A systematic review on resting state functional connectivity in patients with neurodegenerative disease and hallucinations

Spinosa, Vittoria; Brattico, Elvira; Campo, Fulvia; Logroscino, Giancarlo

doi:10.1016/j.nicl.2022.103112

Cited by 11 publications

(10 citation statements)

References 71 publications

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“…Tracking neural activity during hallucinatory episodes is notoriously difficult, but trait-level signatures of the tendency to hallucinate can be explored using structural imaging or resting state fMRI. [10][11][12] These approaches identify patterns of abnormal brain structure, activity or connectivity associated with the hallucinating phenotype, which are presumably implicated in hallucinatory events. For example, the network abnormalities observed during fMRI of hallucination-like events in Parkinson's disease overlaps with trait-level network abnormalities observed in the resting state.…”

Section: Introductionmentioning

confidence: 99%

Abnormal higher-order network interactions in Parkinson’s disease visual hallucinations

Tan

Müller

Orlando

et al. 2023

Preprint

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Visual hallucinations in Parkinson's disease can be viewed from a systems-level perspective, whereby abnormal communication between brain networks responsible for perception predisposes a person to hallucinate. To this end, abnormal functional interactions between higher-order and primary sensory networks have been implicated in the pathophysiology of visual hallucinations in Parkinson's disease, however the precise signatures remain to be determined. Dimensionality reduction techniques offer a novel means for simplifying the interpretation of multidimensional brain imaging data, identifying hierarchical patterns in the data that are driven by both within- and between- functional network changes. Here, we applied two complementary non-linear dimensionality reduction techniques - diffusion-map embedding and t-distributed Stochastic Neighbour Embedding (t-SNE) - to resting state fMRI data, in order to characterise the altered functional hierarchy associated with susceptibility to visual hallucinations. Our study involved 77 people with Parkinson's disease (31 with hallucinations; 46 without hallucinations) and 19 age-matched healthy controls. In patients with visual hallucinations, we found compression of the unimodal-heteromodal gradient consistent with increased functional integration between sensory and higher order networks. This was mirrored in a traditional functional connectivity analysis, which showed increased connectivity between the visual and default-mode networks in the hallucinating group. Together, these results suggest a route by which higher-order regions may have excessive influence over earlier sensory processes, as proposed by theoretical models of hallucinations across disorders. By contrast, the t-SNE analysis identified distinct alterations in prefrontal regions that were not apparent in the functional connectivity analysis, suggesting complex reconfigurations in functional brain network architecture as a function of the disease process. Together, the results confirm abnormal brain organisation associated with the hallucinating phenotype in Parkinson's disease, and highlight the utility of applying convergent dimensionality reduction techniques to investigate complex clinical symptoms. In addition, the patterns we describe in Parkinson's disease converge with those seen in other conditions, suggesting that reduced hierarchical differentiation across sensory-perceptual systems may be a common transdiagnostic vulnerability in neuropsychiatric disorders with perceptual disturbances.

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Section: Introductionmentioning

confidence: 99%

Abnormal higher-order network interactions in Parkinson’s disease visual hallucinations

Tan

Müller

Orlando

et al. 2023

Preprint

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“…anatomically informed by the MRI scans of each subject. We employed the minimum norm estimates method [90], with the constrained dipoles variant, by which the current dipoles are oriented normally to the cortical surface, to model the orientation of the macrocolumns of pyramidal neurons, perpendicular to the cortex [91] Source-space signals were then filtered in the classical frequency bands: delta (2-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), beta (12-30 Hz), and gamma (30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45). For each subject and frequency band, FC was calculated between the source time series using the Phase Locking Value (PLV, [92]), and the resulting matrices were averaged into the March 7, 2023 13/27 AAL2 parcellation scheme [93].…”

Section: Functional Connectivitymentioning

confidence: 99%

“…However, later findings showed that the brain in resting-state has a rich intrinsic activity [41,42] related to automatic and unconscious cognitive processing [43,44]. Since then, resting-state FC (rsFC) has been used to characterize brain function in health and disease [45][46][47]. It also characterizes aging, where a general decrease in FC has been shown [48,49] and relates to changes in cognitive performance [50].…”

Section: Introductionmentioning

confidence: 99%

Modeling the role of the thalamus in resting-state functional connectivity: nature or structure

Cabrera-Álvarez¹,

Doorn²,

Maestú³

et al. 2023

Preprint

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The thalamus is a central brain structure that serves as a relay station for sensory inputs from the periphery to the cortex and regulates cortical arousal. Traditionally, it has been regarded as a passive relay that transmits information between brain regions. However, recent studies have suggested that the thalamus may also play a role in shaping functional connectivity (FC) in a task-based context. Based on this idea, we hypothesized that due to its centrality in the network and its involvement in cortical activation, the thalamus may also contribute to resting-state FC, a key neurological biomarker widely used to characterize brain function in health and disease. To investigate this hypothesis, we constructed ten in-silico brain network models based on neuroimaging data (MEG, MRI, and dwMRI), and simulated them including and excluding the thalamus. and raising the noise into thalamus to represent the afferences related to the reticular activating system (RAS) and the relay of peripheral sensory inputs. We simulated brain activity and compared the resulting FC to their empirical MEG counterparts to evaluate model's performance. Results showed that a parceled version of the thalamus with higher noise, able to drive damped cortical oscillators, enhanced the match to empirical FC. However, with an already active self-oscillatory cortex, no impact on the dynamics was observed when introducing the thalamus. We also demonstrated that the enhanced performance was not related to the structural connectivity of the thalamus, but to its higher noisy inputs. Additionally, we highlighted the relevance of a balanced signal-to-noise ratio in thalamus to allow it to propagate its own dynamics. In conclusion, our study sheds light on the role of the thalamus in shaping brain dynamics and FC in resting-state and allowed us to discuss the general role of criticality in the brain at the mesoscale level.

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“…Advanced neuroimaging techniques represent a valid tool to study brain physiology and neural mechanisms in several pathological conditions such as neuropsychiatric disorders (Spinosa et al, 2022 ), allowing to examine brain structural and functional changes (Cieri and Esposito, 2018 ; Esposito et al, 2018 ; Cieri et al, 2020 ). This Research Topic is a second volume of a previous Research Topic, now convening nine research articles based on the current understanding of brain neuroimaging technique addressing theoretical and methodological questions.…”

Section: Introductionmentioning

confidence: 99%

Editorial: Dynamic functioning of resting state networks in physiological and pathological conditions, volume II

et al. 2023

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A systematic review on resting state functional connectivity in patients with neurodegenerative disease and hallucinations

Cited by 11 publications

References 71 publications

Abnormal higher-order network interactions in Parkinson’s disease visual hallucinations

Abnormal higher-order network interactions in Parkinson’s disease visual hallucinations

Modeling the role of the thalamus in resting-state functional connectivity: nature or structure

Editorial: Dynamic functioning of resting state networks in physiological and pathological conditions, volume II

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