Research ReportDedifferentiated face processing in older adults is linked to lower resting state metabolic activity in fusiform face area
Introduction
Theories of life span cognition propose that development is marked by the differentiation of abilities from childhood through adulthood with dedifferentiation in older adulthood when cognitive abilities become less distinctive and more homogeneous (Balinsky, 1941, Baltes, 1987, Ghisletta and de Ribaupierre, 2005). Age-related changes in differentiation have been evidenced at both the behavioral and neural levels. The present study extended previous research examining older adults (OA) neural dedifferentiation in visual processing by investigating whether it can be explained by age-related declines in visual acuity, cognitive function, cortical thickness, and/or cerebral blood flow.
Neural dedifferentiation can be conceptualized as an increasingly shared neural substrate for particular stimuli or tasks that yield less specificity in the activation pattern. Age related increases have been observed in various paradigms, and two non-mutually exclusive explanations for these age-related changes in specificity have been suggested: (1) functional compensation for neural decline that may yield age-related changes in recruitment of additional regions of activation and (2) difficulty recruiting specialized neural mechanisms that may yield age-related decreases in the ‘tuning’ of activation.
Evidence for neural dedifferentiation in OA has been empirically demonstrated in more brain activation in OA than younger adults (YA) during various cognitive tasks (Burianova et al., 2013, Grady, 2002, Zarahn et al., 2007). Greater activation in OA has been noted most frequently in frontal regions, consistent with the idea that this is a compensatory mechanism reflecting increased effort or increased demands on executive functions (Cabeza et al., 1997, Grady et al., 1994). Other research has provided evidence for dedifferentiation within the visual system. OA show within category dedifferentiation of faces, as evidenced by greater OA than YA adaptation in the FFA to faces that are moderately similar (Goh et al., 2010). This effect parallels behavioral research demonstrating that OA make fewer distinctions among faces when forming trait impressions (Ng et al., 2014), and show reduced accuracy in both face recognition (Bartlett and Leslie, 1986, Bartlett et al., 1989, Goh et al., 2010) and emotion recognition (Orgeta and Phillips, 2008, Ruffman et al., 2008, Ruffman et al., 2009a, Slessor et al., 2010), although the latter age effect may depend on the methods used (Hahn et al., 2006, Mather and Knight, 2006, Murphy et al., 2010, Ruffman et al., 2009b). OA also show between category neural dedifferentiation when attempting to remember a series of visual stimuli (Park et al., 2004), or when passively viewing them (Park et al., 2012), with a smaller difference in activation to faces than to other stimulus categories in voxels specialized for faces, and a parallel age difference for activation to buildings or chairs vs. other stimulus categories in voxels specialized for places or objects, respectively. These effects are consistent with the idea that OA dedifferentiation reflects difficulty recruiting specialized neural mechanisms.
In the present study, we examined age-related neural dedifferentiation during passive viewing of different categories of stimuli that included faces, buildings, objects and cars. We examined activation in whole brain as well as in ROIs located in the areas that should respond maximally to faces, buildings, or objects: the FFA (Kanwisher et al., 1997), the parahippocampal place area (PPA; (Epstein et al., 1999)), and the medial fusiform object area (FOA; (Hadjikhani et al., 2004, Ishai et al., 1999)), respectively. We also included a category of front views of car stimuli, because some research indicates that the face-like appearance of car grills can elicit activation in the FFA (Kuhn et al., 2014). Neural dedifferentiation in OA was conceptualized as: 1) a less specific, broader activation pattern to stimuli from each of the categories in the whole brain 2) a less specific, more uniform pattern of activation in each ROI, as evidenced by weaker differences between the preferred stimulus category and the other categories. Finally, in addition to the aim of replicating previous research evidence for OA neural dedifferentiation, we investigated possible mediators of these effects, including visual acuity, cognitive function, cortical thickness, and blood flow at rest.
Since OA show reduced visual acuity and contrast sensitivity, these peripheral mechanisms may mediate OA neural dedifferentiation to visual stimuli. OA deficits in executive function or speed also could mediate, as Grady (2002) found greater dedifferentiation with increased cognitive load, and Park et al. (2010) found that greater fluid processing ability predicted greater neural specificity of the BOLD response to faces and houses. Gray matter cortical thinning also has been shown in healthy OA (Fjell et al., 2009, Liu et al., 2010, Salat et al., 2004). Here we examined whether age-related cortical thinning mediated age-related BOLD dedifferentiation. Recent research has shown that weaker BOLD activation in OA than YA at rest is due not to age-related differences in cerebral vasculature alone but also to cognitive and structural factors (Marstaller et al., 2015). In order to examine whether lower cerebral blood flow (CBF) was at the origin of differences in BOLD signal, we also measured CBF at rest using asymmetric spin labeling, and determined whether any age differences in CBF mediated age differences in BOLD dedifferentiation within the ROIs we examined.
Section snippets
Vision and cognition measures
As shown in Table 1, OA performed significantly worse than YA on visual acuity and contrast sensitivity, but not on the Benton face recognition test. OA also showed significantly slower performance on a speeded pattern comparison task, consistent with decreases in processing speed in older adulthood (Salthouse, 1993). On the card sorting task assessing executive control, OA showed marginally more perseverative errors, and significantly more non-perseverative errors. In contrast to poorer
Discussion
Replicating previous research investigating neural dedifferentiation in OA, we found neural dedifferentiation during passive viewing of stimuli both at the level of the whole brain and within the FFA. We further found that neither age differences in visual and cognitive function nor age differences in cortical thickness could explain the age-related dedifferentiation of FFA activation to various stimulus categories. The mediation that our data did support was resting state blood flow, with age
Participants
Forty-five participants were scanned. Of these, two OA and two YA participants were removed due to truncated data, 1 OA did not complete the study due to claustrophobia, 1 OA was removed due to excessive movement and 1 OA was removed due to BOLD responses ranging from 3.96 to 4.07 standard deviations above the mean. Of the remaining 38 participants, 20 (10 males) were YA aged 19–33 (M=24.55, SD=3.61), and 18 (8 males) were OA aged 65–88 (75.56, SD=7.14). OA were screened using the Mini-Mental
Acknowledgements
This work was supported by NIH Grant 5 RO1 AG038375 to LZ. The funder played no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The authors want to thank Eri Ichijo for her help with the cortical thickness analysis, and Luke Hanlin for his help with the data acquisition, as well as the participants who took part in the experiments.
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