Log Signal Duration

FIGURE 11.1 Temporal discrimination in mice that are heterozygous for the dopamine transporter deletion (DAT+/-) and their wild-type littermates (WT).

Log Signal Duration

FIGURE 11.1 Temporal discrimination in mice that are heterozygous for the dopamine transporter deletion (DAT+/-) and their wild-type littermates (WT).

last four signals (6.4, 8.0, 10.8, and 12.7 sec). Eight-signal training lasted 13 days, and it was followed by four test days during which each group was tested in a single daily session, each consisting of 40 trials. There were no correction trials during the test days.

Figure 11.1 shows that P(Long) increased as a sigmoidal function of signal duration for both DAT+/- and WT mice (F(7, 56) = 3.62, P = .003). Data points represent the proportion of long responses for each signal, averaged first across sessions and then across subjects. Interestingly, the psychometric function of the DAT+/- group is shifted to the left relative to that of the WT group, although this effect was not statistically significant (P = .310).

Why do the DAT+/- mice have a higher tendency than their WT littermates to make a "long" response for any given signal duration? Does this behavioral effect reflect a perceptual difference whereby the DAT+/- mice perceive time as more stretched out than do the WT mice? In rats, systemic injections of methamphetamine, a hyperdopaminergia-causing agent, produce a similar leftward shift in psychometric functions. At first glance, one is tempted to argue that because DAT+/- mice also have functional hyperdopaminergia, the leftward shift of their temporal discrimination function relative to that of the WTs should also reflect a difference in temporal perception between the two groups. But does it?

An altered state of duration perception cannot be observed directly; rather, it is inferred as the perceptual change leads to a behavioral change. Perceptual differences can be detected if the performance of the same individuals is measured under different perceptual states using the same experimental protocol. For example, if a group of rats is trained to perform a temporal discrimination procedure under saline, and then tested under methamphetamine, a methamphetamine-induced leftward shift is observable in full extent during the first session of drug administration (Meck,

1983). Further, under certain experimental conditions, the leftward shift is perfectly parallel; i.e., neither the slope nor the asymptote of the function is affected, indicating that other performance factors such as discriminability are spared (Cevik, 2000). Under these conditions, the leftward shift of the psychometric function is highly likely to have resulted from a change in temporal perception, which causes the signals to be perceived as longer than they were in the absence of methamphetamine. However, when the performance in a temporal discrimination procedure of two groups of rats — one trained under saline and the other under methamphetamine — is compared, no difference in behavior can be observed. The psychometric functions overlap in spite of the difference in the perceptual states because each group of subjects has learned to perform the task in relation to its own perceptual state (Meck, 1983). In general, when performance can be calibrated to the current state of perception, a between-subjects comparison is not appropriate to detect perceptual differences.

Why, then, did the psychometric functions of the DAT+/- and WT groups not overlap in the present experiment? If discrimination of durations can be calibrated to one's speed of timing to yield optimal performance, the psychometric functions of the DAT+/- and WT groups should have overlapped with their temporal bisection point at the geometric mean (Church and Deluty, 1977). Notice that the current procedure involved the reinforcement of intermediate as well as the shortest and longest signals, which forced the bisection point to be at the geometric mean. Nevertheless, the DAT+/- group slightly underestimated the geometric mean, whereas the WT group overestimated it to a somewhat larger extent. So what, if not a perceptual difference, accounts for the deviation of the DAT+/- and WT functions from each other and from the geometric mean?

The psychometric functions were parallel with similar slope and asymptote values, indicating that discriminability and overall performance accuracy were similar for DAT+/- and WT mice. The proportion of correct responses (which is equal to the obtained probability of reinforcement) was 0.76 and 0.78 for DAT+/- and WT groups, respectively, and both groups responded during more than 90% of the trials. Further, the learning rate was not different for the two groups; the number of training sessions to steady-state performance was similar for DAT+/- and WT mice. Taken together, these results suggest that neither overall learning ability nor performance factors that are not related to timing were likely to have affected the position of the psychometric functions.

What else, if not a difference in perception, learning, or motivation, can account for the observed divergence in temporal discrimination functions of the DAT+/- and WT mice? A difference in attentional processes is a likely candidate. Although attention is too elusive a concept to be offered as a satisfactory explanation for behavioral differences, we are all familiar with the feeling that time passes too slowly as we wait, counting the seconds, for something to happen. In other words, time seems to be stretched out as we pay attention to it (e.g., waiting for the stats class to be over), but it flies by if we are too happily involved with something else to pay attention to time (e.g., being on vacation). Notice, that although homozygous DAT/have been suggested as a model for human ADHD, the behavioral profile of the heterozygous DAT+/- is suggestive of an enhanced, rather than impaired, attention.

DAT+/- mice might have enhanced attention relative to both DAT-/- and WT mice because attention is an inverted-U-shaped function of the effective levels of dopamine transmission. For example, it is a well-known effect that attention and vigilance change as inverted-U-shaped functions of amphetamine dose (e.g., Grilly et al., 1998). Consistent with this argument is the fact that reaction times were lower for the DAT+/- group, indicating that they were indeed more vigilant than the WTs.

In sum, hyperdopaminergia of DAT+/- seems to have caused these mice to become more likely to respond "long" under a temporal discrimination procedure, which might reflect higher attentiveness of these animals. This hypothesis can be tested by exposing these animals to more detailed tests of attention and vigilance. Alternatively, the divergence in the temporal discrimination functions of the DAT-/- and WT mice might reflect a difference in temporal perception; however, whether the chronic state of hyperdopaminergia of the DAT+/- produces the same perceptual state as an acute methamphetamine administration is disputable.


Single-gene mutations do not always produce major effects on the phenotypic expression of a complex behavioral trait that is under polygenic control. In several instances (e.g., schizophrenia), single genes with major phenotypic effects elude identification (for a review, see Plomin et al., 1994). In such cases, the phenotypic expression of the behavioral trait seems to be controlled in a continuous, quantitative manner by a set of genes called the quantitative trait loci (QTL). Although individual QTL are inherited in a Mendelian manner, they do not result in discrete, discontinuous phenotypic classes since each exerts an effect of relatively small size. The mutation of any one of these loci might therefore fail to affect the behavioral phenotype in any clear, detectable manner in spite of the actual involvement of that locus in the control of the behavioral trait of interest (Moore and Nagle, 2000).

Linkage techniques that are used to identify single genes can be extended to detect QTL. Alternatively, one can carry out allelic association studies that instead of linking the expression of a phenotypic trait to a chromosomal locus, attempt to associate variations on a behavioral phenotype with specific allelic forms of genes. Both approaches are based on exploiting the naturally occurring variations in a behavioral trait. Therefore, the feasibility of research aimed at QTL identification, much like the forward genetic approach, depends critically on the generation time and maintenance costs of the model organism, efficient and task-relevant behavioral essays that can detect differences in the behavioral phenotype, availability of inbred strains to be used in linkage analysis, and the presence of a high-density linkage map to be used in positional cloning (Taylor, 2000).

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