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

Abstract

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.

Keywords: Concurrent EEG/fMRI; Persisting psychotic illness; Post-movement beta rebound; Psychosis; Transient beta oscillations; Working memory.

Figure 1

Group independent component analysis (ICA) component selected for identifying beta bursts, example of a beta burst, and average time–frequency spectrograms showing mean movement-related beta modulation. (A) Topography of the group ICA component chosen to derive neural activity time courses for identifying beta bursts in the continuous electroencephalography data of individual participants. (B) Standardized low-resolution brain electromagnetic tomography source analysis (57) of the chosen group ICA component, plotted on the Montreal Neurological Institute 152 brain (58) using LORETA-Key software (http://www.uzh.ch/keyinst/loreta.htm). (C) Time–frequency spectrogram showing a beta event that exceeded the selection threshold (black plus sign). Yellow and blue represent areas of high and low spectral power, respectively. The inset image shows the corresponding component time course, with the plus location marked by a vertical red line. The abscissa is arbitrarily set to start at zero for this image. The spectrogram was constructed using 0.1-Hz bins, while the analysis was conducted using 1-Hz bins. (D, E) Time–frequency spectrograms showing the traditionally measured post-movement beta rebound for control participants (D) and patients (E), computed by averaging time–frequency spectrograms across epochs, relative to the time of a motor response. Colors represent power in decibels relative to power in the −3- to −1.5-second baseline window used to calculate post-movement beta rebound in this article. The black rectangle encases the post-movement beta rebound window used in this study. a, anterior; l, left; p, posterior; r, right.

Figure 2

Performance by each group on the n-back task. No participant made any errors of commission, and the target detection rate was significantly above chance (p < .001) for all participants. Nonetheless, all groups missed more targets at higher loads than at lower loads (A), and patients were overall significantly less accurate than healthy control participants. Reaction times (RTs) (B) were also longer at higher loads, and patients were significantly slower overall than healthy control participants. Upper and lower bounds of each box denote interquartile range, horizontal line denotes median, X denotes mean, whiskers denote range if within 1.5 × interquartile range, and datapoints outside this range are shown as circles. BD, bipolar disorder; C, control; Sz, schizophrenia or schizoaffective disorder.

Figure 3

Relationships between beta burst rate and timings of responses or stimuli as well as relationships with clinical group, Global Assessment of Functioning (GAF), and task difficulty. (A–C) Mean beta bursts per second calculated in 500-ms sliding windows for control participants (solid black lines) and patients (dashed gray lines) time locked to motor responses (A), target stimuli (B), and nontarget stimuli (C). The shaded region in (A) indicates the post-movement beta rebound (PMBR) window. (D) Boxplots showing distributions of PMBR (increase in burst probability following a motor response relative to the baseline window) for control participants (C) vs. patients (P) and for patients with bipolar disorder (BD) vs. patients with schizophrenia or schizoaffective disorder (Sz) (collapsed across task conditions). Upper and lower bounds of each box denote interquartile range, horizontal line denotes median, X denotes mean, whiskers denote range if within 1.5 × interquartile range, and datapoints outside this range are shown as circles. (E) GAF score plotted against PMBR (collapsed across task conditions). Each data point is a single patient. The dashed line indicates the line of best fit. (F) Mean beta burst rate for control participants and patients for rest (R), 0-back, 1-back, and 2-back conditions. Error bars denote ±1 SEM.

Figure 4

Clusters (k ≥ 20) showing significant increases in blood oxygen level–dependent activity associated with beta bursts (cluster threshold p < .05, familywise error corrected; voxel threshold p < .05, false discovery rate corrected). (A) Axial 5-mm slice view overlaid on the SPM single-subject brain. (B) Clusters shown on the SPM glass brain in three orthogonal planes. (C) Orthogonal sections through the global maximum (Montreal Neurological Institute: x = −51, y = −12, z = 27) overlaid on the SPM single-subject brain.

Figure 5

Beta burst effects during task and rest compared with the correlates of task and rest blocks. All clusters shown are of voxels significant at p < .001, uncorrected, in clusters significant at p < .05, familywise error corrected. (A) Positive and negative correlates of beta bursts. Top row: Positive correlates of task beta bursts (Task β+ve) and rest beta bursts (Rest β+ve). Bottom row: Negative correlates of task beta bursts (Task β−ve) and rest beta bursts (Rest β−ve). Beta bursts activated similar regions whether produced during task or rest, but they suppressed different regions. (B) Negative correlates of task beta bursts (top) and rest beta bursts (bottom) overlaid on correlates of task block (Task > Rest and Rest > Task). Beta bursts produced during task suppressed regions otherwise more active during task, while beta bursts produced during rest suppressed regions otherwise more active during rest.

Figure 6

Boxplots showing distribution of blood oxygen level–dependent (BOLD) activation associated with beta bursts within sensorimotor-verbal (SM-verbal), sensorimotor-manual (SM-manual), and left cerebellar (Ce) regions of interest. Upper and lower bounds of each box denote interquartile range, horizontal line denotes median, X denotes mean, whiskers denote range if within 1.5 × interquartile range, and datapoints outside this range are shown as circles. (A) Control participants (C) vs. patients (P). (B) Patients with bipolar disorder (BD) vs. patients with schizophrenia or schizoaffective disorder (Sz). (C) Significant clusters of positive beta burst–related activity (β+ve) in patients (yellow) compared with control participants (red). Areas of overlap are shown in orange. Activation by beta bursts was not only stronger in patients but also more extensive.