The Importance Of Interval Timing In Memory And Attention

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Human learning and memory is also highly sensitive to temporal factors, and oscillator-based models have been proposed for the coding of serial order in memory (e.g., Brown and Chater, 2001; Brown et al., 2000; McCormack and Hoerl, 2001). In addition, deficits in learning, memory, set shifting, and interval timing have been observed in a variety of patient populations with damage to the basal ganglia, including Parkinson's disease and Huntington's disease patients, as well as other cortical and subcortical brain structures affected by Alzheimer's disease, injury, and stroke (see Cronin-Golomb et al., 1994; Diedrichsen et al., this volume; Gabrieli et al., 1996; Harrington and Haaland, 1999; Malapani and Rakitin, this volume; Nichelli et al., 1993; Stebbins et al., 1999). Temporal bisection data obtained from age-matched controls (n = 6), cerebellar lesion patients (n = 3), Alzheimer's disease patients (n = 4), and Parkinson's disease patients (n = 4) tested off of their medication are presented in Figure 2 (for procedural details, see Penney, this volume; Penney et al., 2000). These temporal bisection functions show the typical modality difference in which sounds are judged longer than lights of equal physical durations for all groups of participants. The major difference among the groups is in the quality of the temporal discriminations. Patients with cerebellar damage are little affected on this task, whereas Alzheimer's disease patients show a similar decline in sensitivity for both auditory and visual stimuli that may reflect deficits in attention and memory. Interestingly, Parkinson's disease patients tested off of their medication are the most disrupted in their sensitivity to signal duration and show a differential effect as a function of signal modality, with an exaggerated bias for calling auditory stimuli long and visual stimuli short. In either case, Parkinson's disease patients are severely compromised in their ability to accurately judge signal duration and resort to a greater reliance on response biases consistent with the involvement of the basal ganglia in timing and time perception (see Malapani and Rakitin, this volume; Malapani et al., 1998b).

As a complement to these neuropsychological studies, specialized techniques have been developed to study interval timing in humans using the brain imaging technologies of functional magnetic resonance imaging and event-related scalp potentials (see Brannon and Roitman, this volume; Hinton, this volume; Hinton et al., 1996; Hinton and Meck, 1997b; Lejeune et al., 1997; Lewis and Miall, this volume; Maquet et al., 1996; Meck et al., 1998; Pouthas, this volume; Pouthas et al., 1999, 2000; Rao et al., 2001).

A number of researchers have presented psychophysical data suggesting that duration judgments depend on the amount of attentional resources allocated to a

FIGURE 2 Temporal bisection procedure: probability of a long response as a function of signal duration (3.0, 3.37, 3.78, 4.25, 4.77, 5.35, and 6.0 sec) for auditory (A) and visual (V) stimuli presented within the same session. Participants were age-matched controls (n = 6), cerebellar lesion patients (n = 3), Parkinson's disease (PD) patients (n = 4), or Alzheimer's disease (AD) patients (n = 4). See Penney et al. (2000) for additional procedural details.

Signal Duration (s)

FIGURE 2 Temporal bisection procedure: probability of a long response as a function of signal duration (3.0, 3.37, 3.78, 4.25, 4.77, 5.35, and 6.0 sec) for auditory (A) and visual (V) stimuli presented within the same session. Participants were age-matched controls (n = 6), cerebellar lesion patients (n = 3), Parkinson's disease (PD) patients (n = 4), or Alzheimer's disease (AD) patients (n = 4). See Penney et al. (2000) for additional procedural details.

temporal processor or internal clock (e.g., Buhusi, this volume; Droit-Volet, this volume; Fortin, this volume; Lustig, this volume; Penney, this volume). For example, Fortin and Massé (1999, 2000) and Fortin and Rousseau (1987) have shown that if participants expect the timing of an ongoing signal to be interrupted by a gap or another type of task, they will divide attention between timing the ongoing signal and monitoring for the onset of the interrupting event. This division of attention leads to shorter-than-normal duration judgments as a function of the location of the interruption, suggesting that the internal clock runs at a slower rate when attention is divided in this manner. Because monitoring continues until the interruption is completed, the maximal effect will be observed when an interruption is expected, but none actually occurs — thus requiring the participant to monitor the entire interval. These data provide strong and convincing evidence for the role of attentional time-sharing in interval timing (see also Lejeune, 1998; Zakay and Block, 1996). Some electrophysiological support for this proposal has been provided by showing a relationship between the amplitude of brain wave activity and performance when participants focus their attention on the temporal parameters of a task (e.g., Casini and Macar, 1996a, 1996b, 1999; Pouthas, this volume). Identifying the ways in which attentional processes come under temporal control (and vice versa) is an exciting direction for future research efforts with important neuropsychological applications in both young and aged populations (see Casini and Ivry, 1999; Droit-Volet, this volume; Ferrandez and Pouthas, 2001; Harrington et al., 1998; Lustig, this volume; Lustig and Meck, 2001; Pang and McAuley, this volume; Perbal et al., 2001; Vanneste and Pouthas, 1999). Other nontemporal variables affecting attention and temporal judgments (e.g., stimulus modality and salience) are now being incorporated into SET as well as other theories of interval timing (see Buhusi, this volume; Buhusi and Meck, 2000, 2002; Meck, 1984; Penney, this volume; Penney et al., 1996, 2000).

The ability of organisms to time and coordinate temporal sequences of events and to select particular aspects of their internal and external environments to which they will attend has inspired some investigators to propose ways in which the same frontal-striatal circuits keep time and shift attention using the gating properties of this system (see Meck and Benson, 2002; Pang and McAuley, this volume). The attentional control of the perception and production of short durations appears to be better accounted for by an interval-based, as opposed to a beat-based, timing system, suggesting that the timing system is rapidly reset upon command (e.g., Pashler, 2001). It is also interesting to note that some researchers have argued that a primary function of the internal clock is to allow for the efficient transfer of information from one stage of information processing to another at regularly spaced intervals. This oscillatory pattern of information transfer between processing stages is achieved by the internal clock producing periodic inhibition with each clock pulse, thereby temporarily increasing the signal-to-noise ratio (e.g., Burle and Bonnet, 1999).

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