Ordinal Probit Functional Regression Models with Application to Computer-Use Behavior in Rhesus Monkeys

Research in functional regression has made great strides in expanding to non-Gaussian functional outcomes, however the exploration of ordinal functional outcomes remains limited. Motivated by a study of computer-use behavior in rhesus macaques (\emph{Macaca mulatta}), we introduce the Ordinal Probit Functional Regression Model or OPFRM to perform ordinal function-on-scalar regression. The OPFRM is flexibly formulated to allow for the choice of different basis functions including penalized B-splines, wavelets, and O'Sullivan splines. We demonstrate the operating characteristics of the model in simulation using a variety of underlying covariance patterns showing the model performs reasonably well in estimation under multiple basis functions. We also present and compare two approaches for conducting posterior inference showing that joint credible intervals tend to out perform point-wise credible. Finally, in application, we determine demographic factors associated with the monkeys' computer use over the course of a year and provide a brief analysis of the findings

Using Reinforcement-Based Models Of Transitive Inference To Stimulate Primate Data

Olga F. Lazareva (Mentor)The ability of reinforcement-based models to predict transitive inference behavior has been extensively documented. However, most of the research on models of TI has relied on data from pigeons. Pigeons are trained sequentially (first A+ B-, then B+ C-, etc.); the number of stimuli is limited to 5; and correction trials are used during training. In contrast, primates can be trained with 7 stimuli (A to G) introduced simultaneously with no correction trials. Would the models still accurately account for these data? We will present the results of simulations with two configural models of TI (Wynne, 1995; Siemann & Delius, 1998) used to predict transitive choices of rhesus monkeys after successive and simultaneous training in 7-item series task, as well as after a list-linking procedure. Our results suggest that reinforcement-based models do not account for symbolic distance effect after backward training (first F+ G-, then E+ F-, and so on). Surprisingly, the models provide a relatively good fit of list linking data, contrary to common belief that list-linking design presents a challenge for such models.Drake University, Department of Psychology, College of Arts & Science

Monkeys choose, but do not learn, through exclusion

Human children will select a novel object from among a group of known objects when presented with a novel object name. This disambiguation by exclusion may facilitate new name-object mappings and may play a role in the rapid word learning shown by young children. Animals including dogs, apes, monkeys, and birds make similar exclusion choices. However, evidence regarding whether children and nonhuman animals learn new associations through choice by exclusion is mixed. In the present study, we dissociate choice by exclusion from learning by exclusion in rhesus monkeys using a paired-associate task. In Experiment 1, monkeys demonstrated choice by exclusion by choosing a novel comparison image from among known comparison images when presented with a novel sample image. In Experiment 2, monkeys showed little if any benefit from choice by exclusion in learning new sets of paired associates. Monkeys were trained with new sets of four paired associates by trial and error alone or by a combination of exclusion and trial and error. Despite choosing correctly by exclusion on almost 100% of opportunities, monkeys did not learn any faster by exclusion than by trial and error alone. These results indicate that monkeys choose, but do not learn, through exclusion, highlighting the importance of separately evaluating choice and learning in studies of the role of exclusion in word learning

Influences of demographic, seasonal, and social factors on automated touchscreen computer use by rhesus monkeys (Macaca mulatta) in a large naturalistic group.

Animals housed in naturalistic social groups with access to automated cognitive testing vary in whether and how much they participate in cognitive testing. Understanding how demographic, seasonal, and social factors relate to participation is essential to evaluating the usefulness of these systems for studying cognition and in assessing the data produced. We evaluated how sex, age, reproductive experience, seasonality, and rank related to patterns of participation in a naturalistic group of rhesus monkeys over a 4-year period. Females interacted with the touchscreen systems more than males and were more likely to complete initial training. Age was positively correlated with touchscreen activity through adolescence in females, at which point seasonality and reproductive experience were stronger associates of participation. While monkeys in different rank categories did not differ in how much they interacted with the touchscreen systems, monkeys of different ranks tended not to work at the same times, perhaps reflecting avoidance of high ranking animals by those of lower rank. Automated cognitive testing systems for naturalistic social groups of rhesus monkeys can yield quality cognitive data from individuals of all ages and ranks, but participation biases may make it difficult to study sex differences or seasonal variation in cognition