Browsing by Author "Legaz, Agustina"
Now showing 1 - 7 of 7
Results Per Page
Sort Options
Publication Author Correction: Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations(2024) Moguilner, Sebastian; Baez, Sandra; Hernandez, Hernan; Migeot, Joaquín; Legaz, Agustina; Gonzalez, Raul; Farina, Francesca; Prado, Pavel; Cuadros, Jhosmary; Tagliazucchi, Enzo; Altschuler, Florencia; Maito, Marcelo; Godoy, María; Cruzat, Josefina; Valdes, Pedro; Lopera, Francisco; Ochoa, John; Gonzalez, Alfredis; Bonilla, Jasmin; Gonzalez, Rodrigo; Anghinah, Renato; d'Almeida, Luís; Fittipaldi, Sol; Medel, Vicente; Olivares, Daniela; Yener, Görsev; Escudero, Javier; Babiloni, Claudio; Whelan, Robert; Güntekin, Bahar; Yırıkoğulları, Harun; Santamaria, Hernando; Fernández, Alberto; Huepe, David; Di Caterina, Gaetano; Soto, Marcio; Birba, Agustina; Sainz, Agustin; Coronel, Carlos; Yigezu, Amanuel; Behrens, Maria IsabelLos relojes cerebrales capturan la diversidad y las disparidades en el envejecimiento y la demencia en poblaciones geográficamente diversas. Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations. Brain clocks, which quantify discrepancies between brain age and chronological age, hold promise for understanding brain health and disease. However, the impact of diversity (including geographical, socioeconomic, sociodemographic, sex and neurodegeneration) on the brain-age gap is unknown. We analyzed datasets from 5,306 participants across 15 countries (7 Latin American and Caribbean countries (LAC) and 8 non-LAC countries). Based on higher-order interactions, we developed a brain-age gap deep learning architecture for functional magnetic resonance imaging (2,953) and electroencephalography (2,353). The datasets comprised healthy controls and individuals with mild cognitive impairment, Alzheimer disease and behavioral variant frontotemporal dementia. LAC models evidenced older brain ages (functional magnetic resonance imaging: mean directional error = 5.60, root mean square error (r.m.s.e.) = 11.91; electroencephalography: mean directional error = 5.34, r.m.s.e. = 9.82) associated with frontoposterior networks compared with non-LAC models. Structural socioeconomic inequality, pollution and health disparities were influential predictors of increased brain-age gaps, especially in LAC (R² = 0.37, F² = 0.59, r.m.s.e. = 6.9). An ascending brain-age gap from healthy controls to mild cognitive impairment to Alzheimer disease was found. In LAC, we observed larger brain-age gaps in females in control and Alzheimer disease groups compared with the respective males. The results were not explained by variations in signal quality, demographics or acquisition methods. These findings provide a quantitative framework capturing the diversity of accelerated brain aging.Publication Author Correction: the BrainLat project, a multimodal neuroimaging dataset of neurodegeneration from underrepresented backgrounds(2024) Prado, Pavel; Medel, Vicente; González, Raúl; Sainz, Agustín; Vidal, Víctor; Santamaría, Hernando; Moguilner, Sebastián; Mejía, Jhony; Slachevsky Chonchol, Andrea; Behrens, Maria Isabel; Aguillón, David; Lopera, Francisco; Parra, Mario; Matallana, Diana; Adrián, Marcelo; García, Adolfo; Custodio, Nilton; Ávila, Alberto; Piña, Stefanie; Birba, Agustina; Fittipaldi, Sol; Legaz, Agustina; Ibáñez, AgustínIn this article the author name Maria Isabel Behrens was incorrectly written as Maria Isabel Beherens. The original article has been corrected.Publication Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations(2024) Moguilner, Sebastian; Baez, Sandra; Hernandez, Hernan; Migeot, Joaquín; Legaz, Agustina; Gonzalez, Raul; Farina, Francesca; Prado, Pavel; Cuadros, Jhosmary; Tagliazucchi, Enzo; Altschuler, Florencia; Maito, Marcelo; Godoy, María; Cruzat, Josefina; Valdes, Pedro; Lopera, Francisco; Ochoa, John; González, Alfredis; Bonilla, Jazmín; Gonzalez, Rodrigo; Anghinah, Renato; d'Almeida, Luis; Fittipaldi, Sol; Medel, Vicente; Olivares, Daniela; Yener, Görsev; Escudero, Javier; Babiloni, Claudio; Whelan, Robert; Guntekin, Bahar; Yırıkoğulları, Harun; Santamaria, Hernando; Fernández, Alberto; Huepe, David; Di Caterina, Gaetano; Soto, Marcio; Birba, Agustina; Sainz, Agustin; Coronel, Carlos; Yigezu, Amanuel; Behrens, Maria IsabelBrain clocks, which quantify discrepancies between brain age and chronological age, hold promise for understanding brain health and disease. However, the impact of diversity (including geographical, socioeconomic, sociodemographic, sex and neurodegeneration) on the brain-age gap is unknown. We analyzed datasets from 5,306 participants across 15 countries (7 Latin American and Caribbean countries (LAC) and 8 non-LAC countries). Based on higher-order interactions, we developed a brain-age gap deep learning architecture for functional magnetic resonance imaging (2,953) and electroencephalography (2,353). The datasets comprised healthy controls and individuals with mild cognitive impairment, Alzheimer disease and behavioral variant frontotemporal dementia. LAC models evidenced older brain ages (functional magnetic resonance imaging: mean directional error = 5.60, root mean square error (r.m.s.e.) = 11.91; electroencephalography: mean directional error = 5.34, r.m.s.e. = 9.82) associated with frontoposterior networks compared with non-LAC models. Structural socioeconomic inequality, pollution and health disparities were influential predictors of increased brain-age gaps, especially in LAC (R² = 0.37, F² = 0.59, r.m.s.e. = 6.9). An ascending brain-age gap from healthy controls to mild cognitive impairment to Alzheimer disease was found. In LAC, we observed larger brain-age gaps in females in control and Alzheimer disease groups compared with the respective males. The results were not explained by variations in signal quality, demographics or acquisition methods. These findings provide a quantitative framework capturing the diversity of accelerated brain aging. Los relojes cerebrales, que cuantifican las discrepancias entre la edad cerebral y la edad cronológica, son prometedores para comprender la salud y la enfermedad cerebral. Sin embargo, se desconoce el impacto de la diversidad (incluida la geográfica, socioeconómica, sociodemográfica, sexual y neurodegenerativa) en la brecha de edad cerebral. Analizamos conjuntos de datos de 5306 participantes en 15 países (7 países de América Latina y el Caribe (ALC) y 8 países no pertenecientes a ALC). Con base en interacciones de orden superior, desarrollamos una arquitectura de aprendizaje profundo de brecha de edad cerebral para imágenes de resonancia magnética funcional (2953) y electroencefalografía (2353). Los conjuntos de datos comprendían controles sanos e individuos con deterioro cognitivo leve, enfermedad de Alzheimer y demencia frontotemporal variante conductual. Los modelos LAC evidenciaron edades cerebrales más avanzadas (imágenes por resonancia magnética funcional: error direccional medio = 5,60, error cuadrático medio (rmse) = 11,91; electroencefalografía: error direccional medio = 5,34, rmse = 9,82) asociadas con redes frontoposteriores en comparación con los modelos no LAC. La desigualdad socioeconómica estructural, la contaminación y las disparidades en la salud fueron predictores influyentes de mayores brechas de edad cerebral, especialmente en LAC (R² = 0,37, F² = 0,59, rmse = 6,9). Se encontró una brecha ascendente de edad cerebral desde controles sanos hasta deterioro cognitivo leve y enfermedad de Alzheimer. En LAC, observamos brechas de edad cerebral más grandes en mujeres en los grupos de control y enfermedad de Alzheimer en comparación con los respectivos hombres. Los resultados no se explicaron por variaciones en la calidad de la señal, la demografía o los métodos de adquisición. Estos hallazgos proporcionan un marco cuantitativo que captura la diversidad del envejecimiento cerebral acelerado.Publication Educational disparities in brain health and dementia across Latin America and the United States(2024) Gonzalez, Raul; Legaz, Agustina; Moguilner, Sebastián; Cruzat, Josephine; Hernández, Hernán; Baez, Sandra; Cocchi, Rafael; Coronel, Carlos; Medel,Vicente; Tagliazuchi, Enzo; Migeot, Joaquín; Ochoa, Carolina; Maito, Marcelo; Reyes, Pablo; Santamaria, Hernando; Godoy, Maria; Javande, Shireen; García, Adolfo; Matallana, Diana; Avila, José; Slachevsky Chonchol, Andrea; Behrens, María; Custodio, Nilton; Cardona, Juan; Brusco, Ignacio; Bruno, Martín; Sosa, Ana; Pina, Stefanie; Takada, Leonel; França, Elisa; Valcour, Victor; Possin, Katherine; De Oliveira, Maira; Lopera, Francisco; Lawlor, Brian; Hu, Kun; Miller, Bruce; Yokoyama, Jennifer; Gonzalez, Cecilia; Ibañez, AgustinBackground: Education influences brain health and dementia. However, its impact across regions, specifically Latin America (LA) and the United States (US), is unknown. Methods: A total of 1412 participants comprising controls, patients with Alzheimer's disease (AD), and frontotemporal lobar degeneration (FTLD) from LA and the US were included. We studied the association of education with brain volume and functional connectivity while controlling for imaging quality and variability, age, sex, total intracranial volume (TIV), and recording type. Results: Education influenced brain measures, explaining 24%-98% of the geographical differences. The educational disparities between LA and the US were associated with gray matter volume and connectivity variations, especially in LA and AD patients. Education emerged as a critical factor in classifying aging and dementia across regions. Discussion: The results underscore the impact of education on brain structure and function in LA, highlighting the importance of incorporating educational factors into diagnosing, care, and prevention, and emphasizing the need for global diversity in research. Highlights: Lower education was linked to reduced brain volume and connectivity in healthy controls (HCs), Alzheimer's disease (AD), and frontotemporal lobar degeneration (FTLD). Latin American cohorts have lower educational levels compared to the those in the United States. Educational disparities majorly drive brain health differences between regions. Educational differences were significant in both conditions, but more in AD than FTLD. Education stands as a critical factor in classifying aging and dementia across regions.Publication Multimodal mechanisms of human sociallyreinforced learning across neurodegenerative diseases(2022) Legaz, Agustina; Abrevaya, Sofía; Dottori, Martín; González, Cecilia; Birba, Agustina; Martorell, Miguel; Aguirre, Julieta; Slachevsky Chonchol, Andrea; Aranguiz, Rafael; Serrano, Cecilia; Gillan, Claire; Leroi, Iracema; García, Adolfo; Fittipaldi, Sol; Ibañez, AgustínSocial feedback can selectively enhance learning in diverse domains. Relevant neurocognitive mechanisms have been studied mainly in healthy persons, yielding correlational findings. Neurodegenerative lesion models, coupled with multimodal brain measures, can complement standard approaches by revealing direct multidimensional correlates of the phenomenon. To this end, we assessed socially reinforced and non-socially reinforced learning in 40 healthy participants as well as persons with behavioural variant frontotemporal dementia (n = 21), Parkinson's disease (n = 31) and Alzheimer's disease (n = 20). These conditions are typified by predominant deficits in social cognition, feedback-based learning and associative learning, respectively, although all three domains may be partly compromised in the other conditions. We combined a validated behavioural task with ongoing EEG signatures of implicit learning (medial frontal negativity) and offline MRI measures (voxel-based morphometry). In healthy participants, learning was facilitated by social feedback relative to non-social feedback. In comparison with controls, this effect was specifically impaired in behavioural variant frontotemporal dementia and Parkinson's disease, while unspecific learning deficits (across social and non-social conditions) were observed in Alzheimer's disease. EEG results showed increased medial frontal negativity in healthy controls during social feedback and learning. Such a modulation was selectively disrupted in behavioural variant frontotemporal dementia. Neuroanatomical results revealed extended temporo-parietal and fronto-limbic correlates of socially reinforced learning, with specific temporo-parietal associations in behavioural variant frontotemporal dementia and predominantly fronto-limbic regions in Alzheimer's disease. In contrast, non-socially reinforced learning was consistently linked to medial temporal/hippocampal regions. No associations with cortical volume were found in Parkinson's disease. Results are consistent with core social deficits in behavioural variant frontotemporal dementia, subtle disruptions in ongoing feedback-mechanisms and social processes in Parkinson's disease and generalized learning alterations in Alzheimer's disease. This multimodal approach highlights the impact of different neurodegenerative profiles on learning and social feedback. Our findings inform a promising theoretical and clinical agenda in the fields of social learning, socially reinforced learning and neurodegeneration.Publication Multimodal Neurocognitive Markers of Naturalistic Discourse Typify Diverse Neurodegenerative Diseases(2022) Birba, Agustina; Fittipaldi, Sol; Cediel Escobar, Judith C.; Gonzalez Campo, Cecilia; Legaz, Agustina; Galiani, Agostina; Díaz Rivera, Mariano N.; Martorell Caro, Miquel; Alifano, Florencia; Piña-Escudero, Stefanie D.; Cardona, Juan Felipe; Neely, Alejandra; Forno, Gonzalo; Carpinella , Mariela; Slachevsky Chonchol, Andrea; Serrano, Cecilia; Sedeño, Lucas; Ibáñez, Agustín; García, Adolfo M.Neurodegeneration has multiscalar impacts, including behavioral, neuroanatomical, and neurofunctional disruptions. Can disease-differential alterations be captured across such dimensions using naturalistic stimuli? To address this question, we assessed comprehension of four naturalistic stories, highlighting action, nonaction, social, and nonsocial events, in Parkinson's disease (PD) and behavioral variant frontotemporal dementia (bvFTD) relative to Alzheimer's disease patients and healthy controls. Text-specific correlates were evaluated via voxel-based morphometry, spatial (fMRI), and temporal (hd-EEG) functional connectivity. PD patients presented action-text deficits related to the volume of action-observation regions, connectivity across motor-related and multimodal-semantic hubs, and frontal hd-EEG hypoconnectivity. BvFTD patients exhibited social-text deficits, associated with atrophy and spatial connectivity patterns along social-network hubs, alongside right frontotemporal hd-EEG hypoconnectivity. Alzheimer's disease patients showed impairments in all stories, widespread atrophy and spatial connectivity patterns, and heightened occipitotemporal hd-EEG connectivity. Our framework revealed disease-specific signatures across behavioral, neuroanatomical, and neurofunctional dimensions, highlighting the sensitivity and specificity of a single naturalistic task. This investigation opens a translational agenda combining ecological approaches and multimodal cognitive neuroscience for the study of neurodegeneration.Publication The BrainLat project, a multimodal neuroimaging dataset of neurodegeneration from underrepresented backgrounds(2023) Prado, Pavel; Medel, Vicente; Gonzalez, Raul; Sainz, Agustín; Vidal , Victor; Santamaría, Hernando; Moguilner, Sebastian; Mejia, Jhony; Slachevsky Chonchol, Andrea; Behrens, Maria; Aguillon, David; Lopera, Francisco; Parra, Mario; Matallana,Diana; Maito, Marcelo; Garcia, Adolfo; Custodio, Nilton; Ávila, Alberto; Piña, Stefanie; Birba, Agustina; Fittipaldi, Sol; Legaz, Agustina; Ibañez, AgustínThe Latin American Brain Health Institute (BrainLat) has released a unique multimodal neuroimaging dataset of 780 participants from Latin American. The dataset includes 530 patients with neurodegenerative diseases such as Alzheimer's disease (AD), behavioral variant frontotemporal dementia (bvFTD), multiple sclerosis (MS), Parkinson's disease (PD), and 250 healthy controls (HCs). This dataset (62.7 ± 9.5 years, age range 21-89 years) was collected through a multicentric effort across five Latin American countries to address the need for affordable, scalable, and available biomarkers in regions with larger inequities. The BrainLat is the first regional collection of clinical and cognitive assessments, anatomical magnetic resonance imaging (MRI), resting-state functional MRI (fMRI), diffusion-weighted MRI (DWI), and high density resting-state electroencephalography (EEG) in dementia patients. In addition, it includes demographic information about harmonized recruitment and assessment protocols. The dataset is publicly available to encourage further research and development of tools and health applications for neurodegeneration based on multimodal neuroimaging, promoting the assessment of regional variability and inclusion of underrepresented participants in research.