Objective:Understanding the factors contributing to optimal cognitive function throughout the aging process is essential to better understand successful cognitive aging. Processing speed is an age sensitive cognitive domain that usually declines early in the aging process; however, this cognitive skill is essential for other cognitive tasks and everyday functioning. Evaluating brain network interactions in cognitively healthy older adults can help us understand how brain characteristics variations affect cognitive functioning. Functional connections among groups of brain areas give insight into the brain’s organization, and the cognitive effects of aging may relate to this large-scale organization. To follow-up on our prior work, we sought to replicate our findings regarding network segregation’s relationship with processing speed. In order to address possible influences of node location or network membership we replicated the analysis across 4 different node sets.Participants and Methods:Data were acquired as part of a multi-center study of 85+ cognitively normal individuals, the McKnight Brain Aging Registry (MBAR). For this analysis, we included 146 community-dwelling, cognitively unimpaired older adults, ages 85-99, who had undergone structural and BOLD resting state MRI scans and a battery of neuropsychological tests. Exploratory factor analysis identified the processing speed factor of interest. We preprocessed BOLD scans using fmriprep, Ciftify, and XCPEngine algorithms. We used 4 different sets of connectivity-based parcellation: 1)MBAR data used to define nodes and Power (2011) atlas used to determine node network membership, 2) Younger adults data used to define nodes (Chan 2014) and Power (2011) atlas used to determine node network membership, 3) Older adults data from a different study (Han 2018) used to define nodes and Power (2011) atlas used to determine node network membership, and 4) MBAR data used to define nodes and MBAR data based community detection used to determine node network membership.Segregation (balance of within-network and between-network connections) was measured within the association system and three wellcharacterized networks: Default Mode Network (DMN), Cingulo-Opercular Network (CON), and Fronto-Parietal Network (FPN). Correlation between processing speed and association system and networks was performed for all 4 node sets.Results:We replicated prior work and found the segregation of both the cortical association system, the segregation of FPN and DMN had a consistent relationship with processing speed across all node sets (association system range of correlations: r=.294 to .342, FPN: r=.254 to .272, DMN: r=.263 to .273). Additionally, compared to parcellations created with older adults, the parcellation created based on younger individuals showed attenuated and less robust findings as those with older adults (association system r=.263, FPN r=.255, DMN r=.263).Conclusions:This study shows that network segregation of the oldest-old brain is closely linked with processing speed and this relationship is replicable across different node sets created with varied datasets. This work adds to the growing body of knowledge about age-related dedifferentiation by demonstrating replicability and consistency of the finding that as essential cognitive skill, processing speed, is associated with differentiated functional networks even in very old individuals experiencing successful cognitive aging.

Episodic memory is widely recognized as a critically important aspect of cognition that is often impacted by cognitive and brain aging. Prior work has shown that episodic memory is related to the presence of teeth-like folds on the dentate gyrus, called dentation. We hypothesized that episodic memory performance relates to overall hippocampal structure (i.e., dentation and volume) in an oldest-old cohort. We used data from the McKnight Brain Aging Registry, which consisted of cognitively healthy 85+-year-old adults. We conducted a canonical correlation analysis on 111 participants between a set of episodic memory tests and a set of characterizations of hippocampal structure. The analysis yielded a strong canonical correlation between episodic memory and hippocampal structure (r = 0.491, p = <0.001). The results suggest there is a connection between hippocampal morphology and function in the oldest-old. Our findings suggest that dentation may play an important role in relation to the individual differences observed in episodic memory performance among the oldest old and that hippocampal structure supports healthy cognitive aging. Highlights ### Competing Interest Statement The authors have declared no competing interest.

Cognitive training has shown promise for improving cognition in older adults. Age-related neuroanatomical changes may affect cognitive training outcomes. White matter hyperintensities are one common brain change in aging reflecting decreased white matter integrity. The current study assessed (1) proximal cognitive training performance following a 3-month randomized control trial and (2) the contribution of baseline whole-brain white matter hyperintensity load, or total lesion volume (TLV), on pre-post proximal training change. Sixty-two healthy older adults were randomized to either adaptive cognitive training or educational training control interventions. Repeated-measures analysis of covariance revealed two-way group × time interactions such that those assigned cognitive training demonstrated greater improvement on proximal composite (total training composite) and sub-composite (processing speed training composite, working memory training composite) measures compared to education training counterparts. Multiple linear regression showed higher baseline TLV associated with lower pre-post change on processing speed training sub-composite (β = -0.19, p = 0.04), but not other composite measures. These findings demonstrate the utility of cognitive training for improving post-intervention proximal performance in older adults. Additionally, pre-post proximal processing speed training change appears to be particularly sensitive to white matter hyperintensity load versus working memory training change. These data suggest that TLV may serve as an important factor for consideration when planning processing speed-based cognitive training interventions for remediation of cognitive decline in older adults.

Frontal lobe structures decline faster than most other brain regions in older adults. Age-related change in the frontal lobe is associated with poorer executive function (e.g., working memory, switching/set-shifting, and inhibitory control). The effects and presence of frontal lobe white matter hyperintensities (WMH) on executive function in normal aging is relatively unknown. The current study assessed relationships between region-specific frontal WMH load and cognitive performance in healthy older adults using three executive function tasks from the NIH Toolbox (NIHTB) Cognition Battery. A cohort of 279 healthy older adults ages 65–88 completed NIHTB and 3T T1-weighted and FLAIR MRI. Lesion Segmentation Toolbox quantified WMH volume and generated lesion probability maps. Individual lesion maps were registered to the Desikan-Killiany atlas in FreeSurfer 6.0 to define regions of interest (ROI). Independent linear regressions assessed relationships between executive function performance and region-specific WMH in frontal lobe ROIs. All models included age, sex, education, estimated total intracranial volume, multi-site scanner differences, and cardiovascular disease risk using Framingham criteria as covariates. Poorer set-shifting performance was associated with greater WMH load in three frontal ROIs including bilateral superior frontal (left β = −0.18, FDR-p = 0.02; right β = −0.20, FDR-p = 0.01) and right medial orbitofrontal (β = −0.17, FDR-p = 0.02). Poorer inhibitory performance associated with higher WMH load in one frontal ROI, the right superior frontal (right β = −0.21, FDR-p = 0.01). There were no significant associations between working memory and WMH in frontal ROIs. Our study demonstrates that location and pattern of frontal WMH may be important to assess when examining age-related differences in cognitive functions involving switching/set-shifting and inhibition. On the other hand, working memory performance was not related to presence of frontal WMH in this sample. These data suggest that WMH may contribute selectively to age-related declines in executive function. Findings emerged beyond predictors known to be associated with WMH presence, including age and cardiovascular disease risk. The spread of WMH within the frontal lobes may play a key role in the neuropsychological profile of cognitive aging. Further research should explore whether early intervention on modifiable vascular factors or cognitive interventions targeted for executive abilities may help mitigate the effect of frontal WMH on executive function.

Affective agnosia, an impairment in knowing how one feels emotionally, has been described as an extreme deficit in the experience and expression of emotion that may confer heightened risk for adverse medical outcomes. Alexithymia, by contrast, has been proposed as an over-arching construct that includes a spectrum of deficits of varying severity, including affective agnosia at the more severe end. This perspective has been challenged by Taylor and colleagues, who argue that the concept of affective agnosia is unnecessary. We compare these two perspectives by highlighting areas of agreement, reasons for asserting the importance of the affective agnosia concept, errors in Taylor and colleagues' critique, and measurement issues. The need for performance-based measures of the ability to mentally represent emotional states in addition to metacognitive measures is emphasized. We then draw on a previously proposed three-process model of emotional awareness that distinguishes affective response generation, conceptualization and cognitive control processes which interact to produce a variety of emotional awareness and alexithymia phenotypes - including affective agnosia. The tools for measuring these three processes, their neural substrates, the mechanisms of brain-body interactions that confer heightened risk for adverse medical outcomes, and the differential treatment implications for different kinds of deficits are described. By conceptualizing alexithymia as a spectrum of deficits, the opportunity to match specific deficit mechanisms with personalized treatment for patients will be enhanced.

We describe a new type of agnosia consisting of an impairment in the ability to mentally represent or know what one is feeling. Freud the neurologist coined the term “agnosia” in 1891 before creating psychoanalysis in 1895 but the term has not been previously applied to the domain of affective processing. We propose that the concept of “affective agnosia” advances the theory, measurement and treatment of what is now called “alexithymia,” meaning “lack of words for emotion.” We trace the origin of the alexithymia construct and discuss the strengths and limitations of extant research. We review evidence that the ability to represent and put emotions into words is a developmental achievement that strongly influences one's ability to experience, recognize, understand and use one's own emotional responses. We describe the neural substrates of emotional awareness and affective agnosia and compare and contrast these with related conditions. We then describe how this expansion of the conceptualization and measurement of affective processing deficits has important implications for basic emotion research and clinical practice.