An Information Processing Model of Interval Timing

Most information-processing models of interval timing, including SET, share a basic structure, as proposed by Treisman (1963). SET is described more fully elsewhere in this volume, including the introduction, but the features important for the present discussion are pictured in Figure 10.1. These models include a pacemaker that emits pulses that then pass through an attention-controlled switch or gate before piling up in an accumulator (e.g., Gibbon et al., 1984; Zakay and Block, 1997; for a discussion of attention's role in different models of interval timing, see Lejeune, 1998). The accumulator values may then be compared to values stored in long-term reference memory to make judgments about current time relative to past durations.

FIGURE 10.1 Basic structure of information-processing models of timing, including scalar expetancy theory (Gibbon et al., 1984). Attention to a to-be-timed stimulus closes the switch, allowing pacemaker pulses to pass into the accumulator. The current accumulator value is compared to a past value representing the target sampled from reference memory to decide if it meets criterion to be judged the same as (yes) or different from (no) the target.

FIGURE 10.1 Basic structure of information-processing models of timing, including scalar expetancy theory (Gibbon et al., 1984). Attention to a to-be-timed stimulus closes the switch, allowing pacemaker pulses to pass into the accumulator. The current accumulator value is compared to a past value representing the target sampled from reference memory to decide if it meets criterion to be judged the same as (yes) or different from (no) the target.

The clock stage of this model has been the target of most questions about older adults' interval timing performance because of its relevance to other investigations of cognitive aging. Extensive animal research, more recently supplemented by human neuropsychological and neuroimaging studies (e.g., Hinton, this volume; Hinton et al., 1996; Malapani and Rakitin, this volume; Pouthas, this volume; Rao et al., 2001), locates this stage in the frontal-striatal circuits of the brain, and its functioning is heavily influenced by dopaminergic and catecholamine neurotransmitter systems (Meck, 1996; Meck and Benson, 2002). Changes in these brain systems are thought to be of critical importance to many of the cognitive changes that occur with age (see, e.g., Cabeza, 2001; Park et al., 2001; Rubin, 1999). In particular, they are thought to be centrally involved in age differences in attentional functioning.

As Figure 10.1 indicates, attention plays an important role in interval timing models. Fluctuations in attention can cause a "flickering" of the switch that allows pulses to pass from the pacemaker to the accumulator, leading to a loss of pulses and thus a lower — and consequently slower — clock reading for a given unit of physical time. These models thus allow for clear predictions about the interval timing performance of individuals and groups that have problems with attentional functioning, including older adults.

Of course, aging affects many aspects of behavior and cognition in addition to attention. For example, depending on the situation, older adults may adopt more or less conservative decision criteria than do young adults, and memory complaints are ubiquitous among older adults (see recent reviews by Craik and Jennings, 1992; Light, 1991; Zacks et al., 2000). Fortunately, research using information-processing models of interval timing has revealed ways of separating out effects on these different functions. In particular, a central tenet of SET is that temporal processes reliant on the clock and memory stages have scalar variability; that is, their variability increases or decreases as a constant proportion of the duration being timed. Manipulations that shift the accuracy of duration judgments but lead to violations of this scalar property are likely to have their effects on nontemporal processes, such as decision criteria or response execution (Gibbon et al., 1984, 1997).

Furthermore, variables that influence attention or other components of the clock stage can often be differentiated from those that influence memory stages by observing the effects of feedback (Meck, 1983). With feedback, participants can learn to adjust to a speeded or slowed clock by increasing or decreasing the number of accumulator counts associated with a response. However, distortions that occur in memory are resistant to feedback, as the correct feedback value will also be stored in a distorted fashion. This distinction is extensively used in animal research on interval timing to differentiate behavioral, pharmacological, and surgical manipulations that have an effect on attention and clock functioning from those that have an effect on temporal memory, and shows similar promise for differentiating these components in older adults (e.g., Malapani et al., 2002b; Rakitin et al., submitted; Wearden et al., 1997).

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