Brain regional networks active during the mismatch negativity vary with paradigm

Weighted Blind Source Separation Can Decompose the Frequency Mismatch Response by Deviant Concatenation: An MEG Study

The mismatch response (MMR) is thought to be a neurophysiological measure of novel auditory detection that could serve as a translational biomarker of various neurological diseases. When recorded with electroencephalography (EEG) or magnetoencephalography (MEG), the MMR is traditionally extracted by subtracting the event-related potential/field (ERP/ERF) elicited in response to “deviant” sounds that occur randomly within a train of repetitive “standard” sounds. However, there are several problems with such a subtraction, which include increased noise and the neural adaptation problem. On the basis of the original theory underlying MMR (i.e., the memory-comparison process), the MMR should be present only in deviant epochs. Therefore, we proposed a novel method called weighted-BSST/k, which uses only the deviant response to derive the MMR. Deviant concatenation and weight assignment are the primary procedures of weighted-BSST/k, which maximize the benefits of time-delayed correlation. We hypothesized that this novel weighted-BSST/k method highlights responses related to the detection of the deviant stimulus and is more sensitive than independent component analysis (ICA). To test this hypothesis and the validity and efficacy of the weighted-BSST/k in comparison with ICA (infomax), we evaluated the methods in 12 healthy adults. Auditory stimuli were presented at a constant rate of 2 Hz. Frequency MMRs at a sensor level were obtained from the bilateral temporal lobes with the subtraction approach at 96–276 ms (the MMR time range), defined based on spatio-temporal cluster permutation analysis. In the application of the weighted-BSST/k, the deviant responses were given a constant weight using a rectangular window on the MMR time range. The ERF elicited by the weighted deviant responses demonstrated one or a few dominant components representing the MMR that fitted well with that of the sensor space analysis using the conventional subtraction approach. In contrast, infomax or weighted-infomax revealed many minor or pseudo components as constituents of the MMR. Our single-trial, contrast-free approach may assist in using the MMR in basic and clinical research, and it opens a new and potentially useful way to analyze event-related MEG/EEG data.

Frontotemporal network in automatic / pre-attentive detection of abstract change: An event-related optical signal (EROS) study

The human brain constantly monitors the environment for unexpected changes. Under the prediction violation account, the Inferior Frontal Cortex (IFC) is involved in prediction-related processes for deviance detection processes in the Superior Temporal Cortex (STC). Consistent with this account, previous studies revealed an IFC-to-STC-followed-by-IFC mismatch response pattern to physical changes using event-related optical signals (EROS). However, detecting physical changes can be achieved by direct comparison of physical features between stimuli without making predictions, thus direct evidence supporting the prediction nature of the IFC-STC network in pre-attentive change detection was lacking. To address this issue, this study examined the EROS mismatch responses of the IFC-STC network when detecting the violation of an abstract rule. The rule "the higher the frequency of a tone, the stronger the intensity" established by standards was violated by deviants of 12 deviance levels. When deviants were preceded by a short train of standards, early IFC, STC, and late IFC EROS mismatch responses linearly increased with the deviance levels. When deviants were preceded by a longer train of standards, the STC but not the early or late IFC EROS mismatch responses were elicited by all the deviants without modulation by deviance levels. These results demonstrate a functional role of the IFC in the abstract change detection when insufficient rule-conforming information could be extracted from the preceding standards and are consistent with the predictive violation account of pre-attentive change detection.

Objective electroencephalography-based assessment for auditory rehabilitation of pediatric cochlear implant users

The cochlear implant (CI) has an effective habilitation modality for hearing-impaired children by promoting sound perception, vocalization, and language ability. However, the major challenge that remained was the lack of assessment standards for pediatric CI users, especially prelingually deaf children, to evaluate hearing rehabilitation effectiveness. In the present study, we conducted an oddball paradigm with stimuli varying in pure-tone, syllable, and tonal sounds. After implantation, we utilized cortical auditory evoked potential (CAEP) and mismatch negativity (MMN) to obtain time-domain analysis; meanwhile, the source localization was investigated to obtain spatial accuracy of the plasticity in the auditory cortex. P1 started to emerge at the third month after implantation, but its peak level was not significant until the sixth month. The temporal lobe was activated between the third and sixth months after implantation. The MMN waveform was basically normal approximately after 12 months. These results suggest that the auditory system goes through a critical period of rapid development between three and six months and enters a maturation period after 12 months. This work indicates that CAEPs are more suitable for assessing the early auditory system reconstruction, while MMN performs better in evaluating the advanced auditory function. Furthermore, source localization has proven to be an efficient tool in exploring auditory cortex plasticity, especially for pediatric CI users.

Empirical Bayes evaluation of fused EEG-MEG source reconstruction: Application to auditory mismatch evoked responses

We here turn the general and theoretical question of the complementarity of EEG and MEG for source reconstruction, into a practical empirical one. Precisely, we address the challenge of evaluating multimodal data fusion on real data. For this purpose, we build on the flexibility of Parametric Empirical Bayes, namely for EEG-MEG data fusion, group level inference and formal hypothesis testing. The proposed approach follows a two-step procedure by first using unimodal or multimodal inference to derive a cortical solution at the group level; and second by using this solution as a prior model for single subject level inference based on either unimodal or multimodal data. Interestingly, for inference based on the same data (EEG, MEG or both), one can then formally compare, as alternative hypotheses, the relative plausibility of the two unimodal and the multimodal group priors. Using auditory data, we show that this approach enables to draw important conclusions, namely on (i) the superiority of multimodal inference, (ii) the greater spatial sensitivity of MEG compared to EEG, (iii) the ability of EEG data alone to source reconstruct temporal lobe activity, (iv) the usefulness of EEG to improve MEG based source reconstruction. Importantly, we largely reproduce those findings over two different experimental conditions. We here focused on Mismatch Negativity (MMN) responses for which generators have been extensively investigated with little homogeneity in the reported results. Our multimodal inference at the group level revealed spatio-temporal activity within the supratemporal plane with a precision which, to our knowledge, has never been achieved before with non-invasive recordings.

Functional connectivity of the frontotemporal network in preattentive detection of abstract changes: Perturbs and observes with transcranial magnetic stimulation and event-related optical signal

Current theories of automatic or preattentive change detection suggest a regularity or prediction violation mechanism involving functional connectivity between the inferior frontal cortex (IFC) and the superior temporal cortex (STC). By disrupting the IFC function with transcranial magnetic stimulation (TMS) and recording the later STC mismatch response with event-related optical signal (EROS), previous study demonstrated a causal IFC-to-STC functional connection in detecting a pitch or physical change. However, physical change detection can be achieved by memory comparison of the physical features and may not necessarily involve regularity/rule extraction and prediction. The current study investigated the IFC-STC functional connectivity in detecting rule violation (i.e., an abstract change). Frequent standard tone pairs with a constant relative pitch difference, but varying pitches, were presented to establish a pitch interval rule. This abstract rule was violated by deviants with reduced relative pitch intervals. The EROS STC mismatch response to the deviants was abolished by the TMS applied at the IFC 80 ms after deviance onset, but preserved in the spatial (TMS on vertex), auditory (TMS sound), and temporal (200 ms after deviance onset) control conditions. These results demonstrate the IFC-STC connection in preattentive abstract change detection and support the regularity or prediction violation account.

Neurophysiological predictors of aphasia recovery in patients with large left-hemispheric infarction

Background:

Although the rehabilitation of aphasia has been extensively studied, the prediction of language outcome still has not received sufficient attention. The aim of this study was to predict the language outcome using mismatch negativity (MMN) in patients with large left-hemispheric infarction.

Methods:

MMN was elicited by an oddball paradigm in which a standard tone (1000 Hz) and deviant tone (1500 Hz) were presented at 90% and 10% of the number of tones, respectively. The mean amplitudes and laterality indexes (LIs) of MMN were measured over the prefrontal, frontal, central, parietal, temporal, and perisylvian electrodes and both hemispheres during the first 7 days (session 1) and 10 to 20 days (session 2) post-onset. Mixed three-way analysis of variance (ANOVA) was used to investigate differences in these factors between two aphasia groups (the good recovery group and poor recovery group). The predictive value of the most significant LI was also compared with the score of National Institutes of Health Stroke Scale score and low-density volume on computed tomography.

Results:

A total of 18 patients were enrolled in this study. Mixed three-way ANOVA showed no interaction effect of session × region of interest (ROI) × group (F [3.59, 57.38] = 1.301, P = 0.282) and no interaction effect of ROI × group (F [1.81, 29.01] = 0.71, P = 0.487) and session × group (F [1.00, 16.00] = 0.084, P = 0.776) for MMN amplitude. No interaction effect of session × ROI × group (F [1.79, 28.58] = 0.62, P = 0.530), but an interaction effect of session × group (F [1.00, 16.00] = 5.21, P = 0.036) was found for LIs. In the poor recovery group, the LIs of MMN over all the ROIs, except the parietal area, became more negative at session 2 than those at session 1 (P < 0.05), but this effect was not observed in the good recovery group. Additionally, significant differences were observed in the LIs at session 2 between the two groups (P < 0.05). The LI over the perisylvian area at session 2 had the highest predictive value with an area under the curve of 0.963 (95% confidence interval: 0.884–1.000). An LI score >−0.36 over the perisylvian area suggested good recovery, but a score <−0.36 suggested poor recovery. The LI cut-off value of −0.36 had the highest sensitivity (90.0%) and specificity (87.5%) for predicting a good language outcome at 3 months post-stroke.

Conclusion:

LIs of MMN amplitudes at approximately 2 weeks post left-hemisphere stroke serve as more sensitive predictors of language outcome, among which the LI over the perisylvian area exhibits the best predictive value.

Search asymmetry in a serial auditory task: Neural source analyses of EEG implicate attention strategies

Here we report a detailed analysis of the fast network dynamics underlying P3a and P3b event-related potential (ERP) subcomponents generated during an unconventional serial auditory search paradigm. We dissect the electroencephalographic (EEG) data from an earlier study of ours, using a variety of advanced signal processing techniques, in order to discover how the brain is processing auditory targets differently when they possess a rare, salient, unpredictable feature not shared with distractors than when targets lack this feature but distractors have it. We find that brain regions associated with the Ventral Attention Network (VAN) are the primary neural generators of the P3a subcomponent in response to feature-present targets, whereas regions associated with the Dorsal Attention Network (DAN), as well as regions associated with detecting auditory oddball stimuli (ODD), may be the primary neural generators of the P3b, in the context of our study, and perhaps in search paradigms in general. Moreover, measurements of the time courses of oscillatory power changes and inter-regional synchronization in theta and low-gamma frequency bands were consistent with the early activation and synchronization within the VAN associated with the P3a subcomponent, and with the later activation and synchronization within the DAN and ODD networks associated with the P3b subcomponent. Implications of these finding for the mechanisms underlying search asymmetry phenomena are discussed.

Body representations as indexed by oscillatory EEG activities in the context of tactile novelty processing

Neural oscillatory activities in different frequency bands are known to reflect different cognitive functions. The current study investigates neural oscillations involved in tactile novelty processing, in particular how physically different digits of the hand may be categorized as being more or less similar to one another. Time-frequency analyses were conducted on EEG responses recorded from a somatosensory mismatch protocol involving stimulation of the 1st, 3rd, and 5th digits. The pattern of tactile stimulation leveraged a functional category boundary between the 1st digit (thumb) and the other fingers. This functional category has been hypothesized to derive, in part, from the way that the hand is used to grasp and haptically explore objects. EEG responses to standard stimuli (the 3rd digit, probability of 80%) and two deviant stimuli (1st digit as across-boundary deviant and 5th digit as within-boundary deviant, probability of 10% each) were examined. Analyses of EEG responses examined changes in power as well as phase information. Deviant tactile stimuli evoked significantly greater theta event-related synchronization and greater phase-locking values compared to the corresponding control stimuli. The increase in theta power evoked by the contrast of the 3rd digit and the 1st digit was significantly larger than for the contrast between the 3rd and 5th digits. Desynchronization in the alpha and beta bands was greater for deviant than control stimuli, which may reflect increased local cortical excitation to novel stimuli, modulated by top-down feedback processes as part of a hierarchical novelty detection mechanism. The results are discussed in the context of the growing literature on neural processes involved in the generation and maintenance of body representations.

A Comparison of Auditory Oddball Responses in Dorsolateral Prefrontal Cortex, Basolateral Amygdala, and Auditory Cortex of Macaque

The mismatch negativity (MMN) is an ERP component seen in response to unexpected "novel" stimuli, such as in an auditory oddball task. The MMN is of wide interest and application, but the neural responses that generate it are poorly understood. This is in part due to differences in design and focus between animal and human oddball paradigms. For example, one of the main explanatory models, the "predictive error hypothesis", posits differences in timing and selectivity between signals carried in auditory and prefrontal cortex (PFC). However, these predictions have not been fully tested because (1) noninvasive techniques used in humans lack the combined spatial and temporal precision necessary for these comparisons and (2) single-neuron studies in animal models, which combine necessary spatial and temporal precision, have not focused on higher order contributions to novelty signals. In addition, accounts of the MMN traditionally do not address contributions from subcortical areas known to be involved in novelty detection, such as the amygdala. To better constrain hypotheses and to address methodological gaps between human and animal studies, we recorded single neuron activity from the auditory cortex, dorsolateral PFC, and basolateral amygdala of two macaque monkeys during an auditory oddball paradigm modeled after that used in humans. Consistent with predictions of the predictive error hypothesis, novelty signals in PFC were generally later than in auditory cortex and were abstracted from stimulus-specific effects seen in auditory cortex. However, we found signals in amygdala that were comparable in magnitude and timing to those in PFC, and both prefrontal and amygdala signals were generally much weaker than those in auditory cortex. These observations place useful quantitative constraints on putative generators of the auditory oddball-based MMN and additionally indicate that there are subcortical areas, such as the amygdala, that may be involved in novelty detection in an auditory oddball paradigm.

Attenuated mismatch negativity in patients with first-episode antipsychotic-naive schizophrenia using a source-resolved method

BACKGROUND

Mismatch negativity (MMN) is a measure of pre-attentive auditory information processing related to change detection. Traditional scalp-level EEG methods consistently find attenuated MMN in patients with chronic but not first-episode schizophrenia. In the current paper, we use a source-resolved method to assess MMN and hypothesize that more subtle changes can be identified with this analysis method.

METHOD

Fifty-six first-episode antipsychotic-naïve schizophrenia (FEANS) patients (31 males, 25 females, mean age 24.6) and 64 matched controls (37 males, 27 females, mean age 24.8) were assessed for duration-, frequency- and combined-type MMN and P3a as well as 4 clinical, 3 cognitive and 3 psychopathological measures. To evaluate and correlate MMN at source-level, independent component analysis (ICA) was applied to the continuous EEG data to derive equivalent current dipoles which were clustered into 19 clusters based on cortical location.

RESULTS

No scalp channel group MMN or P3a amplitude differences were found. Of the localized clusters, several were in or near brain areas previously suggested to be involved in the MMN response, including frontal and anterior cingulate cortices and superior temporal and inferior frontal gyri. For duration deviants, MMN was attenuated at the right superior temporal gyrus in patients compared to healthy controls (p = 0.01), as was P3a at the superior frontal cortex (p = 0.01). No individual patient correlations with clinical, cognitive, or psychopathological measures survived correction for multiple comparisons.

CONCLUSION

Attenuated source-localized MMN and P3a peak contributions can be identified in FEANS patients using a method based on independent component analysis (ICA). This indicates that deficits in pre-attentive auditory information processing are present at this early stage of schizophrenia and are not the result of disease chronicity or medication. This is to our knowledge the first study on FEANS patients using this more detailed method.

Dysfunction of attention switching networks in amyotrophic lateral sclerosis

OBJECTIVE

To localise and characterise changes in cognitive networks in Amyotrophic Lateral Sclerosis (ALS) using source analysis of mismatch negativity (MMN) waveforms.

RATIONALE

The MMN waveform has an increased average delay in ALS. MMN has been attributed to change detection and involuntary attention switching. This therefore indicates pathological impairment of the neural network components which generate these functions. Source localisation can mitigate the poor spatial resolution of sensor-level EEG analysis by associating the sensor-level signals to the contributing brain sources. The functional activity in each generating source can therefore be individually measured and investigated as a quantitative biomarker of impairment in ALS or its sub-phenotypes.

METHODS

MMN responses from 128-channel electroencephalography (EEG) recordings in 58 ALS patients and 39 healthy controls were localised to source by three separate localisation methods, including beamforming, dipole fitting and exact low resolution brain electromagnetic tomography.

RESULTS

Compared with controls, ALS patients showed significant increase in power of the left posterior parietal, central and dorsolateral prefrontal cortices (false discovery rate = 0.1). This change correlated with impaired cognitive flexibility (rho = 0.45, 0.45, 0.47, p = .042, .055, .031 respectively). ALS patients also exhibited a decrease in the power of dipoles representing activity in the inferior frontal (left: p = 5.16 × 10-6, right: p = 1.07 × 10-5) and left superior temporal gyri (p = 9.30 × 10-6). These patterns were detected across three source localisation methods. Decrease in right inferior frontal gyrus activity was a good discriminator of ALS patients from controls (AUROC = 0.77) and an excellent discriminator of C9ORF72 expansion-positive patients from controls (AUROC = 0.95).

INTERPRETATION

Source localization of evoked potentials can reliably discriminate patterns of functional network impairment in ALS and ALS subgroups during involuntary attention switching. The discriminative ability of the detected cognitive changes in specific brain regions are comparable to those of functional magnetic resonance imaging (fMRI). Source analysis of high-density EEG patterns has excellent potential to provide non-invasive, data-driven quantitative biomarkers of network disruption that could be harnessed as novel neurophysiology-based outcome measures in clinical trials.

Mapping the spatiotemporal dynamics of processing task-relevant and task-irrelevant sound feature changes using concurrent EEG-fMRI

The cortical processing of changes in auditory input involves auditory sensory regions as well as different frontoparietal brain networks. The spatiotemporal dynamics of the activation spread across these networks has, however, not been investigated in detail so far. We here approached this issue using concurrent functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), providing us with simultaneous information on both the spatial and temporal patterns of change-related activity. We applied an auditory stimulus categorization task with switching categorization rules, allowing to analyze change-related responses as a function of the changing sound feature (pitch or duration) and the task relevance of the change. Our data show the successive progression of change-related activity from regions involved in early change detection to the ventral and dorsal attention networks, and finally the central executive network. While early change detection was found to recruit feature-specific networks involving auditory sensory but also frontal and parietal brain regions, the later spread of activity across the frontoparietal attention and executive networks was largely independent of the changing sound feature, suggesting the existence of a general feature-independent processing pathway of change-related information. Task relevance did not modulate early auditory sensory processing, but was mainly found to affect processing in frontal brain regions. Hum Brain Mapp 37:3400-3416, 2016. © 2016 Wiley Periodicals, Inc.

Oscillatory power and functional connectivity in the speech change detection network

We used passive and active oddball conditions with two types of acoustic contrasts, between speech syllables that cross phonetic boundaries (across-category, AC) and between those that do not cross them (within-category, WC), to explore the effects of meaningful speech contrasts on the dynamics of the neural network underlying the mismatch negativity (MMN) to the speech deviants. We found that easily detected AC deviants evoked a MMN response that lateralized to the left hemisphere, but the very difficult to detect WC deviants did not elicit a MMN response at all. Based on independent component analysis of the continuous EEG, we computed both power changes within, and functional connectivity (phase synchronization) between, brain regional sources comprising the neural network associated with the MMN for these speech stimuli. We found that for acoustic contrasts for which an MMN was generated, power changes suggested whether a particular brain region was more involved with processing standards or deviants. Moreover, we not only replicated the changes in functional connectivity between orbitofrontal cortex and superior temporal gyrus found in previous experiments, but also found significant increases in synchronization between those regions and regions of the left inferior frontal gyrus (Broca's area), which is thought to be involved in the storage and retrieval of phonological and semantic information.