Lexical representation explains cortical entrainment during speech comprehension
June 18, 2017 Β· Declared Dead Β· π PLoS ONE
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Stefan Frank, Jinbiao Yang
arXiv ID
1706.05656
Category
q-bio.NC
Cross-listed
cs.CL
Citations
41
Venue
PLoS ONE
Last Checked
6 months ago
Abstract
Results from a recent neuroimaging study on spoken sentence comprehension have been interpreted as evidence for cortical entrainment to hierarchical syntactic structure. We present a simple computational model that predicts the power spectra from this study, even though the model's linguistic knowledge is restricted to the lexical level, and word-level representations are not combined into higher-level units (phrases or sentences). Hence, the cortical entrainment results can also be explained from the lexical properties of the stimuli, without recourse to hierarchical syntax.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β q-bio.NC
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
SuperSpike: Supervised learning in multi-layer spiking neural networks
R.I.P.
π»
Ghosted
Generic decoding of seen and imagined objects using hierarchical visual features
R.I.P.
π»
Ghosted
Convolutional Neural Networks as a Model of the Visual System: Past, Present, and Future
R.I.P.
π»
Ghosted
A probabilistic atlas of the human thalamic nuclei combining ex vivo MRI and histology
R.I.P.
π»
Ghosted
Why Neurons Have Thousands of Synapses, A Theory of Sequence Memory in Neocortex
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted