Effects of acoustic periodicity and intelligibility on the neural oscillations in response to speech

Although several studies have investigated neural oscillations in response to acoustically degraded speech, it is still a matter of debate which neural frequencies reflect speech intelligibility. Part of the problem is that effects of acoustics and intelligibility have so far not been considered independently. In the current electroencephalography (EEG) study the amount of acoustic periodicity (i.e. the amount of time the stimulus sentences were voiced) was manipulated, while using the listeners’ spoken responses to control for differences in intelligibility. Firstly, the total EEG power changes in response to completely aperiodic (noise-vocoded) speech and speech with a natural mix of periodicity and aperiodicity were almost identical, while an increase in theta power (5–6.3 Hz) and a trend for less beta power (11–18 Hz) were observed in response to completely periodic speech. These two effects are taken to indicate an information processing conflict caused by the unnatural acoustic properties of the stimuli, and that the subjects may have internally rehearsed the sentences as a result of this. Secondly, we separately investigated effects of intelligibility by sorting the trials in the periodic condition according to the listeners’ spoken responses. The comparison of intelligible and largely unintelligible trials revealed that the total EEG power in the delta band (1.7–2.7 Hz) was markedly increased during the second half of the intelligible trials, which suggests that delta oscillations are an indicator of successful speech understanding

Algorithmic procedures for Bayesian MEG/EEG source reconstruction in SPM

AbstractThe MEG/EEG inverse problem is ill-posed, giving different source reconstructions depending on the initial assumption sets. Parametric Empirical Bayes allows one to implement most popular MEG/EEG inversion schemes (Minimum Norm, LORETA, etc.) within the same generic Bayesian framework. It also provides a cost-function in terms of the variational Free energy—an approximation to the marginal likelihood or evidence of the solution. In this manuscript, we revisit the algorithm for MEG/EEG source reconstruction with a view to providing a didactic and practical guide. The aim is to promote and help standardise the development and consolidation of other schemes within the same framework. We describe the implementation in the Statistical Parametric Mapping (SPM) software package, carefully explaining each of its stages with the help of a simple simulated data example. We focus on the Multiple Sparse Priors (MSP) model, which we compare with the well-known Minimum Norm and LORETA models, using the negative variational Free energy for model comparison. The manuscript is accompanied by Matlab scripts to allow the reader to test and explore the underlying algorithm

Across-subjects classification of stimulus modality from human MEG high frequency activity

Single-trial analyses have the potential to uncover meaningful brain dynamics that are obscured when averaging across trials. However, low signal-to-noise ratio (SNR) can impede the use of single-trial analyses and decoding methods. In this study, we investigate the applicability of a single-trial approach to decode stimulus modality from magnetoencephalographic (MEG) high frequency activity. In order to classify the auditory versus visual presentation of words, we combine beamformer source reconstruction with the random forest classification method. To enable group level inference, the classification is embedded in an across-subjects framework. We show that single-trial gamma SNR allows for good classification performance (accuracy across subjects: 66.44%). This implies that the characteristics of high frequency activity have a high consistency across trials and subjects. The random forest classifier assigned informational value to activity in both auditory and visual cortex with high spatial specificity. Across time, gamma power was most informative during stimulus presentation. Among all frequency bands, the 75 Hz to 95 Hz band was the most informative frequency band in visual as well as in auditory areas. Especially in visual areas, a broad range of gamma frequencies (55 Hz to 125 Hz) contributed to the successful classification. Thus, we demonstrate the feasibility of single-trial approaches for decoding the stimulus modality across subjects from high frequency activity and describe the discriminative gamma activity in time, frequency, and space

Gamma band pitch responses in human auditory cortex measured with magnetoencephalography

We have previously used direct electrode recordings in two human subjects to identify neural correlates of the perception of pitch (Griffiths, Kumar, Sedley et al., Direct recordings of pitch responses from human auditory cortex, Curr. Biol. 22 (2010), pp. 1128–1132). The present study was carried out to assess virtual-electrode measures of pitch perception based on non-invasive magnetoencephalography (MEG). We recorded pitch responses in 13 healthy volunteers using a passive listening paradigm and the same pitch-evoking stimuli (regular interval noise; RIN) as in the previous study. Source activity was reconstructed using a beamformer approach, which was used to place virtual electrodes in auditory cortex. Time-frequency decomposition of these data revealed oscillatory responses to pitch in the gamma frequency band to occur, in Heschl's gyrus, from 60 Hz upwards. Direct comparison of these pitch responses to the previous depth electrode recordings shows a striking congruence in terms of spectrotemporal profile and anatomical distribution. These findings provide further support that auditory high gamma oscillations occur in association with RIN pitch stimuli, and validate the use of MEG to assess neural correlates of normal and abnormal pitch perception

The role of acoustic periodicity in perceiving speech

This thesis investigated the role of one important acoustic feature, periodicity, in the perception of speech. In the context of this thesis, periodicity denotes that a speech sound is voiced, giving rise to a sonorous sound quality sharply opposed to that of noisy unvoiced sounds. In a series of behavioural and electroencephalography (EEG) experiments, it was tested how the presence and absence of periodicity in both target speech and background noise affects the ability to understand speech, and its cortical representation. Firstly, in quiet listening conditions, speech with a natural amount of periodicity and completely aperiodic speech were equally intelligible, while completely periodic speech was much harder to understand. In the presence of a masker, however, periodicity in the target speech mattered little. In contrast, listeners substantially benefitted from periodicity in the masker and this socalled masker-periodicity benefit (MPB) was about twice as large as the fluctuatingmasker benefit (FMB) obtained from masker amplitude modulations. Next, cortical EEG responses to the same three target speech conditions were recorded. In an attempt to isolate effects of periodicity and intelligibility, the trials were sorted according to the correctness of the listeners’ spoken responses. More periodicity rendered the event-related potentials more negative during the first second after sentence onset, while a slow negativity was observed when the sentences were more intelligible. Additionally, EEG alpha power (7–10 Hz) was markedly increased before the least intelligible sentences. This finding is taken to indicate that the listeners have not been fully focussed on the task before these trials. The same EEG data were also analysed in the frequency domain, which revealed a distinct response pattern, with more theta power (5–6.3 Hz) and a trend for less beta power (11–18 Hz), in the fully periodic condition, but again no differences between the other two conditions. This pattern may indicate that the subjects internally rehearsed the sentences in the periodic condition before they verbally responded. Crucially, EEG power in the delta range (1.7–2.7 Hz) was substantially increased during the second half of intelligible sentences, when compared to their unintelligible counterparts. Lastly, effects of periodicity in the perception of speech in noise were examined in simulations of cochlear implants (CIs). Although both were substantially reduced, the MPB was still about twice as large as the FMB, highlighting the robustness of periodicity cues, even with the limited access to spectral information provided by simulated CIs. On the other hand, the larger absolute reduction of the MBP compared to normal-hearing also suggests that the inability to exploit periodicity cues may be an even more important factor in explaining the poor performance of CI users than the inability to benefit from masker fluctuations

Cortical mechanisms for tinnitus in humans /

PhD ThesisThis work sought to characterise neurochemical and neurophysiological processes underlying tinnitus in humans. The first study involved invasive brain recordings from a neurosurgical patient, along with experimental manipulation of his tinnitus, to map the cortical system underlying his tinnitus. Widespread tinnitus-linked changes in low- and high-frequency oscillations were observed, along with inter-regional and cross-frequency patterns of communication. The second and third studies compared tinnitus patients to controls matched for age, sex and hearing loss, measuring auditory cortex spontaneous oscillations (with magnetoencephalography) and neurochemical concentrations (with magnetic resonance spectroscopy) respectively. Unlike in previous studies not controlled for hearing loss, there were no group differences in oscillatory activity attributable to tinnitus. However, there was a significant correlation between gamma oscillations (>30Hz) and hearing loss in the tinnitus group, and between delta oscillations (1-4Hz) and perceived tinnitus loudness. In the neurochemical study, tinnitus patients had significantly reduced GABA concentrations compared to matched controls, and within this group there was a positive correlation between choline concentration (potentially linked to acetylcholine and/or neuronal plasticity) and both hearing loss, and subjective tinnitus intensity and distress. In light of present and previous findings, tinnitus may be best explained by a predictive coding model of perception, which was tested in the final experiment. This directly controlled the three main quantities comprising predictive coding models, and found that delta/theta/alpha oscillations (1-12Hz) encoded the precision of predictions, beta oscillations (12-30Hz) encoded changes to predictions, and gamma oscillations represented surprise (unexpectedness of stimuli based on predictions). The work concludes with a predictive coding model of tinnitus that builds upon the present findings and settles unresolved paradoxes in the literature. In this, precursor processes (in varying combinations) synergise to increase the precision associated with spontaneous activity in the auditory pathway to the point where it overrides higher predictions of ‘silence’.Medical Research Council Wellcome Trust and the National Institutes of Healt

Development of a passive MEG stimulus for measurement of the binaural masking level difference

The ability to hear a target signal over background noise is an important aspect of efficient hearing in everyday situations. This mechanism depends on binaural hearing whenever there are differences in the inter-aural timing of inputs from the noise and the signal. Impairments in binaural hearing may underlie some auditory processing disorders, for example temporal-lobe epilepsies. The binaural masking level difference (BMLD) measures the advantage in detecting a tone whose inter-aural phase differs from that of the masking noise. BMLD’s are typically estimated psychophysically, but this is challenging in children or those with cognitive impairments. The aim of this doctorate is to design a passive measure of BMLD using magnetoencephalography (MEG) and test this in adults, children and patients with different types of epilepsy. The stimulus consists of Gaussian background noise with 500-Hz tones presented binaurally either in-phase or 180° out-of-phase between the ears. Source modelling provides the N1m amplitude for the in-phase and out-of-phase tones, representing the extent of signal perception over background noise. The passive BMLD stimulus is successfully used as a measure of binaural hearing capabilities in participants who would otherwise be unable to undertake a psychophysical task