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Global initiatives call for further understanding of the impact of inequity on aging across underserved populations. Previous research in low- and middle-income countries (LMICs) presents limitations in assessing combined sources of inequity and outcomes (i.e., cognition and functionality). In this study, we assessed how social determinants of health (SDH), cardiometabolic factors (CMFs), and other medical/social factors predict cognition and functionality in an aging Colombian population. We ran a cross-sectional study that combined theory- (structural equation models) and data-driven (machine learning) approaches in a population-based study (N = 23,694;M = 69.8 years) to assess the best predictors of cognition and functionality. We found that a combination of SDH and CMF accurately predicted cognition and functionality, although SDH was the stronger predictor. Cognition was predicted with the highest accuracy by SDH, followed by demographics, CMF, and other factors. A combination of SDH, age, CMF, and additional physical/psychological factors were the best predictors of functional status. Results highlight the role of inequity in predicting brain health and advancing solutions to reduce the cognitive and functional decline in LMICs.

International audience

Objective. The differential diagnosis of behavioral variant frontotemporal dementia (bvFTD) and Alzheimer’s disease (AD) remains challenging in underrepresented, underdiagnosed groups, including Latinos, as advanced biomarkers are rarely available. Recent guidelines for the study of dementia highlight the critical role of biomarkers. Thus, novel cost-effective complementary approaches are required in clinical settings. Approach. We developed a novel framework based on a gradient boosting machine learning classifier, tuned by Bayesian optimization, on a multi-feature multimodal approach (combining demographic, neuropsychological, magnetic resonance imaging (MRI), and electroencephalography/functional MRI connectivity data) to characterize neurodegeneration using site harmonization and sequential feature selection. We assessed 54 bvFTD and 76 AD patients and 152 healthy controls (HCs) from a Latin American consortium (ReDLat). Main results. The multimodal model yielded high area under the curve classification values (bvFTD patients vs HCs: 0.93 (±0.01); AD patients vs HCs: 0.95 (±0.01); bvFTD vs AD patients: 0.92 (±0.01)). The feature selection approach successfully filtered non-informative multimodal markers (from thousands to dozens). Results. Proved robust against multimodal heterogeneity, sociodemographic variability, and missing data. Significance. The model accurately identified dementia subtypes using measures readily available in underrepresented settings, with a similar performance than advanced biomarkers. This approach, if confirmed and replicated, may potentially complement clinical assessments in developing countries.

Across Latin American and Caribbean countries (LACs), the fight against dementia faces pressing challenges, such as heterogeneity, diversity, political instability, and socioeconomic disparities. These can be addressed more effectively in a collaborative setting that fosters open exchange of knowledge. In this work, the Latin American and Caribbean Consortium on Dementia (LAC-CD) proposes an agenda for integration to deliver a Knowledge to Action Framework (KtAF). First, we summarize evidence-based strategies (epidemiology, genetics, biomarkers, clinical trials, nonpharmacological interventions, networking, and translational research) and align them to current global strategies to translate regional knowledge into transformative actions. Then we characterize key sources of complexity (genetic isolates, admixture in populations, environmental factors, and barriers to effective interventions), map them to the above challenges, and provide the basic mosaics of knowledge toward a KtAF. Finally, we describe strategies supporting the knowledge creation stage that underpins the translational impact of KtAF. Fil: Parra, Mario Alfredo. Universidad Autónoma del Caribe; Colombia Fil: Baez, Sandra. Universidad de los Andes; Colombia Fil: Sedeño, Lucas. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Gonzalez Campo, Cecilia. Universidad de San Andrés; Argentina Fil: Santamaría García, Hernando. Pontificia Universidad Javeriana; Colombia Fil: Aprahamian, Ivan. No especifíca; Fil: Bertolucci, Paulo. Universidade Federal de Sao Paulo; Brasil Fil: Bustin, Julian. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina Fil: Camargos Bicalho, Maria Aparecida. Universidade Federal de Minas Gerais; Brasil Fil: Cano Gutierrez, Carlos. Hospital Universitario San Ignacio; Colombia Fil: Caramelli, Paulo. Universidade Federal de Minas Gerais; Brasil Fil: Chaves, Marcia L. F.. Universidade Federal do Rio Grande do Sul; Brasil Fil: Perez Cogram, Patricia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina Fil: Beber, Bárbara Costa. Universidade Federal do Rio Grande do Sul; Brasil Fil: Court, Felipe A.. Universidad Mayor; Chile Fil: de Souza, Leonardo Cruz. Universidade Federal de Minas Gerais; Brasil Fil: Custodio, Nilton. Peruvian Institute of Neurosciences; Perú Fil: Damian, Andres. Universidad de la República; Uruguay Fil: de la Cruz, Myriam. University of California; Estados Unidos Fil: Diehl Rodriguez, Roberta. Universidade de Sao Paulo; Brasil Fil: Dozzi Brucki, Sonia Maria. Universidade de Sao Paulo; Brasil Fil: Fajersztajn, Lais. Universidade de Sao Paulo; Brasil Fil: Farías, Gonzalo A.. Universidad de Chile; Chile Fil: De Felice, Fernanda G.. Universidade Federal do Rio de Janeiro; Brasil Fil: Ferrari, Raffaele. Colegio Universitario de Londres; Reino Unido Fil: Ferreira de Oliveira, Fabricio. Universidade de Sao Paulo; Brasil Fil: Ferreira, Sergio Teixeira. Universidade Federal do Rio de Janeiro; Brasil Fil: Ferretti, Ceres. Universidade de Sao Paulo; Brasil Fil: Figueredo Balthazar, Marcio Luiz. Universidade Estadual de Campinas; Brasil Fil: Ferreira Frota, Norberto Anizio. Universidade de Fortaleza; Brasil Fil: Fuentes, Patricio. No especifíca; Fil: García, Adolfo Martín. Universidad Nacional de Cuyo; Argentina. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Garcia, Patricia J.. Cayetano Heredia University; Perú Fil: de Gobbi Porto, Fábio Henrique. Universidade de Sao Paulo; Brasil Fil: Duque Peñailillo, Lissette. Ecuadorian Dementia Association; Ecuador Fil: Engler, Henry Willy. Universidad de la República; Uruguay Fil: Maier, Irene. Universidad de Chile; Chile Fil: Mata, Ignacio F.. University of Pittsburgh; Estados Unidos Fil: González Billault, Christian. Universidad de Chile; Chile Fil: Lopez, Oscar L.. University of Pittsburgh; Estados Unidos Fil: Morelli, Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; Argentina Fil: Nitrini, Ricardo. Universidade de Sao Paulo; Brasil Fil: Quiroz, Yakeel T.. Harvard Medical School; Estados Unidos Fil: Guerrero Barragan, Alejandra. Universidad de la Sabana; Colombia Fil: Huepe, David. Universidad Adolfo Ibañez; Chile Fil: Pio, Fabricio Joao. Hospital Governador Celso Ramos; Brasil Fil: Suemoto, Claudia Kimie. Universidade de Sao Paulo; Brasil Fil: Kochhann, Renata. Pontificia Universidade Católica do Rio Grande do Sul; Brasil Fil: Kochen, Sara Silvia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia "Prof. Eduardo de Robertis". Universidad de Buenos Aires. Facultad de Medicina. Instituto de Biología Celular y Neurociencia; Argentina Fil: Kumfor, Fiona. University of Western Sydney; Australia Fil: Lanata, Serggio. University of California; Estados Unidos Fil: Miller, Bruce. University of California; Estados Unidos Fil: Lessa Mansur, Leticia. Universidade de Sao Paulo; Brasil Fil: Lie Hosogi, Mirna. Universidade de Sao Paulo; Brasil Fil: Lillo, Patricia. Universidad de Chile; Chile Fil: Llibre Guerra, Jorge. University of California; Estados Unidos Fil: Lira, David. Peruvian Institute of Neurosciences; Perú Fil: Lopera, Francisco. Universidad de Antioquia; Colombia Fil: Comas, Adelina. No especifíca; Fil: Avila Funes, José Alberto. Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán; México Fil: Sosa, Ana Luisa. Instituto Nacional de Neurología y Neurocirugía; México Fil: Ramos, Claudia. University of California; Estados Unidos Fil: de Paula França Resende, Elisa. University of California; Estados Unidos Fil: Snyder, Heather M.. No especifíca; Fil: Tarnanas, Ioannis. University of California; Estados Unidos Fil: Yokoyama, Jenifer. University of California; Estados Unidos Fil: Llibre, Juan. Centro de Estudios de Alzheimer; Cuba Fil: Cardona Londoño, Juan Felipe. Universidad del Valle; Colombia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Possin, Kate. University of California; Estados Unidos Fil: Kosik, Kenneth. University of California; Estados Unidos Fil: Montesinos, Rosa. Peruvian Institute of Neurosciences; Perú Fil: Moguilner, Sebastian Gabriel. University of California; Estados Unidos Fil: Solis, Patricia Cristina Lourdes. Provincia de Buenos Aires. Ministerio de Salud. Hospital Alta Complejidad en Red El Cruce Dr. Néstor Carlos Kirchner Samic; Argentina. Universidad Nacional Arturo Jauretche; Argentina. Universidad de Buenos Aires; Argentina Fil: de Lucena Ferretti Rebustini, Renata Eloah. Universidade de Sao Paulo; Brasil Fil: Ramirez, Jeronimo Martin. No especifíca; Fil: Matallana, Diana. Pontificia Universidad Javeriana; Colombia Fil: Mbakile Mahlanza, Lingani. University of California; Estados Unidos Fil: Mendonça Marques Ton, Alyne. Universidade Federal do Rio de Janeiro; Brasil Fil: Melo Tavares, Ronnielly. Centro Universitario de Belo Horizonte.; Brasil Fil: Miotto, Eliane C.. Universidade de Sao Paulo; Brasil Fil: Muniz-Terrera, Graciela. University of Edinburgh; Reino Unido Fil: MuñozN evárez, Luis Arnoldo. University of California; Estados Unidos Fil: Orozco, David. Universidad Nacional del Sur; Argentina Fil: Okada de Oliveira, Maira. University of California; Estados Unidos Fil: Piguet, Olivier. University of Western Sydney; Australia Fil: Pintado Caipa, Maritza. University of California; Estados Unidos Fil: Piña Escudero, Stefanie Danielle. University of California; Estados Unidos Fil: Porcello Schilling, Lucas. Pontificia Universidade Católica do Rio Grande do Sul; Brasil Fil: Rodrigues Palmeira, André Luiz. Hospital Ernesto Dornelles; Brasil Fil: Sanches Yassuda, Mônica. Universidade de Sao Paulo; Brasil Fil: Santacruz Escudero, Jose Manuel. Pontificia Universidad Javeriana; Colombia Fil: Serafim, Rodrigo Bernardo. Universidade Federal do Rio de Janeiro; Brasil Fil: Smid, Jerusa. Universidade de Sao Paulo; Brasil Fil: Slachevsky, Andrea. Universidad de Chile; Chile Fil: Serrano, Cecilia Mariela. No especifíca; Fil: Soto Añari, Marcio. Universidad Católica San Pablo; Perú Fil: Takada, Leonel Tadao. Universidade de Sao Paulo; Brasil Fil: Tenenholz Grinberg, Lea. Universidade de Sao Paulo; Brasil Fil: Teixeira, Antonio Lucio. Universidade Federal de Minas Gerais; Brasil Fil: Tonidandel Barbosa, Maira. Universidade Federal de Minas Gerais; Brasil Fil: Trépel, Dominic. Trinity College; Estados Unidos Fil: Ibañez, Agustin Mariano. Universidad Autónoma del Caribe; Colombia. Universidad Adolfo Ibañez; Chile. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina

Social factors, such as social cognition skills (SCS) and social determinants of health (SDH), may be vital for mental health, even when compared with classical psycho-physical predictors (demographic, physical, psychiatric, and cognitive factors). Although major risk factors for psychiatric disorders have been previously assessed, the relative weight of SCS and SDH in relation to classical psycho-physical predictors in predicting symptoms of mental disorders remains largely unknown. In this study, we implemented multiple structural equation models (SEM) from a randomized sample assessed in the Colombian National Mental Health Survey of 2015 (CNMHS, n = 2947, females: 1348) to evaluate the role of SCS, SDH, and psycho-physical factors (totaling 17 variables) as predictors of mental illness symptoms (anxiety, depression, and other psychiatric symptoms). Speci!cally, we assessed the structural equation modeling of (a) SCS (emotion recognition and empathy skills); (b) SDH (including the experience of social adversities and social protective factors); (c) and classical psycho-physical factors, including psychiatric antecedents, physical–somatic factors (chronic diseases), and cognitive factors (executive functioning). Results revealed that the emotion recognition skills, social adverse factors, antecedents of psychiatric disorders and chronic diseases, and cognitive functioning were the best predictors of symptoms of mental illness. Moreover, SCS, particularly emotion recognition skills, and SDH (experiences of social adversities, familial, and social support networks) reached higher predictive values of symptoms than classical psycho-physical factors. Our study provides unprecedented evidence on the impact of social factors in predicting symptoms of mental illness and highlights the relevance of these factors to track early states of disease. CONICET, ANID/FONDAP (15150012) PICT (2017-1818 and 2017-1820) the Inter-American Development Bank (IDB) GBHI ALZ UK-20-639295 NIH/NIA R01 AG057234 Sistema General de Regalías [BPIN2018000100059] Universidad del valle [CI 5316] Colciencias Colombia Ministerio de Salud Colombia, Grant 762-201 National Institutes of Aging of the National Institutes of Health, an Alzheimer’s Association grant (SG-20-725707-ReDLat) Rainwater Foundation Global Brain Health Institute UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias de la Salud::Centro de Investigación en Neurociencias (CIN) UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Sociales::Instituto de Investigaciones Psicológicas (IIP)

Measures of social cognition have now become central in neuropsychology, being essential for early and differential diagnoses, follow-up, and rehabilitation in a wide range of conditions. With the scientific world becoming increasingly interconnected, international neuropsychological and medical collaborations are burgeoning to tackle the global challenges that are mental health conditions. These initiatives commonly merge data across a diversity of populations and countries, while ignoring their specificity.In this context, we aimed to estimate the influence of participants' nationality on social cognition evaluation. This issue is of particular importance as most cognitive tasks are developed in highly specific contexts, not representative of that encountered by the world's population.Through a large international study across 18 sites, neuropsychologists assessed core aspects of social cognition in 587 participants from 12 countries using traditional and widely used tasks.Age, gender, and education were found to impact measures of mentalizing and emotion recognition. After controlling for these factors, differences between countries accounted for more than 20% of the variance on both measures. Importantly, it was possible to isolate participants' nationality from potential translation issues, which classically constitute a major limitation.Overall, these findings highlight the need for important methodological shifts to better represent social cognition in both fundamental research and clinical practice, especially within emerging international networks and consortia. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

BackgroundThe triggering receptor expressed on myeloid cell 2 (TREM2) is a major regulator of neuroinflammatory processes in neurodegeneration. To date, the p.H157Y variant ofTREM2has been reported only in patients with Alzheimer’s disease. Here, we report three patients with frontotemporal dementia (FTD) from three unrelated families with heterozygous p.H157Y variant ofTREM2: two patients from Colombian families (study 1) and a third Mexican origin case from the USA (study 2).MethodsTo determine if the p.H157Y variant might be associated with a specific FTD presentation, we compared in each study the cases with age-matched, sex-matched and education-matched groups—a healthy control group (HC) and a group with FTD with neitherTREM2mutations nor family antecedents (Ng-FTD and Ng-FTD-MND).ResultsThe two Colombian cases presented with early behavioural changes, greater impairments in general cognition and executive function compared with both HC and Ng-FTD groups. These patients also exhibited brain atrophy in areas characteristic of FTD. Furthermore, TREM2 cases showed increased atrophy compared with Ng-FTD in frontal, temporal, parietal, precuneus, basal ganglia, parahippocampal/hippocampal and cerebellar regions. The Mexican case presented with FTD and motor neuron disease (MND), showing grey matter reduction in basal ganglia and thalamus, and extensive TDP-43 type B pathology.ConclusionIn all TREM2 cases, multiple atrophy peaks overlapped with the maximum peaks ofTREM2gene expression in crucial brain regions including frontal, temporal, thalamic and basal ganglia areas. These results provide the first report of an FTD presentation potentially associated with the p.H157Y variant with exacerbated neurocognitive impairments.

Background The Colombian population, as well as those in other Latin American regions, arose from a recent tri-continental admixture among Native Americans, Spanish invaders, and enslaved Africans, all of whom passed through a population bottleneck due to widespread infectious diseases that left small isolated local settlements. As a result, the current population reflects multiple founder effects derived from diverse ancestries. Methods We characterized the role of admixture and founder effects on the origination of the mutational landscape that led to neurodegenerative disorders under these historical circumstances. Genomes from 900 Colombian individuals with Alzheimer’s disease (AD) [n = 376], frontotemporal lobar degeneration-motor neuron disease continuum (FTLD-MND) [n = 197], early-onset dementia not otherwise specified (EOD) [n = 73], and healthy participants [n = 254] were analyzed. We examined their global and local ancestry proportions and screened this cohort for deleterious variants in disease-causing and risk-conferring genes. Results We identified 21 pathogenic variants in AD-FTLD related genes, and PSEN1 harbored the majority (11 pathogenic variants). Variants were identified from all three continental ancestries. TREM2 heterozygous and homozygous variants were the most common among AD risk genes (102 carriers), a point of interest because the disease risk conferred by these variants differed according to ancestry. Several gene variants that have a known association with MND in European populations had FTLD phenotypes on a Native American haplotype. Consistent with founder effects, identity by descent among carriers of the same variant was frequent. Conclusions Colombian demography with multiple mini-bottlenecks probably enhanced the detection of founder events and left a proportionally higher frequency of rare variants derived from the ancestral populations. These findings demonstrate the role of genomically defined ancestry in phenotypic disease expression, a phenotypic range of different rare mutations in the same gene, and further emphasize the importance of inclusiveness in genetic studies.

From molecular mechanisms to global brain networks, atypical fluctuations are the hallmark of neurodegeneration. Yet, traditional fMRI research on resting-state networks (RSNs) has favored static and average connectivity methods, which by overlooking the fluctuation dynamics triggered by neurodegeneration, have yielded inconsistent results. The present multicenter study introduces a data-driven machine learning pipeline based on dynamic connectivity fluctuation analysis (DCFA) on RS-fMRI data from 300 participants belonging to three groups: behavioral variant frontotemporal dementia (bvFTD) patients, Alzheimer's disease (AD) patients, and healthy controls. We considered non-linear oscillatory patterns across combined and individual resting-state networks (RSNs), namely: the salience network (SN), mostly affected in bvFTD; the default mode network (DMN), mostly affected in AD; the executive network (EN), partially compromised in both conditions; the motor network (MN); and the visual network (VN). These RSNs were entered as features for dementia classification using a recent robust machine learning approach (a Bayesian hyperparameter tuned Gradient Boosting Machines (GBM) algorithm), across four independent datasets with different MR scanners and recording parameters. The machine learning classification accuracy analysis revealed a systematic and unique tailored architecture of RSN disruption. The classification accuracy ranking showed that the most affected networks for bvFTD were the SN + EN network pair (mean accuracy = 86.43%, AUC = 0.91, sensitivity = 86.45%, specificity = 87.54%); for AD, the DMN + EN network pair (mean accuracy = 86.63%, AUC = 0.89, sensitivity = 88.37%, specificity = 84.62%); and for the bvFTD vs. AD classification, the DMN + SN network pair (mean accuracy = 82.67%, AUC = 0.86, sensitivity = 81.27%, specificity = 83.01%). Moreover, the DFCA classification systematically outperformed canonical connectivity approaches (including both static and linear dynamic connectivity). Our findings suggest that non-linear dynamical fluctuations surpass two traditional seed-based functional connectivity approaches and provide a pathophysiological characterization of global brain networks in neurodegenerative conditions (AD and bvFTD) across multicenter data.

Accurate early diagnosis of neurodegenerative diseases represents a growing challenge for current clinical practice. Promisingly, current tools can be complemented by computational decision-support methods to objectively analyze multidimensional measures and increase diagnostic confidence. Yet, widespread application of these tools cannot be recommended unless they are proven to perform consistently and reproducibly across samples from different countries. We implemented machine-learning algorithms to evaluate the prediction power of neurocognitive biomarkers (behavioral and imaging measures) for classifying two neurodegenerative conditions –Alzheimer Disease (AD) and behavioral variant frontotemporal dementia (bvFTD)– across three different countries (>200 participants). We use machine-learning tools integrating multimodal measures such as cognitive scores (executive functions and cognitive screening) and brain atrophy volume (voxel based morphometry from fronto-temporo-insular regions in bvFTD, and temporo-parietal regions in AD) to identify the most relevant features in predicting the incidence of the diseases. In the Country-1 cohort, predictions of AD and bvFTD became maximally improved upon inclusion of cognitive screenings outcomes combined with atrophy levels. Multimodal training data from this cohort allowed predicting both AD and bvFTD in the other two novel datasets from other countries with high accuracy (>90%), demonstrating the robustness of the approach as well as the differential specificity and reliability of behavioral and neural markers for each condition. In sum, this is the first study, across centers and countries, to validate the predictive power of cognitive signatures combined with atrophy levels for contrastive neurodegenerative conditions, validating a benchmark for future assessments of reliability and reproducibility. Fil: Bachli, M. Belen. Universidad Nacional de San Martín; Argentina Fil: Sedeño, Lucas. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina Fil: Ochab, Jeremi K.. No especifíca; Fil: Piguet, Olivier. University Of Technology Sydney.; Australia Fil: Kumfor, Fiona. University Of Technology Sydney.; Australia Fil: Reyes, Pablo. Hospital Universitario San Ignacio; Colombia Fil: Torralva, Teresa. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Instituto de Neurología Cognitiva. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Fundación Favaloro. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt; Argentina Fil: Roca, María. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Instituto de Neurología Cognitiva. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Fundación Favaloro. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt; Argentina Fil: Cardona, Juan Felipe. Universidad del Valle; Colombia Fil: Gonzalez Campo, Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Instituto de Neurología Cognitiva. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Fundación Favaloro. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt; Argentina Fil: Herrera, Eduar. Universidad Icesi; Colombia Fil: Slachevsky, Andrea. Universidad del Desarrollo; Chile Fil: Matallana, Diana. Pontificia Universidad Javeriana; Colombia Fil: Manes, Facundo Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Instituto de Neurología Cognitiva. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Fundación Favaloro. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt; Argentina Fil: García, Adolfo Martín. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Instituto de Neurología Cognitiva. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Fundación Favaloro. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt; Argentina. Universidad Nacional de Cuyo. Facultad de Educación Elemental y Especial; Argentina Fil: Ibañez, Agustin Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Instituto de Neurología Cognitiva. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Fundación Favaloro. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt; Argentina. Universidad Adolfo Ibañez; Chile Fil: Chialvo, Dante Renato. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Instituto de Neurología Cognitiva. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Fundación Favaloro. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt; Argentina

Background: Social factors, such as social cognition skills (SCS) and social determinants of health (SDH), may be vital for mental health, even when compared with classical psycho-physical predictors (demographic, physical, psychiatric, and cognitive factors). Although major risk factors for psychiatric disorders have been previously assessed, the relative weight of SCS and SDH in relation to classical psycho-physical predictors in predicting symptoms of mental disorders remains largely unknown. Methods: In this study, we implemented multiple structural equation models (SEM) from a randomized sample assessed in the Colombian National Mental Health Survey of 2015 (CNMHS, n=2,947) to evaluate the role of SCS, SDH and psycho-physical factors (totaling 17 variables) as predictors of mental illness symptoms (anxiety, depression and other psychiatric symptoms). Specifically, we assessed the structural equation modeling of (a) SCS (emotion recognition and empathy skills); (b) SDH (including the experience of social adversities and social protective factors); (c) and classical psycho-physical factors, including psychiatric antecedents, physical-somatic factors (chronic diseases), and cognitive factors (executive functioning). Findings: Results revealed that emotion recognition skills, social adverse factors, past medical history of psychiatric disorders, the presence of chronic diseases and cognitive functioning were the best predictors of symptoms of mental illness. Moreover, SCS, particularly emotion recognition skills, and SDH (experiences of social adversities, familial and social support networks) reached higher predictive values of symptoms of mental illness than classical psycho-physical factors. Interpretation: Our study provides unprecedented evidence on the impact of social factors in predicting symptoms of mental illness and highlights the relevance of these factors to track early states of disease. Funding Statement: AI is partially supported by CONICET, CONICYT/FONDECYT (Regular 1170010 and 1171200), FONDAP (15150012), the INECO Foundation, PICT (2017-1818 and 2017- 1820), the Inter-American Development Bank (IDB), the Global Brain Health Institute (GBHI), GBHI ALZ UK-20-639295, and NIH/NIA R01 AG057234. This study has been partially supported by Colciencias Colombia and the Ministerio de Salud Colombia, Grant 762-201. Declaration of Interests: The authors declare neither competing financial interests nor other conflicts of interest. Ethics Approval Statement: The study was approved by the institutional ethics committee.

The SARS-CoV-2 global pandemic will disproportionately impact countries with weak economies and vulnerable populations including people with dementia. Latin American and Caribbean countries (LACs) are burdened with unstable economic development, fragile health systems, massive economic disparities, and a high prevalence of dementia. Here, we underscore the selective impact of SARS-CoV-2 on dementia among LACs, the specific strain on health systems devoted to dementia, and the subsequent effect of increasing inequalities among those with dementia in the region. Implementation of best practices for mitigation and containment faces particularly steep challenges in LACs. Based upon our consideration of these issues, we urgently call for a coordinated action plan, including the development of inexpensive mass testing and multilevel regional coordination for dementia care and related actions. Brain health diplomacy should lead to a shared and escalated response across the region, coordinating leadership, and triangulation between governments and international multilateral networks. Fil: Ibañez, Agustin Mariano. Universidad Adolfo Ibáñez; Chile. Universidad de San Andrés; Argentina. Universidad Autónoma del Caribe; Colombia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Santamaria Garcia, Hernando. Pontificia Universidad Javeriana; Colombia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Guerrero Barragan, Alejandra. University of California; Estados Unidos Fil: Kornhuber, Alexander. University of California; Estados Unidos Fil: Mendonca Marques Ton, Alyne. Universidade Vila Velha; Brasil Fil: Slachevsky, Andrea. Universidad de Chile; Chile Fil: Teixeira, Antonio Lucio. No especifíca; Fil: Mar Meza, Beatriz Marcela. University of California; Estados Unidos Fil: Serrano, Cecilia Mariela. Unidad Asistencial "Dr. César Milstein"; Argentina Fil: Cano, Carlos. Pontificia Universidad Javeriana; Colombia Fil: Arias Gonzalez, Carolina. University of California; Estados Unidos Fil: González Billault, Christian. Universidad de Chile; Chile Fil: Butler, Christopher. University of Oxford; Reino Unido. Pontificia Universidad Católica de Chile; Chile Fil: Bustin, Julian. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Instituto de Neurología Cognitiva. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Fundación Favaloro. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt; Argentina Fil: Duran Aniotz, Claudia. Universidad Adolfo Ibañez; Chile Fil: Acosta, Daisy. Universidad Nacional Pedro Henríquez Ureña; República Dominicana Fil: Matallana, Diana L.. Pontificia Universidad Javeriana; Colombia Fil: Acosta Alvear, Diego. University of California; Estados Unidos Fil: Trépel, Dominic. No especifíca; Fil: De Paula França Resende, Elisa. University of California; Estados Unidos. Universidade Federal do Rio de Janeiro; Brasil Fil: Ferreira de Oliveira, Fabricio. Universidade Federal de Sao Paulo; Brasil Fil: Ibanez, Francisco. Universidad Nacional de San Juan; Argentina Fil: De Felice, Fernanda G.. Universidade Federal do Rio de Janeiro; Brasil Fil: Navarrete, Gorka. Universidad Adolfo Ibañez; Chile Fil: Tarnanas, Ioannis. No especifíca; Fil: Meier, Irene B.. No especifíca; Fil: Smid, Jerusa. No especifíca; Fil: Llibre-Guerra, Jorge. University of California; Estados Unidos Fil: Llibre Rodriguez, Juan J.. Universidad de Ciencias Médicas; Cuba Fil: Fajersztajn, Laís. University of California; Estados Unidos. Universidade de Sao Paulo; Brasil Fil: Tadao Takada, Leonel. Universidade de Sao Paulo; Brasil Fil: Duque, Lissette. National Commission In Bioethics; Ecuador Fil: Okada de Oliveira, Maira. Universidade de Sao Paulo; Brasil Fil: Aparecida Camargos Bicalho, Maria. Universidade Federal de Minas Gerais; Brasil Fil: Behrens, María Isabel. Universidad Nacional de San Juan; Argentina. Universidad de Chile; Chile Fil: Pintado Caipa, Maritza. University of California; Estados Unidos Fil: Parra, Mario. University of Strathclyde; Reino Unido Fil: Wilson, Maxwell Z.. University of California; Estados Unidos Fil: De La Cruz Puebla, Myriam. Universidad de Barcelona; España. University of California; Estados Unidos Fil: Custodio, Nilton. Peruvian National Institute Of Health; Perú Fil: Santibanez, Rodrigo. Pontificia Universidad Católica de Chile; Chile. Universidad Católica de Chile; Chile Fil: Serafim, Rodrigo Bernardo. No especifíca; Fil: Melo Tavares, Ronnielly. Universidade Federal do Rio de Janeiro; Brasil Fil: Piña Escudero, Stefanie Danielle. University of California; Estados Unidos Fil: Rodriguez, Tomas Leon. Universidad de Chile; Chile Fil: Dawson, Walter. University of California; Estados Unidos Fil: Miller, Bruce L.. University of California; Estados Unidos Fil: Kosik, Kenneth. University of California; Estados Unidos

Introduction Timely diagnosis of behavioral variant frontotemporal dementia (bvFTD) remains challenging because it depends on clinical expertise and potentially ambiguous diagnostic guidelines. Recent recommendations highlight the role of multimodal neuroimaging and machine learning methods as complementary tools to address this problem. Methods We developed an automatic, cross-center, multimodal computational approach for robust classification of patients with bvFTD and healthy controls. We analyzed structural magnetic resonance imaging and resting-state functional connectivity from 44 patients with bvFTD and 60 healthy controls (across three imaging centers with different acquisition protocols) using a fully automated processing pipeline, including site normalization, native space feature extraction, and a random forest classifier. Results Our method successfully combined multimodal imaging information with high accuracy (91%), sensitivity (83.7%), and specificity (96.6%). Discussion This multimodal approach enhanced the system's performance and provided a clinically informative method for neuroimaging analysis. This underscores the relevance of combining multimodal imaging and machine learning as a gold standard for dementia diagnosis., Highlights • A multimodal computational approach was implemented to identify patients with bvFTD. • We combined features from structural MRI data and fMRI-based functional connectivity. • Our approach was validated over 103 subjects from three different centers. • Our multimodal approach yielded high classification accuracy (91%) across centers. • Multimodal computational approaches may be useful complements for dementia diagnosis.

Normal 0 21 false false false ES-TRAD JA X-NONE Abstract Previous studies have shown the usefulness of cognitive remediation therapy (CRT) in patients with eating disorders (ED). The objective of this study was to assess a new cognitive technique called " With the head in the clouds " (WHC). A total of 22 women with ED (13 with anorexia nervosa and 9 with bulimia nervosa), between 14 and 29 years ( M = 19.0, SD = 3.4), completed the six group sessions of this technique. Under a design pre-post intervention, participants were assessed in: visuo-constructive functions (Copy of the Rey-Osterrieth Complex Figure [CRCF]), creative thinking (Torrance Creative Thinking Test [TCTT]), cognitive flexibility (CRCF and TCTT) and cognitive control (Stroop Test). The intervention improved different cognitive domains, such as: greater global coherence, creative thinking and resistance to closure, as well as less fragmentation. Based on CRT, aimed at stimulating the new processing of visual stimuli, the technique WHC showed an improvement in some of the cognitive processes involved in the onset of symptoms in patients with ED. Resumen Estudios previos han indicado la utilidad de la terapia de remediacion cognitiva (TRC) en pacientes con trastornos de conducta alimentaria (TCA). El objetivo de este estudio fue evaluar una nueva tecnica de innovacion cognitiva llamada “Con la cabeza en las nubes” (CCN). Participaron 22 mujeres con TCA (13 con anorexia nerviosa y 9 con bulimia nerviosa), de entre 14 y 29 anos de edad ( M = 19.0, DE = 3.4), quienes completaron las seis sesiones grupales de que consta dicha tecnica. Bajo un diseno pre-post intervencion, las participantes fueron evaluadas en cuanto a: funciones viso-constructivas (Copia de la Figura Compleja de Rey-Osterrieth [CFCR]) , pensamiento creativo (Test de Pensamiento Creativo de Torrance [TPCT]), flexibilidad cognitiva (CFCR y TPCT) y control cognitivo (Test de Stroop). La intervencion genero una mejora en distintos dominios cognitivos, como son: mayor coherencia global, pensamiento creativo y resistencia al cierre, asi como menor fragmentacion. Basada en la TRC, encaminada a estimular el procesamiento novedoso de estimulos visuales, la tecnica CCN mostro mejorar algunos de los procesos cognitivos implicados en la generacion de los sintomas de pacientes con TCA.

Frontotemporal dementia (FTD) affects behavior, language, and personality. This study aims to explore functional connectivity changes in three FTD variants: behavioral (bvFTD), semantic (svPPA), and nonfluent variant (nfvPPA). Seventy-six patients diagnosed with FTD by international criteria and thirty-two controls were investigated. Functional connectivity from resting functional magnetic resonance imaging (fMRI) was estimated for the whole brain. Two types of analysis were done: network basic statistic and topological measures by graph theory. Several hubs in the limbic system and basal ganglia were compromised in the behavioral variant apart from frontal networks. Nonfluent variants showed a major disconnection with respect to the behavioral variant in operculum and parietal inferior. The global efficiency had lower coefficients in nonfluent variants than behavioral variants and controls. Our results support an extensive disconnection among frontal, limbic, basal ganglia, and parietal hubs.

Biomarkers represent a critical research area in neurodegeneration disease as they can contribute to studying potential disease-modifying agents, fostering timely therapeutic interventions, and alleviating associated financial costs. Functional connectivity (FC) analysis represents a promising approach to identify early biomarkers in specific diseases. Yet, virtually no study has tested whether potential FC biomarkers prove to be reliable and reproducible across different centers. As such, their implementation remains uncertain due to multiple sources of variability across studies: the numerous international centers capable conducting FC research vary in their scanning equipment and their samples’ socio-cultural background, and, more troublingly still, no gold-standard method exists to analyze FC. In this unprecedented study, we aim to address both issues by performing the first multicenter FC research in the behavioral-variant frontotemporal dementia (bvFTD), and by assessing multiple FC approaches to propose a gold-standard method for analysis. We enrolled 52 bvFTD patients and 60 controls from three international clinics (with different fMRI recording parameters), and three additional neurological patient groups. To evaluate FC, we focused on seed analysis, inter-regional connectivity, and several graph-theory approaches. Only graph-theory analysis, based on weighted-matrices, yielded consistent differences between bvFTD and controls across centers. Also, graph metrics robustly discriminated bvFTD from the other neurological conditions. The consistency of our findings across heterogeneous contexts highlights graph-theory as a potential gold-standard approach for brain network analysis in bvFTD. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc.

Resumen Introduccion El desarrollo emocional y social de los humanos es extraordinariamente complejo. El conocimiento acerca de si mismo, la percepcion de los otros, las motivaciones y el entorno cultural modulan las respuestas empaticas y los juicios morales sobre acciones particulares. En la Encuesta Nacional de Salud Mental, se exploraron aspectos de la cognicion social como el reconocimiento de emociones, la empatia y los juicios morales frente a situaciones que significan dolor al otro. Objetivo Describir los resultados generales de la Encuesta Nacional de Salud Mental en relacion con el reconocimiento de emociones y respuestas empaticas frente a situaciones que generan, intencionada o accidentalmente, un dolor al otro. Metodos Se encuesto a 15.351 sujetos y 3.863 adultos de edad ≥ 18-96 anos de esta poblacion: se les pidio que identificaran dos rostros de seis emociones. Ademas, con cinco secuencias de tres fotografias cada una (tarea de empatia frente al dolor modificada), se pregunto sobre elementos cognitivos, afectivos y morales de la empatia. Resultados Identificaron las emociones positivas el 91,5, el 65 y el 55% de los sujetos, y solo el 19,7, el 21,8 y el 27,4% reconocieron las emociones negativas: miedo, asco y tristeza, en ese orden. Cuando se analizan los datos por grupos de edad, condicion de pobreza y diferentes regiones del pais, los resultados tienden a variar. En cuanto a la empatia, el 73,7% identifico correctamente la accion intencional y el 56,6%, la accidental. Los juicios morales frente a las acciones accidentales merecen algun castigo (poco, el 20,7%; moderado, el 26,8%), aun en acciones accidentales. Conclusiones Se proponen posibles direcciones que debe seguir el analisis de los datos, dados algunos resultados llamativos: el reconocimiento de la emocion alegria en contraposicion con la aparente dificultad para reconocer la tristeza y los hallazgos paradojicos en torno al castigo y la empatia cuando se comete una accion que ocasiona dolor.

Resumen Introduccion La Encuesta Nacional de Salud Mental 2015 (ENSM 2015) es la cuarta que se realiza en el pais y se enmarca en el Sistema Nacional de Encuestas y estudios poblacionales para salud de Colombia. Metodos Se presenta una descripcion narrativa de los antecedentes, los referentes, el proceso de elaboracion y las caracteristicas del protocolo de la ENSM 2015. La ENSM 2015 y el protocolo parten de unos requisitos que dan soporte a las politicas nacionales en salud e internacionales relacionadas con salud mental. Para su elaboracion se trabaja junto con el Ministerio de Salud y Proteccion Social para definir los objetivos, los instrumentos de recoleccion, la muestra y el plan operativo. Como objetivo principal se definio brindar informacion actualizada acerca de la salud mental, los problemas, los trastornos mentales, la accesibilidad de los servicios y la valoracion de estados de salud, de la poblacion colombiana rural y urbana mayor de 7 anos de edad, en la que privilegio su comprension desde los determinantes sociales y la equidad. Para ello se decidio realizar un estudio observacional de corte transversal en el ambito nacional, con representatividad nacional, regional y por franjas de edad: 7-11, 12-17 y ≥ 18 anos. Las regiones consideradas fueron: Central, Oriental, Atlantica, Pacifica y Bogota, con un tamano de muestra total calculado como minimo de 12.080 sujetos y maximo de 14.496. Conclusiones Se presenta un breve resumen del protocolo que puede ser consultado en su totalidad en la pagina web del MSPS que incluye los instrumentos de recoleccion.

Resumen Introduccion Se ha definido corrientemente la salud mental como la ausencia de trastornos mentales. Para abordarla en el sentido mas llano de sanitas, se considero la necesidad de estructurar para la Encuesta Nacional de Salud Mental de 2015 un componente que respondiera a las orientaciones y las particularidades del pais. Objetivo Describir la estructuracion y los contenidos del componente de salud mental de la Encuesta Nacional de Salud Mental de 2015 para la poblacion colombiana de 7 y mas anos. Metodos Revision, analisis documental y discusion acerca de conceptos e instrumentos con el equipo responsable de la Encuesta Nacional de Salud Mental de 2015 y otros grupos. Resultados Se revisaron 353 documentos, de los que se incluyo el analisis de 180 para este articulo. Se plantea el modelo del componente que, considerando como elemento central la dimension etica de cuidado en las relaciones, entrecruza dos dimensiones o categorias de indagacion: subjetiva-relacional y social-colectiva. Conclusiones El componente de salud mental estructurado permite obtener informacion acerca de toda la poblacion y pensar la salud mental desde la «buena vida» personal y colectiva.

The importance of sociodemographic factors in the evaluation of sleep apnea has been presented recently in a pediatric population. Objective:to evaluate the impact of those factors on cognition of adult patients with OSA. Methods: A total of 39 patients were recruited. Environmental factors (dwelling and light/dark cycle) and sociodemographic factors were correlated with polysomnography (PSG), brain imaging (MRI) and psychological tests. Results:77% of the patients were highlanders (HL: dwelling above 2000 m asl) and presented a higher frequency of cerebrovascular changes (43%) in contrast with lowlanders (22%). Data as mean±SEM. Differences in Paced Auditory Serial Addition (PASAT) 3 min (HL: 9±1, LL:4±2) were significant (p

Obstructive sleep apnea (OSA) has been associated with mild cognitive impairment (MCI). Cerebral small vessel disease (CSVD) is considered a neuroimaging marker for MCI. Objective: To evaluate the association between OSA, cognitive impairment and vessel disease. Methods: We prospectively recruited individuals diagnosed through polysomnography with severe OSA (S; n=21), moderate OSA (M; n=18), and healthy individuals (H; n=9). Behavioral Data included screening tests with Montreal Cognitive assessment test (MOCA), Ineco Frontal Screening Test (IFS), Language by verbal fluency, Verbal Memory by selective memory verbal test, Attention executive by paced auditory serial addition test (PASAT), selective attention by digit symbol of WAIS, and executive functions like inhibition by Stroop test and Hayling test. Lesions in white matter was established through Magnetic resonance imaging (MRI). Results: The frequency of CSVD was higher in patients with OSA ((H=22%; M=38%; S=38%). Splitting the participants according to SVD, we found significant differences in cognitive parameters such LTMs (nonSVD=29; SVD=38, p=0.05) and PASAT (nonSVD=6.7; SVD=10.6 p=0.03). Data as mean ± SEM. LTMs scores varied according to the group (H=40±6; M=38±3 and S=28±3) with significant differences H vs S (p=0.04) and M vs S (p=0.02). Remaining cognitive measurements, between those groups were not different. Conclusions: These preliminary findings suggest that mild cognitive impairment in patients with OSA is associated with CSVD

Summary The identification of human violence determinants has sparked multiple questions from different academic fields. Innovative methodological assessments of the weight and interaction of multiple determinants are still required. Here, we examine multiple features potentially associated with confessed acts of violence in ex-members of illegal armed groups in Colombia (N = 26,349) through deep learning and feature-derived machine learning. We assessed 162 social-contextual and individual mental health potential predictors of historical data regarding consequentialist, appetitive, retaliative, and reactive domains of violence. Deep learning yields high accuracy using the full set of determinants. Progressive feature elimination revealed that contextual factors were more important than individual factors. Combined social network adversities, membership identification, and normalization of violence were among the more accurate social-contextual factors. To a lesser extent the best individual factors were personality traits (borderline, paranoid, and antisocial) and psychiatric symptoms. The results provide a population-based computational classification regarding historical assessments of violence in vulnerable populations., Highlights • Classification of violence using sociocontextual and individual mental health factors • Study of appetitive, consequentialist, and impulsive DoVs • Confessed DoVs in a large sample of Colombian ex-members of illegal armed groups • Neural networks and machine learning identified the top factors associated with violence, The bigger picture We assessed a comprehensive group of social-contextual and individual mental health factors to classify confessed acts of violence committed in the past among a large sample of Colombian ex-members of illegal armed groups (N = 26,349). We used a novel data-driven approach to classify subjects based on four confessed domains of violence (DoVs) and including two groups, (1) ex-members who admitted violent acts and (2) ex-members who denied violence in each DoV, matched by sex, age, and education stage. We found that accurate classification required both social-contextual and individual mental health factors, although the social-contextual factors were the most relevant. Our study provides population-based evidence on the factors associated with historical assessments of violence and describes a powerful analytical approach. This study opens up a new agenda for developing computational approaches for situated, multidimensional, and evidence-based assessments of violence., The study of human violence calls for methodological innovations. Here, we examined historical records for a large sample of ex-members of illegal armed groups in Colombia (N = 26,349) and combined deep learning and machine learning methods to identify the most relevant factors (>160) associated with different confessed domains of violence (DoVs). Results showed that accurate DoV classification required a combination of both social-contextual and individual mental health factors. The results support the development of computational approaches for multidimensional assessments of confessed DoV.

Previous works highlight the neurocognitive differences between apathetic and disinhibited clinical presentations of the behavioral variant frontotemporal dementia (bvFTD). However, little is known regarding how the early presentation (i.e., first symptom) is associated to the neurocognitive correlates of the disease's clinical presentation at future stages of disease.We analyzed the neurocognitive correlates of patients with bvFTD who debuted with apathy or disinhibition as first symptom of disease.We evaluated the neuropsychological, clinical, and neuroanatomical (3T structural images) correlates in a group of healthy controls (n = 30) and two groups of bvFTD patients (presented with apathy [AbvFTD, n = 18] or disinhibition [DbvFTD, n = 16]). To differentiate groups according to first symptoms, we used multivariate analyses.The first symptom in patients described the evolution of the disease. AbvFTD and DbvFTD patients showed increased brain atrophy and increased levels of disinhibition and apathy, respectively. Whole brain analyzes in AbvFTD revealed atrophy in the frontal, insular, and temporal areas. DbvFTD, in turn, presented atrophy in the prefrontal regions, temporoparietal junction, insula, and temporoparietal region. Increased atrophy in DbvFTD patients (compared to AbvFTD) was observed in frontotemporal regions. Multivariate analyses confirmed that a set of brain areas including right orbitofrontal, right dorsolateral prefrontal, and left caudate were enough to distinguish the patients' subgroups.∥Conclusion: First symptom in bvFTD patients described the neurocognitive impairments after around three years of disease, playing an important role in the early detection, disease tracking, and neuroanatomical specification of bvFTD, as well as in future research on potential disease-modifying treatments.

Objectives: Behavioral variant frontotemporal dementia (bvFTD) is characterized by early atrophy in the frontotemporoinsular regions. These regions overlap with networks that are engaged in social cognition-executive functions, two hallmarks deficits of bvFTD. We examine (i) whether Network Centrality (a graph theory metric that measures how important a node is in a brain network) in the frontotemporoinsular network is disrupted in bvFTD, and (ii) the level of involvement of this network in social-executive performance. Methods: Patients with probable bvFTD, healthy controls, and frontoinsular stroke patients underwent functional MRI resting-state recordings and completed social-executive behavioral measures. Results: Relative to the controls and the stroke group, the bvFTD patients presented decreased Network Centrality. In addition, this measure was associated with social cognition and executive functions. To test the specificity of these results for the Network Centrality of the frontotemporoinsular network, we assessed the main areas from six resting-state networks. No group differences or behavioral associations were found in these networks. Finally, Network Centrality and behavior distinguished bvFTD patients from the other groups with a high classification rate. Conclusions: bvFTD selectively affects Network Centrality in the frontotemporoinsular network, which is associated with high-level social and executive profile. Fil: Sedeño, Lucas. Instituto de Neurología Cognitiva. Laboratorio de Psicología Experimental y Neurociencia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. Universidad Diego Portales; Chile Fil: Couto, Juan Blas Marcos. Instituto de Neurología Cognitiva. Laboratorio de Psicología Experimental y Neurociencia; Argentina. Universidad Diego Portales; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina Fil: García Cordero, Indira Ruth. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. Instituto de Neurología Cognitiva. Laboratorio de Psicología Experimental y Neurociencia; Argentina Fil: Melloni, Margherita. Universidad Diego Portales; Chile. Instituto de Neurología Cognitiva. Laboratorio de Psicología Experimental y Neurociencia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina Fil: Báez Buitrago, Sandra Jimena. Universidad Diego Portales; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. Instituto de Neurología Cognitiva. Laboratorio de Psicología Experimental y Neurociencia; Argentina Fil: Sepúlveda, Juan Pablo Morales. Universidad Diego Portales; Chile Fil: Fraiman Borrazás, Daniel Edmundo. Universidad de San Andrés. Departamento de Matemáticas y Ciencias; Argentina. Pontificia Universidad Católica de Chile; Chile Fil: Huepe, David. Universidad Diego Portales; Chile Fil: Hurtado, Esteban. Pontificia Universidad Católica de Chile; Chile. Universidad Diego Portales; Chile Fil: Matallana, Diana. Pontificia Universidad Javeriana; Colombia Fil: Kuljis, Rodrigo. Universidad Diego Portales; Chile Fil: Torralva, Teresa. Universidad Diego Portales; Chile. Instituto de Neurología Cognitiva. Laboratorio de Psicología Experimental y Neurociencia; Argentina. Macquarie University; Australia Fil: Chialvo, Dante Renato. Universidad Torcuato Di Tella; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Sigman, Mariano. University of New South Wales; Australia Fil: Piguet, Olivier. University of New South Wales; Australia. Macquarie University; Australia Fil: Manes, Facundo Francisco. Macquarie University; Australia. Universidad Diego Portales; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. Instituto de Neurología Cognitiva. Laboratorio de Psicología Experimental y Neurociencia; Argentina Fil: Ibáñez Barassi, Agustín Mariano. Macquarie University; Australia. Universidad Diego Portales; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. Instituto de Neurología Cognitiva. Laboratorio de Psicología Experimental y Neurociencia; Argentina. Universidad Autónoma del Caribe; Colombia

The search for biomarkers of neurodegenerative diseases via fMRI functional connectivity (FC) research has yielded inconsistent results. Yet, most FC studies are blind to non-linear brain dynamics. To circumvent this limitation, we developed a “weighted Symbolic Dependence Metric” (wSDM) measure. Using symbolic transforms, we factor in local and global temporal features of the BOLD signal to weigh a robust copula-based dependence measure by symbolic similarity, capturing both linear and non-linear associations. We compared this measure with a linear connectivity metric (Pearson’s R) in its capacity to identify patients with behavioral variant frontotemporal dementia (bvFTD) and controls based on resting-state data. We recruited participants from two international centers with different MRI recordings to assess the consistency of our measure across heterogeneous conditions. First, a seed-analysis comparison of the salience network (a specific target of bvFTD) and the default-mode network (as a complementary control) between patients and controls showed that wSDM yields better identification of resting-state networks. Moreover, machine learning analysis revealed that wSDM yielded higher classification accuracy. These results were consistent across centers, highlighting their robustness despite heterogeneous conditions. Our findings underscore the potential of wSDM to assess fMRI-derived FC data, and to identify sensitive biomarkers in bvFTD. Fil: Moguilner, Sebastian Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Instituto de Neurología Cognitiva. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Fundación Favaloro. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt; Argentina. Universidad Nacional de Cuyo; Argentina. Comisión Nacional de Energía Atómica; Argentina Fil: García, Adolfo Martín. Universidad Nacional de Cuyo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Instituto de Neurología Cognitiva. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Fundación Favaloro. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt; Argentina Fil: Mikulan, Ezequiel Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Instituto de Neurología Cognitiva. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Fundación Favaloro. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt; Argentina Fil: Hesse Rizzi, Eugenia Fátima. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Instituto de Neurología Cognitiva. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Fundación Favaloro. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt; Argentina Fil: García Cordero, Indira Ruth. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Instituto de Neurología Cognitiva. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Fundación Favaloro. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt; Argentina Fil: Melloni, Margherita. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Instituto de Neurología Cognitiva. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Fundación Favaloro. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt; Argentina Fil: Cervetto, Sabrina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Instituto de Neurología Cognitiva. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Fundación Favaloro. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt; Argentina Fil: Serrano, Cecilia Mariela. Unidad Asistencial "Dr. César Milstein"; Argentina Fil: Herrera Murcia, Eduar. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Instituto de Neurología Cognitiva. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Fundación Favaloro. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt; Argentina Fil: Reyes, Pablo. Pontificia Universidad Javeriana; Colombia Fil: Matallana, Diana. Pontificia Universidad Javeriana; Colombia Fil: Manes, Facundo Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Instituto de Neurología Cognitiva. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Fundación Favaloro. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt; Argentina Fil: Ibañez, Agustin Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Instituto de Neurología Cognitiva. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Fundación Favaloro. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt; Argentina. Universidad Adolfo Ibañez; Chile. Universidad Autónoma del Caribe; Colombia Fil: Sedeño, Lucas. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Instituto de Neurología Cognitiva. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt | Fundación Favaloro. Instituto de Neurociencia Cognitiva y Traslacional. Fundación Ineco Rosario Sede del Incyt; Argentina

Empathy is a complex cognitive and affective process that allows humans to experience concern for others, comprehend their emotions, and eventually help them. In addition to studies with healthy subjects and various neuropsychiatric populations, a few reports have examined this domain focusing on mental health workers, whose daily work requires the development of a saliently empathic character. Building on this research line, the present population-based study aimed to (a) assess different dimensions of empathy for pain in mental health workers relative to general-physicians and non-medical workers; and (b) evaluate their relationship with relevant factors, such as moral profile, age, gender, years of experience, and workplace type. Relative to both control groups, mental health workers exhibited higher empathic concern and discomfort for others' suffering, and they favored harsher punishment to harmful actions. Furthermore, this was the only group in which empathy variability was explained by moral judgments, years of experience, and workplace type. Taken together, these results indicate that empathy is continuously at stake in mental health care scenarios, as it can be affected by contextual factors and social contingencies. More generally, they highlight the importance of studying this domain in populations characterized by extreme empathic demands. Fil: Santamaria Garcia, Hernando. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina Fil: Báez Buitrago, Sandra Jimena. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina Fil: García, Adolfo Martín. Instituto de Neurología Cognitiva. Laboratorio de Psicología Experimental y Neurociencia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina. Universidad Nacional de Cuyo. Facultad de Educación Elemental y Especial; Argentina Fil: Flichtentrei, Daniel. Intramed; Argentina Fil: Prats, Lucía María. Intramed; Argentina. Centro de Educaciones Médicas e Investigación Clínica "Norberto Quirno"; Argentina Fil: Mastandueno, Ricardo. Intramed; Argentina Fil: Sigman, Mariano. Universidad Torcuato di Tella; Argentina Fil: Matallana, Diana. Pontificia Universidad Javeriana; Colombia Fil: Cetkovich Bakmas, Marcelo Gustavo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina Fil: Ibanez Barassi, Agustin Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Neurociencia Cognitiva. Fundación Favaloro. Instituto de Neurociencia Cognitiva; Argentina

Los cambios en la cognicion social son encontrados frecuentemente en pacientes con trauma craneoencefalico leve (TCE) aunque no exista evidencia de lesiones estructurales. Aunque los instrumentos utilizados para evaluar la cognicion social son sensibles al cambio, la ausencia de dano estructural en los pacientes con TCE, puede llevar pasar por inadvertidos estos problemas. El objetivo de este estudio fue desarrollar una herramienta diagnostica complementaria como un paradigma para resonancia magnetica funcional (RMf), la cual involucra una tarea simple que pudiera explicar como los pacientes entienden ciertos comportamientos sociales complejos por medio de movimientos con o sin intencion social sin intermediacion del lenguaje. Participaron once pacientes con TCE leve y con reporte de alteraciones en cognicion social, estos fueron emparejados con doce sujetos control por variables demograficas. Un paradigma de RMf fue desarrollado por medio de la animacion puntos blancos sobre una pantalla negra que representan el movimiento humano, el movimiento humano con la intencion social como el baile o el compartir, y puntos que se mueven sin significado. Los pacientes tuvieron menos activacion en la union parietotemporal y giro frontal medio bilateral frente al movimiento social en comparacion con los sujetos del grupo de control. El paradigma de fMRI desarrollado puede ser una herramienta de diagnostico adicional para identificar las alteraciones cognitivas sociales en pacientes con TCE leve. Independientemente de la ausencia de lesion estructural, los cambios en las areas de activacion sugieren la posibilidad de usar esta herramienta como pronostico dado que los resultados clinicos, cognitivos y funcionales soportan este hallazgo.

Moral emotions have been assessed with correlational imaging techniques and framed as monolithic domains. Hernando et al. present a novel task indexing dimensions of schadenfreude and envy: deservingness, morality, and legality. An increase in both schadenfreude and envy accompanies atrophy of social cognition networks in patients with behavioural variant FTD., The study of moral emotions (i.e. Schadenfreude and envy) is critical to understand the ecological complexity of everyday interactions between cognitive, affective, and social cognition processes. Most previous studies in this area have used correlational imaging techniques and framed Schadenfreude and envy as unified and monolithic emotional domains. Here, we profit from a relevant neurodegeneration model to disentangle the brain regions engaged in three dimensions of Schadenfreude and envy: deservingness, morality, and legality. We tested a group of patients with behavioural variant frontotemporal dementia (bvFTD), patients with Alzheimer’s disease, as a contrastive neurodegeneration model, and healthy controls on a novel task highlighting each of these dimensions in scenarios eliciting Schadenfreude and envy. Compared with the Alzheimer’s disease and control groups, patients with bvFTD obtained significantly higher scores on all dimensions for both emotions. Correlational analyses revealed an association between envy and Schadenfreude scores and greater deficits in social cognition, inhibitory control, and behaviour disturbances in bvFTD patients. Brain anatomy findings (restricted to bvFTD and controls) confirmed the partially dissociable nature of the moral emotions’ experiences and highlighted the importance of socio-moral brain areas in processing those emotions. In all subjects, an association emerged between Schadenfreude and the ventral striatum, and between envy and the anterior cingulate cortex. In addition, the results supported an association between scores for moral and legal transgression and the morphology of areas implicated in emotional appraisal, including the amygdala and the parahippocampus. By contrast, bvFTD patients exhibited a negative association between increased Schadenfreude and envy across dimensions and critical regions supporting social-value rewards and social-moral processes (dorsolateral prefrontal cortex, angular gyrus and precuneus). Together, this study provides lesion-based evidence for the multidimensional nature of the emotional experiences of envy and Schadenfreude. Our results offer new insights into the mechanisms subsuming complex emotions and moral cognition in neurodegeneration. Moreover, this study presents the exacerbation of envy and Schadenfreude as a new potential hallmark of bvFTD that could impact in diagnosis and progression.

Biomarkers represent a critical research area in neurodegeneration disease as they can contribute to studying potential disease‐modifying agents, fostering timely therapeutic interventions, and alleviating associated financial costs. Functional connectivity (FC) analysis represents a promising approach to identify early biomarkers in specific diseases. Yet, virtually no study has tested whether potential FC biomarkers prove to be reliable and reproducible across different centers. As such, their implementation remains uncertain due to multiple sources of variability across studies: the numerous international centers capable conducting FC research vary in their scanning equipment and their samples’ socio‐cultural background, and, more troublingly still, no gold‐standard method exists to analyze FC. In this unprecedented study, we aim to address both issues by performing the first multicenter FC research in the behavioral‐variant frontotemporal dementia (bvFTD), and by assessing multiple FC approaches to propose a gold‐standard method for analysis. We enrolled 52 bvFTD patients and 60 controls from three international clinics (with different fMRI recording parameters), and three additional neurological patient groups. To evaluate FC, we focused on seed analysis, inter‐regional connectivity, and several graph‐theory approaches. Only graph‐theory analysis, based on weighted‐matrices, yielded consistent differences between bvFTD and controls across centers. Also, graph metrics robustly discriminated bvFTD from the other neurological conditions. The consistency of our findings across heterogeneous contexts highlights graph‐theory as a potential gold‐standard approach for brain network analysis in bvFTD. Hum Brain Mapp 38:3804–3822, 2017. © 2017 Wiley Periodicals, Inc.

Background: Moral judgment has been proposed to rely on a distributed brain network. This function is impaired in behavioral variant frontotemporal dementia (bvFTD), a condition involving damage to some regions of this network. However, no studies have investigated moral judgment in bvFTD via structural neuroimaging. Methods: We compared the performance of 21 bvFTD patients and 19 controls on a moral judgment task involving scenarios that discriminate between the contributions of intentions and outcomes. Voxel-based morphometry was used to assess (a) the atrophy pattern in bvFTD patients, (b) associations between gray matter (GM) volume and moral judgments, and (c) structural differences between bvFTD subgroups (patients with relatively preserved moral judgment and patients with severer moral judgment impairments). Results: Patients judged attempted harm as more permissible and accidental harm as less permissible than controls. The groups' performance on accidental harm was associated with GM volume in the precuneus. In controls, it was al- so associated with the ventromedial prefrontal cortex (VMPFC). Also, both groups' performance on attempted harm was associated with GM volume in the temporoparietal junction. Patients exhibiting worse performance displayed smaller GM volumes in the precuneus and temporal pole. Conclusions: Results suggest that moral judgment abnormalities in bvFTD are associated with impaired integration of intentions and outcomes, which depends on an extended brain network. In bvFTD, moral judgment seems to critically depend on areas beyond the VMPFC.

Introduction: Patients with syndromes that involve fronto-temporal areas have developed occasionally, either an interest in art or an emergence of creative pictorial activity not present before the disease. Objective: We present the case of a 66 year-old woman who had no premorbid artistic ability but started to paint at the age of 56, before the onset of behavioral and expressive language impairment. Marked deterioration of language and behavior progressed to

To study the effect of education and language of response at the interview on performance in the Mini-Mental State Examination (MMSE) domains, we studied 2861 Mexican Americans aged 65 and older from the Hispanic Established Populations for Epidemiologic Studies of the Elderly (EPESE) followed from 1993 to 1994 until 2004 to 2005. The MMSE was examined as total score (0-30) or divided into 2 global domains: (1) no-memory (score 0-24): Orientation, attention, and language; and (2) memory (score 0-6): working and delayed memory. Mean age and total MMSE were 72.7 years and 24.6 at baseline, and 81.7 years and 20.5 at 11 years of follow-up. Spanish-speaking participants had less education (4.1 vs 7.4 years, P < .0001), they had significantly higher adjusted mean scores for memory, no-memory, and total MMSE compared with English-speaking participants. In multivariate longitudinal analyses, participants with more years of education performed better than those with less education, especially in total MMSE and no-memory domain. Spanish-speaking participants with 4 to 6 years of education had higher memory scores than those speaking English (estimate 0.40, standard error [SE] = 0.14, P < .001), 7 to 11 (estimate 0.27, standard error = 0.13, P < .01) or 12+ (estimate 0.44, standard error = 0.13, P < .001). Results suggest that cultural factors and variables related to preferred language use determined variations in MMSE performance. Because the memory domain of the MMSE is less affected by education, it may be used along with other cognitive tests for early detection of cognitive decline in older populations with low education.