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Conceptualising the Impact of Arousal and Affective State on Training Outcomes of Operant Conditioning.

Starling MJ, Branson N, Cody D, McGreevy PD - Animals (Basel) (2013)

Bottom Line: It provides a series of three-dimensional conceptual graphs as exemplars to describing putative influences of both affective state and arousal on the likelihood of dogs and horses performing commonly desired behaviours.These graphs are referred to as response landscapes, and they highlight the flexibility available for improving training efficacy and the likely need for different approaches to suit animals in different affective states and at various levels of arousal.Knowledge gaps are discussed and suggestions made for bridging them.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Veterinary Science, University of Sydney, Sydney NSW 2006, Australia. mjstarling@fastmail.com.au.

ABSTRACT
Animal training relies heavily on an understanding of species-specific behaviour as it integrates with operant conditioning principles. Following on from recent studies showing that affective states and arousal levels may correlate with behavioural outcomes, we explore the contribution of both affective state and arousal in behavioural responses to operant conditioning. This paper provides a framework for assessing how affective state and arousal may influence the efficacy of operant training methods. It provides a series of three-dimensional conceptual graphs as exemplars to describing putative influences of both affective state and arousal on the likelihood of dogs and horses performing commonly desired behaviours. These graphs are referred to as response landscapes, and they highlight the flexibility available for improving training efficacy and the likely need for different approaches to suit animals in different affective states and at various levels of arousal. Knowledge gaps are discussed and suggestions made for bridging them.

No MeSH data available.


Related in: MedlinePlus

A breakdown of the conceptual response landscape for training a dog to heel on leash, showing each operant training quadrant on a separate graph.
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animals-03-00300-f001: A breakdown of the conceptual response landscape for training a dog to heel on leash, showing each operant training quadrant on a separate graph.

Mentions: Figure 1 shows a breakdown of the response landscape for training heeling on leash in dogs, displaying individual response landscapes for each operant training approach. In the figure, the y-axis tracks the possible probability of a dog heeling on leash depending on the dog’s affective (z-axis) and arousal states (x-axis), both of which are shown on a simple, representative scale of 0–10, where 0 is low arousal and a very negative affective state and 10 is high arousal and a very positive affective state, respectively. Figure 1(a) shows the positive reinforcement response landscape, characterised by high probabilities of the dog heeling on leash, peaking at moderate arousal where arousal matches the required activity level, and positive affective state where the dog may be most attentive to opportunities to access reinforcers. Figure 1(b) shows the negative reinforcement landscape, which steadily decreases in efficacy as arousal and affective state values increase. Increased arousal may result in a higher likelihood of behaviours more active than heeling on leash, and more positive affective state may be associated with greater distractibility as the dog attends to stimuli in the environment that may signal access to environmental reinforcers. These conditions may combine to reduce the dog’s attention to negative reinforcement. Figure 1(c) shows the response landscape of negative punishment, which is most effective at high arousal and very positive affective state. In this condition the dog is likely to be attentive to opportunities to access reinforcement, yet may be prone to extraneous behaviour related to an arousal state higher than is appropriate for on-leash heeling. Negative punishment may aid in reducing undesired behaviour while maintaining desired behaviour. Efficacy may decrease with decreased values for arousal and affective state as dogs become more sensitive to reinforcement loss as their affective state declines, and less likely to persist in activities as arousal decreases. Figure 1(d) shows the response landscape for positive punishment. Efficacy is very low where affective state is negative and arousal is low as the dog is less likely to display any behaviours and more likely to be sensitive to punishment. Efficacy increases only at high arousal and very positive affective state where the dog may be more likely to display excessive undesired behaviour that may benefit from strategic suppression. Response landscape graphs may be accessed in interactive form at the following URL: http://hdl.handle.net/2123/8989.


Conceptualising the Impact of Arousal and Affective State on Training Outcomes of Operant Conditioning.

Starling MJ, Branson N, Cody D, McGreevy PD - Animals (Basel) (2013)

A breakdown of the conceptual response landscape for training a dog to heel on leash, showing each operant training quadrant on a separate graph.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4494394&req=5

animals-03-00300-f001: A breakdown of the conceptual response landscape for training a dog to heel on leash, showing each operant training quadrant on a separate graph.
Mentions: Figure 1 shows a breakdown of the response landscape for training heeling on leash in dogs, displaying individual response landscapes for each operant training approach. In the figure, the y-axis tracks the possible probability of a dog heeling on leash depending on the dog’s affective (z-axis) and arousal states (x-axis), both of which are shown on a simple, representative scale of 0–10, where 0 is low arousal and a very negative affective state and 10 is high arousal and a very positive affective state, respectively. Figure 1(a) shows the positive reinforcement response landscape, characterised by high probabilities of the dog heeling on leash, peaking at moderate arousal where arousal matches the required activity level, and positive affective state where the dog may be most attentive to opportunities to access reinforcers. Figure 1(b) shows the negative reinforcement landscape, which steadily decreases in efficacy as arousal and affective state values increase. Increased arousal may result in a higher likelihood of behaviours more active than heeling on leash, and more positive affective state may be associated with greater distractibility as the dog attends to stimuli in the environment that may signal access to environmental reinforcers. These conditions may combine to reduce the dog’s attention to negative reinforcement. Figure 1(c) shows the response landscape of negative punishment, which is most effective at high arousal and very positive affective state. In this condition the dog is likely to be attentive to opportunities to access reinforcement, yet may be prone to extraneous behaviour related to an arousal state higher than is appropriate for on-leash heeling. Negative punishment may aid in reducing undesired behaviour while maintaining desired behaviour. Efficacy may decrease with decreased values for arousal and affective state as dogs become more sensitive to reinforcement loss as their affective state declines, and less likely to persist in activities as arousal decreases. Figure 1(d) shows the response landscape for positive punishment. Efficacy is very low where affective state is negative and arousal is low as the dog is less likely to display any behaviours and more likely to be sensitive to punishment. Efficacy increases only at high arousal and very positive affective state where the dog may be more likely to display excessive undesired behaviour that may benefit from strategic suppression. Response landscape graphs may be accessed in interactive form at the following URL: http://hdl.handle.net/2123/8989.

Bottom Line: It provides a series of three-dimensional conceptual graphs as exemplars to describing putative influences of both affective state and arousal on the likelihood of dogs and horses performing commonly desired behaviours.These graphs are referred to as response landscapes, and they highlight the flexibility available for improving training efficacy and the likely need for different approaches to suit animals in different affective states and at various levels of arousal.Knowledge gaps are discussed and suggestions made for bridging them.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Veterinary Science, University of Sydney, Sydney NSW 2006, Australia. mjstarling@fastmail.com.au.

ABSTRACT
Animal training relies heavily on an understanding of species-specific behaviour as it integrates with operant conditioning principles. Following on from recent studies showing that affective states and arousal levels may correlate with behavioural outcomes, we explore the contribution of both affective state and arousal in behavioural responses to operant conditioning. This paper provides a framework for assessing how affective state and arousal may influence the efficacy of operant training methods. It provides a series of three-dimensional conceptual graphs as exemplars to describing putative influences of both affective state and arousal on the likelihood of dogs and horses performing commonly desired behaviours. These graphs are referred to as response landscapes, and they highlight the flexibility available for improving training efficacy and the likely need for different approaches to suit animals in different affective states and at various levels of arousal. Knowledge gaps are discussed and suggestions made for bridging them.

No MeSH data available.


Related in: MedlinePlus