scholarly journals Multiple encoding of word attributes in memory

1976 ◽  
Vol 4 (3) ◽  
pp. 307-310 ◽  
Author(s):  
Delos D. Wickens ◽  
Ruth E. Dalezman ◽  
F. Thomas Eggemeier
Keyword(s):  
2005 ◽  
Author(s):  
Yoko Greenberg ◽  
Minoru Tsuzaki ◽  
Hiroaki Kato ◽  
Yoshinori Sagisaka

1969 ◽  
Vol 12 (2) ◽  
pp. 308-318 ◽  
Author(s):  
Dean E. Williams ◽  
Franklin H. Silverman ◽  
Joseph A. Kools

One hundred fifty-two children from kindergarten and grades one through six, 76 stutterers and 76 nonstutterers, performed a speech task. Each of the kindergarten and first-grade children repeated 10 sentences after the experimenter, and each of the second- through sixth-grade children read a passage. All words judged to have been spoken disfluently were analyzed for the presence of each of Brown’s four word attributes—initial phoneme, grammatical function, sentence position, and word length. Disfluencies were not randomly distributed in the speech of these children. For both stutterers and nonstutterers, disfluencies occurred most frequently on words possessing the same attributes as those reported by Brown to be troublesome for adult stutterers. The findings of this study demonstrate the essential similarity in the loci of instances of disfluency in the speech of (1) children and adults and (2) stutterers and nonstutterers.


2021 ◽  
Author(s):  
Oscar Woolnough ◽  
Cristian Donos ◽  
Aidan Curtis ◽  
Patrick S Rollo ◽  
Zachary J Roccaforte ◽  
...  

Reading words aloud is a foundational aspect of the acquisition of literacy. The rapid rate at which multiple distributed neural substrates are engaged in this process can only be probed via techniques with high spatiotemporal resolution. We used direct intracranial recordings in a large cohort to create a holistic yet fine-grained map of word processing, enabling us to derive the spatiotemporal neural codes of multiple word attributes critical to reading: lexicality, word frequency and orthographic neighborhood. We found that lexicality is encoded by early activity in mid-fusiform (mFus) cortex and precentral sulcus. Word frequency is also first represented in mFus followed by later engagement of the inferior frontal gyrus (IFG) and inferior parietal sulcus (IPS), and orthographic neighborhood is encoded solely in the IPS. A lexicality decoder revealed high weightings for electrodes in the mFus, IPS, anterior IFG and the pre-central sulcus. These results elaborate the neural codes underpinning extant dual-route models of reading, with parallel processing via the lexical route, progressing from mFus to IFG, and the sub-lexical route, progressing from IPS to anterior IFG.


1974 ◽  
Vol 44 (6) ◽  
pp. 317-327 ◽  
Author(s):  
TSUGUO OGAWA ◽  
YOSHISADA INAMURA
Keyword(s):  

2013 ◽  
Vol 433-435 ◽  
pp. 1593-1596 ◽  
Author(s):  
Hong Xin Wan ◽  
Yun Peng

The topic model LDA can uncover latent topics in text mining, through the probability distribution of words in the text to get the distribution of topics. This approach ignores the correlation between the topics, so in some actual domain it is not enough to reflect the real situations of the topics. We can divide the topics into two classes: key topics and unimportant topics. The key topics can reflect the word attributes well, and other topics can be look as subordinate. Considering the relations of the topics, a topic reduction algorithm is proposed to retain the key topics and delete the redundant topics based on rough set. Because the LDA topics exists uncertainty distribution and rough set can deal with uncertain data well, so the algorithm based on rough set can improve the accuracy of topics analysis.


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