A Network Analysis of Digital Clock Drawing for Command and Copy Conditions.

Graphomotor and time-based variables from the digital Clock Drawing Test (dCDT) characterize cognitive functions. However, no prior publications have quantified the strength of the associations between digital clock variables as they are produced. We hypothesized that analysis of the production of clock features and their interrelationships, as suggested, will differ between the command and copy test conditions. Older adults aged 65+ completed a digital clock drawing to command and copy conditions. Using a Bayesian hill-climbing algorithm and bootstrapping (10,000 samples), we derived directed acyclic graphs (DAGs) to examine network structure for command and copy dCDT variables. Although the command condition showed moderate associations between variables (µ|ßz|= 0.34) relative to the copy condition (µ|ßz| = 0.25), the copy condition network had more connections (18/18 versus 15/18 command). Network connectivity across command and copy was most influenced by five of the 18 variables. The direction of dependencies followed the order of instructions better in the command condition network. Digitally acquired clock variables relate to one another but differ in network structure when derived from command or copy conditions. Continued analyses of clock drawing production should improve understanding of quintessential normal features to aid in early neurodegenerative disease detection.

Perioperative Extracellular Brain Free-Water Changes for Older Adults Electing Total Knee Arthroplasty with General versus Spinal Anesthesia: A Pilot Study.

BACKGROUND: Recent research shows that older adults electing to undergo total knee arthroplasty with general anesthesia have a pre- to postoperative acute increase in molecular free-water within their cerebral white matter. It is unknown if this change is similar for individuals who elect spinal anesthesia methods. OBJECTIVE: To explore white matter microstructural changes in a pilot sample of older adults undergoing total knee arthroplasty and receiving general or spinal anesthesia. METHODS: We assessed acute perioperative changes in brain white matter free-water in a limited number of older adults electing total knee arthroplasty under spinal anesthesia (n = 5) and matched groups of older adults who received general anesthesia (n = 5) or had no surgery (n = 5). Patterns of free-water changes were also compared in the larger group of older adults electing total knee arthroplasty under general anesthesia (n = 61) and older adults with chronic knee pain who received no surgical intervention (n = 65). RESULTS: Our pilot results suggest older adults receiving general anesthesia had pre- to post-surgery free-water increases extensively throughout their white matter whereas those receiving spinal anesthesia appeared to have less consistent free-water increases. CONCLUSIONS: Our pilot results possibly suggest different patterns of perioperative brain white matter free-water changes based on anesthetic approach. We recommend future, larger studies to further examine the effects of anesthetic approach on perioperative brain free-water. The results of our study have potential implications for acute and chronic cognitive changes, perioperative complications, neurodegenerative processes including Alzheimer's disease, and understanding neuroinflammation.

Remote and in-clinic digital cognitive screening tools outperform the MoCA to distinguish cerebral amyloid status among cognitively healthy older adults.

INTRODUCTION: We evaluated the accuracy of remote and in-person digital tests to distinguish between older adults with and without AD pathological change and used the Montreal Cognitive Assessment (MoCA) as a comparison test. METHODS: Participants were 69 cognitively normal older adults with known beta-amyloid (Aß) PET status. Participants completed smartphone-based assessments 3×/day for 8 days, followed by TabCAT tasks, DCTclock™, and MoCA at an in-person study visit. We calculated the area under the curve (AUC) to compare task accuracies to distinguish Aß status. RESULTS: Average performance on the episodic memory (Prices) smartphone task showed the highest accuracy (AUC = 0.77) to distinguish Aß status. On in-person measures, accuracy to distinguish Aß status was greatest for the TabCAT Favorites task (AUC = 0.76), relative to the DCTclockTM (AUC = 0.73) and MoCA (AUC = 0.74). DISCUSSION: Although further validation is needed, our results suggest that several digital assessments may be suitable for more widespread cognitive screening application.

Contributions of Cardiovascular Burden, Peripheral Inflammation, and Brain Integrity on Digital Clock Drawing Performance in Non-Demented Older Adults.

BACKGROUND: Greater cardiovascular burden and peripheral inflammation are associated with dysexecutive neuropsychological profiles and a higher likelihood of conversion to vascular dementia. The digital clock drawing test (dCDT) is useful in identifying neuropsychological dysfunction related to vascular etiology. However, the specific cognitive implications of the combination of cardiovascular risk, peripheral inflammation, and brain integrity remain unknown. OBJECTIVE: We aimed to examine the role of cardiovascular burden, inflammation, and MRI-defined brain integrity on dCDT latency and graphomotor metrics in older adults. METHODS: 184 non-demented older adults (age 69±6, 16±3 education years, 46% female, 94% white) completed dCDT, vascular assessment, blood draw, and brain MRI. dCDT variables of interest: total completion time (TCT), pre-first hand latency, digit misplacement, hour hand distance from center, and clock face area. Cardiovascular burden was calculated using the Framingham Stroke Risk Profile (FSRP-10). Peripheral inflammation markers included interleukin (IL)-6, IL-8, IL-10, tumor necrosis factor-alpha, and high sensitivity C-reactive protein. Brain integrity included bilateral entorhinal cortex volume, lateral ventricular volume, and whole brain leukoaraiosis. RESULTS: FSRP-10, peripheral inflammation, and brain integrity explained an additional 14.6% of the variance in command TCT, where FSRP-10 was the main predictor. FSRP-10, inflammatory markers, and brain integrity explained an additional 17.0% in command digit misplacement variance, with findings largely driven by FSRP-10. CONCLUSION: Subtle graphomotor behavior operationalized using dCDT metrics (i.e., TCT and digit misplacement) is partly explained by cardiovascular burden, peripheral inflammation, and brain integrity and may indicate vulnerability to a disease process.

The functional connectivity and neuropsychology underlying mental planning operations: data from the digital clock drawing test.

We examined the construct of mental planning by quantifying digital clock drawing digit placement accuracy in command and copy conditions, and by investigating its underlying neuropsychological correlates and functional connectivity. We hypothesized greater digit misplacement would associate with attention, abstract reasoning, and visuospatial function, as well as functional connectivity from a major source of acetylcholine throughout the brain: the basal nucleus of Meynert (BNM). Participants (n = 201) included non-demented older adults who completed all metrics within 24 h of one another. A participant subset met research criteria for mild cognitive impairment (MCI; n = 28) and was compared to non-MCI participants on digit misplacement accuracy and expected functional connectivity differences. Digit misplacement and a comparison dissociate variable of total completion time were acquired for command and copy conditions. a priori fMRI seeds were the bilateral BNM. Command digit misplacement is negatively associated with semantics, visuospatial, visuoconstructional, and reasoning (p's < 0.01) and negatively associated with connectivity from the BNM to the anterior cingulate cortex (ACC; p = 0.001). Individuals with MCI had more misplacement and less BNM-ACC connectivity (p = 0.007). Total completion time involved posterior and cerebellar associations only. Findings suggest clock drawing digit placement accuracy may be a unique metric of mental planning and provide insight into neurodegenerative disease.

Variational autoencoder provides proof of concept that compressing CDT to extremely low-dimensional space retains its ability of distinguishing dementia.

The clock drawing test (CDT) is an inexpensive tool to screen for dementia. In this study, we examined if a variational autoencoder (VAE) with only two latent variables can capture and encode clock drawing anomalies from a large dataset of unannotated CDTs (n = 13,580) using self-supervised pre-training and use them to classify dementia CDTs (n = 18) from non-dementia CDTs (n = 20). The model was independently validated using a larger cohort consisting of 41 dementia and 50 non-dementia clocks. The classification model built with the parsimonious VAE latent space adequately classified dementia from non-dementia (0.78 area under receiver operating characteristics (AUROC) in the original test dataset and 0.77 AUROC in the secondary validation dataset). The VAE-identified atypical clock features were then reviewed by domain experts and compared with existing literature on clock drawing errors. This study shows that a very small number of latent variables are sufficient to encode important clock drawing anomalies that are predictive of dementia.

Sepsis and Cognitive Assessment.

Sepsis disproportionally affects people over the age of 65, and with an exponentially increasing older population, sepsis poses additional risks for cognitive decline. This review summarizes published literature for (1) authorship qualification; (2) the type of cognitive domains most often assessed; (3) timelines for cognitive assessment; (4) the control group and analysis approach, and (5) sociodemographic reporting. Using key terms, a PubMed database review from January 2000 to January 2021 identified 3050 articles, and 234 qualified as full text reviews with 18 ultimately retained as summaries. More than half (61%) included an author with an expert in cognitive assessment. Seven (39%) relied on cognitive screening tools for assessment with the remaining using a combination of standard neuropsychological measures. Cognitive domains typically assessed were declarative memory, attention and working memory, processing speed, and executive function. Analytically, 35% reported on education, and 17% included baseline (pre-sepsis) data. Eight (44%) included a non-sepsis peer group. No study considered sex or race/diversity in the statistical model, and only five studies reported on race/ethnicity, with Caucasians making up the majority (74%). Of the articles with neuropsychological measures, researchers report acute with cognitive improvement over time for sepsis survivors. The findings suggest avenues for future study designs.

Proof of concept: digital clock drawing behaviors prior to transcatheter aortic valve replacement may predict length of hospital stay and cost of care.

AIMS: Reduced pre-operative cognitive functioning in older adults is a risk factor for postoperative complications, but it is unknown if preoperative digitally-acquired clock drawing test (CDT) cognitive screening variables, which allow for more nuanced examination of patient performance, may predict lengthier hospital stay and greater cost of hospital care. This issue is particularly relevant for older adults undergoing transcatheter aortic valve replacement (TAVR), as this surgical procedure is chosen for intermediate-risk older adults needing aortic replacement. This proof of concept research explored if specific latency and graphomotor variables indicative of planning from digitally-acquired command and copy clock drawing would predict post-TAVR duration and cost of hospitalization, over and above age, education, American Society of Anesthesiologists (ASA) physical status classification score, and frailty. METHODS: Form January 2018 to December 2019, 162 out of 190 individuals electing TAVR completed digital clock drawing as part of a hospital wide cognitive screening program. Separate hierarchical regressions were computed for the command and copy conditions of the CDT and assessed how a-priori selected clock drawing metrics (total time to completion, ideal digit placement difference, and hour hand distance from center; included within the same block) incrementally predicted outcome, as measured by R2 change significance values. RESULTS: Above and beyond age, education, ASA physical status classification score, and frailty, only digitally-acquired CDT copy performance explained significant variance for length of hospital stay (9.5%) and cost of care (8.9%). CONCLUSIONS: Digital variables from clock copy condition provided predictive value over common demographic and comorbidity variables. We hypothesize this is due to the sensitivity of the copy condition to executive dysfunction, as has been shown in previous studies for subtypes of cognitive impairment. Individuals undergoing TAVR procedures are often frail and executively compromised due to their cerebrovascular disease. We encourage additional research on the value of digitally-acquired clock drawing within different surgery types. Type of cognitive impairment and the value of digitally-acquired CDT command and copy parameters in other surgeries remain unknown.

Classifying Non-Dementia and Alzheimer's Disease/Vascular Dementia Patients Using Kinematic, Time-Based, and Visuospatial Parameters: The Digital Clock Drawing Test.

BACKGROUND: Advantages of digital clock drawing metrics for dementia subtype classification needs examination. OBJECTIVE: To assess how well kinematic, time-based, and visuospatial features extracted from the digital Clock Drawing Test (dCDT) can classify a combined group of Alzheimer's disease/Vascular Dementia patients versus healthy controls (HC), and classify dementia patients with Alzheimer's disease (AD) versus vascular dementia (VaD). METHODS: Healthy, community-dwelling control participants (n = 175), patients diagnosed clinically with Alzheimer's disease (n = 29), and vascular dementia (n = 27) completed the dCDT to command and copy clock drawing conditions. Thirty-seven dCDT command and 37 copy dCDT features were extracted and used with Random Forest classification models. RESULTS: When HC participants were compared to participants with dementia, optimal area under the curve was achieved using models that combined both command and copy dCDT features (AUC = 91.52%). Similarly, when AD versus VaD participants were compared, optimal area under the curve was, achieved with models that combined both command and copy features (AUC = 76.94%). Subsequent follow-up analyses of a corpus of 10 variables of interest determined using a Gini Index found that groups could be dissociated based on kinematic, time-based, and visuospatial features. CONCLUSION: The dCDT is able to operationally define graphomotor output that cannot be measured using traditional paper and pencil test administration in older health controls and participants with dementia. These data suggest that kinematic, time-based, and visuospatial behavior obtained using the dCDT may provide additional neurocognitive biomarkers that may be able to identify and tract dementia syndromes.

Normative References for Graphomotor and Latency Digital Clock Drawing Metrics for Adults Age 55 and Older: Operationalizing the Production of a Normal Appearing Clock.

BACKGROUND: Relative to the abundance of publications on dementia and clock drawing, there is limited literature operationalizing 'normal' clock production. OBJECTIVE: To operationalize subtle behavioral patterns seen in normal digital clock drawing to command and copy conditions. METHODS: From two research cohorts of cognitively-well participants age 55 plus who completed digital clock drawing to command and copy conditions (n = 430), we examined variables operationalizing clock face construction, digit placement, clock hand construction, and a variety of time-based, latency measures. Data are stratified by age, education, handedness, and number anchoring. RESULTS: Normative data are provided in supplementary tables. Typical errors reported in clock research with dementia were largely absent. Adults age 55 plus produce symmetric clock faces with one stroke, with minimal overshoot and digit misplacement, and hands with expected hour hand to minute hand ratio. Data suggest digitally acquired graphomotor and latency differences based on handedness, age, education, and anchoring. CONCLUSION: Data provide useful benchmarks from which to assess digital clock drawing performance in Alzheimer's disease and related dementias.

Functional connectivity of key resting state networks and objectively measured physical activity in older adults with joint pain: A pilot study.

BACKGROUND: Greater brain network integrity may associate with physically active lifestyles. Three resting state networks may provide unique insights into known physical activity-mediated brain health benefits: the default mode network (involved with self-monitoring), the salience network (involved in orienting oneself to salient external and internal stimuli), and the central executive network (responsible for higher level cognitive task). The current study explored relationships between system-wide neural network integrity measured by functional magnetic resonance imaging and objectively-measured physical activity. We hypothesize connectivity patterns as measured by fMRI networks will relate to actigraphy markers such that 1) there will be higher connectivity within the central executive network in more physically active individuals, and 2) there will be higher connectivity within the default mode network and salience network in those with higher levels of physical activity. METHODS: Eighteen non-demented older adults with orthopedic pain (age 67.11 ± 5.61, 50% female, education 15.94 ± 2.51 years) completed brain magnetic resonance imaging, and wore an actigraphy device to objectively measure types of physical and sedentary engagement. RESULTS: Results showed a negative relationship between central executive network connectivity and sedentary time (ß = -0.108, p = .039), and a positive relationship with both moderate-to-vigorous physical activity (ß = 0.629, p = .029) and total activity time (ß = 0.645, p = .039). Results also showed positive relationships for the default mode network (ß = 0.588, p = .033) and the salience network (ß = 0.608, p = .037) with mean cadence (i.e. steps per minute). CONCLUSIONS: Our work adds to the existing literature on specific types of activity measurement (i.e. sedentary time, cadence and moderate-to-vigorous physical activity) which will be useful for interventions aimed at improving the integrity of underlying neural networks.

Parkinson's Disease Cognitive Phenotypes Show Unique Clock Drawing Features when Measured with Digital Technology.

BACKGROUND: A companion paper (Crowley et al., 2020) reports on the neuroimaging and neuropsychological profiles of statistically determined idiopathic non-dementia Parkinson's disease (PD). OBJECTIVE: The current investigation sought to further examine subtle behavioral clock drawing differences within the same PD cohort by comparing 1) PD to non-PD peers on digitally acquired clock drawing latency and graphomotor metrics, and 2) PD memory, executive, and cognitively well phenotypes on the same variables. METHODS: 230 matched participants (115 PD, 115 non-PD) completed neuropsychological tests and dCDT. Statistically-derived PD cognitive phenotypes characterized PD participants as PD low executive (PDExe; n = 25), PD low memory (PDMem; n = 34), PD cognitively well (PDWell; n = 56). Using a Bayesian framework and based on apriori hypotheses, we compared groups on: total completion time (TCT), pre-first hand latency (PFHL), post-clock face latency (PCFL), total clock face area (TCFA), and total number of pen strokes. RESULTS: Fewer strokes and slower performance to command were associated with higher odds of PD diagnosis, while a larger clock face in the copy condition was associated with lower odds of PD diagnosis. Within PD cognitive phenotypes, slower performance (TCT, PCFL) and smaller clock face to command were associated with higher odds of being PDExe than PDWell, whereas larger clock faces associated with higher odds of being PDMem than PDWell. Longer disease duration, more pen strokes (command) and smaller clocks (command) associated with higher odds of being PDExe than PDWell. CONCLUSION: Digitally-acquired clock drawing profiles differ between PD and non-PD peers, and distinguish PD cognitive phenotypes.

Phenotyping Cognitive Impairment using Graphomotor and Latency Features in Digital Clock Drawing Test.

The Clock Drawing Test, where the participant is asked to draw a clock from memory and copy a model clock, is widely used for screening of cognitive impairment. The digital version of the clock test, the digital clock drawing test (dCDT), employs accelerometer and pressure sensors of a digital pen to capture time and pressure information from a participant's performance in a granular digital format. While visual features of the clock drawing test have previously been studied, little is known about the relationship between demographic and cognitive impairment characteristics with dCDT latency and graphomotor features. Here, we examine dCDT feature clusters with respect to sociodemographic and cognitive impairment outcomes. Our results show that the clusters are not significantly different in terms of age and gender, but did significantly differ in terms of education, Mini-Mental State Exam scores, and cognitive impairment diagnoses.This study shows that features extracted from digital clock drawings can provide important information regarding cognitive reserve and cognitive impairments.

Cognitive Correlates of Digital Clock Drawing Metrics in Older Adults with and without Mild Cognitive Impairment.

BACKGROUND: A digital version of the clock drawing test (dCDT) provides new latency and graphomotor behavioral measurements. These variables have yet to be validated with external neuropsychological domains in non-demented adults. OBJECTIVE: The current investigation reports on cognitive constructs associated with selected dCDT latency and graphomotor variables and compares performances between individuals with mild cognitive impairment (MCI) and non-MCI peers. METHODS: 202 non-demented older adults (age 68.79 ± 6.18, 46% female, education years 16.02 ± 2.70) completed the dCDT and a comprehensive neuropsychological protocol. dCDT variables of interest included: total completion time (TCT), pre-first hand latency (PFHL), post-clock face latency (PCFL), and clock face area (CFA). We also explored variables of percent time drawing (i.e., 'ink time') versus percent time not drawing (i.e., 'think time'). Neuropsychological domains of interest included processing speed, working memory, language, and declarative memory. RESULTS: Adjusting for age and premorbid cognitive reserve metrics, command TCT positively correlated with multiple cognitive domains; PFHL and PCFL negatively associated with worse performance on working memory and processing speed tests. For Copy, TCT, PCFL, and PFHL negatively correlated with processing speed, and CFA negatively correlated with language. Between-group analyses show MCI participants generated slower command TCT, produced smaller CFA, and required more command 'think' (% Think) than 'ink' (% Ink) time. CONCLUSION: Command dCDT variables of interest were primarily processing speed and working memory dependent. MCI participants showed dCDT differences relative to non-MCI peers, suggesting the dCDT may assist with classification. Results document cognitive construct validation to digital metrics of clock drawing.

The oblique effect: The relationship between profiles of visuospatial preference, cognition, and brain connectomics in older adults.

The oblique effect (OE) describes the visuospatial advantage for identifying stimuli oriented horizontally or vertically rather than diagonally; little is known about brain aging and the OE. We investigated this relationship using the Judgment of Line Orientation (JLO) in 107 older adults (∼age = 67.8 ± 6.6; 51% female) together with neuropsychological tests of executive functioning (EF), attention/information processing (AIP), and neuroimaging. Only JLO lines falling between 36-54° or 126-144° were considered oblique. To quantify the oblique effect, we calculated z-scores for oblique errors (zOblique = #oblique errors/#oblique lines), and similarly, horizontal + vertical line errors (zHV), and a composite measure of oblique relative to HV errors (zOE). Composite z-scores of EF and AIP reflected domains associated with JLO performance. Graph theory analysis integrated T1-derived volumetry and diffusion MRI-derived white matter tractography into connectivity matrices analyzed for select network properties. Participants produced more zOblique than zHV errors (p < 0.001). Age was not associated with zOE adjusting for sex, education, and MMSE. Similarly adjusted linear regression models revealed that lower EF was associated with a larger oblique effect (p < 0.001). Modular analyses of neural connectivity revealed a differential patterns of network affiliation that varied by high versus low group status determined via median split of zOblique and zHV errors, separately. Older adults exhibit the oblique effect and it is associated with specific cognitive processes and regional brain networks that may facilitate future investigations of visuospatial preference in aging.

Cardiovascular disease risk factors, tract-based structural connectomics, and cognition in older adults.

Cardiovascular disease risk factors (CVD-RFs) are associated with decreased gray and white matter integrity and cognitive impairment in older adults. Less is known regarding the interplay between CVD-RFs, brain structural connectome integrity, and cognition. We examined whether CVD-RFs were associated with measures of tract-based structural connectivity in 94 non-demented/non-depressed older adults and if alterations in connectivity mediated associations between CVD-RFs and cognition. Participants (age = 68.2 years; 52.1% female; 46.8% Black) underwent CVD-RF assessment, MRI, and cognitive evaluation. Framingham 10-year stroke risk (FSRP-10) quantified CVD-RFs. Graph theory analysis integrated T1-derived gray matter regions of interest (ROIs; 23 a-priori ROIs associated with CVD-RFs and dementia), and diffusion MRI-derived white matter tractography into connectivity matrices analyzed for local efficiency and nodal strength. A principal component analysis resulted in three rotated factor scores reflecting executive function (EF; FAS, Trail Making Test (TMT) B-A, Letter-Number Sequencing, Matrix Reasoning); attention/information processing (AIP; TMT-A, TMT-Motor, Digit Symbol); and memory (CVLT-II Trials 1-5 Total, Delayed Free Recall, Recognition Discriminability). Linear regressions between FSRP-10 and connectome ROIs adjusting for word reading, intracranial volume, and white matter hyperintensities revealed negative associations with nodal strength in eight ROIs (p-values<.05) and negative associations with efficiency in two ROIs, and a positive association in one ROI (p-values<.05). There was mediation of bilateral hippocampal strength on FSRP-10 and AIP, and left rostral middle frontal gyrus strength on FSRP-10 and AIP and EF. Stroke risk plays differential roles in connectivity and cognition, suggesting the importance of multi-modal neuroimaging biomarkers in understanding age-related CVD-RF burden and brain-behavior.

Sedentary Time and White Matter Hyperintensity Volume in Older Adults.

PURPOSE: Cerebrovascular disease in the form of white matter hyperintensities (WMH) increases with age and is associated separately with sedentary time and reduced kidney function. A better understanding of the relationships among these variables would help clarify whether sedentary time should be considered more closely in older adults at particular levels of kidney function to reduce the risk of WMH. METHODS: We analyzed information from 94 healthy community-dwelling older adults to determine the association of sedentary time and WMH in nondemented, nondepressed older adults, and whether level of kidney function was an effect modifier of the relationship between sedentary time and WMH. Sedentary behavior was measured using the Sedentary Behavior Questionnaire. White matter hyperintensity was assessed using whole-brain 3T magnetic resonance imaging T1- and T2-weighted images. Kidney function was calculated by the epi-chronic kidney disease formula for estimated glomerular filtration rate (eGFR). Exposures or predictors were sedentary time, age, sex, education in years, Framingham stroke risk 10-yr prediction score, and eGFR. The analytical approach was multiple linear regression. RESULTS: Adjusting for age, sex, education in years, Framingham stroke risk 10-yr prediction score, greater sedentary time was associated with greater WMH but this effect was dependent on level of eGFR (sedentary time-eGFR interaction b = -0.0005, P = 0.022). At eGFR values of 69, 81, and 93 mL·min per 1.73 m (the 25th, 50th, and 75th percentiles), sedentary time b coefficients were b = 0.021 (95% confidence interval [CI], 0.011-0.031), b = 0.015 (95% CI, 0.008-0.022), and b = 0.009 (95% CI, 0.003-0.016). The effect weakened linearly as eGFR increased, with no significant association at eGFR ≥97 mL·min per 1.73 m. CONCLUSIONS: Findings suggest that sedentary time is associated with WMH in persons with an eGFR ≤96 mL·min per 1.73 m and that this association is stronger with lower levels of kidney function.

Associations of the Mediterranean diet with cognitive and neuroimaging phenotypes of dementia in healthy older adults.

Background: Accumulating evidence suggests that higher Mediterranean diet (MedDiet) adherence is associated with higher global cognitive performance and brain structural integrity as well as decreased risk of Alzheimer disease (AD) and vascular dementia (VaD). Objectives: We directly examined cross-sectional associations between the MedDiet and cognitive and neuroimaging phenotypes associated with AD and VaD (separately) in a cohort of nondemented, nondepressed older adults. Methods: Community-dwelling older adults (n = 82; aged ∼68.8 y; 50% female, 50% minority) underwent dietary (Block Food Frequency Questionnaire 2005) and neuropsychological assessments and neuroimaging. MedDiet scores were quantified with the use of published criteria, and participants were divided into High and Low (median split) adherence groups. We focused our neuropsychological investigation on cognitive phenotypes primarily associated with AD [i.e., learning and memory (L&M)] and VaD (i.e., information processing and executive functioning). AD neuroimaging phenotypes consisted of hippocampal and dentate gyrus volumes quantified using T1-weighted images and the FreeSurfer 6.0 segmentation pipeline (http://surfer.nmr.mgh.harvard.edu). The VaD neuroimaging phenotype consisted of total white matter hyperintensity (WMH) volumes quantified using combined T1-weighted and T2-fluid-attenuated inversion recovery images. Neuroimaging metrics were adjusted for total intracranial volume. Separate multivariable linear regression models controlling for age, sex, education, body mass index, and caloric intake examined the associations between MedDiet groups (High compared with Low) and cognitive and neuroimaging outcomes. Results: When compared with the Low MedDiet group, the High MedDiet group was associated with better L&M performance and larger dentate gyri. MedDiet adherence was not associated with information processing, executive functioning, or WMH. Conclusion: Results highlight the association between increasing MedDiet adherence and specific cognitive and neuroimaging phenotypes that, when altered, are associated with AD.

Multidimensional prediction of treatment response to antidepressants with cognitive control and functional MRI.

Predicting treatment response for major depressive disorder can provide a tremendous benefit for our overstretched health care system by reducing number of treatments and time to remission, thereby decreasing morbidity. The present study used neural and performance predictors during a cognitive control task to predict treatment response (% change in Hamilton Depression Rating Scale pre- to post-treatment). Forty-nine individuals diagnosed with major depressive disorder were enrolled with intent to treat in the open-label study; 36 completed treatment, had useable data, and were included in most data analyses. Participants included in the data analysis sample received treatment with escitalopram (n = 22) or duloxetine (n = 14) for 10 weeks. Functional MRI and performance during a Parametric Go/No-go test were used to predict per cent reduction in Hamilton Depression Rating Scale scores after treatment. Haemodynamic response function-based contrasts and task-related independent components analysis (subset of sample: n = 29) were predictors. Independent components analysis component beta weights and haemodynamic response function modelling activation during Commission errors in the rostral and dorsal anterior cingulate, mid-cingulate, dorsomedial prefrontal cortex, and lateral orbital frontal cortex predicted treatment response. In addition, more commission errors on the task predicted better treatment response. Together in a regression model, independent component analysis, haemodynamic response function-modelled, and performance measures predicted treatment response with 90% accuracy (compared to 74% accuracy with clinical features alone), with 84% accuracy in 5-fold, leave-one-out cross-validation. Convergence between performance markers and functional magnetic resonance imaging, including novel independent component analysis techniques, achieved high accuracy in prediction of treatment response for major depressive disorder. The strong link to a task paradigm provided by use of independent component analysis is a potential breakthrough that can inform ways in which prediction models can be integrated for use in clinical and experimental medicine studies.

Comorbid anxiety increases cognitive control activation in Major Depressive Disorder.

BACKGROUND: Major Depressive Disorder (MDD) and anxiety disorders often co-occur, with poorer treatment response and long-term outcomes. However, little is known about the shared and distinct neural mechanisms of comorbid MDD and anxiety (MDD+Anx). This study examined how MDD and MDD+Anx differentially impact cognitive control. METHODS: Eighteen MDD, 29 MDD+Anx, and 54 healthy controls (HC) completed the Parametric Go/No-Go (PGNG) during fMRI, including Target, Commission, and Rejection trials. RESULTS: MDD+Anx had more activation in the anterior dorsolateral prefrontal cortex, hippocampus, and caudate during Rejections, and inferior parietal lobule during correct Targets than MDD and HC. During Rejections HC had greater activation in a number of cognitive control regions compared to MDD; in the posterior cingulate compared to MDD+Anx; and in the fusiform gyrus compared to all MDD. During Commissions HC had greater activation in the right inferior frontal gyrus than all MDD. MDD had more activation in the mid-cingulate, inferior parietal lobule, and superior temporal gyrus than MDD+Anx during Commissions. CONCLUSIONS: Despite similar performance, MDD and MDD+Anx showed distinct differences in neural mechanisms of cognitive control in relation to each other, as well as some shared differences in relation to HC. The results were consistent with our hypothesis of hypervigilance in MDD+Anx within the cognitive control network, but inconsistent with our hypothesis that there would be greater engagement of salience and emotion network regions. Comorbidity of depression and anxiety may cause increased heterogeneity in study samples, requiring further specificity in detection and measurement of intermediate phenotypes and treatment Targets.