EEG

Human language is unprecedented in its combinatorial capacity; we are capable of producing and understanding sentences we have never heard before. Although the mechanisms underlying this capacity have been described in formal linguistics and cognitive science, how they are implemented in the brain remains to a large extent unknown. A large body of earlier work from the cognitive neuroscientific literature implies a role for delta-band neural activity in the representation of linguistic structure and meaning. In this work, we combine these insights and techniques with findings from psycholinguistics to show that meaning is more than the sum of its parts; the delta-band MEG signal differentially reflects lexical information inside and outside sentence structures.

A presentation and summary of my main PhD results

Word surprisal and word entropy, derived from a recurrent neural networl for language modelling, are represented in EEG signals in several freuqency bands. The neural encoding is quantified using temporal response functions with continuous EEG recorded during naturalsitic story listening.

Neural activity tracks the envelope of a speech signal at latencies from 50 ms to 300 ms. Modulating this neural tracking through …

Poster presented at SNL 2017

This projects encouraged scientists to experiment with innovative and novel analysis techniques with the aim to expand the way scientists usually look at brain wave data.