Andrea María Slachevsky Conchol

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Slachevsky Chonchol, Andrea

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Slachevsky Chonchol

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Andrea María Slachevsky Conchol

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Automated free speech analysis reveals distinct markers of Alzheimer's and frontotemporal dementia
(2024) Lopes da Cunha, Pamela; Ruiz, Fabián; Ferrante, Franco; Sterpin, Lucas; Ibáñez, Agustín; Slachevsky Chonchol, Andrea; Matallana, Diana; Martínez, Ángela; Hesse, Eugenia; García, Adolfo
Dementia can disrupt how people experience and describe events as well as their own role in them. Alzheimer's disease (AD) compromises the processing of entities expressed by nouns, while behavioral variant frontotemporal dementia (bvFTD) entails a depersonalized perspective with increased third-person references. Yet, no study has examined whether these patterns can be captured in connected speech via natural language processing tools. To tackle such gaps, we asked 96 participants (32 AD patients, 32 bvFTD patients, 32 healthy controls) to narrate a typical day of their lives and calculated the proportion of nouns, verbs, and first- or third-person markers (via part-of-speech and morphological tagging). We also extracted objective properties (frequency, phonological neighborhood, length, semantic variability) from each content word. In our main study (with 21 AD patients, 21 bvFTD patients, and 21 healthy controls), we used inferential statistics and machine learning for group-level and subject-level discrimination. The above linguistic features were correlated with patients' scores in tests of general cognitive status and executive functions. We found that, compared with HCs, (i) AD (but not bvFTD) patients produced significantly fewer nouns, (ii) bvFTD (but not AD) patients used significantly more third-person markers, and (iii) both patient groups produced more frequent words. Machine learning analyses showed that these features identified individuals with AD and bvFTD (AUC = 0.71). A generalizability test, with a model trained on the entire main study sample and tested on hold-out samples (11 AD patients, 11 bvFTD patients, 11 healthy controls), showed even better performance, with AUCs of 0.76 and 0.83 for AD and bvFTD, respectively. No linguistic feature was significantly correlated with cognitive test scores in either patient group. These results suggest that specific cognitive traits of each disorder can be captured automatically in connected speech, favoring interpretability for enhanced syndrome characterization, diagnosis, and monitoring.
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, Agustín
Social 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.
Multi-feature computational framework for combined signatures of dementia in underrepresented settings
(2022) Moguilner, Sebastián; Birba, Agustina; Fittipaldi, Sol; Gonzalez, Cecilia; Tagliazucchi, Enzo; Reyes, Pablo; Matallana, Diana; Parra, Mario; Slachevsky Chonchol, Andrea; Farías, Gonzalo; Cruzat, Josefina; García, Adolfo; Eyre, Harris; La Joie, Renaud; Rabinovici, Gil; Whelan, Robert; Ibáñez, Agustín
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
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, Agustín
In this article the author name Maria Isabel Behrens was incorrectly written as Maria Isabel Beherens. The original article has been corrected.
Neurocognitive correlates of semantic memory navigation in Parkinson's disease
(2024) Toro, Felipe; Migeot, Joaquín; Marchant, Nicolás; Olivares, Daniela; Ferrante, Franco; González, Raúl; González, Cecilia; Fittipaldi, Sol; Rojas, Gonzalo; Moguilner, Sebastian; Slachevsky Chonchol, Andrea; Chaná, Pedro; Ibáñez, Agustín; Chaigneau, Sergio; García, Adolfo
Cognitive studies on Parkinson's disease (PD) reveal abnormal semantic processing. Most research, however, fails to indicate which conceptual properties are most affected and capture patients' neurocognitive profiles. Here, we asked persons with PD, healthy controls, and individuals with behavioral variant frontotemporal dementia (bvFTD, as a disease control group) to read concepts (e.g., 'sun') and list their features (e.g., hot). Responses were analyzed in terms of ten word properties (including concreteness, imageability, and semantic variability), used for group-level comparisons, subject-level classification, and brain-behavior correlations. PD (but not bvFTD) patients produced more concrete and imageable words than controls, both patterns being associated with overall cognitive status. PD and bvFTD patients showed reduced semantic variability, an anomaly which predicted semantic inhibition outcomes. Word-property patterns robustly classified PD (but not bvFTD) patients and correlated with disease-specific hypoconnectivity along the sensorimotor and salience networks. Fine-grained semantic assessments, then, can reveal distinct neurocognitive signatures of PD.
Author Correction: Neurocognitive correlates of semanticmemory navigation in Parkinson’s disease
(2024) Toro, Felipe; Migeot, Joaquín; Marchant, Nicolás; Olivares, Daniela; Ferrante, Franco; González, Raúl; González, Cecilia; Fittipaldi, Sol; Rojas, Gonzalo; Moguilner, Sebastian; Slachevsky Chonchol, Andrea; Chaná, Pedro; Ibáñez, Agustín; Chaigneau, Sergio; García, Adolfo
Correction to: npj Parkinson’s Disease https://doi.org/10.1038/ s41531-024-00630-4, published online 9 January 2024. In this article the funding from ‘Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile, #BL-SRGP2021-01’ for author Adolfo M. García was omitted. The original article has been corrected.
Advancements in dementia research, diagnostics, and care in Latin America: Highlights from the 2023 Alzheimer's Association International conference satellite symposium in Mexico City
(2024) Sosa, Ana; Brucki; Sonia; Crivelli, Lucia; Lopera, Francisco; Acosta, Daisy; Acosta, Juliana; Aguilar, Diego; Aguilar.Sara; Allegri, Ricardo; Bertolucci, Paulo; Calandri, Ismael; Carrillo, Maria; Chrem , Patricio; Cornejo, Mario; Custodio, Nilton; Damian, Andrés; Cruz , Leonardo; Duran, Claudia; García, Adolfo; García, Carmen; Gonzales, Mitzi; Grinberg, Lea; Ibanez, Agustin; Illanes, Maryenela; Jack, Clifford; Leon, Jorge; Llibre, Jorge; Luna, José; Matallana, Diana; Miller, Bruce; Naci, Lorina; Parra, Mario; Pericak, Margaret; Piña, Stefanie; França, Elisa de Paula; Ringman, John; Sevlever, Gustavo; Slachevsky Chonchol, Andrea; Kimie, Claudia; Valcour, Victor; Villegas, Andres
Introduction: While Latin America (LatAm) is facing an increasing burden of dementia due to the rapid aging of the population, it remains underrepresented in dementia research, diagnostics, and care. Methods: In 2023, the Alzheimer's Association hosted its eighth satellite symposium in Mexico, highlighting emerging dementia research, priorities, and challenges within LatAm. Results: Significant initiatives in the region, including intracountry support, showcased their efforts in fostering national and international collaborations; genetic studies unveiled the unique genetic admixture in LatAm; researchers conducting emerging clinical trials discussed ongoing culturally specific interventions; and the urgent need to harmonize practices and studies, improve diagnosis and care, and use affordable biomarkers in the region was highlighted. Discussion: The myriad of topics discussed at the 2023 AAIC satellite symposium highlighted the growing research efforts in LatAm, providing valuable insights into dementia biology, genetics, epidemiology, treatment, and care.
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, Agustin
Background: 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.