Aging, cingulate cortex, and cognition: insights from structural MRI, emotional recognition, and theory of mind.

The cingulate cortex is a limbic structure involved in multiple functions, including emotional processing, pain, cognition, memory, and spatial orientation. The main goal of this structural Magnetic Resonance Imaging (MRI) study was to investigate whether age affects the cingulate cortex uniformly across its anteroposterior dimensions and determine if the effects of age differ based on sex, hemisphere, and regional cingulate anatomy, in a large cohort of healthy individuals across the adult lifespan. The second objective aimed to explore whether the decline in emotional recognition accuracy and Theory of Mind (ToM) is linked to the potential age-related reductions in the pregenual anterior cingulate (ACC) and anterior midcingulate (MCC) cortices. We recruited 126 healthy participants (18-85 years) for this study. MRI datasets were acquired on a 4.7 T system. The cingulate cortex was manually segmented into the pregenual ACC, anterior MCC, posterior MCC, and posterior cingulate cortex (PCC). We observed negative relationships between the presence and length of the superior cingulate gyrus and bilateral volumes of pregenual ACC and anterior MCC. Age showed negative effects on the volume of all cingulate cortical subregions bilaterally except for the right anterior MCC. Most of the associations between age and the cingulate subregional volumes were linear. We did not find a significant effect of sex on cingulate cortical volumes. However, stronger effects of age were observed in men compared to women. This study also demonstrated that performance on an emotional recognition task was linked to pregenual ACC volume, whist the ToM capabilities were related to the size of pregenual ACC and anterior MCC. These results suggest that the cingulate cortex contributes to emotional recognition ability and ToM across the adult lifespan.

Contributions of hippocampal subfields and subregions to episodic memory performance in healthy cognitive aging.

In the present study we investigated whether hippocampal subfield (cornu ammonis 1-3, dentate gyrus, and subiculum) and anteroposterior hippocampal subregion (head,body, and tail) volumes can predict episodic memory function using high-field high resolution structural magnetic resonance imaging (MRI). We recruited 126 healthy participants (18-85 years). MRI datasets were collected on a 4.7 T system. Participants were administered the Wechsler Memory Scale (WMS-IV) to evaluate episodic memory function. Structural equation modeling was used to test the relationship between studied variables. We found that the volume of the dentate gyrus subfield and posterior hippocampus (body) showed a significant direct effect on visuospatial memory performance; additionally, an indirect effect of age on visuospatial memory mediated through these hippocampal subfield/subregion was significant. Logical and verbal memory were not significantly associated with hippocampal subfield or subregion volumes.

Emotional recognition across the adult lifespan: Effects of age, sex, cognitive empathy, alexithymia traits, and amygdala subnuclei volumes.

The ability to recognize others' emotions is vital to everyday life. The goal of this study was to assess which emotions show age-related decline in recognition accuracy of facial emotional expressions across the entire adult lifespan and how this process is related to cognitive empathy (Theory of Mind [ToM]), alexithymia traits, and amygdala subnuclei volumes in a large cohort of healthy individuals. We recruited 140 healthy participants 18-85 years old. Facial affect processing was assessed with the Penn Emotion Recognition task (ER40) that contains images of the five basic emotions: Neutral, Happy, Sad, Angry, and Fearful. Structural magnetic resonance imaging (MRI) datasets were acquired on a 4.7T MRI system. Structural equation modeling was used to test the relationship between studied variables. We found that while both sexes demonstrated age-related reduction in recognition of happy emotions and preserved recognition of sadness, male participants showed age-related reduction in recognition of fear, while in female participants, age-related decline was linked to recognition of neutral and angry facial expressions. In both sexes, accurate recognition of sadness negatively correlated with alexithymia traits. On the other hand, better ToM capabilities in male participants were associated with improvement in recognition of positive and neutral emotions. Finally, none of the observed age-related reductions in emotional recognition were related to amygdala and its subnuclei volumes. In contrast, both global volume of amygdala and its cortical and centromedial subnuclei had significant direct effects on recognition of sad images.

Diffusion tensor imaging of superficial prefrontal white matter in healthy aging.

The prefrontal cortex (PFC) is a heterogenous structure that is highly susceptible to the effects of aging. Few studies have investigated age effects on the superficial white matter (WM) contained within the PFC using in-vivo magnetic resonance imaging (MRI). This study used diffusion tensor imaging (DTI) tractography to examine the effects of age, sex, and intracranial volume (ICV) on superficial WM within specific PFC subregions, and to model the relationships with age using higher order polynomial regression modelling. PFC WM of 140 healthy individuals, aged 18-85, was segmented into medial and lateral orbitofrontal, medial prefrontal, and dorsolateral prefrontal subregions. Differences due to age in microstructural parameters such as fractional anisotropy (FA), axial and radial diffusivities, and macrostructural measures of tract volumes, fiber counts, average fiber lengths, and average number of fibers per voxel were examined. We found that most prefrontal subregions demonstrated age effects, with decreases in FA, tract volume, and fiber counts, and increases in all diffusivity measures. Age relationships were mostly non-linear, with higher order regressions chosen in most cases. Declines in PFC FA began at the onset of adulthood while the greatest changes in diffusivity and volume did not occur until middle age. The effects of age were most prominent in medial tracts while the lateral orbitofrontal tracts were less affected. Significant effects of sex and ICV were also observed in certain parameters. The patterns mostly followed myelination order, with late-myelinating prefrontal subregions experiencing earlier and more pronounced age effects, further supporting the frontal theory of aging.

Diffusion tensor imaging of the corpus callosum in healthy aging: Investigating higher order polynomial regression modelling.

Previous diffusion tensor imaging (DTI) studies confirmed the vulnerability of corpus callosum (CC) fibers to aging. However, most studies employed lower order regressions to study the relationship between age and white matter microstructure. The present study investigated whether higher order polynomial regression modelling can better describe the relationship between age and CC DTI metrics compared to lower order models in 140 healthy participants (ages 18-85). The CC was found to be non-uniformly affected by aging, with accelerated and earlier degradation occurring in anterior portion; callosal volume, fiber count, fiber length, mean fibers per voxel, and FA decreased with age while mean, axial, and radial diffusivities increased. Half of the parameters studied also displayed significant age-sex interaction or intracranial volume effects. Higher order models were chosen as the best fit, based on Bayesian Information Criterion minimization, in 16 out of 23 significant cases when describing the relationship between DTI measurements and age. Higher order model fits provided different estimations of aging trajectory peaks and decline onsets than lower order models; however, a likelihood ratio test found that higher order regressions generally did not fit the data significantly better than lower order polynomial or linear models. The results contrast the modelling approaches and highlight the importance of using higher order polynomial regression modelling when investigating associations between age and CC white matter microstructure.