Knowing about People and Naming Them: Can Alzheimer's Disease Patients Do One without the Other?

1998 ◽  
Vol 51 (1) ◽  
pp. 121-134 ◽  
Author(s):  
R. Hodges John ◽  
John D.W. Greene

It has recently been suggested that patients with semantic breakdown may show the phenomenon of so-called “naming without semantics”. If substantiated, this finding would clearly have a major impact on theories of face and object processing, all of which assume that access to semantic knowledge is a prerequisite for successful naming. In order to investigate this issue, we studied recognition, identification (the ability to provide accurate information), and naming of 50 famous faces by 24 patients with mild to moderate dementia of Alzheimer type (DA T) and 30 age-matched controls. The DA T group was impaired in all three conditions. An analysis of the concordance between identification and naming by each patient, for each stimulus item, established that naming a famous face was possible only with semantic knowledge sufficient to identify the person. Our data support the hypothesis that naming is not possible unless semantic information associated with the target is available. Naming without semantics, therefore, did not occur in patients with DAT. By contrast, there were 206 instances (17% of the total responses) in which the patients were able to provide detailed, accurate identifying information yet were unable to name the person represented. The implication of these findings for models of face identification and naming are discussed.

1997 ◽  
Vol 36 (3) ◽  
pp. 153-158 ◽  
Author(s):  
R. Chiaramonti ◽  
G.C. Muscas ◽  
M. Paganini ◽  
Th.J. Müller ◽  
A.J. Fallgatter ◽  
...  

Author(s):  
Sheng Zhang ◽  
Qi Luo ◽  
Yukun Feng ◽  
Ke Ding ◽  
Daniela Gifu ◽  
...  

Background: As a known key phrase extraction algorithm, TextRank is an analogue of PageRank algorithm, which relied heavily on the statistics of term frequency in the manner of co-occurrence analysis. Objective: The frequency-based characteristic made it a neck-bottle for performance enhancement, and various improved TextRank algorithms were proposed in the recent years. Most of improvements incorporated semantic information into key phrase extraction algorithm and achieved improvement. Method: In this research, taking both syntactic and semantic information into consideration, we integrated syntactic tree algorithm and word embedding and put forward an algorithm of Word Embedding and Syntactic Information Algorithm (WESIA), which improved the accuracy of the TextRank algorithm. Results: By applying our method on a self-made test set and a public test set, the result implied that the proposed unsupervised key phrase extraction algorithm outperformed the other algorithms to some extent.


1994 ◽  
Vol 9 (2) ◽  
pp. 105-109
Author(s):  
G Mecheri ◽  
Y Bissuel ◽  
J Dalery ◽  
JL Terra ◽  
G Balvay ◽  
...  

SummaryIn vivo NMR 31p spectroscopy is a non invasive, non ionizing method of exploration of energy and phospholipid metabolism in the brain. This study consisted of comparing 31p spectra in five patients with Senile Dementia of Alzheimer Type (SDAT) with those of four controls of similar ages. Abnormal phosphonionocsters (PME) concentrations, either high or low, were found in the patients, but statistical analysis did not elicit any significant difference relative to controls.


2008 ◽  
Vol 64 (3) ◽  
pp. 298-304 ◽  
Author(s):  
Carolina Dello Russo ◽  
Paola Di Giulio ◽  
Cinzia Brunelli ◽  
Valerio Dimonte ◽  
Daniele Villani ◽  
...  

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