The importance of ‘memory’ in statistical models for animal feeding behaviour

Allcroft, David J.; Tolkamp, B.J.; Glasbey, C. A.; Kyriazakis, Ι.

doi:10.1016/j.beproc.2004.03.014

Cited by 12 publications

(8 citation statements)

References 28 publications

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“…Clustering feeding into meals has been observed in many species (Tolkamp et al, 2011b) and thus cannot be overlooked (Musial et al, 1999;Allcroft et al, 2004;Zorrilla et al, 2005). Feeding visits give a closer representation of the true feeding duration, while during a meal an animal is thought to be still 'busy with the concept of eating', even when it's not actually feeding.…”

Section: Meal Criterionmentioning

confidence: 99%

Review: Quantifying animal feeding behaviour with a focus on pigs

Maselyne

Saeys

Nuffel³

2015

Physiology & Behavior

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The study of animal feeding behaviour is of interest to understand feeding, to investigate the effect of treatments and conditions or to predict illness. This paper reviews the different steps to undertake when studying animal feeding behaviour, with illustrations for group-housed pigs. First, one must be aware of the mechanisms that control feeding and the various influences that can change feeding behaviour. Satiety is shown to largely influence free feeding (ad libitum and without an operant condition) in animals, but 'free' feeding seems a very fragile process, given the many factors that can influence feeding behaviour. Second, a measurement method must be chosen that is compatible with the goal of the research. Several measurement methods exist, which lead to different experimental set-ups and measurement data. Sensors are available for lab conditions, for research on group-housed pigs and also for on-farm use. Most of these methods result in a record of feeding visits. However, these feeding visits are often found to be clustered into meals. Thus, the third step is to choose which unit of feeding behaviour to use for analysis. Depending on the situation, either meals, feeding visits, other raw data, or a combination thereof can be suitable. Meals are more appropriate for analysing short-term feeding behaviour, but this may not be true for disease detection. Further research is therefore needed. To cluster visits into meals, an appropriate analysis method has to be selected. The last part of this paper provides a review and discussion of the existing methods for meal determination. A variety of methods exist, with the most recent methods based on the influence of satiety on feeding. More thorough validation of the recent methods, including validation from a behavioural point of view and uniformity in the applied methods is therefore necessary.

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Section: Meal Criterionmentioning

confidence: 99%

Review: Quantifying animal feeding behaviour with a focus on pigs

Maselyne

Saeys

Nuffel³

2015

Physiology & Behavior

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“…These characteristics of foraging behavior were reflected in a bimodal inter-choice interval (ICI) distribution comprised of a power-law for the short timescale (i.e., short ICIs) and the Weibull distribution for the longer timescale (i.e., longer ICIs). Although the specific mechanisms of the bimodal inter-event times could vary across different systems [9], [10], [14], [24], [25], [74], [75], a common dynamical feature of the underlying mechanisms appears to be the combination of distinct processes at different timescales [14], [25], [37]. To capture the temporal dynamics underlying foraging behavior, we propose a dual-state model consisting of active and inactive states for short and longer timescales based on a satiation-attainment process for bursty activity in the active states, and a non-homogeneous Poisson process for longer inactivity between bursts in the inactive states.…”

Section: Discussionmentioning

confidence: 99%

Bursts and Heavy Tails in Temporal and Sequential Dynamics of Foraging Decisions

et al. 2014

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A fundamental understanding of behavior requires predicting when and what an individual will choose. However, the actual temporal and sequential dynamics of successive choices made among multiple alternatives remain unclear. In the current study, we tested the hypothesis that there is a general bursting property in both the timing and sequential patterns of foraging decisions. We conducted a foraging experiment in which rats chose among four different foods over a continuous two-week time period. Regarding when choices were made, we found bursts of rapidly occurring actions, separated by time-varying inactive periods, partially based on a circadian rhythm. Regarding what was chosen, we found sequential dynamics in affective choices characterized by two key features: (a) a highly biased choice distribution; and (b) preferential attachment, in which the animals were more likely to choose what they had previously chosen. To capture the temporal dynamics, we propose a dual-state model consisting of active and inactive states. We also introduce a satiation-attainment process for bursty activity, and a non-homogeneous Poisson process for longer inactivity between bursts. For the sequential dynamics, we propose a dual-control model consisting of goal-directed and habit systems, based on outcome valuation and choice history, respectively. This study provides insights into how the bursty nature of behavior emerges from the interaction of different underlying systems, leading to heavy tails in the distribution of behavior over time and choices.

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“…We investigated for each species whether log e -transformation of interval lengths would lead to distributions as seen in dairy cows and, therefore, allow applications of models in Eqs. [3][4][5][6][7][8] to estimate meal criteria. A double log-normal could be fitted to the frequency distribution of the lengths of between-feeding intervals observed in dolphin calves (Fig.…”

Section: Frequency Distributions Of Between-feeding Interval Lengthsmentioning

confidence: 99%

The temporal structure of feeding behavior

Tolkamp

Allcroft

Barrio

et al. 2011

American Journal of Physiology-Regulatory, Integrative and Comp

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Meals have long been considered relevant units of feeding behavior. Large data sets of feeding behavior of cattle, pigs, chickens, ducks, turkeys, dolphins, and rats were analyzed with the aims of 1) describing the temporal structure of feeding behavior and 2) developing appropriate methods for estimating meal criteria. Longer (between-meal) intervals were never distributed as the negative exponential assumed by traditional methods, such as log-survivorship analysis, but as a skewed Gaussian, which can be (almost) normalized by log-transformation of interval lengths. Log-transformation can also normalize frequency distributions of within-meal intervals. Meal criteria, i.e., the longest interval considered to occur within meals, can be estimated after fitting models consisting of Gaussian functions alone or of one Weibull and one or more Gaussian functions to the distribution of log-transformed interval lengths. Nonuniform data sets may require disaggregation before this can be achieved. Observations from all species were in conflict with assumptions of random behavior that underlie traditional methods for criteria estimation. Instead, the observed structure of feeding behavior is consistent with 1) a decrease in satiety associated with an increase in the probability of animals starting a meal with time since the last meal and 2) an increase in satiation associated with an increase in the probability of animals ending a meal with the amount of food already consumed. The novel methodology proposed here will avoid biased conclusions from analyses of feeding behavior associated with previous methods and, as demonstrated, can be applied across a range of species to address questions relevant to the control of food intake.

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The importance of ‘memory’ in statistical models for animal feeding behaviour

Cited by 12 publications

References 28 publications

Review: Quantifying animal feeding behaviour with a focus on pigs

Review: Quantifying animal feeding behaviour with a focus on pigs

Bursts and Heavy Tails in Temporal and Sequential Dynamics of Foraging Decisions

The temporal structure of feeding behavior

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