Some theories of aging have linked age-related cognitive decline to a reduction in distinctiveness of neural processing. Observed age-related correlation increases among disparate cognitive tasks have supported the dedifferentiation hypothesis. We previously showed cross-sectional evidence for age-related correlation decreases instead, supporting an alternative disintegration hypothesis. In the current study, we extended our previous research to a longitudinal sample. We tested 135 participants (20–80 years) at two time points—baseline and 5-year follow-up—on a battery of 12 in-scanner tests, each tapping one of four reference abilities. We performed between-tasks correlations within domain (convergent) and between domain (discriminant) at both the behavioral and neural level, calculating a single measure of construct validity (convergent − discriminant). Cross-sectionally, behavioral construct validity was significantly different from chance at each time point, but longitudinal change was not significant. Analysis by median age split revealed that older adults showed higher behavioral validity, driven by higher discriminant validity (lower between-tasks correlations). Participant-level neural validity decreased over time, with convergent validity consistently greater than discriminant validity; this finding was also observed at the cross-sectional level. In addition, a disproportionate decrease in neural validity with age remained significant after controlling for demographic factors. Factors predicting longitudinal changes in global cognition (mean performance across all 12 tasks) included age, change in neural validity, education, and National Adult Reading Test (premorbid intelligence). Change in neural validity partially mediated the effect of age on change in global cognition. Our findings support the theory of age-related disintegration, linking cognitive decline to changes in neural representations over time.

Cognitive psychologists posit several specific cognitive abilities that are measured with sets of cognitive tasks. Tasks that purportedly tap a specific underlying cognitive ability are strongly correlated with one another, whereas performances on tasks that tap different cognitive abilities are less strongly correlated. For these reasons, latent variables are often considered optimal for describing individual differences in cognitive abilities. Although latent variables cannot be directly observed, all cognitive tasks representing a specific latent ability should have a common neural underpinning. Here, we show that cognitive tasks representing one ability (i.e., either perceptual speed or fluid reasoning) had a neural activation pattern distinct from that of tasks in the other ability. One hundred six participants between the ages of 20 and 77 years were imaged in an fMRI scanner while performing six cognitive tasks, three representing each cognitive ability. Consistent with prior research, behavioral performance on these six tasks clustered into the two abilities based on their patterns of individual differences and tasks postulated to represent one ability showed higher similarity across individuals than tasks postulated to represent a different ability. This finding was extended in the current report to the spatial resemblance of the task-related activation patterns: The topographic similarity of the mean activation maps for tasks postulated to reflect the same reference ability was higher than for tasks postulated to reflect a different reference ability. Furthermore, for any task pairing, behavioral and topographic similarities of underlying activation patterns are strongly linked. These findings suggest that differences in the strengths of correlations between various cognitive tasks may be because of the degree of overlap in the neural structures that are active when the tasks are being performed. Thus, the latent variable postulated to account for correlations at a behavioral level may reflect topographic similarities in the neural activation across different brain regions.

Despite the intuition that strongly held beliefs are particularly difficult to change, the data on error correction indicate that general information errors that people commit with a high degree of belief are especially easy to correct. This finding is called the hypercorrection effect . The hypothesis was tested that the reason for hypercorrection stems from enhanced attention and encoding that results from a metacognitive mismatch between the person's confidence in their responses and the true answer. This experiment, which is the first to use imaging to investigate the hypercorrection effect, provided support for this hypothesis, showing that both metacognitive mismatch conditions—that in which high confidence accompanies a wrong answer and that in which low confidence accompanies a correct answer—revealed anterior cingulate and medial frontal gyrus activations. Only in the high confidence error condition, however, was an error that conflicted with the true answer mentally present. And only the high confidence error condition yielded activations in the right TPJ and the right dorsolateral pFC. These activations suggested that, during the correction process after error commission, people (1) were entertaining both the false belief as well as the true belief (as in theory of mind tasks, which also manifest the right TPJ activation) and (2) may have been suppressing the unwanted, incorrect information that they had, themselves, produced (as in think/no-think tasks, which also manifest dorsolateral pFC activation). These error-specific processes as well as enhanced attention because of metacognitive mismatch appear to be implicated.