Performance of African elephants (Loxodonta africana) and California sea lions (Zalophus californianus) on a two-choice object discrimination task

This study documents the ability of African elephants (Loxodonta africana) and California sea lions (Zalophus californianus) to perform a two-choice object discrimination task. Both species were able to perform this task. However, California sea lions took fewer trials overall to reach a criterion of 10 consecutively correct responses than did African elephants. The performance of California sea lions did not change significantly during this study. However, African elephants showed a gradual learning of the task, as exhibited by a gradual decrease in the number of trials needed to reach criterion. This performance difference may reflect differences in either visual abilities or cognitive functioning, which in turn may be influenced by either different evolutionary pressures exerted on herbivores and carnivores, or by the context in which visual information is used in the lives of these animals. © 1994 Wiley-Liss, Inc.     

Integral equation models for endemic infectious diseases

Summary Endemic infectious diseases for which infection confers permanent immunity are described by a system of nonlinear Volterra integral equations of convolution type. These constant-parameter models include vital dynamics (births and deaths), immunization and distributed infectious period. The models are shown to be well posed, the threshold criteria are determined and the asymptotic behavior is analysed. It is concluded that distributed delays do not change the thresholds and the asymptotic behaviors of the models.This work was partially supported by NIH Grant AI 13233.     

Information processing in miniature brains

Since a comprehensive understanding of brain function and evolution in vertebrates is often hobbled by the sheer size of the nervous system, as well as ethical concerns, major research efforts have been made to understand the neural circuitry underpinning behaviour and cognition in invertebrates, and its costs and benefits under natural conditions. This special feature of Proceedings of the Royal Society B contains an idiosyncratic range of current research perspectives on neural underpinnings and adaptive benefits (and costs) of such diverse phenomena as spatial memory, colour vision, attention, spontaneous behaviour initiation, memory dynamics, relational rule learning and sleep, in a range of animals from marine invertebrates with exquisitely simple nervous systems to social insects forming societies with many thousands of individuals working together as a 'superorganism'. This introduction provides context and history to tie the various approaches together, and concludes that there is an urgent need to understand the full neuron-to-neuron circuitry underlying various forms of information processing-not just to explore brain function comprehensively, but also to understand how (and how easily) cognitive capacities might evolve in the face of pertinent selection pressures. In the invertebrates, reaching these goals is becoming increasingly realistic.     

Integrating ecology,psychology and neurobiology within a food-hoarding paradigm

Many animals regularly hoard food for future use, which appears to be an important adaptation to a seasonally and/or unpredictably changing environment. This food-hoarding paradigm is an excellent example of a natural system that has broadly influenced both theoretical and empirical work in the field of biology. The food-hoarding paradigm has played a major role in the conceptual framework of numerous fields from ecology (e.g. plant–animal interactions) and evolution (e.g. the coevolution of caching, spatial memory and the hippocampus) to psychology (e.g. memory and cognition) and neurobiology (e.g. neurogenesis and the neurobiology of learning and memory). Many food-hoarding animals retrieve caches by using spatial memory. This memory-based behavioural system has the inherent advantage of being tractable for study in both the field and laboratory and has been shaped by natural selection, which produces variation with strong fitness consequences in a variety of taxa. Thus, food hoarding is an excellent model for a highly integrative approach to understanding numerous questions across a variety of disciplines. Recently, there has been a surge of interest in the complexity of animal cognition such as future planning and episodic-like-memory as well as in the relationship between memory, the environment and the brain. In addition, new breakthroughs in neurobiology have enhanced our ability to address the mechanisms underlying these behaviours. Consequently, the field is necessarily becoming more integrative by assessing behavioural questions in the context of natural ecological systems and by addressing mechanisms through neurobiology and psychology, but, importantly, within an evolutionary and ecological framework. In this issue, we aim to bring together a series of papers providing a modern synthesis of ecology, psychology, physiology and neurobiology and identifying new directions and developments in the use of food-hoarding animals as a model system.     

Views and opinion on BDNF as a target for diabetic cognitive dysfunction

Type 2 diabetes mellitus (T2DM) is a known cause of cognitive dysfunction and involves increased risk of dementia. Brain-derivedneurotrophic factor (BDNF) is a member of neurotrophic family of nerve growth factors, a key protein in promoting memory,growth and survival of neurons. BDNF is recognized as a metabotrophic factor, a molecule that is involved in Alzheimer’s disease(AD) as well as in other neurological disorders. It provides cellular and local regulatory mechanisms for mediating synapticplasticity. Impaired BDNF signaling can compromise many aspects of brain functions. Studies investigating the relationshipbetween diabetes and BDNF in adults demonstrate that BDNF levels are decreased in T2DM and are regulated in response toplasma levels of glucose. BDNF could serve as biomarker in predicting the development of obesity and T2DM. Thirty-two cavitieswere predicted to locate the active sites of BDNF for the ligands to bind. The shape of the site was identified by extracting thecavity volume surfaces enclosing regions with highest probability. Different ligands can be chosen for interaction of active sites ofBDNF and can be targeted for drug discovery. This review focuses on computational exploitation selectively to deliver BDNF as adrug to appropriate hypothalamic neurons, which can serve as a novel approach in diabetic encephalopathy treatment.