Objective: To examine trajectories of declines in learning and retention during the predementia phase of Alzheimer’s disease (AD) using the picture version of the Free and Cued Selective Reminding Test with Immediate Recall (pFCSRT+IR). Method: Learning was defined by the sum of free recall over three test trials. Retention was defined in two ways: by delayed free recall (DFR) and by savings; DFR adjusted for learning. The performances of 217 incident AD cases from the Baltimore Longitudinal Study of Aging (BLSA) were aligned based on the time that AD was first diagnosed. The predementia phase of learning and retention decline was assessed using change point models in which cognitive trajectories are described by a series of linear components with knots delineating times of accelerating decline. Results: Trajectories for both learning and DFR had two change points: the first at 6.58 (95% confidence intervals (CI): 6.56, 6.60) to 7.29 (95% CI: 6.13, 8.46) years before diagnosis followed by gradual decline over the next 4 years, and a second acceleration of decline 1.89 (0.56, 3.24) to 2.93 (95% CI: 1.56, 4.30) years before diagnosis. The change points for DFR were not significantly earlier in the predementia phase than the change points for learning. Savings had one change point, 5.3 (95% CI: 3.56, 7.04) years before diagnosis. Conclusion: Both learning and DFR showed similar profiles of decline in the years prior to the clinical diagnosis of AD. When delayed recall was adjusted for initial learning, the measure was less sensitive to early disease. (JINS, 2019, 25, 699–705)

Objectives: Research has shown that analyzing intrusion errors generated on verbal learning and memory measures is helpful for distinguishing between the memory disorders associated with Alzheimer’s disease (AD) and other neurological disorders, including Huntington’s disease (HD). Moreover, preliminary evidence suggests that certain clinical populations may be prone to exhibit different types of intrusion errors. Methods: We examined the prevalence of two new California Verbal Learning Test-3 (CVLT-3) intrusion subtypes – across-trial novel intrusions and across/within trial repeated intrusions – in individuals with AD or HD. We hypothesized that the encoding/storage impairment associated with medial-temporal involvement in AD would result in a greater number of novel intrusions on the delayed recall trials of the CVLT-3, whereas the executive dysfunction associated with subcortical-frontal involvement in HD would result in a greater number of repeated intrusions across trials. Results: The AD group generated significantly more across-trial novel intrusions than across/within trial repeated intrusions on the delayed cued-recall trials, whereas the HD group showed the opposite pattern on the delayed free-recall trials. Conclusions: These new intrusion subtypes, combined with traditional memory analyses (e.g., recall versus recognition performance), promise to enhance our ability to distinguish between the memory disorders associated with primarily medial-temporal versus subcortical-frontal involvement.

Objectives: Reading aloud (vocal production) enhances memory relative to reading silently, the Production Effect (PE) in memory. Thus, vocalization has been suggested as a mnemonic device. The current study tested the PE in a sample of adults with ADHD and in a control sample, evaluating verbal learning. Methods: Twenty adults with ADHD and 21 controls learned a list of words, half by reading aloud and half by reading silently. Free recall test followed. The participants with ADHD performed the task twice (in two different sessions in a counterbalanced order), before self-administration of a single dose of methylphenidate (MPH) and 60-min after dosage. Results: PEs were found for all groups. Memory was better for the controls than for the ADHD group (with or without MPH). In the ADHD group, recall rates and the PE were higher with than without MPH. Conclusions: These results suggest that vocalization yields a larger memory gain with MPH. Possibly, MPH enables the ADHD participants to better shift their attention to the aloud words, enhancing their retrieval rates. Theoretically, these findings stress the role of attention in the PE. (JINS, 2019, 25, 230–235)

Objectives: The goal of the present study was to elucidate the influence of demographic and neuropathological moderators on the longitudinal trajectory neuropsychological functions during the first year after moderate to severe traumatic brain injury (TBI). In addition to examining demographic moderators such as age and education, we included a measure of whole-brain diffuse axonal injury (DAI), and examined measures of processing speed (PS), executive function (EF), and verbal learning (VL) separately. Methods: Forty-six adults with moderate to severe TBI were examined at 3, 6, and 12 months post-injury. Participants underwent neuropsychological evaluation and neuroimaging including diffusion tensor imaging. Using linear mixed effects modeling, we examined longitudinal trajectories and moderating factors of cognitive outcomes separately for three domains: PS, VL, and EF. Results: VL and EF showed linear improvements, whereas PS exhibited a curvilinear trend characterized by initial improvements that plateaued or declined, depending on age. Age moderated the recovery trajectories of EF and PS. Education and DAI did not influence trajectory but were related to initial level of functioning for PS and EF in the case of DAI, and all three cognitive domains in the case of education. Conclusions: We found disparate recovery trajectories across cognitive domains. Younger age was associated with more favorable recovery of EF and PS. These findings have both clinical and theoretical implications. Future research with a larger sample followed over a longer time period is needed to further elucidate the factors that may influence cognitive change over the acute to chronic period after TBI. (JINS, 2018, 24, 237–246)

A symptom of mild cognitive impairment (MCI) and Alzheimer’s disease(AD) is a flat learning profile. Learning slope calculation methods vary, andthe optimal method for capturing neuroanatomical changes associated with MCI andearly AD pathology is unclear. This study cross-sectionally compared fourdifferent learning slope measures from the Rey Auditory Verbal Learning Test(simple slope, regression-based slope, two-slope method, peak slope) tostructural neuroimaging markers of early AD neurodegeneration (hippocampalvolume, cortical thickness in parahippocampal gyrus, precuneus, and lateralprefrontal cortex) across the cognitive aging spectrum [normalcontrol (NC); (n=198;age=76±5), MCI (n=370;age=75±7), and AD (n=171;age=76±7)] in ADNI. Within diagnostic group,general linear models related slope methods individually to neuroimagingvariables, adjusting for age, sex, education, and APOE4 status. Among MCI,better learning performance on simple slope, regression-based slope, and lateslope (Trial 2–5) from the two-slope method related to largerparahippocampal thickness (all p-values<.01) andhippocampal volume (p<.01). Better regression-basedslope (p<.01) and late slope(p<.01) were related to larger ventrolateralprefrontal cortex in MCI. No significant associations emerged between any slopeand neuroimaging variables for NC (p-values ≥.05) orAD (p-values ≥.02). Better learning performancesrelated to larger medial temporal lobe (i.e., hippocampal volume,parahippocampal gyrus thickness) and ventrolateral prefrontal cortex in MCIonly. Regression-based and late slope were most highly correlated withneuroimaging markers and explained more variance above and beyond other commonmemory indices, such as total learning. Simple slope may offer an acceptablealternative given its ease of calculation. (JINS, 2015,21, 455–467)

Traumatic brain injury (TBI) is likely to disrupt structural network properties due to diffuse white matter pathology. The present study aimed to detect alterations in structural network topology in TBI and relate them to cognitive and real-world behavioral impairment. Twenty-two people with moderate to severe TBI with mostly diffuse pathology and 18 demographically matched healthy controls were included in the final analysis. Graph theoretical network analysis was applied to diffusion tensor imaging (DTI) data to characterize structural connectivity in both groups. Neuropsychological functions were assessed by a battery of psychometric tests and the Frontal Systems Behavior Scale (FrSBe). Local connection-wise analysis demonstrated reduced structural connectivity in TBI arising from subcortical areas including thalamus, caudate, and hippocampus. Global network metrics revealed that shortest path length in participants with TBI was longer compared to controls, and that this reduced network efficiency was associated with worse performance in executive function and verbal learning. The shortest path length measure was also correlated with family-reported FrSBe scores. These findings support the notion that the diffuse form of neuropathology caused by TBI results in alterations in structural connectivity that contribute to cognitive and real-world behavioral impairment. (JINS, 2014, 20, 1–10)

Impairments in learning and recall have been well established in amnestic mild cognitive impairment (aMCI). However, a relative dearth of studies has examined the profiles of memory strategy use in persons with aMCI relative to those with Alzheimer's disease (AD). Participants with aMCI, nonamnestic MCI, AD, and healthy older adults were administered the California Verbal Learning Test-II (CVLT-II). Measures of semantic clustering and recall were obtained across learning and delayed recall trials. In addition, we investigated whether deficits in semantic clustering were related to progression from healthy aging to aMCI and from aMCI to AD. The aMCI group displayed similar semantic clustering performance as the AD participants, whereas the AD group showed greater impairments on recall relative to the aMCI participants. Control participants who progressed to aMCI showed reduced semantic clustering at the short delay at baseline compared to individuals who remained diagnostically stable across follow-up visits. These findings show that the ability to engage in an effective memory strategy is compromised in aMCI, before AD has developed, suggesting that disruptions in semantic networks are an early marker of the disease. (JINS, 2014, 20, 1–11)

Numerous studies have shown that there are acute cognitive side-effects of chemotherapy for breast cancer. Presumably, patients are more concerned about chronic treatment effects. This report from a prospective longitudinal study compares cognitive functioning in 56 breast cancer patients 1 year after chemotherapy to that of 56 healthy individuals. Neuropsychological test scores were combined into verbal memory, visual memory, working memory, and processing speed scores, as well as an overall summary score, and analyzed using multi-level growth modeling. Frequency of cognitive decline was assessed using regression-based change scores. There was significant rebound in the overall summary score from end of treatment to 1-year follow-up as well as a substantial reduction in the frequency of cognitive decline. However, more than one-third of the breast cancer patients who showed cognitive decline immediately following completion of chemotherapy showed persistent cognitive decline 1 year later. Furthermore, recovery was not seen in all cognitive domains. In fact, the rebound was significant only for working memory. Longer multi-site studies are recommended to explore the risk factors for and the permanence of these longer-term cognitive effects. (JINS, 2013, 20, 1–10)

Age differences in verbal and spatial learning and information processing were tested using a verbal word list learning task and a spatial analogue of this task. Recall was assessed across five learning trials and the same measures of information processing and organization strategy were derived from both tasks. Normal subjects divided into three age groups of 24 subjects each were compared on these instruments. Significant age group differences were found for total recall averaged across trials and type of task (verbal vs. spatial). Age was not differentially related to verbal versus spatial learning and age groups did not show different patterns of recall across trials. Age was related to a clustering measure which assessed organization of information according to verbal semantic categories or inherent spatial clusters. Younger subjects showed increased levels of clustering on earlier learning trials. Similar effects were observed for the verbal and spatial clustering measures. Age was not related to differences in organization according to temporal order of presentation of information. Results show similar age-related changes in verbal and spatial learning and provide evidence that spatial learning, like verbal learning, is dependent upon effortful information processing.

Numerous studies have demonstrated explicit and working memory deficits related to posttraumatic stress disorder (PTSD), but few have addressed longitudinal changes in memory functioning. There is some evidence to suggest an interactive effect of PTSD and aging on verbal memory decline in Holocaust survivors (Yehuda et al., 2006). However, the longitudinal trajectory of neuropsychological functioning has not been investigated in Vietnam veterans, a younger but substantial population of aging trauma survivors. We administered tests of visual and verbal memory, and working memory to derive different dependent measures in veterans between the ages of 41 and 63, the majority of whom served in the Vietnam War. Twenty-five veterans with PTSD and 22 veterans without PTSD were assessed over two time points (mean age at follow-up = 54.0; mean inter-test interval = 34 months). The PTSD+ group, consisting of veterans with chronic, primarily combat-related PTSD, did not show a significant change in PTSD symptoms over time. Compared to veterans without PTSD, veterans with PTSD showed a greater decline in delayed facial recognition only, and this decline was extremely subtle. (JINS, 2009, 15, 853–861.)