Biomedical subjects

BJ Tolkamp

Publications and source records attributed to BJ Tolkamp.

3 recordsLinked to original sources

PubMed1999

To split behaviour into bouts, log-transform the intervals.

Analysis of behaviour that is displayed in bouts depends crucially on quantitative estimates of bout criteria, that is, the lengths of the shortest intervals between bouts. Current methods estimate bout criteria by modelling the log-transformed (cumulative) frequency distributions of intervals between events. For analysis of feeding behaviour, these models will not result in biologically meaningful quantitative estimates (Tolkamp et al. 1998, Journal of Theoretical Biology194, 235-250). We proposed a method that models the frequency distribution of log-transformed interval lengths instead. Applying this method to a single data set showed that the log-transformed lengths of intervals between feeding events were distributed as two Gaussians. Here we test this model using a data set of 35 171 intervals between feeding that was obtained during an experiment with 38 cows in three dietary treatment groups. No meaningful bout criterion could be obtained for some individuals, which casts doubt on the general validity of the proposed model. Addition of a third log-normal improved the fit of the model and we hypothesized that this third population represents intervals including drinking. In a second experiment, we found the measurements to be consistent with this hypothesis. We obtained meaningful meal criteria for all individuals by fitting either a double, or a triple, log-normal model to the frequency distributions of the lengths of intervals between feeding. These log-normal models appear to be not only more biologically meaningful than log (cumulative) frequency models but also far more flexible. Copyright 1999 The Association for the Study of Animal Behaviour.

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PubMed1998

Satiety splits feeding behaviour into bouts

Animal behaviour is frequently displayed in bouts. Bout analysis aims at finding a bout criterion, i.e. that time between events that separates intervals within, from intervals between, bouts. Methods used for quantitative bout analysis are log-supervivorship and log-frequency analysis. Both models assume that the probability of the start of an event (or a bout) is independent of the time since the last event (or bout) and that, therefore, events as well as bouts occur according to Poisson processes, i.e. purely at random. The frequencies of intervals within, as well as between, bouts are then distributed as negative exponentials. These models are also widely applied in feeding behaviour analysis, where bouts can be meals. However, the satiety concept predicts that after terminating a meal, the animal's feeding motivation will be low. The probability of the animal initiating the next meal is expected to increase with time since the last meal and, therefore, meals will not likely be randomly distributed. A negative exponential is then not the most appropriate model to describe the frequency distribution of intervals between meals. Results of an experiment in which feeding behaviour of 16 cows was recorded continuously for 30 days were used to test the suitability of existing bout analysis techniques. It is concluded that these techniques are inadequate for the description of the observed interval distributions. A new model is proposed that takes account of the observed "shortage" of short intervals between meals. In contrast to existing models, that describe log-transformed frequency distributions of interval lengths, the proposed model describes frequency distributions of log-transformed interval lengths. Compared with existing models, this log-normal model is in better agreement with the biological phenomenon of satiety, it gave a better fit to the observed interval distribution and led to a more meaningful meal criterion.Copyright 1998 Academic Press Limited

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PubMed1998

Towards a functional explanation for the occurrence of anorexia during parasitic infections.

The development and occurrence of anorexia, the voluntary reduction in food intake during parasitic infections in animals, is somewhat paradoxical and contrary to conventional wisdom and expectation. We take the view that its occurrence is an evolved, costly behavioural adaptation which serves a function. Five such functional and general hypotheses to account for it are developed: (1) anorexia is induced by the parasite for its own benefit; (2) food intake decreases to starve parasites; (3) the negative effect on the host's energetic efficiency during parasitic diseases has a direct effect on food consumption; (4) food intake decreases for the purpose of promoting an effective immune response in the host; and (5) anorexia allows the host to become more selective in its diet, and thus select foods that either minimize the risk of infection or are high in antiparasitic compounds. Only hypotheses (4) and (5) survive the comparison for consistency with the physiological, metabolic and behavioural alterations that occur during the development of parasitic infections, and with the rule of generality (i.e. account for its occurrence in both protozoan and helminth infections). Both surviving hypotheses will need further experimental testing for their support or rejection, and such experiments are proposed. Also, the advantages and consequences of viewing anorexia during parasitic infections within a functional framework are discussed. These arise from the recognition that anorexia is a disease-coping strategy, part of the mechanism of recognition of parasite invasion by the immune system, which leads to a modification of the host's feeding behaviour. Copyright 1998 The Association for the Study of Animal Behaviour

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