A behavior systems view of the organization of multiple responses during a partially or continuously reinforced interfood clock

Space, time, and context drive anticipatory behavior: Considerations for understanding the behavior of animals in human care

Animal-based measures reflecting the welfare state of individuals are critical for ensuring the well-being of animals under human care. Anticipatory behavior is one potential animal-based measure that has gained traction in recent years, as it is theorized to relate to animals' reward sensitivity. It is of particular interest as an assessment for animals living under human care, as the predictability of the captive environment lends itself to the development of this class of behaviors. Animals are likely to exhibit anticipation in locations related to the anticipated event, often in temporally predictable time frames, and before specific contexts they experience in their day-to-day management. In this sense and under certain circumstances, anticipatory behaviors are likely to drive observed behavioral or space use patterns of animals under human care. Drawing conclusions from such data without identifying anticipation may result in misleading conclusions. Here we discuss how space, time, and context are related to patterns of anticipatory behaviors in animals under human care, how unidentified anticipation may alter conclusions regarding animal behavior or welfare under certain circumstances.

Children's perception of emotions in the context of live interactions: Eye movements and emotion judgements

Research examining children's understanding of emotional expressions has generally used static, isolated facial expressions presented in a non-interactive context. However, these tasks do not resemble children's experiences with expressions in daily life, where they must attend to a range of information, including others' facial expressions, movements, and the situation surrounding the expression. In this research, we examine the development of visual attention to another's emotional expressions during a live interaction. Via an eye-tracker, children (4-11 years old) and adults viewed an experimenter open a series of opaque boxes and make an expression (happiness, sadness, fear, or disgust) based on the object inside. Participants determined which of four possible objects (stickers, a broken toy, a spider, or dog poop) was in the box. We examined the proportion of the trial in which participants looked to three areas of the face (the eyes, mouth, and nose area), and the available contextual information (the box held by the experimenter, the four objects). Although children spent less time looking to the face than adults did, their pattern of visual attention within the face and to object AOIs did not differ from that of adults. Finally, for adults, increased accuracy was linked to spending less time looking to the objects whereas increased accuracy for children was not strongly linked to any emotion cue. These data indicate that although children spend less time looking to the face during live interactions than adults do, the proportion of time spent looking to areas of the face and context are generally adult-like.

Do rats learn conditional independence?

If acquired associations are to accurately represent real relevance relations, there is motivation for the hypothesis that learning will, in some circumstances, be more appropriately modelled, not as direct dependence, but as conditional independence. In a serial compound conditioning experiment, two groups of rats were presented with a conditioned stimulus (CS1) that imperfectly (50%) predicted food, and was itself imperfectly predicted by a CS2. Groups differed in the proportion of CS2 presentations that were ultimately followed by food (25% versus 75%). Thus, the information presented regarding the relevance of CS2 to food was ambiguous between direct dependence and conditional independence (given CS1). If rats learnt that food was conditionally independent of CS2, given CS1, subjects of both groups should thereafter respond similarly to CS2 alone. Contrary to the conditionality hypothesis, subjects attended to the direct food predictability of CS2, suggesting that rats treat even distal stimuli in a CS sequence as immediately relevant to food, not conditional on an intermediate stimulus. These results urge caution in representing indirect associations as conditional associations, accentuate the theoretical weight of the Markov condition in graphical models, and challenge theories to articulate the conditions under which animals are expected to learn conditional associations, if ever.

A Kinect-based system for automatic recording of some pigeon behaviors

Contact switches and touch screens are the state of the art for recording pigeons' pecking behavior. Recording other behavior, however, requires a different sensor for each behavior, and some behaviors cannot easily be recorded. We present a flexible and inexpensive image-based approach to detecting and counting pigeon behaviors that is based on the Kinect sensor from Microsoft. Although the system is as easy to set up and use as the standard approaches, it is more flexible because it can record behaviors in addition to key pecking. In this article, we show how both the fast, fine motion of key pecking and the gross body activity of feeding can be measured. Five pigeons were trained to peck at a lighted contact switch, a pigeon key, to obtain food reward. The timing of the pecks and the food reward signals were recorded in a log file using standard equipment. The Kinect-based system, called BehaviorWatch, also measured the pecking and feeding behavior and generated a different log file. For key pecking, BehaviorWatch had an average sensitivity of 95% and a precision of 91%, which were very similar to the pecking measurements from the standard equipment. For detecting feeding activity, BehaviorWatch had a sensitivity of 95% and a precision of 97%. These results allow us to demonstrate that an advantage of the Kinect-based approach is that it can also be reliably used to measure activity other than key pecking.

Time to rethink the neural mechanisms of learning and memory

Most studies in the neurobiology of learning assume that the underlying learning process is a pairing - dependent change in synaptic strength that requires repeated experience of events presented in close temporal contiguity. However, much learning is rapid and does not depend on temporal contiguity, which has never been precisely defined. These points are well illustrated by studies showing that the temporal relations between events are rapidly learned- even over long delays- and that this knowledge governs the form and timing of behavior. The speed with which anticipatory responses emerge in conditioning paradigms is determined by the information that cues provide about the timing of rewards. The challenge for understanding the neurobiology of learning is to understand the mechanisms in the nervous system that encode information from even a single experience, the nature of the memory mechanisms that can encode quantities such as time, and how the brain can flexibly perform computations based on this information.

Acquisition of "Start" and "Stop" response thresholds in peak-interval timing is differentially sensitive to protein synthesis inhibition in the dorsal and ventral striatum

Time-based decision-making in peak-interval timing procedures involves the setting of response thresholds for the initiation (“Start”) and termination (“Stop”) of a response sequence that is centered on a target duration. Using intracerebral infusions of the protein synthesis inhibitor anisomycin, we report that the acquisition of the “Start” response depends on normal functioning (including protein synthesis) in the dorsal striatum (DS), but not the ventral striatum (VS). Conversely, disruption of the VS, but not the DS, impairs the acquisition of the “Stop” response. We hypothesize that the dorsal and ventral regions of the striatum function as a competitive neural network that encodes the temporal boundaries marking the beginning and end of a timed response sequence.

Time and Associative Learning

In a basic associative learning paradigm, learning is said to have occurred when the conditioned stimulus evokes an anticipatory response. This learning is widely believed to depend on the contiguous presentation of conditioned and unconditioned stimulus. However, what it means to be contiguous has not been rigorously defined. Here we examine the empirical bases for these beliefs and suggest an alternative view based on the hypothesis that learning about the temporal relationships between events determines the speed of emergence, vigor and form of conditioned behavior. This temporal learning occurs very rapidly and prior to the appearance of the anticipatory response. The temporal relations are learned even when no anticipatory response is evoked. The speed with which an anticipatory response emerges is proportional to the informativeness of the predictive cue (CS) regarding the rate of occurrence of the predicted event (US). This analysis gives an account of what we mean by "temporal pairing" and is in accord with the data on speed of acquisition and basic findings in the cue competition literature. In this account, learning depends on perceiving and encoding temporal regularities rather than stimulus contiguities.

Timing and anticipation: conceptual and methodological approaches

Anticipation occurs on timescales ranging from milliseconds to hours to days. This paper relates the theoretical and methodological developments in the study of interval timing in the seconds, minutes and hours range to research on the anticipatory activity induced by regularly timed daily meals. Daily food-anticipatory activity (FAA) is entrained by procedures which are formally identical to procedures studied in Pavlovian and operant conditioning except for the long duration of the interval between feeding opportunities. As in FAA, the conditioning procedures induce orderly anticipatory activity in advance of food presentation. During the interval between foods the behaviors that express anticipation change as the interval progresses. Consequently, no single response represents a pure measure of anticipation. The ability to distinguish between properties of general anticipatory timing mechanisms such as the scalar property (Gibbon, 1977) and dynamic properties of specific response output systems has been facilitated by teaching animals to use arbitrary anticipatory responses like bar-pressing to obtain food. Interval timing research highlights the importance of identifying the mechanisms of perception, memory, decision making and motivation that all contribute to food anticipation. We suggest that future work focused on the similarities and differences in the neural bases of FAA and interval timing may be useful in unravelling the mechanisms mediating timing behavior.