Financial decision making (FDM) refers to the ability to conduct financial tasks autonomously to manage one’s finances without error or preventable financial loss (Lichtenberg, Stoltman, Ficker, Iris, & Mast, 2015; Marson, 2016; National Academies of Sciences & Medicine, 2016). Several studies highlight that older adults (OAs), an especially vulnerable but wealthy segment of the population, experience financial loss ranging from $2.9 to $36.5 billion annually (Lichtenberg et al., 2015; Teaster, Roberto, Migliaccio, Timmermann, & Blancato, 2012). Age-related cognitive decline may increase susceptibility to poor decision making (Agarwal, Driscoll, Gabaix, & Laibson, 2009; Fenge, 2017; Tymula, Belmaker, Ruderman, Glimcher, & Levy, 2013). Identifying the cognitive abilities and brain regions that contribute to FDM earlier in the spectrum of cognitive aging, among cognitively healthy OAs, will help to identify individuals at risk for poor FDM at a time when they are likely to be responsible for managing the assets they have accumulated over their lifetimes.
In those with mild cognitive impairment (MCI) and Alzheimer’s disease (AD), impairments in cognitive abilities including numeracy, executive functioning, memory, and visuomotor sequencing are associated with reduced FDM (Sherod et al., 2009). However, the role of specific cognitive abilities in supporting FDM among healthy OAs is unclear. Some studies find no association between specific cognitive abilities and FDM, while others report links between FDM and numeracy, attention, executive abilities, memory, visuomotor construction and processing speed (Pachana et al., 2014; Sherod et al., 2009; Shivapour, Nguyen, Cole, & Denburg, 2012).
Examining specific cognitive abilities along with regional brain structure among cognitively healthy OAs will allow stronger inferences regarding the aspects of cognition and brain integrity that may be critical for maintaining intact FDM. Few studies have investigated these links in healthy OAs, with most studies focusing on neurological populations (i.e., MCI, AD). Across these volumetric studies, cortical and subcortical regions including the angular gyrus, precuneus, medial and dorsolateral prefrontal cortex, inferior temporal and middle temporal cortex, cingulate cortex, nucleus accumbens, left medial and lateral amygdala and anterior thalamic radiation have been implicated in FDM (Benavides-Varela et al., 2020; Griffith et al., 2010; Han et al., 2016; Stoeckel et al., 2013). However, the relationship between cortical thickness measures and FDM has not yet been examined.
It is equally important to concurrently understand the substrates of financial awareness (FA), i.e., the awareness of one’s own FDM abilities. There is evidence that FA is a reliable construct, independent from FDM itself, and associated with memory awareness (i.e., metamemory, or the knowledge of one’s memory abilities), a well-established aspect of self-awareness (Sunderaraman, Chapman, Barker, & Cosentino, 2020). Of the various metacognitive metrics that was used to calculate FA, a calibration score reflecting the average degree of confidence was found to be the most meaningful method. It is arguable that with reduced FA, individuals may jeopardize their own financial well-being, be vulnerable to financial exploitation, and potentially incur heavy financial losses. Empirical evidence from memory awareness studies in individuals with MCI and AD has found that, those with impaired memory awareness are less likely to modify their approach to cognitively demanding tasks (e.g., using a pillbox to manage medications) (Cosentino, Metcalfe, Cary, De Leon, & Karlawish, 2011; Shaked et al., 2019) and may engage in more dangerous behaviors (e.g., driving)(Starkstein, Jorge, Mizrahi, Adrian, & Robinson, 2007).
Little is known about the neurocognitive substrates of FA. Historically, elements of self-awareness more broadly, particularly metamemory, have been linked to executive abilities and the structural integrity of the prefrontal cortex (Cosentino, Metcalfe, Holmes, Steffener, & Stern, 2011a; Fleming & Dolan, 2012). Increasingly, however, evidence points to a prominent role for midline structures, including the insula and cingulate, in supporting metamemory and self-evaluative processing more broadly (Bertrand et al., 2018; Buchy & Lepage, 2015; Klein, Ullsperger, & Danielmeier, 2013; van der Meer, Costafreda, Aleman, & David, 2010). Finally, regarding laterality, there is evidence that regions in the right hemisphere may differentially contribute to elements of self-awareness (Cosentino et al., 2015b; Harwood et al., 2005; Klein et al., 2013). Whether or not similar regions are associated with FA remain to be seen. In those with neurodegenerative conditions such as AD and fronto-temporal dementia, the right-hemisphere medial temporal regions have been associated with self-awareness.
The current study examined the cognitive and structural correlates of FDM and FA in healthy OAs and cortical thickness. On an exploratory basis, a whole brain analysis was run by selecting all 34 bilateral regions of interest (ROIs) and examining their associations with FDM, and between FA and 7 cortical ROIs (per hemisphere) based on previous literature (Bertrand et al., 2018; Cosentino et al., 2015b). To check for convergent validity, we explored the associations between a well-validated memory awareness measure (metamemory; Cosentino, Metcalfe, Butterfield, & Stern, 2007) and cortical thickness in the same pre-specified 7 ROIs.
Based on our previous work, we operationalized FA along a spectrum from under- to overconfidence in FDM. We hypothesized the following: (1) FDM and cognition: Numeracy, executive functioning, and vocabulary will show stronger associations with FDM compared to processing speed or memory. (2) FDM and cortical thickness: FDM will be more strongly associated with thickness of bilateral dorsolateral prefrontal and bilateral inferior parietal regions than that of other brain regions. (3) FA and Cognition: FA will be more strongly associated with memory awareness than primary cognitive domains (i.e., memory, executive functioning, processing speed, and vocabulary). (4) FA and Thickness: FA will show stronger associations with thickness in the right-sided insula, anterior cingulate cortex, and prefrontal region.