1 |
Integrated deep visual and semantic attractor neural networks predict fMRI pattern-information along the ventral object processing pathway
|
|
|
|
BASE
|
|
Show details
|
|
2 |
Oscillatory Dynamics of Perceptual to Conceptual Transformations in the Ventral Visual Pathway
|
|
|
|
BASE
|
|
Show details
|
|
3 |
Integrated deep visual and semantic attractor neural networks predict fMRI pattern-information along the ventral object processing pathway
|
|
|
|
BASE
|
|
Show details
|
|
4 |
Phonological and syntactic competition effects in spoken word recognition: evidence from corpus-based statistics. ...
|
|
|
|
BASE
|
|
Show details
|
|
5 |
Phonological and syntactic competition effects in spoken word recognition: evidence from corpus-based statistics.
|
|
|
|
BASE
|
|
Show details
|
|
6 |
Phonological and syntactic competition effects in spoken word recognition: evidence from corpus-based statistics
|
|
|
|
BASE
|
|
Show details
|
|
8 |
Feature Statistics Modulate the Activation of Meaning During Spoken Word Processing.
|
|
|
|
BASE
|
|
Show details
|
|
10 |
Feature Statistics Modulate the Activation of Meaning During Spoken Word Processing
|
|
|
|
BASE
|
|
Show details
|
|
11 |
The Centre for Speech, Language and the Brain (CSLB) concept property norms. ...
|
|
|
|
Abstract:
Theories of the representation and processing of concepts have been greatly enhanced by models based on information available in semantic property norms. This information relates both to the identity of the features produced in the norms and to their statistical properties. In this article, we introduce a new and large set of property norms that are designed to be a more flexible tool to meet the demands of many different disciplines interested in conceptual knowledge representation, from cognitive psychology to computational linguistics. As well as providing all features listed by 2 or more participants, we also show the considerable linguistic variation that underlies each normalized feature label and the number of participants who generated each variant. Our norms are highly comparable with the largest extant set (McRae, Cree, Seidenberg, & McNorgan, 2005) in terms of the number and distribution of features. In addition, we show how the norms give rise to a coherent category structure. We provide ...
|
|
Keyword:
Adolescent; Adult; Concept Formation; Female; FOS Languages and literature; Humans; Language; Linguistics; Male; Reference Values; Semantics; Speech; Word Association Tests; Young Adult
|
|
URL: https://www.repository.cam.ac.uk/handle/1810/271869 https://dx.doi.org/10.17863/cam.18877
|
|
BASE
|
|
Hide details
|
|
12 |
The Centre for Speech, Language and the Brain (CSLB) concept property norms.
|
|
|
|
BASE
|
|
Show details
|
|
13 |
Representational Similarity Analysis Reveals Commonalities and Differences in the Semantic Processing of Words and Objects
|
|
|
|
BASE
|
|
Show details
|
|
14 |
Objects and categories: Feature statistics and object processing in the ventral stream
|
|
|
|
BASE
|
|
Show details
|
|
15 |
Syntactic computations in the language network: characterizing dynamic network properties using representational similarity analysis.
|
|
|
|
BASE
|
|
Show details
|
|
16 |
Syntactic Computations in the Language Network: Characterizing Dynamic Network Properties Using Representational Similarity Analysis
|
|
|
|
BASE
|
|
Show details
|
|
17 |
The Centre for Speech, Language and the Brain (CSLB) concept property norms
|
|
|
|
BASE
|
|
Show details
|
|
20 |
Contrasting effects of feature-based statistics on the categorisation and identification of visual objects
|
|
|
|
BASE
|
|
Show details
|
|
|
|