Decoding speech comprehension from continuous EEG recordings

Human language is a remarkable manifestation of our cognitive abilities which is unique to our species. It is key to communication, but also to our faculty of generating complex thoughts. We organise, conceptualise, and share ideas through language. Neuroscience has shed insightful lights on our understanding of how language is processed by the brain although the exact neural organisation, structural or functional, underpinning this processing remains poorly known. This project aims to employ new methodology to understand speech comprehension during naturalistic listening condition. One achievement of this thesis lies in bringing evidence towards putative predictive processing mechanisms for language comprehension and confront those with rule-based grammar processing. Namely, we looked on the one hand at cortical responses to information-theoretic measures that are relevant for predictive coding in the context of language processing and on the other hand to the response to syntactic tree structures. We successfully recorded responses to linguistic features from continuous EEG recordings during naturalistic speech listening. The use of ecologically valid stimuli allowed us to embed neural response in the context in which they naturally occur when hearing speech. This fostered the development of new analysis tools adapted for such experimental designs. Finally, we demonstrate the ability to decode comprehension from the EEG signals of participants with above-chance accuracy. This could be used as a better indicator of the severity and specificity of language disorders, and also to assess if a patient in a vegetative state understands speech without the need for any behavioural response. Hence a primary outcome is our contribution to the neurobiology of language comprehension. Furthermore, our results pave the way to the development of a new range of diagnostic tools to measure speech comprehension of patients with language impairment.Open Acces

Modulation of speech-in-noise comprehension through transcranial current stimulation with the phase-shifted speech envelope

This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/Neural activity tracks the envelope of a speech signal at latencies from 50 ms to 300 ms. Modulating this neural tracking through transcranial alternating current stimulation influences speech comprehension. Two important variables that can affect this modulation are the latency and the phase of the stimulation with respect to the sound. While previous studies have found an influence of both variables on speech comprehension, the interaction between both has not yet been measured. We presented 17 subjects with speech in noise coupled with simultaneous transcranial alternating current stimulation. The currents were based on the envelope of the target speech but shifted by different phases, as well as by two temporal delays of 100 ms and 250 ms. We also employed various control stimulations, and assessed the signal-to-noise ratio at which the subject understood half of the speech. We found that, at both latencies, speech comprehension is modulated by the phase of the current stimulation. However, the form of the modulation differed between the two latencies. Phase and latency of neurostimulation have accordingly distinct influences on speech comprehension. The different effects at the latencies of 100 ms and 250 ms hint at distinct neural processes for speech processing.Peer reviewe

Example of stimuli used in experiment

<p>Three setences (semantically unpredictable sentences, see code on language processing) synthesized by IVONA femal voice:</p> <p>- normal condition, just synthesized</p> <p>- fast condition, compressed using PSOLA from Praat by a factor 3</p> <p>- Gap inserted</p> <p> </p> <p>Inspired from ghittza (2009) experiment.</p

EEG methods to assess speech comprehension

<p>Entrainment of cortical oscillations, a Neural correlate for speech comprehension?</p

Effects of psilocybin on the human brain functional network

<p>MSc Final year thesis (Imperial College of London, Department of physics)</p

Code MRes Neurotechnology

<p>All the code from python code to generate SUS, to script generating stimuli and stimuli presentaion in Matlab with Psychtoolbox, including my staircase procedure , is included here.</p> <p>This code has been used in the MRes project about EEG analysis to study speech comprehension.</p> <p>/!\ The code, especially related to the experiment, is not in any case in a distribuable version !!</p> <p>For further info please contact [email protected]</p> <p>The project is based on Ghitza (2009) exeperiment.</p

Source, code, figures of my MSc final year project

<p>The project is a master thesis that I did at Imperial College of London, department of physics. I was supervised by Tim Evans.</p> <p>The project is a study of the effects of psilocybin on the human brain functional network.</p

Cortical Tracking of Surprisal during Continuous Speech Comprehension

Speech comprehension requires rapid online processing of a continuous acoustic signal to extract structure and meaning. Previous studies on sentence comprehension have found neural correlates of the predictability of a word given its context, as well as of the precision of such a prediction. However, they have focused on single sentences and on particular words in those sentences. Moreover, they compared neural responses to words with low and high predictability, as well as with low and high precision. However, in speech comprehension, a listener hears many successive words whose predictability and precision vary over a large range. Here, we show that cortical activity in different frequency bands tracks word surprisal in continuous natural speech and that this tracking is modulated by precision. We obtain these results through quantifying surprisal and precision from naturalistic speech using a deep neural network and through relating these speech features to EEG responses of human volunteers acquired during auditory story comprehension. We find significant cortical tracking of surprisal at low frequencies, including the delta band as well as in the higher frequency beta and gamma bands, and observe that the tracking is modulated by the precision. Our results pave the way to further investigate the neurobiology of natural speech comprehension