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Aberrant functional connectivity of resting state networks related to misperceptions and intra-individual variability in Parkinson's disease.

ABSTRACT: Patients with Parkinson's disease (PD) frequently suffer from visual misperceptions and hallucinations, which are difficult to objectify and quantify. We aimed to develop an image recognition task to objectify misperceptions and to assess performance fluctuations in PD patients with and without self-reported hallucinations. Thirty-two non-demented patients with Parkinson's disease (16 with and 16 without self-reported visual hallucinations) and 25 age-matched healthy controls (HC) were tested. Participants performed a dynamic image recognition task with real and scrambled images. We assessed misperception scores and intra-individual variability in recognition times. To gain insight into possible neural mechanisms related to misperceptions and performance fluctuations we correlated resting state network connectivity to the behavioral outcomes in a subsample of Parkinson's disease patients (N?=?16). We found that PD patients with self-reported hallucinations (PD-VH) exhibited higher perceptual error rates, due to decreased perceptual sensitivity and not due to changed decision criteria. In addition, PD-VH patients exhibited higher intra-individual variability in recognition times than HC or PD-nonVH patients. Both, misperceptions and intra-individual variability were negatively correlated with resting state functional connectivity involving frontal and parietal brain regions, albeit in partly different subregions. Consistent with previous research suggesting that hallucinations arise from dysfunction in attentional networks, misperception scores correlated with reduced functional connectivity between the dorsal attention and salience network. Intra-individual variability correlated with decreased connectivity between somatomotor and right fronto-parietal networks. We conclude that our task can detect visual misperceptions that are more prevalent in PD-VH patients. In addition, fluctuating visual performance appear to be a signature of PD-VH patients, which might assist further studies of the underlying pathophysiological mechanisms and cognitive processes.

SUBMITTER: Miloserdov K

PROVIDER: S-EPMC6906716 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Aberrant functional connectivity of resting state networks related to misperceptions and intra-individual variability in Parkinson's disease.

Miloserdov Kristina K Schmidt-Samoa Carsten C Williams Kathleen K Weinrich Christiane Anne CA Kagan Igor I Bürk Katrin K Trenkwalder Claudia C Bähr Mathias M Wilke Melanie M

NeuroImage. Clinical 20191105

Patients with Parkinson's disease (PD) frequently suffer from visual misperceptions and hallucinations, which are difficult to objectify and quantify. We aimed to develop an image recognition task to objectify misperceptions and to assess performance fluctuations in PD patients with and without self-reported hallucinations. Thirty-two non-demented patients with Parkinson's disease (16 with and 16 without self-reported visual hallucinations) and 25 age-matched healthy controls (HC) were tested. P ...[more]

PMID: 31794926

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Project description:BackgroundTransient ischemic attack (TIA) is usually defined as a neurologic ischemic disorder without permanent cerebral infarction. Studies have showed that patients with TIA can have lasting cognitive functional impairment. Inherent brain activity in the resting state is spatially organized in a set of specific coherent patterns named resting state networks (RSNs), which epitomize the functional architecture of memory, language, attention, visual, auditory and somato-motor networks. Here, we aimed to detect differences in RSNs between TIA patients and healthy controls (HCs).MethodsTwenty one TIA patients suffered an ischemic event and 21 matched HCs were enrolled in the study. All subjects were investigated using cognitive tests, psychiatric tests and functional magnetic resonance imaging (fMRI). Independent component analysis (ICA) was adopted to acquire the eight brain RSNs. Then one-sample t-tests were calculated in each group to gather the spatial maps of each RSNs, followed by second level analysis to investigate statistical differences on RSNs between twenty one TIA patients and 21 controls. Furthermore, a correlation analysis was performed to explore the relationship between functional connectivity (FC) and cognitive and psychiatric scales in TIA group.ResultsCompared with the controls, TIA patients exhibited both decreased and increased functional connectivity in default mode network (DMN) and self-referential network (SRN), and decreased functional connectivity in dorsal attention network (DAN), central-executive network (CEN), core network (CN), somato-motor network (SMN), visual network (VN) and auditory network (AN). There was no correlation between neuropsychological scores and functional connectivity in regions of RSNs.ConclusionsWe observed selective impairments of RSN intrinsic FC in TIA patients, whose all eight RSNs had aberrant functional connectivity. These changes indicate that TIA is a disease with widely abnormal brain networks. Our results might put forward a novel way to look into neuro-pathophysiological mechanisms in TIA patients.

Project description:Parkinson's disease (PD) is a neurodegenerative disorder affecting dopaminergic neurons in the substantia nigra leading to dysfunctional cortico-striato-thalamic-cortical loops. In addition to the characteristic motor symptoms, PD patients often show cognitive impairments, affective changes and other non-motor symptoms, suggesting system-wide effects on brain function. Here, we used functional magnetic resonance imaging and graph-theory based analysis methods to investigate altered whole-brain intrinsic functional connectivity in PD patients (n = 37) compared to healthy controls (n = 20). Global network properties indicated less efficient processing in PD. Analysis of brain network modules pointed to increased connectivity within the sensorimotor network, but decreased interaction of the visual network with other brain modules. We found lower connectivity mainly between the cuneus and the ventral caudate, medial orbitofrontal cortex and the temporal lobe. To identify regions of altered connectivity, we mapped the degree of intrinsic functional connectivity both on ROI- and on voxel-level across the brain. Compared to healthy controls, PD patients showed lower connectedness in the medial and middle orbitofrontal cortex. The degree of connectivity was also decreased in the occipital lobe (cuneus and calcarine), but increased in the superior parietal cortex, posterior cingulate gyrus, supramarginal gyrus and supplementary motor area. Our results on global network and module properties indicated that PD manifests as a disconnection syndrome. This was most apparent in the visual network module. The higher connectedness within the sensorimotor module in PD patients may be related to compensation mechanism in order to overcome the functional deficit of the striato-cortical motor loops or to loss of mutual inhibition between brain networks. Abnormal connectivity in the visual network may be related to adaptation and compensation processes as a consequence of altered motor function. Our analysis approach proved sensitive for detecting disease-related localized effects as well as changes in network functions on intermediate and global scale.

Project description:The spatial coherence of spontaneous slow fluctuations in the blood-oxygen-level dependent (BOLD) signal at rest is routinely used to characterize the underlying resting-state networks (RSNs). Studies have demonstrated that these patterns are organized in space and highly reproducible from subject to subject. Moreover, RSNs reorganizations have been suggested in pathological conditions. Comparisons of RSNs organization have been performed between groups of subjects but have rarely been applied at the individual level, a step required for clinical application. Defining the notion of modularity as the organization of brain activity in stable networks, we propose Detection of Abnormal Networks in Individuals (DANI) to identify modularity changes at the individual level. The stability of each RSN was estimated using a spatial clustering method: Bootstrap Analysis of Stable Clusters (BASC) (Bellec et al., 2010). Our contributions consisted in (i) providing functional maps of the most stable cores of each networks and (ii) in detecting "abnormal" individual changes in networks organization when compared to a population of healthy controls. DANI was first evaluated using realistic simulated data, showing that focussing on a conservative core size (50% most stable regions) improved the sensitivity to detect modularity changes. DANI was then applied to resting state fMRI data of six patients with focal epilepsy who underwent multimodal assessment using simultaneous EEG/fMRI acquisition followed by surgery. Only patient with a seizure free outcome were selected and the resected area was identified using a post-operative MRI. DANI automatically detected abnormal changes in 5 out of 6 patients, with excellent sensitivity, showing for each of them at least one "abnormal" lateralized network closely related to the epileptic focus. For each patient, we also detected some distant networks as abnormal, suggesting some remote reorganization in the epileptic brain.

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Aberrant functional connectivity of resting state networks related to misperceptions and intra-individual variability in Parkinson's disease.

Publications

Aberrant functional connectivity of resting state networks related to misperceptions and intra-individual variability in Parkinson's disease.

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