The Persistence of Time

Humans and other animals engage in a startlingly diverse array of behaviors that depend critically on the time of day or the ability to time short intervals. Timing intervals on the scale of many hours to around a day are mediated by the circadian timing system, while in the range of seconds to minutes a different system, known as interval timing, is used. Nonlinearities in the sensitivity to time as well as a dependence on the normal functioning of the suprachiasmatic region of the hypothalamus have been observed for both systems, suggesting a greater degree of commonality between circadian and interval timing than is often appreciated (see Cohen et al., 1997; Crystal, 1999, 2001, this volume; Crystal et al., 1997; Killeen, 2002). Fortunately, recent advances have illuminated some of the functional and neural mechanisms underlying the "internal clocks" of these two different timing systems, including the identification of molecular circuitry associated with circadian and interval timing (see Allada et al., 2001; Blakeslee, 1998; Cevik, this volume; Hills, this volume; Hinton and Meck, 1997b; King et al., 2001; Meck, 2001; Morell, 1996; Travis, 1996; Wright, 2002; as well as the British Broadcasting Company documentary "The Body Clock: What Makes Us Tick?" 1999).

The term interval timing is used to describe the temporal discrimination processes involved in the estimation and reproduction of relatively short durations in the sec-onds-to-minutes range that form the fabric of our everyday existence and unite our mental representations of action sequences and rhythmical structures (e.g., Fraisse, 1963; Gallistel, 1990; Gibbon and Allan, 1984; Krampe et al., 2002; Macar et al., 1992; McAuley and Jones, 2002; Pressing, 1999; Rousseau and Rousseau, 1996). A classic example of interval timing comes from the fixed-interval (FI) procedure in which a subject is reinforced for the first response it makes after a programmed interval has elapsed since the previous reinforcement (Skinner, 1936). Subjects (e.g., primates, rodents, birds, and fish) trained on this procedure typically show what is known as the fixed-interval scallop. This pattern of behavior involves pausing after the delivery of reinforcement and starting to respond after a fixed proportion of the interval has elapsed despite the absence of any external time cues. Interval timing of this type has been identified in the majority of vertebrate animals in which it has been tested for (Richelle and Lejeune, 1980, 1984) and has been shown to be exquisitely sensitive to the effect of neurotoxicants and psychoactive drugs (e.g., Meck, 1996; Paule et al., 1999). The FI procedure gave rise to a discrete trial variant known as the peak-interval (PI) procedure (Catania, 1970; Roberts, 1981), which is now widely used in animal (e.g., Buhusi and Meck, 2000, 2002; Hinton and Meck, 1997a; Liu et al., 2002; Matell and Meck, 1999; Meck, 2000a, 2000b; Meck and Church, 1984; Olton et al., 1988; Ohyama et al., 2000; Pang et al., 2001; Penney et al., 1996)

and human (e.g., Malapani et al., 1998b, 2002; Rakitin et al., 1998) studies of interval timing. In this procedure a stimulus such as a tone or light is turned on to signal the beginning of the interval, and in a proportion of trials the subject is reinforced for the first response it makes after the criterion time. In the remainder of the trials, known as probe trials, no reinforcement is given and the stimulus remains on for two or three times the criterion time. When the mean response rate in many probe trials is calculated, an approximately Gaussian peak of responses is seen centered on the criterion. The time at which this timing function is at its maximum, also known as the peak time, gives an estimate of how accurately the subject is timing; precision is indicated by the spread of the timing function. These quantitative measures make the PI procedure an attractive tool for the study of interval timing. In addition, the temporal relations defined by the start and stop times for responding on individual trials have been used to identify sources of variability contributed by clock, memory, and response thresholds (e.g., Abner et al., 2001; Cheng and Westwood, 1993; Cheng et al., 1993; Church et al., 1994; Rakitin et al., 1998).

An example of interval timing data collected from an adult participant (ALB) diagnosed with attentional-deficit disorder (ADD) using the PI procedure is shown in Figure 1. The top panel illustrates percent maximum response rate for ALB in an unmedicated state (NicPre) plotted as a function of 7-s and 17-s criteria trained using methods reported by Levin et al, 1996, 1998; Rakitin et al., 1998. In this procedure, a blue square presented on a computer monitor is transformed to magenta at the appropriate criterion time during fixed-time training trials. Thereafter, participants are requested to reproduce the temporal criterion for a sequence of test trials for which a distribution of their responses is plotted on a relative time scale immediately following the trial during the inter-trial interval (ITI). This ITI feedback is displayed on the computer monitor and provides the participant with information concerning the relative accuracy and precision of their temporally-controlled responding on the preceding trial. ITI feedback can be randomly presented following a fixed proportion of trials (in this case 25% and 100%). As can be seen in the top panel of the figure, when the participant is provided with ITI feedback on 100% of the trials the PI functions are centered at the correct times showing excellent accuracy of the reproduced intervals. In contrast, when ITI feedback is provided on only 25% of the trials a proportional rightward shift is observed in the timing of the 7-s and 17-s intervals, reflecting a discrepancy in the accuracy of temporal reproductions that is not observed in normal participants. This rightward shift is accompanied by a broadening of the PI functions indicating a decrease in temporal precision with lower levels of feedback. Both of these findings are consistent with a slowing of the internal clock as a function of the probability of feedback and may be the result of an attentional deficit (e.g., flickering mode switch) as described by Lustig (this volume), Meck and Benson, 2002, and Penney (this volume). Interestingly, the bottom panel indicates that when the participant is given a stimulant drug (transdermal nicotine skin patch) that increases dopamine levels in the brain during the NicPost condition the effects of 25% ITI feedback are enhanced and produce levels of temporal accuracy and precision that are equivalent to the 100% ITI feedback condition in both the medicated and unmedicated states. These results suggest an equivalence of the ITI feedback effects and the types of pharmacological stimulation

Time (sec)

FIGURE 1 Peak-interval procedure: Percent maximum response rate plotted as a function of signal duration for a single adult participant (ALB) diagnosed with attention deficit disorder (ADD) trained at two criterion times (7s and 17s) under two conditions of intertrial interval (ITI) feedback (25% and 100%). The top panel shows performance at these two criterion times under the two ITI feedback conditions in an unmedicated state (NicPre) and the bottom panel shows performance in a medicated state (NicPost). See Levin et al. (1996, 1998) for additional procedural details.

Time (sec)

FIGURE 1 Peak-interval procedure: Percent maximum response rate plotted as a function of signal duration for a single adult participant (ALB) diagnosed with attention deficit disorder (ADD) trained at two criterion times (7s and 17s) under two conditions of intertrial interval (ITI) feedback (25% and 100%). The top panel shows performance at these two criterion times under the two ITI feedback conditions in an unmedicated state (NicPre) and the bottom panel shows performance in a medicated state (NicPost). See Levin et al. (1996, 1998) for additional procedural details.

provided to ADD patients by drugs such as nicotine (see Levin et al., 1996, 1998). These findings also support the proposal that attentional deficits can lead to the underestimation of signal durations in a manner that is consistent with a slowing of an internal clock that is sensitive to dopaminergic manipulations whether they are produced by behavioral (ITI feedback) or pharmacological (nicotine patch) means.

Behavioral data derived from timing tasks such as the PI procedure have influenced the development of a number of different psychological theories of interval timing (for a review, see Grondin, 2001; Matell and Meck, 2000). Of these theories, scalar timing theory, or scalar expectancy theory (SET), stands out because not only does it explain much behavioral data, but it has also been useful in interpreting and guiding anatomical and pharmacological work in the attempt to identify the neuropsychological mechanisms responsible for these behaviors (e.g., Allan, 1998; Gibbon, 1977, 1991; Gibbon et al., 1984, 1997; Gibbon and Malapani, 2002; Killeen, 2002; Wearden, 1999). SET provides both a formal quantitative and an information-processing account of interval timing that postulates three distinct stages: a clock, a memory, and a decision stage. The clock stage is hypothesized to consist of a pacemaker that emits pulses which are gated to an accumulator by a switch. When reinforcement occurs the current count in the accumulator is transferred to reference memory. As training with a particular interval progresses, a distribution of values in the reference memory is formed. Finally, if the participant needs to estimate or produce the learned interval, this is done in the decision stage of the system by making a ratio comparison between the current value in the accumulator and a random sample drawn from reference memory (see Church, this volume). At its heart, SET is a model in which Poisson, constant, and scalar sources of variability compete for control over temporal discrimination. In most cases it is the scalar source of variability that comes to dominate behavior, but the other sources also play a critical role in the clock, memory, and decision stages of interval timing. The interested reader should refer to Gibbon (1992), Killeen (2002), and Rousseau et al. (1984) for cogent discussions of the ubiquity of a Poisson process underlying time estimation.

The Smoker's Sanctuary

The Smoker's Sanctuary

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