Time varying dynamics of hallucinations in clinical and non-clinical voice-hearers

Marschall, Theresa M; Koops, Sanne; Brederoo, Sanne; Cabral, Joana; Ćurčić‐Blake, Branislava; Sommer, Iris E.

doi:10.1016/j.nicl.2023.103351

Cited by 3 publications

(2 citation statements)

References 136 publications

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“…Correspondingly, individuals on the upper end of the non-clinical HP continuum might display a heightened vulnerability to transition to clinical AVH. This continuum perspective is empirically supported by various behavioral, electrophysiological, structural, and functional neuroimaging studies (Allen et al, 2005;Badcock & Hugdahl, 2012;Diederen et al, 2012;Marschall et al, 2023;Paulik, Badcock, & Maybery, 2008;Pinheiro, Farinha-Fernandes, Roberto, & Kotz, 2019).…”

Section: Auditory Verbal Hallucinations and Hallucination Pronenessmentioning

confidence: 90%

“…Together, these findings yield important evidence for altered RSN interactions associated with a predisposition to AVH. Another recently proposed method to investigate time varying AVH dynamics, called the leading eigenvector dynamics analysis (LEiDA), was applied to fMRI time series of clinical and non-clinical voice hearers (Marschall et al, 2023). The results showed that network dynamics differed substantially between pure rest and periods during which participants hallucinated but were similar in clinical and nonclinical AVH.…”

Section: Resting State Dynamicsmentioning

confidence: 99%

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EEG resting state alpha dynamics predict individual proneness to auditory hallucinations

Honcamp,

Duggirala,

Rodino Climent

et al. 2023

Preprint

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Introduction: Auditory verbal hallucinations (AVH) are a transdiagnostic phenomenon but also occur in the general population. The disposition to experience AVH is considered a continuous expression from non-clinical to clinical hallucination proneness (HP). Currently, little is known about the neurophysiology of the non-clinical HP part of the continuum. AVH might result from a heightened sensitivity to sensory inputs and a decreased ability to differentiate between externally and internally generated input. Resting state (RS) alpha band activity is associated with perceptual sensitivity, attentional shifts, and cognitive control. Accordingly, spontaneous alpha fluctuations might present as a HP correlate. To investigate the time-varying dynamics of alpha band activity, we deployed a novel method for brain state allocation. Methods: We recorded RS electroencephalography (EEG) data from 33 individuals with varying levels of HP but without clinically relevant hallucinations and used a Hidden Semi-Markov Model (HsMM) to identify five recurrent alpha states with unique temporal dynamics and topographies. The states mean duration and occupancy were analyzed as a function of HP. The sources of each state were reconstructed to identify the most active brain areas and their correspondence with known resting state networks. Results: Occupancy and mean duration of a state corresponding to sensorimotor, auditory, and default-mode network (DMN) areas significantly predicted auditory and auditory-verbal HP, but not general HP. The temporal dynamics of all other states did not relate to HP. Conclusion: Alpha brain state sources align with prior results on the role of the alpha in the DMN. The temporal dynamics of alpha might reflect individual differences for attentional biases to internally generated sensory events and altered auditory perceptual sensitivity. Thus, changes in the temporal brain state dynamics of RS alpha oscillations could present as a neural marker of increased vulnerability to auditory hallucinatory experiences.

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Section: Auditory Verbal Hallucinations and Hallucination Pronenessmentioning

confidence: 90%

Section: Resting State Dynamicsmentioning

confidence: 99%

EEG resting state alpha dynamics predict individual proneness to auditory hallucinations

Honcamp,

Duggirala,

Rodino Climent

et al. 2023

Preprint

View full text Add to dashboard Cite

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EEG resting state alpha dynamics predict an individual’s vulnerability to auditory hallucinations

Honcamp,

Duggirala,

Rodiño Climent

et al. 2024

Cogn Neurodyn

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Task-free brain activity exhibits spontaneous fluctuations between functional states, characterized by synchronized activation patterns in distributed resting-state (RS) brain networks. The temporal dynamics of the networks’ electrophysiological signatures reflect individual variations in brain activity and connectivity linked to mental states and cognitive functions and can predict or monitor vulnerability to develop psychiatric or neurological disorders. In particular, RS alpha fluctuations modulate perceptual sensitivity, attentional shifts, and cognitive control, and could therefore reflect a neural correlate of increased vulnerability to sensory distortions, including the proneness to hallucinatory experiences. We recorded 5 min of RS EEG from 33 non-clinical individuals varying in hallucination proneness (HP) to investigate links between task-free alpha dynamics and vulnerability to hallucinations. To this end, we used a dynamic brain state allocation method to identify five recurrent alpha states together with their spatiotemporal dynamics and most active brain areas through source reconstruction. The dynamical features of a state marked by activation in somatosensory, auditory, and posterior default-mode network areas predicted auditory and auditory-verbal HP, but not general HP, such that individuals with higher vulnerability to auditory hallucinations spent more time in this state. The temporal dynamics of spontaneous alpha activity might reflect individual differences in attention to internally generated sensory events and altered auditory perceptual sensitivity. Altered RS alpha dynamics could therefore instantiate a neural marker of increased vulnerability to auditory hallucinations.

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Low-frequency repetitive transcranial magnetic stimulation alters the individual functional dynamical landscape

Huang

Zhang

et al. 2023

Cerebral Cortex

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Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive approach to modulate brain activity and behavior in humans. Still, how individual resting-state brain dynamics after rTMS evolves across different functional configurations is rarely studied. Here, using resting state fMRI data from healthy subjects, we aimed to examine the effects of rTMS to individual large-scale brain dynamics. Using Topological Data Analysis based Mapper approach, we construct the precise dynamic mapping (PDM) for each participant. To reveal the relationship between PDM and canonical functional representation of the resting brain, we annotated the graph using relative activation proportion of a set of large-scale resting-state networks (RSNs) and assigned the single brain volume to corresponding RSN-dominant or a hub state (not any RSN was dominant). Our results show that (i) low-frequency rTMS could induce changed temporal evolution of brain states; (ii) rTMS didn’t alter the hub-periphery configurations underlined resting-state brain dynamics; and (iii) the rTMS effects on brain dynamics differ across the left frontal and occipital lobe. In conclusion, low-frequency rTMS significantly alters the individual temporo-spatial dynamics, and our finding further suggested a potential target-dependent alteration of brain dynamics. This work provides a new perspective to comprehend the heterogeneous effect of rTMS.

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Time varying dynamics of hallucinations in clinical and non-clinical voice-hearers

Cited by 3 publications

References 136 publications

EEG resting state alpha dynamics predict individual proneness to auditory hallucinations

EEG resting state alpha dynamics predict individual proneness to auditory hallucinations

EEG resting state alpha dynamics predict an individual’s vulnerability to auditory hallucinations

Low-frequency repetitive transcranial magnetic stimulation alters the individual functional dynamical landscape

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