CRIS

Permanent URI for this communityhttps://investigadores.udd.cl/handle/123456789/1

Browse

Search Results

Now showing 1 - 5 of 5
  • Some of the metrics are blocked by your 
    Item type:Publication,
    Qualitative and quantitative educational disparities and brain signatures in healthy aging and dementia across global settings
    (Elsevier BV, 2025-04)
    Raul Gonzalez-Gomez
    ;
    Josephine Cruzat
    ;
    Hernán Hernández
    ;
    Joaquín Migeot
    ;
    Agustina Legaz
    Scopus© Citations 4  3
  • Some of the metrics are blocked by your 
    Item type:Publication,
    Functional Capacity in Activities of Daily Living in the Alzheimer’s Disease Continuum
    (Wiley, 2024-12) ;
    Carmen Dominguez
    ;
    Fabrissio Grandi
    ;
    Cecilia Gonzalez Campo
    ;
    Patricio Riquelme Contreras
    The most common and prevalent dementia worldwide is Alzheimer’s disease (AD). AD is a continuum composed of Subjective Cognitive Impairment (SCD), Mild Cognitive Impairment (MCI), and Alzheimer’s Disease dementia (ADD) stage. One of the main clinical variables in patients with dementia is performance in functional capacity since its alterations are associated with poor prognosis and disease progression. Functional capacity is measured through activities of daily living (ADL), which are divided into three domains: i) Basic (BADL), ii) Instrumental (IADL), and iii) Advanced (AADL). The study aimed to characterize the performance of the different stages of the AD continuum in the ADL domains and their association with cognitive abilities.</jats:p></jats:sec><jats:sec><jats:title>Method</jats:title><jats:p>A cross‐sectional study of subjects at different stages of the AD continuum was conducted: Healthy Controls (CTR) (n = 17), SCD (n = 77), MCI (n = 30), and ADD (n = 23), who were matched for age, sex, and education. ADLs were estimated using The Technology‐Activities of Daily Living Questionnaire (T‐ADLQ), which assesses the three domains and a total score. T‐ADLQ performance was compared across groups and correlated with cognitive ability instruments (ACE‐III and IFS).</jats:p></jats:sec><jats:sec><jats:title>Result</jats:title><jats:p>The results showed that patients with ADD performed worse on the BADL, IADL, and total ADLs compared to the other three groups. There were no significant differences between the CTR, SCD, and MCI on the BADL, IADL, and total ADLs. However, the AADL, in addition to differentiating the ADD patients from the other three groups, also showed differences between CTR and MCI subjects and between SCD and MCI subjects (Table 1 and Figure 1). The correlation study showed that AADL correlated significantly with global cognitive and executive function assessment (Figure 2).</jats:p></jats:sec><jats:sec><jats:title>Conclusion</jats:title><jats:p>AADL shows progressive functional impairment at different stages of the AD continuum, which is further associated with global cognitive and executive function performances. As one progresses to a more advanced stage of the disease continuum, the performance of ADLs, especially AADLs, worsens, which could indicate a marker of disease progression, allowing for better patient follow‐up.
      1
  • Some of the metrics are blocked by your 
    Item type:Publication,
    Multivariate word properties in fluency tasks reveal markers of Alzheimer's dementia
    (2023)
    Franco J. Ferrante
    ;
    Joaquín Migeot
    ;
    Agustina Birba
    ;
    Lucía Amoruso
    ;
    Gonzalo Pérez
    <jats:title>Abstract</jats:title><jats:sec><jats:title>INTRODUCTION</jats:title><jats:p>Verbal fluency tasks are common in Alzheimer's disease (AD) assessments. Yet, standard valid response counts fail to reveal disease‐specific semantic memory patterns. Here, we leveraged automated word‐property analysis to capture neurocognitive markers of AD vis‐à‐vis behavioral variant frontotemporal dementia (bvFTD).</jats:p></jats:sec><jats:sec><jats:title>METHODS</jats:title><jats:p>Patients and healthy controls completed two fluency tasks. We counted valid responses and computed each word's frequency, granularity, neighborhood, length, familiarity, and imageability. These features were used for group‐level discrimination, patient‐level identification, and correlations with executive and neural (magnetic resonanance imaging [MRI], functional MRI [fMRI], electroencephalography [EEG]) patterns.</jats:p></jats:sec><jats:sec><jats:title>RESULTS</jats:title><jats:p>Valid responses revealed deficits in both disorders. Conversely, frequency, granularity, and neighborhood yielded robust group‐ and subject‐level discrimination only in AD, also predicting executive outcomes. Disease‐specific cortical thickness patterns were predicted by frequency in both disorders. Default‐mode and salience network hypoconnectivity, and EEG beta hypoconnectivity, were predicted by frequency and granularity only in AD.</jats:p></jats:sec><jats:sec><jats:title>DISCUSSION</jats:title><jats:p>Word‐property analysis of fluency can boost AD characterization and diagnosis.</jats:p></jats:sec><jats:sec><jats:title>Highlights</jats:title><jats:p><jats:list list-type="bullet"> <jats:list-item><jats:p>We report novel word‐property analyses of verbal fluency in AD and bvFTD.</jats:p></jats:list-item> <jats:list-item><jats:p>Standard valid response counts captured deficits and brain patterns in both groups.</jats:p></jats:list-item> <jats:list-item><jats:p>Specific word properties (e.g., frequency, granularity) were altered only in AD.</jats:p></jats:list-item> <jats:list-item><jats:p>Such properties predicted cognitive and neural (MRI, fMRI, EEG) patterns in AD.</jats:p></jats:list-item> <jats:list-item><jats:p>Word‐property analysis of fluency can boost AD characterization and diagnosis.</jats:p></jats:list-item> </jats:list></jats:p></jats:sec>
      3Scopus© Citations 10
  • Some of the metrics are blocked by your 
    Item type:Publication,
    Interoception Primes Emotional Processing: Multimodal Evidence from Neurodegeneration
    (2021)
    Paula C. Salamone
    ;
    Agustina Legaz
    ;
    Lucas Sedeño
    ;
    Sebastián Moguilner
    ;
    Matías Fraile-Vazquez
      7Scopus© Citations 80
  • Some of the metrics are blocked by your 
    Item type:Publication,
    Evaluating the reliability of neurocognitive biomarkers of neurodegenerative diseases across countries: A machine learning approach
    (2020)
    M. Belen Bachli
    ;
    Lucas Sedeño
    ;
    Jeremi K. Ochab
    ;
    Olivier Piguet
    ;
    Fiona Kumfor
      16  1Scopus© Citations 56