Emotional valence in rapid automatized naming for early detection of Alzheimer disease

Abstract Background Alzheimer disease (AD) worsens naming abilities as the disease progresses. It is argued that traditional naming tests, commonly used to aid in staging AD severity, may overestimate semantic abilities. This study explored whether a more challenging naming task can distinguish between healthy adults and those with amnestic mild cognitive impairment (aMCI) or mild AD. Method In a cross‐sectional study, 16 individuals with aMCI, 15 with mild AD, and 20 healthy controls (see Table 1 for demographic details) performed a rapid automatized naming (RAN) task with emotionally balanced object and action pictures. Naming performance was assessed by response times (RTs) and accuracy (error rates). Regression analyses examined the relationship between RTs/error rates and group, sex, age, education, anxiety, and depression. Receiver operating characteristic (ROC) curves evaluated the discriminative ability of the RAN task. Result Patients with aMCI and mild AD showed significantly slower RTs and higher error rates compared to healthy controls (all p‐values < .001). Naming performance was especially impaired for negative stimuli compared to positive and neutral ones in healthy controls (p < 0.001) and aMCI patients (p < 0.01). However, this effect was absent in the AD group. Regression analyses revealed significant associations between RTs/error rates and group (both p‐values < 0.001), but not for age, sex, education, anxiety, and depression (see Table 2). ROC analysis demonstrated moderate diagnostic accuracy in classifying mild AD versus healthy controls (AUC of 0.887 for RTs; AUC of 0.854 for error rates; see Figure 1), but not in classifying aMCI versus healthy controls. Conclusion The RAN task reliably detects variations in naming ability across different stages of cognitive decline associated with AD. We observed an inhibitory effect of negative valence on lexical retrieval processes, which appeared to be dependent on the degree of cognitive impairment, as it was no longer evident in our AD group. Further research with larger sample sizes is warranted. A significant limitation of our study is the lack of standardization of our visual stimuli. It is possible that the ratings for emotional valence derived from written words may not precisely reflect the emotional responses of our participants.

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Publication Details

Journal
Alzheimer s & Dementia
Published
2024-12-01
DOI
https://doi.org/10.1002/alz.095442
Primary Topic
Biomedical Text Mining and Ontologies
Type
article
Field-Weighted Citation Impact
0.00
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article

Emotional valence in rapid automatized naming for early detection of Alzheimer disease

Fabio Rossini, Wolfgang Staffen, Margarita Kirschner, Vanessa Frey et al.
Alzheimer s & Dementia
Biomedical Text Mining and Ontologies
article

Emotional valence in rapid automatized naming for early detection of Alzheimer disease

Fabio Rossini, Wolfgang Staffen, Margarita Kirschner, Vanessa Frey, Eugen Trinka, Yvonne Höller, Jürgen Bergmann, Sandra Lafenthaler
article en

Abstract

Abstract Background Alzheimer disease (AD) worsens naming abilities as the disease progresses. It is argued that traditional naming tests, commonly used to aid in staging AD severity, may overestimate semantic abilities. This study explored whether a more challenging naming task can distinguish between healthy adults and those with amnestic mild cognitive impairment (aMCI) or mild AD. Method In a cross‐sectional study, 16 individuals with aMCI, 15 with mild AD, and 20 healthy controls (see Table 1 for demographic details) performed a rapid automatized naming (RAN) task with emotionally balanced object and action pictures. Naming performance was assessed by response times (RTs) and accuracy (error rates). Regression analyses examined the relationship between RTs/error rates and group, sex, age, education, anxiety, and depression. Receiver operating characteristic (ROC) curves evaluated the discriminative ability of the RAN task. Result Patients with aMCI and mild AD showed significantly slower RTs and higher error rates compared to healthy controls (all p‐values < .001). Naming performance was especially impaired for negative stimuli compared to positive and neutral ones in healthy controls (p < 0.001) and aMCI patients (p < 0.01). However, this effect was absent in the AD group. Regression analyses revealed significant associations between RTs/error rates and group (both p‐values < 0.001), but not for age, sex, education, anxiety, and depression (see Table 2). ROC analysis demonstrated moderate diagnostic accuracy in classifying mild AD versus healthy controls (AUC of 0.887 for RTs; AUC of 0.854 for error rates; see Figure 1), but not in classifying aMCI versus healthy controls. Conclusion The RAN task reliably detects variations in naming ability across different stages of cognitive decline associated with AD. We observed an inhibitory effect of negative valence on lexical retrieval processes, which appeared to be dependent on the degree of cognitive impairment, as it was no longer evident in our AD group. Further research with larger sample sizes is warranted. A significant limitation of our study is the lack of standardization of our visual stimuli. It is possible that the ratings for emotional valence derived from written words may not precisely reflect the emotional responses of our participants.

Alzheimer s & DementiaVol. 20(S8)
University of Salzburg (AT), Paracelsus Medical University (AT), University of Akureyri (IS)
Openalex Percentile: Top 78%
Biomedical Text Mining and Ontologies
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