Comparison of Endocrine Response to Stress Between Captive-Raised and Wild-Caught Bighorn Sheep

Stress hormones in Rocky Mountain bighorn sheep (Ovis canadensis canadensis), produced in response to environmental changes, road development, or high population density, may impact their immune systems to a threshold level that predisposes them to periodic, large-scale mortality. We compared the stress response to a novel environmental situation and repeated handling between bighorn sheep born and raised in captivity (CR) and bighorn sheep born in the wild (WC) and brought into captivity. We measured plasma epinephrine, norepinephrine, cortisol, and fecal glucocorticoid metabolites (FGM). Three weeks after each group’s arrival we used a one-time drop-net event to elicit an acute stress response, and we collected blood samples from each sheep over 35 minutes, as well as one fecal sample. We collected blood and fecal samples from both groups on 7 other occasions over the subsequent 6 months. We also collected fecal samples from the pen at approximately 24-hour intervals for 3 days following every handling event to monitor the stress response to handling. We found that CR sheep had a stronger autonomic nervous system response than WC sheep, as measured by epinephrine and norepinephrine levels, but we found a very similar hypothalamic–pituitary–adrenal axis (HPA) response, measured by cortisol levels, to the acute stress event of a drop-net restraint. We also found that once the WC sheep had acclimated, as indicated by the return to the initial baseline FGM levels within 12 weeks, the CR and WC groups’ HPA responses to sampling events were not significantly different from one another. Fecal samples can provide a noninvasive mechanism for managers to monitor baseline FGM for a given herd. Using long-term monitoring of FGM rather than values from a single point in time may allow managers to correlate these levels to outside influences on the herd and better understand the impacts of management changes, population density, or increased human developments on the health of the sheep population.

Measuring Success One Student At A Time

This presentation describes Murray State University's proactive efforts to enhance African¬-American students' preparation, recruitment/retention and graduation. Strategies utilized to create and maintain a positive/hospitable campus environment will be delineated. It is our campus-wide responsibility to "nurture" each student with personalized contact and carefully selected services to engender degree persistence.

Generalizing the dynamic field theory of spatial cognition across real and developmental time scales

Within cognitive neuroscience, computational models are designed to provide insights into the organization of behavior while adhering to neural principles. These models should provide sufficient specificity to generate novel predictions while maintaining the generality needed to capture behavior across tasks and/or time scales. This paper presents one such model, the Dynamic Field Theory (DFT) of spatial cognition, showing new simulations that provide a demonstration proof that the theory generalizes across developmental changes in performance in four tasks—the Piagetian A-not-B task, a sandbox version of the A-not-B task, a canonical spatial recall task, and a position discrimination task. Model simulations demonstrate that the DFT can accomplish both specificity—generating novel, testable predictions—and generality—spanning multiple tasks across development with a relatively simple developmental hypothesis. Critically, the DFT achieves generality across tasks and time scales with no modification to its basic structure and with a strong commitment to neural principles. The only change necessary to capture development in the model was an increase in the precision of the tuning of receptive fields as well as an increase in the precision of local excitatory interactions among neurons in the model. These small quantitative changes were sufficient to move the model through a set of quantitative and qualitative behavioral changes that span the age range from 8 months to 6 years and into adulthood. We conclude by considering how the DFT is positioned in the literature, the challenges on the horizon for our framework, and how a dynamic field approach can yield new insights into development from a computational cognitive neuroscience perspective.