safety cues among individuals with panic disorder

Classical fear-conditioning is central to many etiologic accounts of panic disorder (PD), but few lab-based conditioning studies in PD have been conducted. One conditioning perspective proposes associative-learning deficits characterized by deficient safety learning among PD patients. The current study of PD assesses acquisition and retention of discriminative aversive conditioning using a fear-potentiated startle paradigm. This paradigm was chosen for its specific capacity to independently assess safety- and danger learning in the service of characterizing putative anomalies in each type of learning among those with PD. Though no group difference in fear-potentiated startle was found at retention, acquisition results demonstrate impaired discriminative learning among PD patients as indexed by measures of conditioned startle-potentiation to learned safety and danger cues. Importantly, this discrimination deficit was driven by enhanced startle-potentiation to the learned safety cue rather than aberrant reactivity to the danger cue. Consistent with this finding, PD patients relative to healthy individuals reported higher expectancies of dangerous outcomes in the presence of the safety cue, but equal danger expectancies during exposure to the danger cue. Such results link PD to impaired discrimination learning, reflecting elevated fear responding to learned safety cues.     

Applying linear systems analysis to dynamic behavior

In this paper we present an abbreviated discussion of the linear systems analysis in the time domain. We then consider the qualitative character of the behavioral dynamics predicted using the linear form of the analysis. The analysis is then extended to a second-order form. We illustrate some relevant new features introduced by the second-order form with a special case example.     

The linear system theory's account of behavior maintained by variable-ratio schedules.

The mathematical theory of linear systems, which has been used successfully to describe behavior maintained by variable-interval schedules, is extended to describe behavior maintained by variable-ratio schedules. The result of the analysis is a pair of equations, one of which expresses response rate on a variable-ratio schedule as a function of the mean ratio requirement (n) that the schedule arranges. The other equation expresses response rate on a variable-ratio schedule as a function of reinforcement rate. Both equations accurately describe existing data from variable-ratio schedules. The theory accounts for two additional characteristics of behavior maintained by variable-ratio schedules; namely, the appearance of strained, two-valued (i.e., zero or very rapid) responding at large ns, and the abrupt cessation of responding at a boundary n. The theory also accounts for differences between behavior on variable-interval and variable-ratio schedules, including (a) the occurrence of strained responding on variable-ratio but not on variable-interval schedules, (b) the abrupt cessation of responding on occurrence of higher response rates on variable-ratio than on variable-interval schedules. Furthermore, given data from a series of variable-interval schedules and from a series of concurrent variable-ratio variable-interval schedules, the theory permits quantitative prediction of many properties of behavior on single-alternative variable-ratio schedules. The linear system theory's combined account of behavior on variable-interval and variable-ratio schedules is superior to existing versions of six other mathematical theories of variable-interval and variable-ratio responding.