An architecture for encoding sentence meaning in left mid-superior temporal cortex
By Steven M. Frankland, Joshua D. Greene. 2015
112 citations recorded by the source corpus.
Subfields: Cognitive Neuroscience, Natural Language Processing, Neuroscience
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cognitive Neuroscience
- Stanislas Dehaene
- Leonardo G. Cohen
- Robert A. Legenstein
- Joelle Pineau
- Wolfgang Maass
- Sydney S. Cash
- Yuan Yuan
- Chang Liu
In Natural Language Processing
- Koustuv Sinha
- Adina Williams
- Joelle Pineau
- Prasanna Parthasarathi
- Douwe Kiela
- Wolfgang Maass
- Santosh Srinivas Vempala
- Stanislas Dehaene
In Neuroscience
Citations in the corpus
- The roles of the temporal lobe in creative insight: an integrated review (2017, background): “The pSTG and the selective access of various associations Considerable evidence (e.g., Frankland & Greene, 2015; Hoenig & Scheef, 2009; Jung-Beeman, 2005; Poeppel & Hickok, 2004) has revealed that the anterior and posterior parts of the STG are associated with distinct semantic functions and with…”
- Neurophysiological dynamics of phrase-structure building during sentence processing (2017, background): “Higher resolution intracranial recordings (19) or fMRI (59) will be needed to resolve the putative vectors of neural activity that may underlie syntactic operations.”
- Sometimes We Want Ungrammatical Translations (2021, background): “Swapping the arguments of verbs is a classic way to measure the effects of word order both in humans (Frankland and Greene, 2015; Snell and Grainger, 2017) and in models, largely because changing the order of verbal arguments maintains”
- Assembly pointers for variable binding in networks of spiking neurons (2016, background): “Two additional classifiers were able to determine the current agent (orange gradient) and patient (magenta gradient) in sentences, modelling experiment 2 in [5]. pass filtered network activity was extracted for each of the sentences S1 to S4.”