Neural tracking as a diagnostic tool to assess the auditory pathway

Abstract

The neural tracking framework enables the analysis of neural responses (EEG) to continuous natural speech, e.g., a story or a podcast. This allows for objective investigation of a range of auditory and linguistic processes in the brain during natural speech perception. This approach is more ecologically valid than traditional auditory evoked responses and has great potential for both research and clinical applications. In this article, we review the neural tracking framework and highlight three prominent examples of neural tracking analyses. This includes the neural tracking of the fundamental frequency of the voice (f0), the speech envelope and linguistic features. Each of these analyses provides a unique point of view into the hierarchical stages of speech processing in the human brain. f0-tracking assesses the encoding of fine temporal information in the early stages of the auditory pathway, i.e. from the auditory periphery up to early processing in the primary auditory cortex. This fundamental processing in (mostly) subcortical stages forms the foundation of speech perception in the cortex. Envelope tracking reflects bottom-up and top-down speech-related processes in the auditory cortex, and is likely necessary but not sufficient for speech intelligibility. To study neural processes more directly related to speech intelligibility, neural tracking of linguistic features can be used. This analysis focuses on the encoding of linguistic features (e.g. word or phoneme surprisal) in the brain. Together these analyses form a multi-faceted and time-effective objective assessment of the auditory and linguistic processing of an individual.

Speech understanding oppositely affects acoustic and linguistic neural tracking in a speech rate manipulation paradigm

“…For the phoneme-related features, phoneme surprisal and cohort entropy, this peak occurs around 250 ms. For the word-related features, word surprisal and word frequency, this peak occurs somewhat later, around 350 ms. The difference in timescale between both feature groups could be linked to the different speech processing stages (phonemes versus words) they represent (Van Canneyt et al, 2021). Regarding the topographies of these peaks, the understandable speech conditions are associated with a typical topography, similar to the classical N400 responses characterized by central negative channels.…”

Heard or understood? Neural tracking of language features in a comprehensible story, an incomprehensible story and a word list

“…Altogether, this suggests that acoustic tracking is required to comprehend speech but does not necessarily imply speech comprehension. We might overcome this issue by investigating neural tracking of language properties of the speech, hereafter called language tracking (Gillis et al, 2022).…”

Leading and Following: Noise Differently Affects Semantic and Acoustic Processing during Naturalistic Speech Comprehension

“…The time lags for forward modeling were chosen to cover a relatively broad time range, from -1000 to 1000 ms (J. . The λ is the ridge parameter used to prevent overfitting and ranged between 0.1 and 1000 in steps of the powers of 10 empirically (Gillis, Van Canneyt, et al, 2022). The cross-validation procedure was implemented in a leave-one-trial-out manner within each participant: each time the model was trained based on 9 trials and tested on the left-out trial, which was repeated for each of the 10 trials at three noise .…”