Browsing by Author "Parra, Mario"
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Item Mapping the neuroanatomy of functional decline in Alzheimer's disease from basic to advanced activities of daily living(Springer Nature, 2019-06) Slachevsky, Andrea; Forno, Gonzalo; Barraza, Paulo; Mioshi, Eneida; Delgado, Carolina; Lillo, Patricia; Henríquez, Fernando; Bravo, Eduardo; Farias, Mauricio; Muñoz-Neira, Carlos; Ibáñez, Agustín; Parra, Mario; Hornberger, MichaelBackground: Impairments in activities of daily living (ADL) are a criterion for Alzheimer's disease (AD) dementia. However, ADL gradually decline in AD, impacting on advanced (a-ADL, complex interpersonal or social functioning), instrumental (IADL, maintaining life in community), and finally basic functions (BADL, activities related to physiological and self-maintenance needs). Information and communication technologies (ICT) have become an increasingly important aspect of daily functioning. Yet, the links of ADL, ICT, and neuropathology of AD dementia are poorly understood. Such knowledge is critical as it can provide biomarker evidence of functional decline in AD. Methods: ADL were evaluated with the Technology-Activities of Daily Living Questionnaire (T-ADLQ) in 33 patients with AD and 30 controls. ADL were divided in BADL, IADL, and a-ADL. The three domain subscores were covaried against gray matter atrophy via voxel-based morphometry. Results: Our results showed that three domain subscores of ADL correlate with several brain structures, with a varying degree of overlap between them. BADL score correlated mostly with frontal atrophy, IADL with more widespread frontal, temporal and occipital atrophy and a-ADL with occipital and temporal atrophy. Finally, ICT subscale was associated with atrophy in the precuneus. Conclusions: The association between ADL domains and neurodegeneration in AD follows a traceable neuropathological pathway which involves different neural networks. This the first evidence of ADL phenotypes in AD characterised by specific patterns of functional decline and well-defined neuropathological changes. The identification of such phenotypes can yield functional biomarkers for dementias such as AD.Publication 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, AgustínObjective.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 countriesPublication Standardization and diagnostic utility of the Frontal Assessment Battery for healthy people and patients with dementia in the Chilean population(2022) Grandi, Fabrissio; Martínez, David; Parra, Mario; Olavarria, Loreto; Huepe, David; Alegría, Patricia; Aliaga, Álvaro; Lillo, Patricia; Delgado, Carolina; Tenorio, Marcela; Rosas, Ricardo; López, Oscar; Becker, James; Slachevsky Chonchol, AndreaThe Frontal Assessment Battery (FAB) is a screening test that measures executive functions. Although this instrument has been validated in several countries, its diagnostic utility in a Chilean population has not been studied yet. Objectives: This study aimed to (1) adapt FAB in a Chilean population; (2) study the psychometric properties of the FAB in a Chilean population; (3) assess the sociodemographic influence in the performance of the FAB in a sample of healthy controls (HC); and (4) develop normative data for this healthy group. Methods: A HC (n=344) and a group of patients with dementia (n=156) were assessed with the Chilean version of FAB. Results: FAB showed good internal consistency (Cronbach's alpha=0.79) and acceptable validity based on the relationship with other variables. Factor analysis showed the unidimensionality of the instrument. Significant differences were found in the total FAB value between the HC and dementia groups. With the matched sample, the established cutoff point was 13.5, showing a sensitivity of 80.8% and a specificity of 90.4%. Regression analysis showed that education and age significantly predicted FAB performance in the healthy group. Finally, normative data are provided. Conclusions: This study shows that FAB is a useful tool to discriminate between healthy people and people with dementia. However, further studies are needed to explore the capacity of the instrument to characterize the dysexecutive syndrome in people with dementia in the Chilean population.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.