Regional Brain Correlates of Beta Bursts in Health and Psychosis: A Concurrent Electroencephalography and Functional Magnetic Resonance Imaging Study.

BACKGROUND: There is emerging evidence for abnormal beta oscillations in psychosis. Beta oscillations are likely to play a key role in the coordination of sensorimotor information that is crucial to healthy mental function. Growing evidence suggests that beta oscillations typically manifest as transient beta bursts that increase in probability following a motor response, observable as post-movement beta rebound. Evidence indicates that post-movement beta rebound is attenuated in psychosis, with greater attenuation associated with greater symptom severity and impairment. Delineating the functional role of beta bursts therefore may be key to understanding the mechanisms underlying persistent psychotic illness. METHODS: We used concurrent electroencephalography and functional magnetic resonance imaging to identify blood oxygen level-dependent correlates of beta bursts during the n-back working memory task and intervening rest periods in healthy control participants (n = 30) and patients with psychosis (n = 48). RESULTS: During both task blocks and intervening rest periods, beta bursts phasically activated regions implicated in task-relevant content while suppressing currently tonically active regions. Patients showed attenuated post-movement beta rebound that was associated with persisting disorganization symptoms as well as impairments in cognition and role function. Patients also showed greater task-related reductions in overall beta burst rate and showed greater, more extensive, beta burst-related blood oxygen level-dependent activation. CONCLUSIONS: Our evidence supports a model in which beta bursts reactivate latently maintained sensorimotor information and are dysregulated and inefficient in psychosis. We propose that abnormalities in the mechanisms by which beta bursts coordinate reactivation of contextually appropriate content can manifest as disorganization, working memory deficits, and inaccurate forward models and may underlie a core deficit associated with persisting symptoms and impairment.

Automated screening for high-frequency hearing loss.

OBJECTIVE: Hearing loss at high frequencies produces perceptual difficulties and is often an early sign of a more general hearing loss. This study reports the development and validation of two new speech-based hearing screening tests in English that focus on detecting hearing loss at frequencies above 2000 Hz. DESIGN: The Internet-delivered, speech-in noise tests used closed target-word sets of digit triplets or consonant-vowel-consonant (CVC) words presented against a speech-shaped noise masker. The digit triplet test uses the digits 0 to 9 (excluding the disyllabic 7), grouped in quasi-random triplets. The CVC test uses simple words (e.g., "cat") selected for the high-frequency spectral content of the consonants. During testing, triplets or CVC words were identified in an adaptive procedure to obtain the speech reception threshold (SRT) in noise. For these new, high-frequency (HF) tests, the noise was low-pass filtered to produce greater masking of the low-frequency speech components, increasing the sensitivity of the test for HF hearing loss. Individual test tokens (digits, CVCs) were first homogenized using a group of 10 normal-hearing (NH) listeners by equalizing intelligibility across tokens at several speech-in-noise levels. Both tests were then validated and standardized using groups of 24 NH listeners and 50 listeners with hearing impairment. Performance on the new high frequency digit triplet (HF-triplet) and CVC (HF-CVC) tests was compared with audiometric hearing loss, and with that on the unfiltered, broadband digit triplet test (BB-triplet) test, and the ASL (Adaptive Sentence Lists) speech-in-noise test. RESULTS: The HF-triplet and HF-CVC test results (SRT) both correlated positively and highly with high-frequency audiometric hearing loss and with the ASL test. SRT for both tests as a function of high-frequency hearing loss increased at nearly three times the rate as that of the BB-triplet test. The intraindividual variability (SD) on the tests was about 2.1 (HF-triplet) and 1.7 (HF-CVC) times less than that for the BB-triplet test. The effect on the HF-triplet test of varying presentation method (professional or cheap headphones and loudspeakers) was small for the NH group and somewhat larger, but nonsignificant for the hearing-impaired group. Test repetition produced a moderate, significant learning effect for the first and second retests, but was small and nonsignificant for further retesting. The learning effect was about two times larger for the HF-CVC test than for the HF-triplet test. The sensitivity of both new tests for high-frequency hearing loss was similar, with an 87% true-positive and 7% false-positive ratio for detecting an average high-frequency hearing loss of 20 dB or more. CONCLUSIONS: The new HF-triplet and HF-CVC tests provide a sensitive and accurate method for detecting high-frequency hearing loss. The tests may signal developing hearing impairment at an early stage. The HF-triplet is preferred over the HF-CVC test because of its smaller learning effect, smaller error rate, greater simplicity, and lower cultural dependency.

Theta power during encoding predicts subsequent-memory performance and default mode network deactivation.

The subsequent memory paradigm, according to which cerebral activity for later remembered (LR) and later forgotten (LF) items is contrasted, can be used to characterize the processes necessary for successful memory encoding. Previous simultaneous electroencephalography/functional magnetic resonance imaging (EEG/fMRI) memory studies suggest an inverse relationship between frontal theta band power and the blood oxygenation level dependent (BOLD) signal in the default mode network (DMN). The principal aim of this EEG/fMRI study was to test the hypothesis that this putative theta-DMN relationship is less evident in LF compared with LR trials. Fourteen healthy participants performed an episodic memory task in which pictorial stimuli were presented during encoding, and categorized (as LR or LF) by subsequent memory performance. For each encoding trial, the mean of the Hilbert envelope of the theta signal from 400 to 800 ms after stimulus presentation was calculated. To integrate the EEG and fMRI data, general linear models (GLMs) were used to assess the extent to which these single-trial theta values (as modulators of the main effect of stimulus) predicted DMN BOLD signal change, using: (i) whole-head univariate GLMs and (ii) GLMs in which the outcome variable was the time-course of a DMN component derived from spatial independent component analysis of the fMRI data. Theta was significantly greater for LR than LF stimuli. Furthermore, the inverse relationship between theta and BOLD in the DMN was consistently stronger for LR than LF pictures. These findings imply that theta oscillations are key to attenuating processes which may otherwise impair memory encoding.

Motion-related artefacts in EEG predict neuronally plausible patterns of activation in fMRI data.

The simultaneous acquisition and subsequent analysis of EEG and fMRI data is challenging owing to increased noise levels in the EEG data. A common method to integrate data from these two modalities is to use aspects of the EEG data, such as the amplitudes of event-related potentials (ERP) or oscillatory EEG activity, to predict fluctuations in the fMRI data. However, this relies on the acquisition of high quality datasets to ensure that only the correlates of neuronal activity are being studied. In this study, we investigate the effects of head-motion-related artefacts in the EEG signal on the predicted T2*-weighted signal variation. We apply our analyses to two independent datasets: 1) four participants were asked to move their feet in the scanner to generate small head movements, and 2) four participants performed an episodic memory task. We created T2*-weighted signal predictors from indicators of abrupt head motion using derivatives of the realignment parameters, from visually detected artefacts in the EEG as well as from three EEG frequency bands (theta, alpha and beta). In both datasets, we found little correlation between the T2*-weighted signal and EEG predictors that were not convolved with the canonical haemodynamic response function (cHRF). However, all convolved EEG predictors strongly correlated with the T2*-weighted signal variation in various regions including the bilateral superior temporal cortex, supplementary motor area, medial parietal cortex and cerebellum. The finding that movement onset spikes in the EEG predict T2*-weighted signal intensity only when the time course of movements is convolved with the cHRF, suggests that the correlated signal might reflect a BOLD response to neural activity associated with head movement. Furthermore, the observation that broad-spectral EEG spikes tend to occur at the same time as abrupt head movements, together with the finding that abrupt movements and EEG spikes show similar correlations with the T2*-weighted signal, indicates that the EEG spikes are produced by abrupt movement and that continuous regressors of EEG oscillations contain motion-related noise even after stringent correction of the EEG data. If not properly removed, these artefacts complicate the use of EEG data as a predictor of T2*-weighted signal variation.

How much does phase resetting contribute to event-related EEG abnormalities in schizophrenia?

OBJECTIVE: Patients suffering from schizophrenia demonstrate impaired low frequency electrophysiological responses to stimuli, but it remains unclear whether these abnormalities arise from phase resetting of ongoing oscillations, new phase-locked (evoked) activity or non-phase-locked (induced) activity. Our goal is to clarify the contribution of each of these three processes to the impairment of neural activity during information processing in schizophrenia, by using statistics that do not confound increases in the mean post-stimulus signal with phase resetting. METHODS: Thirty-four male schizophrenia patients and 34 healthy matched controls performed an auditory oddball task. We applied the analysis procedure developed by Martinez-Montes et al. based on complex-valued wavelet transform to event-related signal elicited by target stimuli. RESULTS: The largest abnormalities were found for phase-locked delta (1-4 Hz) and non-phase-locked theta (4-8 Hz). Delta phase resetting was moderately impaired and related to symptoms of disorganization. It also predicted evoked theta signal. CONCLUSION: The substantial reduction of both evoked and induced oscillatory activity in schizophrenia indicates diminished recruitment of brain circuits engaged not only in stimulus-locked perceptual processing but also in more extensive processing less tightly time locked to the stimulus. Although reduced phase resetting makes a lesser contribution, it indicates a deficit in the ability to harness ongoing electrical activity.

Disturbances of self-other distinction after stimulation of the extrastriate body area in the human brain.

In a recent experiment with functional magnetic-resonance imaging, we found that brain activity in the extrastriate body area (EBA) distinguished between observed self- and other-generated movements, being significantly higher during observation of someone else's movement. Here, we investigated further the role of EBA in self-other distinctions using low-frequency repetitive transcranial magnetic stimulation (rTMS). As compared with rTMS applied over a control site, rTMS applied over the EBA increased reaction times, without affecting accuracy, for the detection of other-generated movements. Performance on a control motion-direction detection task was unaffected. These findings provide additional evidence for the role of the EBA in processing information necessary for identifying ourselves as agents of self-generated movements.

Neural mechanisms of resistance to peer influence in early adolescence.

During the shift from a parent-dependent child to a fully autonomous adult, peers take on a significant role in shaping the adolescent's behavior. Peer-derived influences are not always positive, however. Here, we explore neural correlates of interindividual differences in the probability of resisting peer influence in early adolescence. Using functional magnetic resonance imaging, we found striking differences between 10-year-old children with high and low resistance to peer influence in their brain activity during observation of angry hand movements and angry facial expressions: compared with subjects with low resistance to peer influence, individuals with high resistance showed a highly coordinated brain activity in neural systems underlying perception of action and decision making. These findings suggest that the probability of resisting peer influence depends on neural interactions during observation of emotion-laden actions.