Test-retest reliability of the magnetic mismatch negativity response to sound duration and omission deviants

Mismatch negativity (MMN) is a neurophysiological measure of auditory novelty detection that could serve as a translational biomarker of psychiatric disorders, such as schizophrenia. However, the replicability of its magnetoencephalographic (MEG) counterpart (MMNm) has been insufficiently addressed. In the current study, test-retest reliability of the MMNm response to both duration and omission deviants was evaluated over two MEG sessions in 16 healthy adults. MMNm amplitudes and latencies were obtained at both sensor- and source-level using a cortically-constrained minimum-norm approach. Intraclass correlations (ICC) were derived to assess stability of MEG responses over time. In addition, signal-to-noise ratios (SNR) and within-subject statistics were obtained in order to determine MMNm detectability in individual participants. ICC revealed robust values at both sensor- and source-level for both duration and omission MMNm amplitudes (ICC = 0.81-0.90), in particular in the right hemisphere, while moderate to strong values were obtained for duration MMNm and omission MMNm peak latencies (ICC = 0.74-0.88). Duration MMNm was robustly identified in individual participants with high SNR, whereas omission MMNm responses were only observed in half of the participants. Our data indicate that MMNm to unexpected duration changes and omitted sounds are highly reproducible, providing support for the use of MEG-parameters in basic and clinical research

Am J Intellect Dev Disabil

METHOD:Participants with FXS (N=41) and controls (N=27) underwent auditory ERP with a 32 lead EEG cap during presentation of an oddball paradigm. Analyses included log age as a covariate.RESULTS:Data was adequate for analysis for 33 participants with FXS and 27 controls (age 4-51y, 13 females (FXS); 4-54y,11 females (control)). Participants with FXS showed larger N1 and P2 amplitudes (p\u2019s0.05).CONCLUSION:Individuals with FXS show previously demonstrated increased in response amplitude and high frequency neural activity. Additionally, despite an overall normal developmental trajectory for most measures, individuals with FXS show age-independent but gender-dependent decreases in complex processing of novel stimuli. Many markers show strong retest reliability even in children and thus are potential biomarkers for clinical trials in FXS.U01 DD001186/DD/NCBDD CDC HHSUnited States/U01DD001186/ACL/ACL HHSUnited States/2021-11-30T00:00:00Z33211818PMC86312341186

Single-Trial EEG-fMRI Reveals the Generation Process of the Mismatch Negativity

Although research on the mismatch negativity (MMN) has been ongoing for 40 years, the generation process of the MMN remains largely unknown. In this study, we used a single-trial electro-encephalography (EEG)-functional magnetic resonance imaging (fMRI) coupling method which can analyze neural activity with both high temporal and high spatial resolution and thus assess the generation process of the MMN. We elicited the MMN with an auditory oddball paradigm while recording simultaneous EEG and fMRI. We divided the MMN into five equal-durational phases. Utilizing the single-trial variability of the MMN, we analyzed the neural generators of the five phases, thereby determining the spatiotemporal generation process of the MMN. We found two distinct bottom-up prediction error propagations: first from the auditory cortex to the motor areas and then from the auditory cortex to the inferior frontal gyrus (IFG). Our results support the regularity-violation hypothesis of MMN generation

Test–Retest Reliability of Mismatch Negativity (MMN) to Emotional Voices

A voice from kin species conveys indispensable social and affective signals with uniquely phylogenetic and ontogenetic standpoints. However, the neural underpinning of emotional voices, beyond low-level acoustic features, activates a processing chain that proceeds from the auditory pathway to the brain structures implicated in cognition and emotion. By using a passive auditory oddball paradigm, which employs emotional voices, this study investigates the test–retest reliability of emotional mismatch negativity (MMN), indicating that the deviants of positively (happily)- and negatively (angrily)-spoken syllables, as compared to neutral standards, can trigger MMN as a response to an automatic discrimination of emotional salience. The neurophysiological estimates of MMN to positive and negative deviants appear to be highly reproducible, irrespective of the subject’s attentional disposition: whether the subjects are set to a condition that involves watching a silent movie or do a working memory task. Specifically, negativity bias is evinced as threatening, relative to positive vocalizations, consistently inducing larger MMN amplitudes, regardless of the day and the time of a day. The present findings provide evidence to support the fact that emotional MMN offers a stable platform to detect subtle changes in current emotional shifts

Reliability of mismatch negativity event-related potentials in a multisite, traveling subjects study

Objective: To determine the optimal methods for measuring mismatch negativity (MMN), an auditory event-related potential (ERP), and quantify sources of MMN variance in a multisite setting. Methods: Reliability of frequency, duration, and double (frequency + duration) MMN was determined from eight traveling subjects, tested on two occasions at eight laboratory sites. Deviant-specific variance components were estimated for MMN peak amplitude and latency measures using different ERP processing methods. Generalizability (G) coefficients were calculated using two-facet (site and occasion), fully-crossed models and single-facet (occasion) models within each laboratory to assess MMN reliability. Results: G-coefficients calculated from two-facet models indicated fair (0.4 0.5). MMN amplitude reliability was greater than latency reliability, and reliability with mastoid referencing significantly outperformed nose-referencing. Conclusions: EEG preprocessing methods have an impact on the reliability of MMN amplitude. Within site MMN reliability can be excellent, consistent with prior single site studies. Significance: With standardized data collection and ERP processing, MMN can be reliably obtained in multisite studies, providing larger samples sizeswithin rare patient groups

Neuromagnetic mismatch negativity in individuals at clinical high risk state for psychosis

Advances in electroencephalography (EEG) and magnetoencephalography (MEG) have allowed the investigation into the neurophysiological basis of perceptual and cognitive disturbances across different stages of psychosis. The EEG/MEG recorded (neuromagnetic) mismatch negativity (MMN(m)) is a component of the event-related potential/field reflecting early pre-attentive auditory processing. Reduced MMN amplitude is a well-replicated finding in chronic schizophrenia patients and there is evidence for a smaller MMN impairment in first episode patients. Interestingly, studies have suggested that MMN deficits may be present even prior to the onset of psychosis in individuals at clinical high risk state for developing psychosis (CHR), suggesting that MMN amplitude could be a potential marker of psychosis risk. However, in contrast to the robust finding of an attenuated MMN amplitude in schizophrenia, results are more inconsistent at the earliest stages of illness. Moreover, to date most studies have used a conventional analysis for assessing MMN amplitudes in different stages of psychosis although brain connectivity measures, such as dynamic causal modelling (DCM) allow investigating effective connectivity in the brain network underlying the MMN generation. Also, two decades of research into characteristics of CHR individuals has revealed that they are functioning poorly regardless of subsequent transition to psychosis. However, while MMN amplitude has been studied as a potential marker for predicting psychosis among CHR individuals in several studies, its utility to predict other clinically relevant outcomes remains unknown. In the current thesis, I sought to examine MEG-recorded MMNm peak amplitude in individuals at different stages of psychosis as well as its association with neuropsychological performance, attenuated psychotic symptoms and psychosocial functioning in CHR individuals (chapter 3). The aim was to assess the potential of MMNm amplitude as a marker for early stages of psychosis and to examine whether MMNm deficits are pronounced in CHR individuals with poor functioning and cognitive deficits. Secondly, I employed DCM to examine whether effective connectivity in the underlying network of duration change detection is altered in CHR individuals compared to controls (chapter 4). Lastly, I investigated whether baseline MMNm amplitude is able to predict the 12-month outcome of CHR individuals in terms of transition to psychosis or sustained subthreshold psychotic symptoms and poor functioning (chapter 5). Given that the current study is the first large study that recruited CHR individuals predominantly from the community, clinical findings will also be reviewed and compared to previous studies with CHR individuals recruited from special early detection and intervention services. The findings in chapter 3 show that compared to controls, MMNm peak amplitudes were intact in CHR individuals as well as in first episode patients. Chapter 3 also indicates a weak positive association between MMNm amplitudes and speed of information processing in CHR individuals. Chapter 4 results indicate that CHR individuals do not have abnormal duration deviant induced changes in frontotemporal connectivity network compared to controls. Collectively these findings suggest that neither the peak amplitude nor the measures of effective connectivity underlying the MMNm response are related to the CHR state. Lastly, chapter 5 indicates that baseline MMNm amplitude is not associated with progression to a first episode psychosis, although this finding needs to be considered limited due to the low transition rate to psychosis, or persistence of subthreshold psychotic symptoms and poor functioning in CHR individuals. Overall, the findings in the thesis do not support the utility of using MMNm as a marker for emerging psychosis. However, future longitudinal studies with several MEG recording time points are required to further determine the timing of MMN deficiency and whether it reflects emerging psychosis or illness progression. The clinical findings of the thesis demonstrate that CHR individuals recruited from the general population are characterised by several clinical concerns and despite the majority of them not developing psychosis and remitting symptomatically over 12 months, CHR individuals were characterised by persistent functional disability, highlighting the importance of evaluating and predicting more systematically psychosocial functioning in this clinically meaningful population. Finally, I discuss the key neurophysiological and clinical findings of the three data chapters in chapter 6 in the context of previous findings as well as the limitations and strengths of the current thesis. I also discuss the possibility and key challenges of implementing electrophysiological measures as part of a multivariate and sequential testing in clinical practice as well as proposals for moving beyond the current UHR paradigm

Brain Responses Track Patterns in Sound

This thesis uses specifically structured sound sequences, with electroencephalography (EEG) recording and behavioural tasks, to understand how the brain forms and updates a model of the auditory world. Experimental chapters 3-7 address different effects arising from statistical predictability, stimulus repetition and surprise. Stimuli comprised tone sequences, with frequencies varying in regular or random patterns. In Chapter 3, EEG data demonstrate fast recognition of predictable patterns, shown by an increase in responses to regular relative to random sequences. Behavioural experiments investigate attentional capture by stimulus structure, suggesting that regular sequences are easier to ignore. Responses to repetitive stimulation generally exhibit suppression, thought to form a building block of regularity learning. However, the patterns used in this thesis show the opposite effect, where predictable patterns show a strongly enhanced brain response, compared to frequency-matched random sequences. Chapter 4 presents a study which reconciles auditory sequence predictability and repetition in a single paradigm. Results indicate a system for automatic predictability monitoring which is distinct from, but concurrent with, repetition suppression. The brain’s internal model can be investigated via the response to rule violations. Chapters 5 and 6 present behavioural and EEG experiments where violations are inserted in the sequences. Outlier tones within regular sequences evoked a larger response than matched outliers in random sequences. However, this effect was not present when the violation comprised a silent gap. Chapter 7 concerns the ability of the brain to update an existing model. Regular patterns transitioned to a different rule, keeping the frequency content constant. Responses show a period of adjustment to the rule change, followed by a return to tracking the predictability of the sequence. These findings are consistent with the notion that the brain continually maintains a detailed representation of ongoing sensory input and that this representation shapes the processing of incoming information

The brain as a generative model: information-theoretic surprise in learning and action

Our environment is rich with statistical regularities, such as a sudden cold gust of wind indicating a potential change in weather. A combination of theoretical work and empirical evidence suggests that humans embed this information in an internal representation of the world. This generative model is used to perform probabilistic inference, which may be approximated through surprise minimization. This process rests on current beliefs enabling predictions, with expectation violation amounting to surprise. Through repeated interaction with the world, beliefs become more accurate and grow more certain over time. Perception and learning may be accounted for by minimizing surprise of current observations, while action is proposed to minimize expected surprise of future events. This framework thus shows promise as a common formulation for different brain functions. The work presented here adopts information-theoretic quantities of surprise to investigate both perceptual learning and action. We recorded electroencephalography (EEG) of participants in a somatosensory roving-stimulus paradigm and performed trial-by-trial modeling of cortical dynamics. Bayesian model selection suggests early processing in somatosensory cortices to encode confidence-corrected surprise and subsequently Bayesian surprise. This suggests the somatosensory system to signal surprise of observations and update a probabilistic model learning transition probabilities. We also extended this framework to include audition and vision in a multi-modal roving-stimulus study. Next, we studied action by investigating a sensitivity to expected Bayesian surprise. Interestingly, this quantity is also known as information gain and arises as an incentive to reduce uncertainty in the active inference framework, which can correspond to surprise minimization. In comparing active inference to a classical reinforcement learning model on the two-step decision-making task, we provided initial evidence for active inference to better account for human model-based behaviour. This appeared to relate to participants’ sensitivity to expected Bayesian surprise and contributed to explaining exploration behaviour not accounted for by the reinforcement learning model. Overall, our findings provide evidence for information-theoretic surprise as a model for perceptual learning signals while also guiding human action.Unsere Umwelt ist reich an statistischen Regelmäßigkeiten, wie z. B. ein plötzlicher kalter Windstoß, der einen möglichen Wetterumschwung ankündigt. Eine Kombination aus theoretischen Arbeiten und empirischen Erkenntnissen legt nahe, dass der Mensch diese Informationen in eine interne Darstellung der Welt einbettet. Dieses generative Modell wird verwendet, um probabilistische Inferenz durchzuführen, die durch Minimierung von Überraschungen angenähert werden kann. Der Prozess beruht auf aktuellen Annahmen, die Vorhersagen ermöglichen, wobei eine Verletzung der Erwartungen einer Überraschung gleichkommt. Durch wiederholte Interaktion mit der Welt nehmen die Annahmen mit der Zeit an Genauigkeit und Gewissheit zu. Es wird angenommen, dass Wahrnehmung und Lernen durch die Minimierung von Überraschungen bei aktuellen Beobachtungen erklärt werden können, während Handlung erwartete Überraschungen für zukünftige Beobachtungen minimiert. Dieser Rahmen ist daher als gemeinsame Bezeichnung für verschiedene Gehirnfunktionen vielversprechend. In der hier vorgestellten Arbeit werden informationstheoretische Größen der Überraschung verwendet, um sowohl Wahrnehmungslernen als auch Handeln zu untersuchen. Wir haben die Elektroenzephalographie (EEG) von Teilnehmern in einem somatosensorischen Paradigma aufgezeichnet und eine trial-by-trial Modellierung der kortikalen Dynamik durchgeführt. Die Bayes'sche Modellauswahl deutet darauf hin, dass frühe Verarbeitung in den somatosensorischen Kortizes confidence corrected surprise und Bayesian surprise kodiert. Dies legt nahe, dass das somatosensorische System die Überraschung über Beobachtungen signalisiert und ein probabilistisches Modell aktualisiert, welches wiederum Wahrscheinlichkeiten in Bezug auf Übergänge zwischen Reizen lernt. In einer weiteren multimodalen Roving-Stimulus-Studie haben wir diesen Rahmen auch auf die auditorische und visuelle Modalität ausgeweitet. Als Nächstes untersuchten wir Handlungen, indem wir die Empfindlichkeit gegenüber der erwarteten Bayesian surprise betrachteten. Interessanterweise ist diese informationstheoretische Größe auch als Informationsgewinn bekannt und stellt, im Rahmen von active inference, einen Anreiz dar, Unsicherheit zu reduzieren. Dies wiederum kann einer Minimierung der Überraschung entsprechen. Durch den Vergleich von active inference mit einem klassischen Modell des Verstärkungslernens (reinforcement learning) bei der zweistufigen Entscheidungsaufgabe konnten wir erste Belege dafür liefern, dass active inference menschliches modellbasiertes Verhalten besser abbildet. Dies scheint mit der Sensibilität der Teilnehmer gegenüber der erwarteten Bayesian surprise zusammenzuhängen und trägt zur Erklärung des Explorationsverhaltens bei, das jedoch nicht vom reinforcement learning-Modell erklärt werden kann. Insgesamt liefern unsere Ergebnisse Hinweise für Formulierungen der informationstheoretischen Überraschung als Modell für Signale wahrnehmungsbasierten Lernens, die auch menschliches Handeln steuern

Atypical Cortical Connectivity in Autism Spectrum Disorder (ASD) as Measured by Magnetoencephalography (MEG)

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition, characterised by impairments in social interaction and communication, the presence of repetitive behaviours, and multisensory hyper- and hypo-sensitives. This thesis utilised magnetoencephalography, in combination with robust analysis techniques, to investigate the neural basis of ASD. Based on previous research, it was hypothesised that cortical activity in ASD would be associated with disruptions to oscillatory synchronisation during sensory processing, as well as during high-level perspective-taking. More specifically, a novel framework was introduced, based on local gamma-band dysregulation, global hypoconnectivity and deficient predictive-coding. To test this framework, data were collected from adolescents diagnosed with ASD and age-matched controls. Using a visual grating stimulus, it was found that in primary visual cortex, ASD participants had reduced coupling between the phase of alpha oscillations and the amplitude of gamma oscillations (i.e. phase amplitude coupling), suggesting dysregulated visual gamma in ASD. These findings were based on a robust analysis pipeline outlined in Chapter 2. Next, directed connectivity in the visual system was quantified using Granger causality. Compared with controls, ASD participants showed reductions in feedback connectivity, mediated by alpha oscillations, but no differences in inter-regional feedforward connectivity, mediated by gamma oscillations. In the auditory domain, it was found that ASD participants had reduced steady-state responses at 40Hz, in terms of oscillatory power and inter-trial coherence, again suggesting dysregulated gamma. Investigating predictive-coding theories of ASD using an auditory oddball paradigm, it was found that evoked responses to the omission of an expected tone were reduced for ASD participants. Finally, we found reductions in theta-band oscillatory power and connectivity for ASD participants, during embodied perspective-taking. Overall, these findings fit the proposed framework, and demonstrate that cortical activity in ASD is characterised by disruptions to oscillatory synchronisation, at the local and global scales, during both sensory processing and higher-level perspective-taking