Distinct grey and white matter changes are associated with the phenomenology of visual hallucinations in Lewy Body Disease

Visual hallucinations in Lewy body disease (LBD) can be differentiated based on phenomenology into minor phenomena (MVH) and complex hallucinations (CVH). MVH include a variety of phenomena, such as illusions, presence and passage hallucinations occurring at early stages of LBD. The neural mechanisms of visual hallucinations are largely unknown. The hodotopic model posits that the hallucination state is due to abnormal activity in specialized visual areas, that occurs in the context of wider network connectivity alterations and that phenomenology of VH, including content and temporal characteristics, may help identify brain regions underpinning these phenomena. Here we investigated both the topological and hodological neural basis of visual hallucinations integrating grey and white matter imaging analyses. We studied LBD patients with VH and age matched healthy controls (HC). VH were assessed using a North-East-Visual-Hallucinations-Interview that captures phenomenological detail. Then we applied voxel-based morphometry and tract based spatial statistics approaches to identify grey and white matter changes. First, we compared LBD patients and HC. We found a reduced grey matter volume and a widespread damage of white tracts in LBD compared to HC. Then we tested the association between CVH and MVH and grey and white matter indices. We found that CVH duration was associated with decreased grey matter volume in the fusiform gyrus suggesting that LBD neurodegeneration-related abnormal activity in this area is responsible for CVH. An unexpected finding was that MVH severity was associated with a greater integrity of white matter tracts, specifically those connecting dorsal, ventral attention networks and visual areas. Our results suggest that networks underlying MVH need to be partly intact and functional for MVH experiences to occur, while CVH occur when cortical areas are damaged. The findings support the hodotopic view and the hypothesis that MVH and CVH relate to different neural mechanisms, with wider implications for the treatment of these symptoms in a clinical context.

Time synchronization between parietal-frontocentral connectivity with MRCP and gait in post-stroke bipedal tasks

BACKGROUND

In post-stroke rehabilitation, functional connectivity (FC), motor-related cortical potential (MRCP), and gait activities are common measures related to recovery outcomes. However, the interrelationship between FC, MRCP, gait activities, and bipedal distinguishability have yet to be investigated.

METHODS

Ten participants were equipped with EEG devices and inertial measurement units (IMUs) while performing lower limb motor preparation (MP) and motor execution (ME) tasks. MRCP, FCs, and bipedal distinguishability were extracted from the EEG signals, while the change in knee degree during the ME phase was calculated from the gait data. FCs were analyzed with pairwise Pearson's correlation, and the brain-wide FC was fed into support vector machine (SVM) for bipedal classification.

RESULTS

Parietal-frontocentral connectivity (PFCC) dysconnection and MRCP desynchronization were related to the MP and ME phases, respectively. Hemiplegic limb movement exhibited higher PFCC strength than nonhemiplegic limb movement. Bipedal classification had a short-lived peak of 75.1% in the pre-movement phase. These results contribute to a better understanding of the neurophysiological functions during motor tasks, with respect to localized MRCP and nonlocalized FC activities. The difference in PFCCs between both limbs could be a marker to understand the motor function of the brain of post-stroke patients.

CONCLUSIONS

In this study, we discovered that PFCCs are temporally dependent on lower limb gait movement and MRCP. The PFCCs are also related to the lower limb motor performance of post-stroke patients. The detection of motor intentions allows the development of bipedal brain-controlled exoskeletons for lower limb active rehabilitation.

Consistent abnormal activity in the putamen by dopamine modulation in Parkinson's disease: A resting-state neuroimaging meta-analysis

OBJECTIVE

This study aimed to elucidate brain areas mediated by oral anti-parkinsonian medicine that consistently show abnormal resting-state activation in PD and to reveal their functional connectivity profiles using meta-analytic approaches.

METHODS

Searches of the PubMed, Web of Science databases identified 78 neuroimaging studies including PD OFF state (PD-OFF) versus (vs.) PD ON state (PD-ON) or PD-ON versus healthy controls (HCs) or PD-OFF versus HCs data. Coordinate-based meta-analysis and functional meta-analytic connectivity modeling (MACM) were performed using the activation likelihood estimation algorithm.

RESULTS

Brain activation in PD-OFF vs. PD-ON was significantly changed in the right putamen and left inferior parietal lobule (IPL). Contrast analysis indicated that PD-OFF vs. HCs had more consistent activation in the right paracentral lobule, right middle frontal gyrus, right thalamus, left superior parietal lobule and right putamen, whereas PD-ON vs. HCs elicited more consistent activation in the bilateral middle temporal gyrus, left occipital gyrus, right inferior frontal gyrus and right caudate. MACM revealed coactivation of the right putamen in the direct contrast of PD-OFF vs. PD-ON. Subtraction analysis of significant coactivation clusters for PD-OFF vs. PD-ON with the medium of HCs showed effects in the sensorimotor, top-down control, and visual networks. By overlapping the MACM maps of the two analytical strategies, we demonstrated that the coactivated brain region focused on the right putamen.

CONCLUSIONS

The convergence of local brain regions and co-activation neural networks are involved the putamen, suggesting its potential as a specific imaging biomarker to monitor treatment efficacy.

SYSTEMATIC REVIEW REGISTRATION

[https://www.crd.york.ac.uk/PROSPERO/], identifier [CRD CRD42022304150].

Parkinson disease psychosis: from phenomenology to neurobiological mechanisms

Parkinson disease (PD) psychosis (PDP) is a spectrum of illusions, hallucinations and delusions that are associated with PD throughout its disease course. Psychotic phenomena can manifest from the earliest stages of PD and might follow a continuum from minor hallucinations to structured hallucinations and delusions. Initially, PDP was considered to be a complication associated with dopaminergic drug use. However, subsequent research has provided evidence that PDP arises from the progression of brain alterations caused by PD itself, coupled with the use of dopaminergic drugs. The combined dysfunction of attentional control systems, sensory processing, limbic structures, the default mode network and thalamocortical connections provides a conceptual framework to explain how new incoming stimuli are incorrectly categorized, and how aberrant hierarchical predictive processing can produce false percepts that intrude into the stream of consciousness. The past decade has seen the publication of new data on the phenomenology and neurobiological basis of PDP from the initial stages of the disease, as well as the neurotransmitter systems involved in PDP initiation and progression. In this Review, we discuss the latest clinical, neuroimaging and neurochemical evidence that could aid early identification of psychotic phenomena in PD and inform the discovery of new therapeutic targets and strategies.

Functional Brain Networks of Minor and Well-Structured Major Hallucinations in Parkinson's Disease

BACKGROUND

Minor hallucinations (mHs) and well-structured major hallucinations (MHs) are common symptoms of Parkinson's disease (PD) psychosis.

OBJECTIVES

To investigate the resting-state networks (RSNs) in patients with PD without hallucinations (PD-nH), with mH (PD-mH), and with MH (PD-MH).

METHODS

A total of 73 patients with PD were enrolled (27 PD-nH, 23 PD-mH, and 23 PD-MH). Using seed-based functional connectivity analyses, we investigated the RSNs supposedly related to hallucinations in PD: the default mode network (DMN), executive control network (ECN), dorsal attention network (DAN), ventral attention network (VAN), and visual network (VN). We compared the cognitive function and RSN connectivity among the three groups. In addition, we performed a seed-to-seed analysis to examine the inter-network connectivity within each group using the corresponding RSN seeds.

RESULTS

PD-MH group had lower test scores for attention and visuospatial functions compared with those in the other groups. The connectivity of the right intracalcarine cortex within the DAN was lower in the PD-MH group than in the others. The PD-mH and PD-MH groups showed higher connectivity in the left orbitofrontal cortex within DMN compared with the PD-nH group, whereas the connectivity was lower in the right middle frontal gyrus (MFG) within ECN, precuneus cortex within VAN, right middle temporal gyrus and precuneus cortex within DAN, and left MFG within VN. The PD-mH and PD-MH groups showed different inter-network connectivity between the five RSNs, especially regarding DAN connectivity.

CONCLUSIONS

DAN dysfunction may be a key factor in the progression from mH to MH in patients with PD. © 2023 International Parkinson and Movement Disorder Society.

Differences and Changes in Cerebellar Functional Connectivity of Parkinson's Patients with Visual Hallucinations

Recent studies have discovered that functional connections are impaired in patients with Parkinson's disease (PD) accompanied by hallucinations (PD-H), even at the preclinical stage. The cerebellum has been implicated in playing a role in cognitive processes. However, the functional connectivity (FC) between the cognitive sub-regions of the cerebellum in PD patients with hallucinations needs further clarification. Resting-state functional magnetic resonance imaging (rs-fMRI) data were collected from three groups (17 PD-H patients, 13 patients with Parkinson's disease not accompanied by hallucinations (PD-NH), and 26 healthy controls (HC)). The data were collected in this study to investigate the impact of cerebellar FC changes on cognitive performance. Additionally, we define cerebellar FC as a training feature for classifying all subjects using Support Vector Machines (SVMs). We found that in the PD-H patients, there was an increase in FC within the left side of the precuneus (PCUN) compared to the HC. Additionally, there was an increase in FC within the bilateral opercular part of the inferior frontal gyrus (IFGoprec) and triangular part of the inferior frontal gyrus (IFCtriang), as well as the left side of the postcentral gyrus (PoCG), inferior parietal lobe (IPL), and PCUN compared to the PD-NH patients. In the machine learning training results, cerebellar FC has also been proven to be an effective biomarker feature, achieving a recognition rate of over 90% for PD-H. These findings indicate that the cortico-cerebellar FC in PD-H and PD-NH patients was significantly disrupted, with different patterns of distribution. The proposed pipeline offers a promising, low-cost alternative for diagnosing preclinical PD-H and may also be beneficial for other degenerative brain disorders.

Structural and Functional Imaging Correlates of Visual Hallucinations in Parkinson's Disease

PURPOSE OF REVIEW

To review recent structural and functional MRI studies of visual hallucinations in Parkinson's disease.

RECENT FINDINGS

Previously, neuroimaging had shown inconsistent findings in patients with Parkinson's hallucinations, especially in studies examining grey matter volume. However, recent advances in structural and functional MRI techniques allow better estimates of structural connections, as well as the direction of connectivity in functional MRI. These provide more sensitive measures of changes in structural connectivity and allow models of the changes in directional functional connectivity to be tested. We identified 27 relevant studies and found that grey matter imaging continues to show heterogeneous findings in Parkinson's patients with visual hallucinations. Newer approaches in diffusion imaging and functional MRI are consistent with emerging models of Parkinson's hallucinations, suggesting shifts in attentional networks. In particular, reduced bottom-up, incoming sensory information, and over-weighting of top-down signals appear to be important drivers of visual hallucinations in Parkinson's disease.

Multimodal visual system analysis as a biomarker of visual hallucinations in Parkinson's disease

Visual hallucinations (VH) are present in up to 75% of Parkinson's disease (PD) patients. However, their neural bases and participation of the visual system in VH are not well-understood in PD. Seventy-four participants, 12 PD with VH (PDVH), 35 PD without VH (PDnoVH) and 27 controls underwent a battery of primary visual function and visual cognition tests, retinal optical coherence tomography and structural and resting-state functional brain MRI. We quantified cortical thickness with Freesurfer and functional connectivity (FC) of Visual (VIS), Fronto-Parietal (FP), Ventral Attention (VAN) and Dorsal Attention (DAN) networks with CONN toolbox. Group comparisons were performed with MANCOVA. Area Under the Curve (AUC) was computed to assess the ability of visual variables to differentiate PDVH and PDnoVH. There were no significant PDVH vs PDnoVH differences in disease duration, motor manifestations, general cognition or dopamine agonist therapy (DA) use. Compared to PDnoVH and HC, and regardless of DA use, PDVH showed significantly reduced contrast sensitivity, visuoperceptive and visuospatial abilities, increased retina photoreceptor layer thickness, reduced cortical thickness mostly in right visual associative areas, decreased between-network VIS-VAN and VAN-DAN connectivity and increased within-network DAN connectivity. The combination of clinical and imaging variables that best discriminated PDVH and PDnoVH (highest AUC), where within-network DAN FC, photoreceptor layer thickness and cube analysis test from Visual Object and Space Perception Battery (accuracy of 81.8%). Compared to PDnoVH, PDVH have specific functional and structural abnormalities within the visual system, which can be quantified non-invasively and could potentially constitute biomarkers for VH in PD.

Changes in both top-down and bottom-up effective connectivity drive visual hallucinations in Parkinson's disease

Visual hallucinations are common in Parkinson's disease and are associated with a poorer quality of life and a higher risk of dementia. An important and influential model that is widely accepted as an explanation for the mechanism of visual hallucinations in Parkinson's disease and other Lewy body diseases is that these arise due to aberrant hierarchical processing, with impaired bottom-up integration of sensory information and overweighting of top-down perceptual priors within the visual system. This hypothesis has been driven by behavioural data and supported indirectly by observations derived from regional activation and correlational measures using neuroimaging. However, until now, there was no evidence from neuroimaging for differences in causal influences between brain regions measured in patients with Parkinson's hallucinations. This is in part because previous resting-state studies focused on functional connectivity, which is inherently undirected in nature and cannot test hypotheses about the directionality of connectivity. Spectral dynamic causal modelling is a Bayesian framework that allows the inference of effective connectivity-defined as the directed (causal) influence that one region exerts on another region-from resting-state functional MRI data. In the current study, we utilize spectral dynamic causal modelling to estimate effective connectivity within the resting-state visual network in our cohort of 15 Parkinson's disease visual hallucinators and 75 Parkinson's disease non-visual hallucinators. We find that visual hallucinators display decreased bottom-up effective connectivity from the lateral geniculate nucleus to primary visual cortex and increased top-down effective connectivity from the left prefrontal cortex to primary visual cortex and the medial thalamus, as compared with non-visual hallucinators. Importantly, we find that the pattern of effective connectivity is predictive of the presence of visual hallucinations and associated with their severity within the hallucinating group. This is the first study to provide evidence, using resting-state effective connectivity, to support a model of aberrant hierarchical predictive processing as the mechanism for visual hallucinations in Parkinson's disease.

Cortical and subcortical morphological alterations in motor subtypes of Parkinson's disease

Parkinson's disease (PD) can be classified into an akinetic-rigid (AR) and a tremor-dominant (TD) subtype based on predominant motor symptoms. Patients with different motor subtypes often show divergent clinical manifestations; however, the underlying neural mechanisms remain unclear. This study aimed to characterize the cortical and subcortical morphological alterations in motor subtypes of PD. T1-weighted MRI images were obtained for 90 patients with PD (64 with the AR subtype and 26 with the TD subtype) and 56 healthy controls (HCs). Cortical surface area, sulcal depth (measured by Freesurfer's Sulc index), and subcortical volume were computed to identify the cortical and subcortical morphological alterations in the two motor subtypes. Compared with HCs, we found widespread surface area reductions in the AR subtype yet sparse surface area reductions in the TD subtype. We found no significant Sulc change in the AR subtype yet increased Sulc in the right supramarginal gyrus in the TD subtype. The hippocampal volumes in both subtypes were lower than those of HCs. In PD patients, the surface area of left posterior cingulate cortex was positively correlated with Mini-Mental State Examination (MMSE) score, while the Sulc value of right middle frontal gyrus was positively correlated with severity of motor impairments. Additionally, the hippocampal volumes were positively correlated with MMSE and Montreal Cognitive Assessment scores and negatively correlated with severity of motor impairments and Hoehn & Yahr scores. Taken together, these findings may contribute to a better understanding of the neural substrates underlying the distinct symptom profiles in the two PD subtypes.

Aberrant gray matter volume and functional connectivity in Parkinson’s disease with minor hallucination

Background

Minor hallucination (MH) is the most common psychotic symptom in Parkinson’s disease (PD); it can develop into well-structured visual hallucination (VH), suggesting that MH may be a staccato form of well-structured VH. However, it remains unclear whether the pathogenesis is the same. Therefore, the aim of this study was to investigate the altered gray matter volume (GMV) and functional connectivity (FC) of MH in PD to further understand the complex mechanisms.

Materials and methods

We included 67 PD patients who attended the outpatient clinic of Nanjing Medical University Affiliated Brain Hospital and recruited 31 healthy controls (HC). Demographic data and clinical characteristics of all subjects were recorded, and cranial structural magnetic resonance imaging (MRI) and resting-state functional MRI data were acquired. Patients were classified into the PD with MH (PD-MH) group and PD without hallucinations or delusions (PD-NH) group. Voxel-based morphometry was used to analyze the differences in GMV in the structural pattern. Seed-based FC was used to analyze the functional pattern. Gaussian random field correction was used, with voxel level P < 0.001 and cluster level P < 0.05 representing statistically significant differences. Finally, the correlation between FC values and scores on the clinical characteristics assessment scale was analyzed.

Results

In the GMV analysis, compared to the PD-NH group, the PD-MH group had reduced GMV in the medial superior frontal gyrus (SFGmed). In the FC analysis, the FC between the SFGmed and the left middle occipital gyrus and right calcarine sulcus decreased in the PD-MH group compared with the PD-NH group, while the FC between SFGmed and the left middle temporal gyrus increased. Correlation analysis revealed that the FC values of the SFGmed and right calcarine sulcus were correlated with the assessment scores for anxiety and sleep symptoms. The FC values of the SFGmed and left middle occipital gyrus were correlated with assessment scores for rapid eye movement disorder.

Conclusion

The aberrant structure and function of the default mode network and visual processing areas seems to facilitate the generation of MH in PD, as the alteration was previously found in well-structured VH, suggesting that the two hallucinations have similar pathophysiological mechanisms.

Changes in dynamic transitions between integrated and segregated states underlie visual hallucinations in Parkinson's disease

Hallucinations are a core feature of psychosis and common in Parkinson's. Their transient, unexpected nature suggests a change in dynamic brain states, but underlying causes are unknown. Here, we examine temporal dynamics and underlying structural connectivity in Parkinson's-hallucinations using a combination of functional and structural MRI, network control theory, neurotransmitter density and genetic analyses. We show that Parkinson's-hallucinators spent more time in a predominantly Segregated functional state with fewer between-state transitions. The transition from integrated-to-segregated state had lower energy cost in Parkinson's-hallucinators; and was therefore potentially preferable. The regional energy needed for this transition was correlated with regional neurotransmitter density and gene expression for serotoninergic, GABAergic, noradrenergic and cholinergic, but not dopaminergic, receptors. We show how the combination of neurochemistry and brain structure jointly shape functional brain dynamics leading to hallucinations and highlight potential therapeutic targets by linking these changes to neurotransmitter systems involved in early sensory and complex visual processing.

Early disturbance of dynamic synchronization and neurovascular coupling in cognitively normal Parkinson's disease

Pathological process in Parkinson's disease (PD) is accompanied with functional and metabolic alterations. The time-varying properties of functional coherence and their coupling to regional perfusion are still rarely elucidated. To investigate early disruption of dynamic regional homogeneity (dReho) and neurovascular coupling in cognitively normal PD patients, dynamic neuronal synchronization and regional perfusion were measured using dReho and cerebral blood flow (CBF), respectively. Neurovascular coupling was assessed by CBF-ReHo correlation coefficient and CBF/ReHo ratio. Multivariate pattern analysis was conducted for the differentiating ability of each feature. Relative to healthy controls (HC) subjects, PD patients demonstrated increased dReho in middle temporal gyrus (MTG), rectus gyrus, middle occipital gyrus, and precuneus, whereas reduced dReho in putamen and supplementary motor area (SMA); while higher CBF/dReho ratio was located in putamen, SMA, paracentral lobule, and postcentral gyrus, whereas lower CBF/dReho ratio in superior temporal gyrus, MTG, precuneus, and angular gyrus (AG). Global and regional CBF-Reho decoupling were both observed in PD groups. The CBF/Reho ratio features achieved more powerful classification performance than other features. From the view of dynamic neural synchronization and neurovascular coupling, this study reinforced the insights into neural basis underlying PD and the potential role in the disease diagnosis and differentiation.

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

Hallucinations are a complex and multidimensional phenomenon which can differ based on the involved pathology, typology and sensory modality. Hallucinations are common in patients with neurodegenerative diseases. Recent sparse evidence from resting state functional magnetic resonance imaging (rs-fMRI) studies has identified altered functional connectivity in those patients within several brain networks, such as the default mode, attentional and sensory ones, without, however, providing an organized picture of the mechanisms involved. This systematic review, following PRISMA guidelines, aims at critically analyzing the current literature on the brain networks associated with the phenomenon of hallucinations in patients with neurodegenerative diseases. Ten rs-fMRI studies fulfilled our selection criteria. All these studies focused on synucleinopathies, and most of them focused on visual hallucinations and were characterized by a heterogeneous methodology. Thus, instead of offering a definite picture of the mechanisms underlying hallucinations in neurodegeneration, this systematic review encourages further research especially concerning tauopathies. Notwithstanding, the findings overall suggest a disruption in the top-down (associated with memory intrusion and difficulty of inhibition) and in the bottom-up processes (associated with the sensory areas involved in the hallucinations). Further investigations are needed in order to disentangle the brain mechanisms involved in hallucinations and to overcome possible limitations characterizing the current literature.

Visual hallucinations in Lewy body disease: pathophysiological insights from phenomenology

Visual hallucinations (VH) in Lewy body disease (LBD) have a heterogenous phenomenology classified into minor phenomena (MVH) and complex hallucinations (CVH). Mechanisms underpinning VH and their temporal aspects are largely unknown. According to the hodotopic model, we investigated whether changes in distinct cognitive domains and neural networks in the hallucination trait underpin temporal aspects of MVH and CVH in the hallucination state. 35 LBD patients with VH underwent a complete neuropsychological evaluation and resting-state fMRI. North-East-Visual-Hallucinations-Interview was used to assess their typical VH content, duration, and frequency. We found that MVH was not associated with cognitive impairment, while CVH was associated with impairments in visuoperceptual processes, attention and visual abstract reasoning. In seed-to-seed functional connectivity (FC) analysis we identified functional couplings associated with MVH and CVH temporal severity (duration x frequency), duration and frequency. MVH severity was negatively associated with FC between early visual areas (EVA) and ventral-visual-stream regions, and negatively associated with FC between brainstem and EVA, which may be linked to LBD brainstem neuropathology. CVH duration was positively associated with FC between ventral-visual stream and salience network (SN). CVH frequency was negatively associated with FC between DMN and SN. Functional alterations in distinct visual and attentional networks and their dynamic interaction in trait LBD hallucinators are linked to both the phenomenology of state content and its temporal characteristics. Within a network, VH frequency and duration may be linked to different types of functional alterations: increased connectivity leading to sustained activity prolonging VH (duration) and decreased connectivity increasing dysregulated, spontaneous activity (frequency). These findings support the hodotopic hypothesis of VH and may reflect a link between VH phenomenology, LBD neuropathological progression and the involvement of specific neurotransmitter systems.

Functional and structural brain network correlates of visual hallucinations in Lewy body dementia

Visual hallucinations are a common feature of Lewy body dementia. Previous studies have shown that visual hallucinations are highly specific in differentiating Lewy body dementia from Alzheimer’s disease dementia and Alzheimer–Lewy body mixed pathology cases. Computational models propose that impairment of visual and attentional networks is aetiologically key to the manifestation of visual hallucinations symptomatology. However, there is still a lack of experimental evidence on functional and structural brain network abnormalities associated with visual hallucinations in Lewy body dementia.

We used EEG source localization and network based statistics to assess differential topographical patterns in Lewy body dementia between 25 participants with visual hallucinations and 17 participants without hallucinations. Diffusion tensor imaging was used to assess structural connectivity between thalamus, basal forebrain and cortical regions belonging to the functionally affected network component in the hallucinating group, as assessed with network based statistics. The number of white matter streamlines within the cortex and between subcortical and cortical regions was compared between hallucinating and not hallucinating groups and correlated with average EEG source connectivity of the affected subnetwork. Moreover, modular organization of the EEG source network was obtained, compared between groups and tested for correlation with structural connectivity.

Network analysis showed that compared to non-hallucinating patients, those with hallucinations feature consistent weakened connectivity within the visual ventral network, and between this network and default mode and ventral attentional networks, but not between or within attentional networks. The occipital lobe was the most functionally disconnected region. Structural analysis yielded significantly affected white matter streamlines connecting the cortical regions to the nucleus basalis of Meynert and the thalamus in hallucinating compared to not hallucinating patients. The number of streamlines in the tract between the basal forebrain and the cortex correlated with cortical functional connectivity in non-hallucinating patients, while a correlation emerged for the white matter streamlines connecting the functionally affected cortical regions in the hallucinating group.

This study proposes, for the first time, differential functional networks between hallucinating and not hallucinating Lewy body dementia patients, and provides empirical evidence for existing models of visual hallucinations. Specifically, the outcome of the present study shows that the hallucinating condition is associated with functional network segregation in Lewy body dementia and supports the involvement of the cholinergic system as proposed in the current literature.

[Causes of visual hallucinations in Parkinson's disease]

BACKGROUND

Visual hallucinations (VH) have mainly been considered as late symptoms of Parkinson's disease (PD); however, minor forms of VH also occur in early stages of the disease. Initially dopaminergic overstimulation was discussed as the cause and later on VH have been considered as an early red flag of dementia in PD.

OBJECTIVE

The present study analyzed whether the pathophysiological concept of VH has been enlarged in recent years.

MATERIAL AND METHODS

Clinical, pharmacological, neuropathological as well as functional magnetic resonance imaging studies dealing with VH were reviewed. A systematic classification in monomodal and multimodal models of VH is proposed. The applicability to various forms of VH and various triggering situations is critically examined.

RESULTS

Reduction of the visual information input, erroneous visual processing, attention deficits, and dysfunctional connectivity between various cerebral networks have been shown. There is partial overlapping with the Lhermitte syndrome and the Charles Bonnet syndrome. No model is able to fully explain all VH variants. Not all VH have the same pathogenesis and the same poor prognosis.

CONCLUSION

The chain of causes underlying VH is complex and can vary from patient to patient. So far the therapeutic applications are largely unexplored; however, there is preliminary evidence that beside adjustment of the medication, improvement of visual acuity, active involvement of the partner, and possibly, individually adaptable coping strategies could be successfully implemented.

Longitudinal brain connectivity changes and clinical evolution in Parkinson's disease

Longitudinal connectivity studies might guide our understanding of the underlying neurodegenerative processes. We report the results of a longitudinal study in patients at different stages of Parkinson's disease (PD), who performed motor and non-motor evaluations and serial resting state (RS) functional MRI (fMRI). Cluster analysis was applied to demographic and clinical data of 146 PD patients to define disease subtypes. Brain network functional alterations were assessed at baseline in PD relative to 60 healthy controls and every year for a maximum of 4 years in PD groups. Progression of brain network changes were compared between patient clusters using RS fMRI. The contribution of network changes in predicting clinical deterioration was explored. Two main PD clusters were identified: mild PD (86 patients) and moderate-to-severe PD (60 patients), with the latter group being older and having earlier onset, longer PD duration, more severe motor, non-motor and cognitive deficits. Within the mild patient cluster, two clinical subtypes were further identified: mild motor-predominant (43) and mild-diffuse (43), with the latter being older and having more frequent non-motor symptoms. Longitudinal functional connectivity changes vary across patients in different disease stages with the coexistence of hypo- and hyper-connectivity in all subtypes. RS fMRI changes were associated with motor, cognitive and non-motor evolution in PD patients. Baseline RS fMRI presaged clinical and cognitive evolution. Our network perspective was able to define trajectories of functional architecture changes according to PD stages and prognosis. RS fMRI may be an early biomarker of PD motor and non-motor progression.

Structural network topology and microstructural alterations of the anterior insula associate with cognitive and affective impairment in Parkinson's disease

The aim of the current study was to assess the structural centrality and microstructural integrity of the cortical hubs of the salience network, the anterior insular cortex (AIC) subregions and anterior cingulate cortex (ACC), and their relationship to cognitive and affective impairment in PD. MRI of 53 PD patients and 15 age-matched controls included 3D-T1 for anatomical registration, and diffusion tensor imaging for probabilistic tractography. Network topological measures of eigenvector and betweenness centrality were calculated for ventral (vAI) and dorsal (dAI) AIC. Microstructural tract integrity between vAI, dAI and the ACC was quantified with fractional anisotrophy (FA) and mean diffusivity (MD). Structural integrity and connectivity were related to cognitive and affective scores. The dAI had significantly higher eigenvector centrality in PD than controls (p < 0.01), associated with higher depression scores (left dAI only, r_s = 0.28, p < 0.05). Tracts between dAI and ACC showed lower FA and higher MD in PD (p < 0.05), and associated with lower semantic fluency, working memory and executive functioning, and higher anxiety scores (range 0.002 < p < 0.05). This study provides evidence for clinically relevant structural damage to the cortical hubs of the salience network in PD, possibly due to extensive local neuropathology and loss of interconnecting AIC-ACC tracts.

Neuroanatomical and cognitive correlates of visual hallucinations in Parkinson's disease and dementia with Lewy bodies: Voxel-based morphometry and neuropsychological meta-analysis

Visual hallucinations (VH) are common in Parkinson's disease and dementia with Lewy bodies, two forms of Lewy body disease (LBD), but the neural substrates and mechanisms involved are still unclear. We conducted meta-analyses of voxel-based morphometry (VBM) and neuropsychological studies investigating the neuroanatomical and cognitive correlates of VH in LBD. For VBM (12 studies), we used Seed-based d Mapping with Permutation of Subject Images (SDM-PSI), including statistical parametric maps for 50% of the studies. For neuropsychology (35 studies), we used MetaNSUE to consider non-statistically significant unreported effects. VH were associated with smaller grey matter volume in occipital, frontal, occipitotemporal, and parietal areas (peak Hedges' g -0.34 to -0.49). In patients with Parkinson's disease without dementia, VH were associated with lower verbal immediate memory performance (Hedges' g -0.52). Both results survived correction for multiple comparisons. Abnormalities in these brain regions might reflect dysfunctions in brain networks sustaining visuoperceptive, attention, and executive abilities, with the latter also being at the basis of poor immediate memory performance.

Alteration of brain structural connectivity in progression of Parkinson's disease: A connectome-wide network analysis

Pinpointing the brain dysconnectivity in idiopathic rapid eye movement sleep behaviour disorder (iRBD) can facilitate preventing the conversion of Parkinson's disease (PD) from prodromal phase. Recent neuroimage investigations reported disruptive brain white matter connectivity in both iRBD and PD, respectively. However, the intrinsic process of the human brain structural network evolving from iRBD to PD still remains largely unknown. To address this issue, 151 participants including iRBD, PD and age-matched normal controls were recruited to receive diffusion MRI scans and neuropsychological examinations. The connectome-wide association analysis was performed to detect reorganization of brain structural network along with PD progression. Eight brain seed regions in both cortical and subcortical areas demonstrated significant structural pattern changes along with the progression of PD. Applying machine learning on the key connectivity related to these seed regions demonstrated better classification accuracy compared to conventional network-based statistic. Our study shows that connectome-wide association analysis reveals the underlying structural connectivity patterns related to the progression of PD, and provide a promising distinct capability to predict prodromal PD patients.

Functional connectivity between resting-state networks reflects decline in executive function in Parkinson's disease: A longitudinal fMRI study

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Over time, Parkinson’s disease (PD) patients declined on multiple cognitive domains.

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Executive dysfunction was related to interactions between specific resting-state networks.

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These interactions involved deep grey matter, frontoparietal, and attentional networks.

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Destabilization of functional network interactions may influence PD progression.

Deficits in cognitive functioning are a common yet poorly understood symptom in Parkinson’s disease (PD). Recent studies have highlighted the importance of (dynamic) interactions between resting-state networks for cognition, which remains understudied in PD. We investigated how altered (dynamic) functional interactions between brain networks relate to cognitive dysfunction in PD patients.

In this fMRI study, 50 PD patients (mean age 65.5 years ± 6.27) on dopaminergic medication were studied cross-sectionally, and of this cohort 31 PD patients were studied longitudinally. MRI imaging and neuropsychological testing was performed at two time points, with a follow-up duration of approximately three years. Functional connectivity within and between seven resting-state networks was calculated (both statically and dynamically) and correlated with four neuropsychological test scores; a combined score of (four) executive tasks, a motor perseveration, memory, and category fluency task. Cognitive dysfunction was determined based on a longitudinal sample of age-matched healthy controls (n = 13).

PD patients showed dysfunction on six out of seven cognitive tasks when compared to healthy controls. Severity of executive dysfunction was correlated with higher static and lower dynamic functional connectivity between deep gray matter regions and the frontoparietal network (DGM-FPN). Over time, declining executive function was related to increasing static DGM-FPN connectivity, together with changes of connectivity involving the dorsal attention network (amongst others with the ventral attention network). Static functional connectivity between the ventral and dorsal attention network correlated with motor perseveration.

Our findings demonstrate that in PD patients, dysfunctional communication between (i) subcortical, fronto-parietal and attention networks mostly underlies worsening of executive functioning, (ii) attention networks are involved in motor perseveration.

Differences in network controllability and regional gene expression underlie hallucinations in Parkinson's disease

Visual hallucinations are common in Parkinson's disease and are associated with poorer prognosis. Imaging studies show white matter loss and functional connectivity changes with Parkinson's visual hallucinations, but the biological factors underlying selective vulnerability of affected parts of the brain network are unknown. Recent models for Parkinson's disease hallucinations suggest they arise due to a shift in the relative effects of different networks. Understanding how structural connectivity affects the interplay between networks will provide important mechanistic insights. To address this, we investigated the structural connectivity changes that accompany visual hallucinations in Parkinson's disease and the organizational and gene expression characteristics of the preferentially affected areas of the network. We performed diffusion-weighted imaging in 100 patients with Parkinson's disease (81 without hallucinations, 19 with visual hallucinations) and 34 healthy age-matched controls. We used network-based statistics to identify changes in structural connectivity in Parkinson's disease patients with hallucinations and performed an analysis of controllability, an emerging technique that allows quantification of the influence a brain region has across the rest of the network. Using these techniques, we identified a subnetwork of reduced connectivity in Parkinson's disease hallucinations. We then used the Allen Institute for Brain Sciences human transcriptome atlas to identify regional gene expression patterns associated with affected areas of the network. Within this network, Parkinson's disease patients with hallucinations showed reduced controllability (less influence over other brain regions), than Parkinson's disease patients without hallucinations and controls. This subnetwork appears to be critical for overall brain integration, as even in controls, nodes with high controllability were more likely to be within the subnetwork. Gene expression analysis of gene modules related to the affected subnetwork revealed that down-weighted genes were most significantly enriched in genes related to mRNA and chromosome metabolic processes (with enrichment in oligodendrocytes) and upweighted genes to protein localization (with enrichment in neuronal cells). Our findings provide insights into how hallucinations are generated, with breakdown of a key structural subnetwork that exerts control across distributed brain regions. Expression of genes related to mRNA metabolism and membrane localization may be implicated, providing potential therapeutic targets.

Studies on the Bottom-Up and Top-Down Neural Information Flow Alterations in Neurodegeneration

BACKGROUND

A proper explanation for perceptual symptoms in neurodegenerative disorders including Alzheimer's disease and Parkinson's disease (PD) is still lacking.

OBJECTIVE

This study aimed at investigating the imbalance between 'bottom-up' and 'top-down' information flow (IF) and processing in PD in relation with visual hallucination symptoms.

METHODS

Here, we looked at bottom-up and top-down IF markers using resting state electroencephalographic (EEG) data from PD patients analyzed through three different IF measures (direct Directed Transfer Function (dDTF), full frequency Directed Transfer Function (ff-DTF), and renormalized Partial Directed Coherence (rPDC).

RESULTS

We observed an increased gamma band IF and a reduced beta band IF in PD patients compared to healthy controls. Additionally, we noticed a reduced theta band IF in PD patients using dDTF as a measure of IF. By source localizing the EEG activity of the PD patients and healthy controls, we looked at the alterations of IF in the prefrontal cortex of PD patients as well.

CONCLUSION

In line with previous studies, our results suggest that the delicate balance between bottom-up and top-down IF is disrupted in Parkinson's disease potentially contributing to the cognitive symptoms of PD patients.

GBA Variants in Parkinson's Disease: Clinical, Metabolomic, and Multimodal Neuroimaging Phenotypes

BACKGROUND

Alterations in the GBA gene (NM_000157.3) are the most important genetic risk factor for Parkinson's disease (PD). Biallelic GBA mutations cause the lysosomal storage disorder Gaucher's disease. The GBA variants p.E365K and p.T408M are associated with PD but not with Gaucher's disease. The pathophysiological role of these variants needs to be further explored.

OBJECTIVE

This study analyzed clinical, neuropsychological, metabolic, and neuroimaging phenotypes of patients with PD carrying the GBA variants p.E365K and p.T408M.

METHODS

GBA was sequenced in 56 patients with mid-stage PD. Carriers of GBA variants were compared with noncarriers regarding clinical history and symptoms, neuropsychological features, metabolomics, and multimodal neuroimaging. Blood plasma gas chromatography coupled to mass spectrometry, 6-[¹⁸ F]fluoro-L-Dopa positron emission tomography (PET), [¹⁸ F]fluorodeoxyglucose PET, and resting-state functional magnetic resonance imaging were performed.

RESULTS

Sequence analysis detected 13 heterozygous GBA variant carriers (7 with p.E365K, 6 with p.T408M). One patient carried a GBA mutation (p.N409S) and was excluded. Clinical history and symptoms were not significantly different between groups. Global cognitive performance was lower in variant carriers. Metabolomic group differences were suggestive of more severe PD-related alterations in carriers versus noncarriers. Both PET scans showed signs of a more advanced disease; [¹⁸ F]fluorodeoxyglucose PET and functional magnetic resonance imaging showed similarities with Lewy body dementia and PD dementia in carriers.

CONCLUSIONS

This is the first study to comprehensively assess (neuro-)biological phenotypes of GBA variants in PD. Metabolomics and neuroimaging detected more significant group differences than clinical and behavioral evaluation. These alterations could be promising to monitor effects of disease-modifying treatments targeting glucocerebrosidase metabolism. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Anterior insular network disconnection and cognitive impairment in Parkinson's disease

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Cognitive dysfunction in PD is related to FC of the dorsal anterior insula (dAI)

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In PD only, FC between the dAI and DMN was most strongly related to cognition.

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FC of dAI with anterior cingulate was reduced and related to cognition in PD.

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Increased DMN and FPN centrality is related to dAI-ACC disconnection in PD.

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Altered interplay between dAI, DMN, and FPN underlies poor cognition in PD.

Background

The insula is a central brain hub involved in cognition and affected in Parkinson’s disease (PD). The aim of this study was to assess functional connectivity (FC) and betweenness centrality (BC) of insular sub-regions and their relationship with cognitive impairment in PD.

Methods

Whole-brain 3D-T1, resting-state functional MRI and a battery of cognitive tests (CAMCOG) were included for 53 PD patients and 15 controls. The insular cortex was segmented into ventral (vAI) and dorsal (dAI) anterior and posterior sub-regions. Connectivity between insular sub-regions and resting-state networks was assessed and related to cognition; BC was used to further explore nodes associated with cognition.

Results

Cognitive performance was significantly lower in PD patients compared to controls (p < 0.01) and was associated with FC of the dAI with default mode network (DMN) (adjusted R² = 0.37, p < 0.001). In controls, cognitive performance was positively related to FC of the dAI with the fronto-parietal network (FPN) only (adjusted R² = 0.5, p = 0.003). Regionally, FC of the dAI with the anterior cingulate cortex (ACC) was significantly reduced in PD (F(1,65) = 11, p = 0.002) and correlated with CAMCOG (r = 0.4, p = 0.001). DMN and FPN showed increased BC in PD which correlated with cognition and reduced connectivity of dAI with the ACC (r_s = −0.33, p = 0.014 and r_s = −0.44, p = 0.001 respectively).

Conclusions

These results highlight the relevance of the insula in cognitive dysfunction in PD. Disconnection of the dAI with ACC was related to altered centrality in the DMN and FPN only in patients. Disturbance in this network triad appears to be particularly relevant for cognitive impairment in PD.

Increased large-scale inter-network connectivity in relation to impulsivity in Parkinson's disease

Impulsivity is a neuropsychiatric feature of Parkinson’s disease (PD). We investigated the pathophysiology of impulsivity in PD using resting-state functional magnetic resonance imaging (rs-fMRI). We investigated 45 patients with idiopathic PD and 21 healthy controls. Based on Barratt Impulsiveness Scale (BIS-11) score, PD patients were classified as higher (PD-HI) or lower impulsivity (PD-LI). Functional connectivity (FC) between various large-scale brain networks were analysed using the CONN toolbox. FC between the right frontoparietal network (FPN) and medial visual network (MVN) was significantly higher in PD-HI patients than PD-LI patients (false discovery rate [FDR]-adjusted p = 0.0315). FC between the right FPN and MVN had a significant positive correlation with total BIS-11 score (FDR-adjusted p = 0.010) and the attentional impulsivity (FDR-adjusted p = 0.046) and non-planning impulsivity subscale scores (FDR-adjusted p = 0.018). On the other hand, motor impulsivity subscale score had a significant negative correlation with the FC between the default-mode and salience networks (right supramarginal gyrus, FDR-adjusted p = 0.018; anterior cingulate cortex, FDR-adjusted p = 0.027); this trend was observed in healthy controls. The attentional and non-planning impulsivity, regarded as ‘cognitive’ impulsivity, may be associated with dysfunction in integration of perceptual information and flexible cognitive control in PD.

ALFF and ReHo Mapping Reveals Different Functional Patterns in Early- and Late-Onset Parkinson's Disease

Heterogeneity between late-onset Parkinson's disease (LOPD) and early-onset Parkinson's disease (EOPD) is mainly reflected in the following aspects including genetics, disease progression, drug response, clinical manifestation, and neuropathological change. Although many studies have investigated these differences in relation to clinical significance, the functional processing circuits and underlying neural mechanisms have not been entirely understood. In this study, regional homogeneity (ReHo) and amplitude of low-frequency fluctuation (ALFF) maps were used to explore different spontaneous brain activity patterns in EOPD and LOPD patients. Abnormal synchronizations were found in the motor and emotional circuits of the EOPD group, as well as in the motor, emotional, and visual circuits of the LOPD group. EOPD patients showed functional activity change in the visual, emotional and motor circuits, and LOPD patients only showed increased functional activity in the emotional circuits. In summary, the desynchronization process in the LOPD group was relatively strengthened, and the brain areas with changed functional activity in the EOPD group were relatively widespread. The results might point out different impairments in the synchronization and functional activity for EOPD and LOPD patients.

Electrophysiological resting state networks of predominantly akinetic-rigid Parkinson patients: Effects of dopamine therapy

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Analysis of whole-brain frequency-specific resting state networks with EEG.

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Comparison of dopamine medication ON and OFF state in Parkinson patients.

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Parkinson patients show distinct frequency-specific network alterations.

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Motor network at beta frequencies is re-instated after dopamine medication.

Parkinson's disease (PD) causes both motor and non-motor symptoms, which can partially be reversed by dopamine therapy. These symptoms as well as the effect of dopamine may be explained by distinct alterations in whole-brain architecture. We used functional connectivity (FC) and in particular resting state network (RSN) analysis to identify such whole-brain alterations in a frequency-specific manner. In addition, we hypothesized that standard dopaminergic medication would have a normalizing effect on these whole brain alterations. We recorded resting-state EEGs of 19 PD patients in the medical OFF and ON states, and of 12 healthy age-matched controls. The PD patients were either of akinetic-rigid or mixed subtype. We extracted RSNs with independent component analysis in the source space for five frequency bands. Within the sensorimotor network (SMN) the supplementary motor area (SMA) showed decreased FC in the OFF state compared to healthy controls. This finding was reversed after dopamine administration. Furthermore, in the OFF state no stable SMN beta component could be identified. The default mode network showed alterations due to PD independent of the medication state. The visual network was altered in the OFF state, and reinstated to a pattern similar to healthy controls by medication. In conclusion, PD causes distinct RSN alterations, which are partly reversed after levodopa administration. The changes within the SMN are of particular interest, because they broaden the pathophysiological understanding of PD. Our results identify the SMA as a central network hub affected in PD and a crucial effector of dopamine therapy.

Changes in structural network topology correlate with severity of hallucinatory behavior in Parkinson's disease

Inefficient integration between bottom-up visual input and higher order visual processing regions is implicated in visual hallucinations in Parkinson's disease (PD). Here, we investigated white matter contributions to this perceptual imbalance hypothesis. Twenty-nine PD patients were assessed for hallucinatory behavior. Hallucination severity was correlated to connectivity strength of the network using the network-based statistic approach. The results showed that hallucination severity was associated with reduced connectivity within a subnetwork that included the majority of the diverse club. This network showed overall greater between-module scores compared with nodes not associated with hallucination severity. Reduced between-module connectivity in the lateral occipital cortex, insula, and pars orbitalis and decreased within-module connectivity in the prefrontal, somatosensory, and primary visual cortices were associated with hallucination severity. Conversely, hallucination severity was associated with increased between- and within-module connectivity in the orbitofrontal and temporal cortex, as well as regions comprising the dorsal attentional and default mode network. These results suggest that hallucination severity is associated with marked alterations in structural network topology with changes in participation along the perceptual hierarchy. This may result in the inefficient transfer of information that gives rise to hallucinations in PD.

Resting-state Functional MRI in Parkinsonian Syndromes

Background

Functional MRI (fMRI) has been widely used to study abnormal patterns of functional connectivity at rest in patients with movement disorders such as idiopathic Parkinson's disease (PD) and atypical parkinsonisms.

Methods

This manuscript provides an educational review of the current use of resting-state fMRI in the field of parkinsonian syndromes.

Results

Resting-state fMRI studies have improved the current knowledge about the mechanisms underlying motor and non-motor symptom development and progression in movement disorders. Even if its inclusion in clinical practice is still far away, resting-state fMRI has the potential to be a promising biomarker for early disease detection and prediction. It may also aid in differential diagnosis and monitoring brain responses to therapeutic agents and neurorehabilitation strategies in different movement disorders.

Conclusions

There is urgent need to identify and validate prodromal biomarkers in PD patients, to perform further studies assessing both overlapping and disease-specific fMRI abnormalities among parkinsonian syndromes, and to continue technical advances to fully realize the potential of fMRI as a tool to monitor the efficacy of chronic therapies.

Stochastic Rank Aggregation for the Identification of Functional Neuromarkers

The main challenge in analysing functional magnetic resonance imaging (fMRI) data from extended samples of subject (N > 100) is to extract as much relevant information as possible from big amounts of noisy data. When studying neurodegenerative diseases with resting-state fMRI, one of the objectives is to determine regions with abnormal background activity with respect to a healthy brain and this is often attained with comparative statistical models applied to single voxels or brain parcels within one or several functional networks. In this work, we propose a novel approach based on clustering and stochastic rank aggregation to identify parcels that exhibit a coherent behaviour in groups of subjects affected by the same disorder and apply it to default-mode network independent component maps from resting-state fMRI data sets. Brain voxels are partitioned into parcels through k-means clustering, then solutions are enhanced by means of consensus techniques. For each subject, clusters are ranked according to their median value and a stochastic rank aggregation method, TopKLists, is applied to combine the individual rankings within each class of subjects. For comparison, the same approach was tested on an anatomical parcellation. We found parcels for which the rankings were different among control subjects and subjects affected by Parkinson's disease and amyotrophic lateral sclerosis and found evidence in literature for the relevance of top ranked regions in default-mode brain activity. The proposed framework represents a valid method for the identification of functional neuromarkers from resting-state fMRI data, and it might therefore constitute a step forward in the development of fully automated data-driven techniques to support early diagnoses of neurodegenerative diseases.

Dopaminergic Modulation of Synaptic Plasticity, Its Role in Neuropsychiatric Disorders, and Its Computational Modeling

Neuromodulators modify intrinsic characteristics of the nervous system in order to reconfigure the functional properties of neural circuits. This reconfiguration is crucial for the flexibility of the nervous system to respond on an input-modulated basis. Such a functional rearrangement is realized by modification of intrinsic properties of the neural circuits including synaptic interactions. Dopamine is an important neuromodulator involved in motivation and stimulus-reward learning process, and adjusts synaptic dynamics in multiple time scales through different pathways. The modification of synaptic plasticity by dopamine underlies the change in synaptic transmission and integration mechanisms, which affects intrinsic properties of the neural system including membrane excitability, probability of neurotransmitters release, receptors’ response to neurotransmitters, protein trafficking, and gene transcription. Dopamine also plays a central role in behavioral control, whereas its malfunction can cause cognitive disorders. Impaired dopamine signaling is implicated in several neuropsychiatric disorders such as Parkinson’s disease, drug addiction, schizophrenia, attention-deficit/hyperactivity disorder, obsessive-compulsive disorder and Tourette’s syndrome. Therefore, dopamine plays a crucial role in the nervous system, where its proper modulation of neural circuits may enhance plasticity-related procedures, but disturbances in dopamine signaling might be involved in numerous neuropsychiatric disorders. In recent years, several computational models are proposed to formulate the involvement of dopamine in synaptic plasticity or neuropsychiatric disorders and address their connection based on the experimental findings.

Alterations of the nigrostriatal pathway in a 6-OHDA rat model of Parkinson's disease evaluated with multimodal MRI

Parkinson's disease is characterized by neurodegeneration of the dopaminergic neurons in the substantia nigra pars compacta. The 6-hydroxydopamine (6-OHDA) rat model has been used to study neurodegeneration in the nigro-striatal dopaminergic system. The goal of this study was to evaluate the reliability of diffusion MRI and resting-state functional MRI biomarkers in monitoring neurodegeneration in the 6-OHDA rat model assessed by quantitative histology. We performed a unilateral injection of 6-OHDA in the striatum of Sprague Dawley rats to produce retrograde degeneration of the dopamine neurons in the substantia nigra pars compacta. We carried out a longitudinal study with a multi-modal approach combining structural and functional MRI together with quantitative histological validation to follow the effects of the lesion. Functional and structural connectivity were assessed in the brain of 6-OHDA rats and sham rats (NaCl injection) at 3 and 6 weeks post-lesioning using resting-state functional MRI and diffusion-weighted. Our results showed (i) increased functional connectivity in ipsi- and contra-lesioned regions of the cortico-basal ganglia network pathway including the motor cortex, the globus pallidus, and the striatum regions at 3 weeks; (ii) increased fractional anisotropy (FA) in the ipsi- and contralateral striatum of the 6-OHDA group at 3 weeks, and increased axial diffusivity (AD) and mean diffusivity in the ipsilateral striatum at 6 weeks; (iii) a trend for increased FA in both substantia nigra of the 6-OHDA group at 3 weeks. Optical density measurements of tyrosine-hydroxylase (TH) staining of the striatum showed good correlations with the FA and AD measurements in the striatum. No correlations were found between the number of TH-stained dopaminergic neurons and MRI measurements in the substantia nigra. This study suggested that (i) FA and AD were reliable biomarkers to evaluate neurodegeneration in the cortico-basal ganglia network of the 6-OHDA model, (ii) diffusion MRI and resting-state functional MRI (rsfMRI) were not sensitive enough to detect changes in the substantia nigra in this model.

Functional MRI in Idiopathic Parkinson's Disease

Functional MRI (fMRI) has been widely used to study abnormal patterns of brain connectivity at rest and activation during a variety of tasks in patients with idiopathic Parkinson's disease (PD). fMRI studies in PD have led to a better understanding of many aspects of the disease including both motor and non-motor symptoms. Although its translation into clinical practice is still at an early stage, fMRI measures hold promise for multiple clinical applications in PD, including the early detection, predicting future change in clinical status, and as a marker of alterations in brain physiology related to neurotherapeutic agents and neurorehabilitative strategies.