The internal auditory clock: what can evoked potentials reveal about the analysis of temporal sound patterns, and abnormal states of consciousness?

A predictive model for consciousness recovery of comatose patients after acute brain injury

Background

Predicting the consciousness recovery for comatose patients with acute brain injury is an important issue. Although some efforts have been made in the study of prognostic assessment methods, it is still unclear which factors can be used to establish model to directly predict the probability of consciousness recovery.

Objectives

We aimed to establish a model using clinical and neuroelectrophysiological indicators to predict consciousness recovery of comatose patients after acute brain injury.

Methods

The clinical data of patients with acute brain injury admitted to the neurosurgical intensive care unit of Xiangya Hospital of Central South University from May 2019 to May 2022, who underwent electroencephalogram (EEG) and auditory mismatch negativity (MMN) examinations within 28 days after coma onset, were collected. The prognosis was assessed by Glasgow Outcome Scale (GOS) at 3 months after coma onset. The least absolute shrinkage and selection operator (LASSO) regression analysis was applied to select the most relevant predictors. We combined Glasgow coma scale (GCS), EEG, and absolute amplitude of MMN at Fz to develop a predictive model using binary logistic regression and then presented by a nomogram. The predictive efficiency of the model was evaluated with AUC and verified by calibration curve. The decision curve analysis (DCA) was used to evaluate the clinical utility of the prediction model.

Results

A total of 116 patients were enrolled for analysis, of which 60 had favorable prognosis (GOS ≥ 3). Five predictors, including GCS (OR = 13.400, P < 0.001), absolute amplitude of MMN at Fz site (FzMMNA, OR = 1.855, P = 0.038), EEG background activity (OR = 4.309, P = 0.023), EEG reactivity (OR = 4.154, P = 0.030), and sleep spindles (OR = 4.316, P = 0.031), were selected in the model by LASSO and binary logistic regression analysis. This model showed favorable predictive power, with an AUC of 0.939 (95% CI: 0.899-0.979), and calibration. The threshold probability of net benefit was between 5% and 92% in the DCA.

Conclusion

This predictive model for consciousness recovery in patients with acute brain injury is based on a nomogram incorporating GCS, EEG background activity, EEG reactivity, sleep spindles, and FzMMNA, which can be conveniently obtained during hospitalization. It provides a basis for care givers to make subsequent medical decisions.

Clinical significance of mismatch negativity in predicting the awakening of comatose patients after severe brain injury

We assessed the clinical significance of mismatch negativity (MMN) in predicting the awakening of comatose patients with severe brain injury. The clinical data of patients with severe brain injury, admitted to the neurosurgical intensive care unit of Xiangya Hospital of Central South University from July 2018 to March 2020, who underwent auditory MMN examinations within 28 days after coma onset, were reviewed. Correlations between clinical factors and prognosis [Glasgow Outcome Scale (GCS) for 3 mo] were analyzed. Fifty-three patients were included; 37 (69.8%) had favorable outcomes. A univariate analysis revealed the Glasgow Coma Scale (GCS) and absolute MMN amplitudes at electrodes Fz and Cz were significantly correlated with prognosis. Only GCS scores and MMN amplitude at Fz were independent predictors in multivariate logistic regression analysis (area under the curve 0.744 vs. 0.753, respectively); both combined, improved accuracy to 84.6%. MMN amplitudes at Fz were dichotomized at a value of 1.08 μV with a sensitivity and specificity of 81.1% and 68.7%, respectively, for predicting comatose patients' awakening. In conclusion, MMN amplitude at Fz is a reliable prognostic indicator for comatose patients with severe brain injury; the prediction value improved when combined with GCS. Thus, an event-related potential component with a clear site and cutoff value may support prognostication in severe brain injury.NEW & NOTEWORTHY Mismatch negativity (MMN) can assess the prognosis of comatose patients after severe brain injury, especially for MMN amplitude. In addition, MMN analysis at electrode Fz best predicts recovery of consciousness in patients with severe brain injury. Importantly, a quantitative approach (cutoff value of 1.08 μV) may improve the use of MMN for prognostication.

Do rat auditory event related potentials exhibit human mismatch negativity attributes related to predictive coding?

Rodent models play a significant role in understanding disease mechanisms and the screening of new treatments. With regard to psychiatric disorders such as schizophrenia, however, it is difficult to replicate the human symptoms in rodents because these symptoms are often either 'uniquely human' or are only conveyed via self-report. There is a growing interest in rodent mismatch responses (MMRs) as a translatable 'biomarker' for disorders such as schizophrenia. In this review, we will summarize the attributes of human MMN, and discuss the scope of exploring the attributes of human MMN in rodents. Here, we examine how reliably MMRs that are measured in rats mimic human attributes, and present original data examining whether manipulations of stimulus conditions known to modulate human MMN, do the same for rat MMRs. Using surgically-implanted epidural electroencephalographic electrodes and wireless telemetry in freely-moving rats, we observed human-like modulations of MMRs, namely that larger MMRs were elicited to unexpected (deviant) stimuli that a) had a larger change in pitch compared to the expected (standard) stimulus, b) were less frequently presented (lower probability), and c) had no jitter (stable stimulus onset asynchrony) compared to high jitter. Overall, these findings contribute to the mounting evidence for rat MMRs as a good analogue of human MMN, bolstering the development of a novel approach in future to validate the preclinical models based on a translatable biomarker, MMN.

Influence of Musical Enculturation on Brain Responses to Metric Deviants

The ability to recognize metric accents is fundamental in both music and language perception. It has been suggested that music listeners prefer rhythms that follow simple binary meters, which are common in Western music. This means that listeners expect odd-numbered beats to be strong and even-numbered beats to be weak. In support of this, studies have shown that listeners exposed to Western music show stronger novelty and incongruity related P3 and irregularity detection related mismatch negativity (MMN) brain responses to attenuated odd- than attenuated even-numbered metric positions. Furthermore, behavioral evidence suggests that music listeners' preferences can be changed by long-term exposure to non-Western rhythms and meters, e.g., by listening to African or Balkan music. In our study, we investigated whether it might be possible to measure effects of music enculturation on neural responses to attenuated tones on specific metric positions. We compared the magnetic mismatch negativity (MMNm) to attenuated beats in a “Western group” of listeners (n = 12) mainly exposed to Western music and a “Bicultural group” of listeners (n = 13) exposed for at least 1 year to both Sub-Saharan African music in addition to Western music. We found that in the “Western group” the MMNm was higher in amplitude to deviant tones on odd compared to even metric positions, but not in the “Bicultural group.” In support of this finding, there was also a trend of the “Western group” to rate omitted beats as more surprising on odd than even metric positions, whereas the “Bicultural group” seemed to discriminate less between metric positions in terms of surprise ratings. Also, we observed that the overall latency of the MMNm was significantly shorter in the Bicultural group compared to the Western group. These effects were not biased by possible differences in rhythm perception ability or music training, measured with the Musical Ear Test (MET). Furthermore, source localization analyses suggest that auditory, inferior temporal, sensory-motor, superior frontal, and parahippocampal regions might be involved in eliciting the MMNm to the metric deviants. These findings suggest that effects of music enculturation can be measured on MMNm responses to attenuated tones on specific metric positions.

How does the extraction of local and global auditory regularities vary with context?

How does the human brain extract regularities from its environment? There is evidence that short range or ‘local’ regularities (within seconds) are automatically detected by the brain while long range or ‘global’ regularities (over tens of seconds or more) require conscious awareness. In the present experiment, we asked whether participants' attention was needed to acquire such auditory regularities, to detect their violation or both. We designed a paradigm in which participants listened to predictable sounds. Subjects could be distracted by a visual task at two moments: when they were first exposed to a regularity or when they detected violations of this regularity. MEG recordings revealed that early brain responses (100–130 ms) to violations of short range regularities were unaffected by visual distraction and driven essentially by local transitional probabilities. Based on global workspace theory and prior results, we expected that visual distraction would eliminate the long range global effect, but unexpectedly, we found the contrary, i.e. late brain responses (300–600 ms) to violations of long range regularities on audio-visual trials but not on auditory only trials. Further analyses showed that, in fact, visual distraction was incomplete and that auditory and visual stimuli interfered in both directions. Our results show that conscious, attentive subjects can learn the long range dependencies present in auditory stimuli even while performing a visual task on synchronous visual stimuli. Furthermore, they acquire a complex regularity and end up making different predictions for the very same stimulus depending on the context (i.e. absence or presence of visual stimuli). These results suggest that while short-range regularity detection is driven by local transitional probabilities between stimuli, the human brain detects and stores long-range regularities in a highly flexible, context dependent manner.

"Change deafness" arising from inter-feature masking within a single auditory object

Our ability to detect prominent changes in complex acoustic scenes depends not only on the ear's sensitivity but also on the capacity of the brain to process competing incoming information. Here, employing a combination of psychophysics and magnetoencephalography (MEG), we investigate listeners' sensitivity in situations when two features belonging to the same auditory object change in close succession. The auditory object under investigation is a sequence of tone pips characterized by a regularly repeating frequency pattern. Signals consisted of an initial, regularly alternating sequence of three short (60 msec) pure tone pips (in the form ABCABC…) followed by a long pure tone with a frequency that is either expected based on the on-going regular pattern ("LONG expected"-i.e., "LONG-expected") or constitutes a pattern violation ("LONG-unexpected"). The change in LONG-expected is manifest as a change in duration (when the long pure tone exceeds the established duration of a tone pip), whereas the change in LONG-unexpected is manifest as a change in both the frequency pattern and a change in the duration. Our results reveal a form of "change deafness," in that although changes in both the frequency pattern and the expected duration appear to be processed effectively by the auditory system-cortical signatures of both changes are evident in the MEG data-listeners often fail to detect changes in the frequency pattern when that change is closely followed by a change in duration. By systematically manipulating the properties of the changing features and measuring behavioral and MEG responses, we demonstrate that feature changes within the same auditory object, which occur close together in time, appear to compete for perceptual resources.

Timing is everything: neural response dynamics during syllable processing and its relation to higher-order cognition in schizophrenia and healthy comparison subjects

Successful linguistic processing requires efficient encoding of successively-occurring auditory input in a time-constrained manner, especially under noisy conditions. In this study we examined the early neural response dynamics to rapidly-presented successive syllables in schizophrenia participants and healthy comparison subjects, and investigated the effects of noise on these responses. We used magnetoencephalography (MEG) to reveal the time-course of stimulus-locked activity over bilateral auditory cortices during discrimination of syllable pairs that differed either in voice onset time (VOT) or place of articulation (POA), in the presence or absence of noise. We also examined the association of these early neural response patterns to higher-order cognitive functions. The M100 response, arising from auditory cortex and its immediate environs, showed less attenuation to the second syllable in patients with schizophrenia than healthy comparison subjects during VOT-based discrimination in noise. M100 response amplitudes were similar between groups for the first syllable during all three discrimination conditions, and for the second syllable during VOT-based discrimination in quiet and POA-based discrimination in noise. Across subjects, the lack of M100 attenuation to the second syllable during VOT-based discrimination in noise was associated with poorer task accuracy, lower education and IQ, and lower scores on measures of Verbal Learning and Memory and Global Cognition. Because the neural response to the first syllable was not significantly different between groups, nor was a schizophrenia-related difference obtained in all discrimination tasks, early linguistic processing dysfunction in schizophrenia does not appear to be due to general sensory input problems. Rather, data suggest that faulty temporal integration occurs during successive syllable processing when the signal-to-noise ratio is low. Further, the neural mechanism by which the second syllable is suppressed during noise-challenged VOT discrimination appears to be important for higher-order cognition and provides a promising target for neuroscience-guided cognitive training approaches to schizophrenia.

Auditory temporal edge detection in human auditory cortex

Auditory objects are detected if they differ acoustically from the ongoing background. In simple cases, the appearance or disappearance of an object involves a transition in power, or frequency content, of the ongoing sound. However, it is more realistic that the background and object possess substantial non-stationary statistics, and the task is then to detect a transition in the pattern of ongoing statistics. How does the system detect and process such transitions? We use magnetoencephalography (MEG) to measure early auditory cortical responses to transitions between constant tones, regularly alternating, and randomly alternating tone-pip sequences. Such transitions embody key characteristics of natural auditory temporal edges. Our data demonstrate that the temporal dynamics and response polarity of the neural temporal-edge-detection processes depend in specific ways on the generalized nature of the edge (the context preceding and following the transition) and suggest that distinct neural substrates in core and non-core auditory cortex are recruited depending on the kind of computation (discovery of a violation of regularity, vs. the detection of a new regularity) required to extract the edge from the ongoing fluctuating input entering a listener's ears.

Stimulus Context Affects Auditory Cortical Responses to Changes in Interaural Correlation

We use magnetoencephalography to study human auditory cortical processing of changes in interaural correlation (IAC). We studied transitions from correlated (identical signals at the 2 ears) to uncorrelated (different signals at the 2 ears) or vice versa for two types of wide-band noise stimuli: CHANGE signals contained a single IAC change (or none) and ALT signals alternated between correlated and uncorrelated at a constant rate. The relevant transitions, from correlated to uncorrelated or vice versa, are physically identical in both stimulus conditions, but auditory cortical response patterns differed substantially. CHANGE stimuli exhibited a response asymmetry in their temporal dynamics and magnetic field morphology according to the direction of change. Distinct field patterns indicate the involvement of separate neural substrates for processing, and distinct latencies are suggestive of different temporal integration windows. In contrast, the temporal dynamics of responses to change in the ALT stimuli did not differ substantially according to the direction of change. Notably, the uncorrelated-to-correlated transition in the ALT stimuli showed a first deflection ∼90 ms earlier than for the same transition in the CHANGE stimuli and with an opposite magnetic field distribution. This finding suggests that as early as 50 ms after the onset of an IAC transition, a given physical change is processed differentially depending on stimulus context. Consequently, even early cortical activation cannot be interpreted independently of the specific long-term stimulus context used in the experiment.

Processing asymmetry of transitions between order and disorder in human auditory cortex

Auditory environments vary as a result of the appearance and disappearance of acoustic sources, as well as fluctuations characteristic of the sources themselves. The appearance of an object is often manifest as a transition in the pattern of ongoing fluctuation, rather than an onset or offset of acoustic power. How does the system detect and process such transitions? Based on magnetoencephalography data, we show that the temporal dynamics and response morphology of the neural temporal-edge detection processes depend in precise ways on the nature of the change. We measure auditory cortical responses to transitions between "disorder," modeled as a sequence of random frequency tone pips, and "order," modeled as a constant tone. Such transitions embody key characteristics of natural auditory edges. Early cortical responses (from approximately 50 ms post-transition) reveal that order-disorder transitions, and vice versa, are processed by different neural mechanisms. Their dynamics suggest that the auditory cortex optimally adjusts to stimulus statistics, even when this is not required for overt behavior. Furthermore, this response profile bears a striking similarity to that measured from another order-disorder transition, between interaurally correlated and uncorrelated noise, a radically different stimulus. This parallelism suggests the existence of a general mechanism that operates early in the processing stream on the abstract statistics of the auditory input, and is putatively related to the processes of constructing a new representation or detecting a deviation from a previously acquired model of the auditory scene. Together, the data reveal information about the mechanisms with which the brain samples, represents, and detects changes in the environment.

The ‘F-complex’ and MMN tap different aspects of deviance

OBJECTIVE

To compare the 'F(fusion)-complex' with the Mismatch negativity (MMN), both components associated with automatic detection of changes in the acoustic stimulus flow.

METHODS

Ten right-handed adult native Hebrew speakers discriminated vowel-consonant-vowel (V-C-V) sequences /ada/ (deviant) and /aga/ (standard) in an active auditory 'Oddball' task, and the brain potentials associated with performance of the task were recorded from 21 electrodes. Stimuli were generated by fusing the acoustic elements of the V-C-V sequences as follows: base was always presented in front of the subject, and formant transitions were presented to the front, left or right in a virtual reality room. An illusion of a lateralized echo (duplex sensation) accompanied base fusion with the lateralized formant locations. Source current density estimates were derived for the net response to the fusion of the speech elements (F-complex) and for the MMN, using low-resolution electromagnetic tomography (LORETA). Statistical non-parametric mapping was used to estimate the current density differences between the brain sources of the F-complex and the MMN.

RESULTS

Occipito-parietal regions and prefrontal regions were associated with the F-complex in all formant locations, whereas the vicinity of the supratemporal plane was bilaterally associated with the MMN, but only in case of front-fusion (no duplex effect).

CONCLUSIONS

MMN is sensitive to the novelty of the auditory object in relation to other stimuli in a sequence, whereas the F-complex is sensitive to the acoustic features of the auditory object and reflects a process of matching them with target categories.

SIGNIFICANCE

The F-complex and MMN reflect different aspects of auditory processing in a stimulus-rich and changing environment: content analysis of the stimulus and novelty detection, respectively.

Interaction between the neuromagnetic responses to sound energy onset and pitch onset suggests common generators

The pitch-onset response (POR) is a negative component of the auditory evoked field which is elicited when the temporal fine structure of a continuous noise is regularized to produce a pitch perception without altering the gross spectral characteristics of the sound. Previously, we showed that the latency of the POR is inversely related to the pitch value and its amplitude is correlated with the salience of the pitch, suggesting that the underlying generators are part of a pitch-processing network [Krumbholz, K., Patterson, R.D., Seither-Preisler, A., Lammertmann, C. & Lütkenhöner, B. (2003) Cereb. Cortex,13, 765-772]. The source of the POR was located near the medial part of Heschl's gyrus. The present study was designed to determine whether the POR originates from the same generators as the energy-onset response (EOR) represented by the N100m/P200m complex. The EOR to the onset of a noise, and the POR to a subsequent transition from noise to pitch, were recorded as the time interval between the noise onset and the transition varied from 500 to 4000 ms. The mean amplitude of the POR increased by approximately 5.9 nA.m with each doubling of the time between noise onset and transition. This suggests an interaction between the POR and the EOR, which may be based on common neural generators.