scholarly journals Beta-frequency electrophysiological bursts: BOLD correlates and relationships with psychotic illness

BJPsych Open ◽  
2021 ◽  
Vol 7 (S1) ◽  
pp. S37-S38
Author(s):  
Paul M Briley ◽  
Elizabeth B Liddle ◽  
Karen J Mullinger ◽  
Molly Simmonite ◽  
Lena Palaniyappan ◽  
...  

AimsTo identify the BOLD (blood oxygenation level dependent) correlates of bursts of beta frequency band electrophysiological activity, and to compare BOLD responses between healthy controls and patients with psychotic illness.The post movement beta rebound (PMBR) is a transient increase in power in the beta frequency band (13-30 Hz), recorded with methods such as electroencephalography (EEG), following the completion of a movement. PMBR size is reduced in patients with schizophrenia and inversely correlated with severity of illness. PMBR size is inversely correlated with measures of schizotypy in non-clinical groups. Therefore, beta-band activity may reflect a fundamental neural process whose disruption plays an important role in the pathophysiology of schizophrenia. Recent work has found that changes in beta power reflect changes in the probability-of-occurrence of transient bursts of beta-frequency activity. Understanding the generators of beta bursts could help unravel the pathophysiology of psychotic illness and thus identify novel treatment targets.MethodEEG data were recorded simultaneously with BOLD data measured with 3T functional magnetic resonance imaging (fMRI), whilst participants performed an n-back working memory task. We included seventy-eight participants – 32 patients with schizophrenia, 16 with bipolar disorder and 30 healthy controls. Beta bursts were identified in the EEG data using a thresholding method and burst timings were used as markers in an event-related fMRI design convolved with a conventional haemodynamic response function. A region of interest analysis compared beta-event-related BOLD activity between patients and controls.ResultBeta bursts phasically activated brain regions implicated in coding task-relevant content (specifically, regions involved in the phonological representation of letter stimuli, as well as areas representing motor responses). Further, bursts were associated with suppression of tonically-active regions. In the EEG, PMBR was greater in controls than patients, and, in patients, PMBR size was positively correlated with Global Assessment of Functioning scores, and negatively correlated with persisting symptoms of disorganisation and performance on a digit symbol substition test. Despite this, patients showed greater, more extensive, burst-related BOLD activation than controls.ConclusionOur findings are consistent with a recent model in which beta bursts serve to reactivate latently-maintained, task-relevant, sensorimotor information. The increased BOLD response associated with bursts in patients, despite reduced PMBR, could reflect inefficiency of burst-mediated cortical synchrony, or it may suggest that the sensorimotor information reactivated by beta bursts is less precisely specified in psychosis. We propose that dysfunction of the mechanisms by which beta bursts reactivate task-relevant content can manifest as disorganisation and working memory deficits, and may contribute to persisting symptoms and impairment in psychosis.

2010 ◽  
Vol 104 (2) ◽  
pp. 829-839 ◽  
Author(s):  
Leslie M. Kay ◽  
Jennifer Beshel

We previously showed that in a two-alternative choice (2AC) task, olfactory bulb (OB) gamma oscillations (∼70 Hz in rats) were enhanced during discrimination of structurally similar odorants (fine discrimination) versus discrimination of dissimilar odorants (coarse discrimination). In other studies (mostly employing go/no-go tasks) in multiple labs, beta oscillations (15–35 Hz) dominate the local field potential (LFP) signal in olfactory areas during odor sampling. Here we analyzed the beta frequency band power and pairwise coherence in the 2AC task. We show that in a task dominated by gamma in the OB, beta oscillations are also present in three interconnected olfactory areas (OB and anterior and posterior pyriform cortex). Only the beta band showed consistently elevated coherence during odor sniffing across all odor pairs, classes (alcohols and ketones), and discrimination types (fine and coarse), with stronger effects in first than in final criterion sessions (>70% correct). In the first sessions for fine discrimination odor pairs, beta power for incorrect trials was the same as that for correct trials for the other odor in the pair. This pattern was not repeated in coarse discrimination, in which beta power was elevated for correct relative to incorrect trials. This difference between fine and coarse odor discriminations may relate to different behavioral strategies for learning to differentiate similar versus dissimilar odors. Phase analysis showed that the OB led both pyriform areas in the beta frequency band during odor sniffing. We conclude that the beta band may be the means by which information is transmitted from the OB to higher order areas, even though task specifics modify dominance of one frequency band over another within the OB.


Author(s):  
Ros Shilawani S. Abdul Kadir ◽  
Azlan Hakimi Yahaya Rashid ◽  
Husna Abdul Rahman ◽  
Mohd Nasir Taib ◽  
Zunairah Hj. Murat ◽  
...  

2018 ◽  
Author(s):  
T. Meindertsma ◽  
N.A. Kloosterman ◽  
A.K. Engel ◽  
E.J. Wagenmakers ◽  
T.H. Donner

AbstractLearning the statistical structure of the environment is crucial for adaptive behavior. Humans and non-human decision-makers seem to track such structure through a process of probabilistic inference, which enables predictions about behaviorally relevant events. Deviations from such predictions cause surprise, which in turn helps improve inference. Surprise about the timing of behaviorally relevant sensory events drives phasic responses of neuromodulatory brainstem systems, which project to the cerebral cortex. Here, we developed a computational model-based magnetoencephalography (MEG) approach for mapping the resulting cortical transients across space, time, and frequency, in the human brain (N=28, 17 female). We used a Bayesian ideal observer model to learn the statistics of the timing of changes in a simple visual detection task. This model yielded quantitative trial-by-trial estimates of temporal surprise. The model-based surprise variable predicted trial-by trial variations in reaction time more strongly than the externally observable interval timings alone. Trial-by-trial variations in surprise were negatively correlated with the power of cortical population activity measured with MEG. This surprise-related power suppression occurred transiently around the behavioral response, specifically in the beta frequency band. It peaked in parietal and prefrontal cortices, remote from the motor cortical suppression of beta power related to overt report (button press) of change detection. Our results indicate that surprise about sensory event timing transiently suppresses ongoing beta-band oscillations in association cortex. This transient suppression of frontal beta-band oscillations might reflect an active reset triggered by surprise, and is in line with the idea that beta-oscillations help maintain cognitive sets.Significance statementThe brain continuously tracks the statistical structure of the environment to anticipate behaviorally relevant events. Deviations from such predictions cause surprise, which in turn drives neural activity in subcortical brain regions that project to the cerebral cortex. We used magnetoencephalography in humans to map out surprise-related modulations of cortical population activity across space, time, and frequency. Surprise was elicited by variable timing of visual stimulus changes requiring a behavioral response. Surprise was quantified by means of an ideal observer model. Surprise predicted behavior as well as a transient suppression of beta frequency band oscillations in frontal cortical regions. Our results are in line with conceptual accounts that have linked neural oscillations in the beta-band to the maintenance of cognitive sets.


2020 ◽  
Vol 204 ◽  
pp. 104758 ◽  
Author(s):  
Michele Scaltritti ◽  
Caterina Suitner ◽  
Francesca Peressotti

2018 ◽  
Vol 38 (35) ◽  
pp. 7600-7610 ◽  
Author(s):  
Thomas Meindertsma ◽  
Niels A. Kloosterman ◽  
Andreas K. Engel ◽  
Eric-Jan Wagenmakers ◽  
Tobias H. Donner

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