Spatial Learning and Memory in Animal Models and Humans

Neuromethods, 1, Volume 50, Animal Models of Behavioral Analysis, Pages 91-109

Gwendolen E. Haley and Jacob Raber

“Spatial learning and memory requiring navigation has been widely assessed as a part of traditional rodent cognitive testing. Significantly fewer studies have examined spatial learning and memory requiring navigation in nonhuman primates and humans. While rodent spatial tasks utilize navigation and an allocentric frame of reference, nonhuman primate and human spatial tasks often utilize an egocentric frame of reference, lacking a navigational component. Due to this difference, cross species comparisons cannot be easily made. In rodent models, both spatial learning and memory and object recognition tasks requiring navigation are used to assess hippocampus-dependent learning and memory. Furthermore, addition of a spatial component to the traditional object recognition task in the mouse and human model has increased the sensitivity of the task to detect cognitive changes. Based on hippocampus-dependent cognitive tests used in our mouse studies, we developed spatial learning and memory tests requiring navigation for nonhuman primates (Spatial Foodport Maze) and humans (Memory Island) as well as the object recognition test Novel Image Novel Location (NINL) for humans. Here, we discuss these translational cognitive tests that are being used to bridge the gap between object recognition and spatial learning and memory tasks across species.”

Python based GIS Tools for Landscape Genetics: Visualising Genetic Relatedness and Measuring Landscape Connectivity

Methods in Ecology and Evolution, Volume 2, Issue 1, pages 52–55, January 2011

Thomas R. Etherington

“Summary

“1. Landscape genetics is an area of research that can help to understand many spatial ecological processes, but requires significant interdisciplinary collaboration. Use of geographic information system (GIS) software is essential, but requires a degree of customisation that is often beyond the non-specialist.

“2. To help address this, a series of Python script based GIS tools have been developed for use in landscape genetics studies.

The test data supplied with the ArcToolbox can be used with a) the Kinship links tool to create lines between sample points which can be symbolised based on the strength of each pair-wise kinship value. This allows for the spatial visualisation of pair-wise relatedness to try and identify genetic patterns in relation to the landscape. From interpretation of the kinship links it is possible to b) assign sensible friction values to the landscape and use the Least-cost path tool to generate a least-cost pathway (LCP) between each pair-wise combination of sample points to see if variation in LCP is correlated to variation in genetic relatedness.

“3.  The scripts convert files, visualise genetic relatedness, and measure landscape connectivity using least-cost path analysis. The scripts are housed in an ArcToolbox that is freely available along with the underlying Python code.

“4. The Python scripts allow researchers to use more current software, provide the option of further development by the user community, and reduce the amount of time that would be spent developing common solutions.”

Mapping the Risk of Anaemia in Preschool-Age Children: The Contribution of Malnutrition, Malaria, and Helminth Infections in West Africa

PLoS Medicine 8(6): e1000438, 07 June 2011

Ricardo J. Soares Magalhães and Archie C. A. Clements

“Background: Childhood anaemia is considered a severe public health problem in most countries of sub-Saharan Africa. We investigated the geographical distribution of prevalence of anaemia and mean haemoglobin concentration (Hb) in children aged 1–4 y (preschool children) in West Africa. The aim was to estimate the geographical risk profile of anaemia accounting for malnutrition, malaria, and helminth infections, the risk of anaemia attributable to these factors, and the number of anaemia cases in preschool children for 2011.

Predictive geographical risk of anaemia in children aged 1–4 y, based on a model-based geostatistical Bernoulli model.

“Methods and Findings: National cross-sectional household-based demographic health surveys were conducted in 7,147 children aged 1–4 y in Burkina Faso, Ghana, and Mali in 2003–2006. Bayesian geostatistical models were developed to predict the geographical distribution of mean Hb and anaemia risk, adjusting for the nutritional status of preschool children, the location of their residence, predicted Plasmodium falciparum parasite rate in the 2- to 10-y age group (Pf PR2–10), and predicted prevalence of Schistosoma haematobium and hookworm infections. In the four countries, prevalence of mild, moderate, and severe anaemia was 21%, 66%, and 13% in Burkina Faso; 28%, 65%, and 7% in Ghana, and 26%, 62%, and 12% in Mali. The mean Hb was lowest in Burkina Faso (89 g/l), in males (93 g/l), and for children 1–2 y (88 g/l). In West Africa, severe malnutrition, Pf PR2–10, and biological synergisms between S. haematobium and hookworm infections were significantly associated with anaemia risk; an estimated 36.8%, 14.9%, 3.7%, 4.2%, and 0.9% of anaemia cases could be averted by treating malnutrition, malaria, S. haematobium infections, hookworm infections, and S. haematobium/hookworm coinfections, respectively. A large spatial cluster of low mean Hb (95%) was predicted for an area shared by Burkina Faso and Mali. We estimate that in 2011, approximately 6.7 million children aged 1–4 y are anaemic in the three study countries.

“Conclusions: By mapping the distribution of anaemia risk in preschool children adjusted for malnutrition and parasitic infections, we provide a means to identify the geographical limits of anaemia burden and the contribution that malnutrition and parasites make to anaemia. Spatial targeting of ancillary micronutrient supplementation and control of other anaemia causes, such as malaria and helminth infection, can contribute to efficiently reducing the burden of anaemia in preschool children in Africa.”