Community structure and dynamics of Monogenea and Trematoda in three North American cyprinid species in the Salt Valley Watershed, Nebraska.

An investigation was made of the communities of gill monogene genus Dactylogyrus (Platyhelminthes, Monogenea) and the populations of blackspot parasite (Platyhelminthes, Trematoda) of Pimephales promelas, Notropis stramineus, and Semotilus atromaculatus in 3 distinct sites along the 3 converging tributaries in southeastern Nebraska from 2004 to 2006. This work constitutes the first multi-site, multi-year study of a complex community of Dactylogyrus spp. and their reproductive activities on native North American cyprinid species. The biological hypothesis that closely related species with direct lifecycles respond differently to shared environmental conditions was tested. It was revealed that in this system that, Cyprinid species do not share Dactylogyrus species, host size and sex are not predictive of infection, and Dactylogyrus community structure is stable, despite variation in seasonal occurrence and populations among sites. The biological hypothesis that closely related species have innate differences in reproductive activities that provide structure to their populations and influence their roles in the parasite community was tested. It was revealed that in this system, host size, sex, and collection site are not predictive of reproductive activities, that egg production is not always continuous and varies in duration among congeners, and that recruitment of larval Dactylogyrus is not continuous across parasites’ reproductive periods. Hatch timing and host availability, not reproductive timing, are the critical factors determining population dynamics of the gill monogenes in time and space. Lastly, the biological hypothesis that innate blackspot biology is responsible for parasite host-specificity, host recruitment strategies and parasite population structure was tested. Field collections revealed that for blackspot, host size, sex, and collection month and year are not predictive of infection, that parasite cysts survive winter, and that host movement is restricted among the 3 collection sites. Finally, experimental infections of hosts with cercaria isolated from 1st intermediate snail hosts reveal that cercarial biology, not environmental circumstances, are responsible for differences in infection among hosts.

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.