Neural Broadening or Neural Attenuation? Investigating Age-Related Dedifferentiation in the Face Network in a Large Lifespan Sample

Abstract

Previous studies have found that cortical responses to different stimuli become less distinctive as people get older. This age-related dedifferentiation may reflect the broadening of the tuning curves of category-selective neurons (broadening hypothesis) or it may be due to decreased activation of category-selective neurons (attenuation hypothesis). In this study, we evaluated these hypotheses in the context of the face-selective neural network. Over 300 participants, ranging in age from 20 to 89 years, viewed images of faces, houses, and control stimuli in a functional magnetic resonance imaging session. Regions within the core face network and extended face network were identified in individual subjects. Activation in many of these regions became significantly less face-selective with age, confirming previous reports of age-related dedifferentiation. Consistent with the broadening hypothesis, this dedifferentiation in the fusiform face area (FFA) was driven by increased activation to houses. In contrast, dedifferentiation in the extended face network was driven by decreased activation to faces, consistent with the attenuation hypothesis. These results suggest that age-related dedifferentiation reflects distinct processes in different brain areas. More specifically, dedifferentiation in FFA activity may be due to broadening of the tuning curves for face-selective neurons, while dedifferentiation in the extended face network reflects reduced face- or emotion-selective activity.

Network-specific effects of age and in-scanner subject motion: A resting-state fMRI study of 238 healthy adults

“…This network-specific mechanism is also supported by a recent study which demonstrated that age-related dedifferentiation reflects distinct processes in different brain areas (Park et al, 2012). Specifically, while age-related dedifferentiation in the fusiform face area was mainly driven by increased activation to houses, dedifferentiation in the extended face network reflected decreased activation to faces (Park et al, 2012). Grady et al (2006) propose that a shift in the balance between neuronal activity and recruitment during rest and task, respectively, may result in behavioral phenotypes of cognitive aging.…”

“…Further studies integrating various structural and functional indices of the aging brain are highly needed, and may reveal novel age-related patterns not easily detected by univariate and unimodal studies (Groves et al, 2012). This network-specific mechanism is also supported by a recent study which demonstrated that age-related dedifferentiation reflects distinct processes in different brain areas (Park et al, 2012). Specifically, while age-related dedifferentiation in the fusiform face area was mainly driven by increased activation to houses, dedifferentiation in the extended face network reflected decreased activation to faces (Park et al, 2012).…”

Motion‐related artifacts in structural brain images revealed with independent estimates of in‐scanner head motion

“…This subsample includes at least 30 participants in each decade of the sampled age range and represents individuals who performed the complete series of seven fMRI runs [e.g., Chan et al, 2014; Kennedy et al, 2015; Park et al, 2012, 2013; see Fig. 1].…”

Age-related decline in differentiated neural responses to rare target versus frequent standard stimuli

“…As individuals grow older, there appears to be a decrease in the specificity of activation of neural modules in response to different kinds of stimuli, such as target vs. non-target letters or numbers, images of faces vs. non-faces, and cued vs. non-cued locations (Curran, Hills, Patterson, & Strauss, 2001; Hahn, Wild-Wall, & Falkenstein, 2011; Kenemans, Smulders, & Kok, 1995; Looren de Jong, Kok, & van Rooy, 1988; Lorenzo-Lopez, Amenedo, Pazo-Alvarez, & Cadaveira, 2007; Park et al, 2012). This age-related loss of neural specialization has been indexed by comparing neural responses to different stimulus types and by measuring changes in the distribution of neural activity recruited to carry out task demands (Cabeza, Anderson, Locantore, & McIntosh, 2002; Lorenzo-Lopez et al, 2007).…”