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• Multiple sclerosis and major depression share morphologic network alterations. • The contrast between the gray and white matters may be a neuroinflammation marker. • Network alterations may underlie symptom severity and depression comorbidity in MS. Neuroinflammation affects brain tissue integrity in multiple sclerosis (MS) and may have a role in major depressive disorder (MDD). Whether advanced magnetic resonance imaging characteristics of the gray-to-white matter border serve as proxy of neuroinflammatory activity in MDD and MS remain unknown. We included 684 participants (132 MDD patients with recurrent depressive episodes (RDE), 70 MDD patients with a single depressive episode (SDE), 222 MS patients without depressive symptoms (nMS), 58 MS patients with depressive symptoms (dMS), and 202 healthy controls (HC)). 3 T-T1w MRI-derived gray-to-white matter contrast (GWc) was used to reconstruct and characterize connectivity alterations of GWc-covariance networks by means of modularity, clustering coefficient, and degree. A cross-validated support vector machine was used to test the ability of GWc to stratify groups according to their depression symptoms, measured with BDI, at the single-subject level in MS and MDD independently. MS and MDD patients showed increased modularity (ANOVA partial-η2 = 0.3) and clustering (partial-η2 = 0.1) compared to HC. In the subgroups, a linear trend analysis attested a gradient of modularity increases in the form: HC, dMS, nMS, SDE, and RDE (ANOVA partial-η2 = 0.28, p < 0.001) while this trend was less evident for clustering coefficient. Reduced morphological integrity (GWc) was seen in patients with increased depressive symptoms (partial-η2 = 0.42, P < 0.001) and was associated with depression scores across patient groups (r = -0.2, P < 0.001). Depressive symptoms in MS were robustly classified (88 %). Similar structural network alterations in MDD and MS exist, suggesting possible common inflammatory events like demyelination, neuroinflammation that are caught by GWc analyses. These alterations may vary depending on the severity of symptoms and in the case of MS may elucidate the occurrence of comorbid depression. [ABSTRACT FROM AUTHOR]

Objective Methods Results Interpretation To investigate whether choroid plexus volumes in subacute coronavirus disease 2019 (COVID‐19) patients with neurological symptoms could indicate inflammatory activation or barrier dysfunction and assess their association with clinical data.Choroid plexus volumes were measured in 28 subacute COVID‐19 patients via cerebral magnetic resonance imaging (MRI), compared with those in infection‐triggered non‐COVID‐19 encephalopathy patients (n = 25), asymptomatic individuals after COVID‐19 (n = 21), and healthy controls (n = 21). Associations with inflammatory serum markers (peak counts of leukocytes, C‐reactive protein [CRP], interleukin 6), an MRI‐based marker of barrier dysfunction (CSF volume fraction [V‐CSF]), and clinical parameters like olfactory performance and cognitive scores (Montreal Cognitive Assessment) were investigated.COVID‐19 patients showed significantly larger choroid plexus volumes than control groups (p < 0.001, η2 = 0.172). These volumes correlated significantly with peak leukocyte levels (p = 0.001, Pearson's r = 0.621) and V‐CSF (p = 0.009, Spearman's rho = 0.534), but neither with CRP nor interleukin 6. No significant correlations were found with clinical parameters.In patients with subacute COVID‐19, choroid plexus volume is a marker of central nervous system inflammation and barrier dysfunction in the presence of neurologic symptoms. The absence of plexus enlargement in infection‐triggered non‐COVID‐19 encephalopathy suggests a specific severe acute respiratory syndrome coronavirus 2 effect. This study also documents an increase in choroid plexus volume for the first time as a parainfectious event. ANN NEUROL 2024 [ABSTRACT FROM AUTHOR]

The identification of prognostic markers in early multiple sclerosis (MS) is challenging and requires reliable measures that robustly predict future disease trajectories. Ideally, such measures should make inferences at the individual level to inform clinical decisions. This study investigated the prognostic value of longitudinal structural networks to predict 5-year Expanded Disability Status Scale (EDSS) progression in patients with relapsing-remitting MS (RRMS). We hypothesized that network measures, derived from MRI, outperform conventional MRI measurements at identifying patients at risk of developing disability progression. This longitudinal, multicentre study within the Magnetic Resonance Imaging in MS (MAGNIMS) network included 406 patients with RRMS (mean age = 35.7 ± 9.1 years) followed up for 5 years (mean follow-up = 5.0 ± 0.6 years). EDSS was determined to track disability accumulation. A group of 153 healthy subjects (mean age = 35.0 ± 10.1 years) with longitudinal MRI served as controls. All subjects underwent MRI at baseline and again 1 year after baseline. Grey matter atrophy over 1 year and white matter lesion load were determined. A single-subject brain network was reconstructed from T1-weighted scans based on grey matter atrophy measures derived from a statistical parameter mapping-based segmentation pipeline. Key topological measures, including network degree, global efficiency and transitivity, were calculated at single-subject level to quantify network properties related to EDSS progression. Areas under receiver operator characteristic (ROC) curves were constructed for grey matter atrophy and white matter lesion load, and the network measures and comparisons between ROC curves were conducted. The applied network analyses differentiated patients with RRMS who experience EDSS progression over 5 years through lower values for network degree [H(2) = 30.0, P < 0.001] and global efficiency [H(2) = 31.3, P < 0.001] from healthy controls but also from patients without progression. For transitivity, the comparisons showed no difference between the groups [H(2) = 1.5, P = 0.474]. Most notably, changes in network degree and global efficiency were detected independent of disease activity in the first year. The described network reorganization in patients experiencing EDSS progression was evident in the absence of grey matter atrophy. Network degree and global efficiency measurements demonstrated superiority of network measures in the ROC analyses over grey matter atrophy and white matter lesion load in predicting EDSS worsening (all P -values < 0.05). Our findings provide evidence that grey matter network reorganization over 1 year discloses relevant information about subsequent clinical worsening in RRMS. Early grey matter restructuring towards lower network efficiency predicts disability accumulation and outperforms conventional MRI predictors. [ABSTRACT FROM AUTHOR]

Background: Gait impairments are common in Parkinson's disease (PD). The pathological mechanisms are complex and not thoroughly elucidated, thus quantitative and objective parameters that closely relate to gait characteristics are critically needed to improve the diagnostic assessments and monitor disease progression. The substantia nigra is a relay structure within basal ganglia brainstem loops that is centrally involved in gait modulation. Objective: We tested the hypothesis that quantitative gait biomechanics are related to the microstructural integrity of the substantia nigra and PD-relevant gait abnormalities are independent from bradykinesia-linked speed reductions. Methods: Thirty-eight PD patients and 33 age-matched control participants walked on a treadmill at fixed speeds. Gait parameters were fed into a principal component analysis to delineate relevant features. We applied the neurite orientation dispersion and density imaging (NODDI) model on diffusion-weighted MR-images to calculate the free-water content as an advanced marker of microstructural integrity of the substantia nigra and tested its associations with gait parameters. Results: Patients showed increased duration of stance phase, load response, pre-swing, and double support time, as well as reduced duration of single support and swing time. Gait rhythmic alterations associated positively with the free-water content in the right substantia nigra in PD, indicating that patients with more severe neurodegeneration extend the duration of stance phase, load response, and pre-swing. Conclusion: The results provide evidence that gait alterations are not merely a byproduct of bradykinesia-related reduced walking speed. The data-supported association between free-water and the rhythmic component highlights the potential of substantia nigra microstructure imaging as a measure of gait-dysfunction and disease-progression. [ABSTRACT FROM AUTHOR]

Background and purpose: The aim of this study was to investigate the relevance of compartmentalized grey matter (GM) pathology and network reorganization in multiple sclerosis (MS) patients with concomitant epilepsy. Methods: From 3‐T magnetic resonance imaging scans of 30 MS patients with epilepsy (MSE group; age 41 ± 15 years, 21 females, disease duration 8 ± 6 years, median Expanded Disability Status Scale [EDSS] score 3), 60 MS patients without epilepsy (MS group; age 41 ± 12 years, 35 females, disease duration 6 ± 4 years, EDSS score 2), and 60 healthy subjects (HS group; age 40 ± 13 years, 27 females) the regional volumes of GM lesions and of cortical, subcortical and hippocampal structures were quantified. Network topology and vulnerability were modelled within the graph theoretical framework. Receiver‐operating characteristic (ROC) curve analysis was applied to assess the accuracy of GM pathology measures to discriminate between MSE and MS patients. Results: Higher lesion volumes within the hippocampus, mesiotemporal cortex and amygdala were detected in the MSE compared to the MS group (all p < 0.05). The MSE group had lower cortical volumes mainly in temporal and parietal areas compared to the MS and HS groups (all p < 0.05). Lower hippocampal tail and presubiculum volumes were identified in both the MSE and MS groups compared to the HS group (all p < 0.05). Network topology in the MSE group was characterized by higher transitivity and assortativity, and higher vulnerability compared to the MS and HS groups (all p < 0.05). Hippocampal lesion volume yielded the highest accuracy (area under the ROC curve 0.80 [0.67–0.91]) in discriminating between MSE and MS patients. Conclusions: High lesion load, altered integrity of mesiotemporal GM structures, and network reorganization are associated with a greater propensity for epilepsy occurrence in people with MS. [ABSTRACT FROM AUTHOR]

Introduction: Deep brain stimulation of the subthalamic nucleus (STN-DBS) is an established therapy for Parkinson's disease (PD). However, a more detailed characterization of the targeted network and its grey matter (GM) terminals that drive the clinical outcome is needed. In this direction, the use of MRI after DBS surgery is now possible due to recent advances in hardware, opening a window for the clarification of the association between the affected tissue, including white matter fiber pathways and modulated GM regions, and the DBS-related clinical outcome. Therefore, we present a computational framework for reconstruction of targeted networks on postoperative MRI. Methods: We used a combination of preoperative whole-brain T1-weighted (T1w) and diffusion-weighted MRI data for morphometric integrity assessment and postoperative T1w MRI for electrode reconstruction and network reconstruction in 15 idiopathic PD patients. Within this framework, we made use of DBS lead artifact intensity profiles on postoperative MRI to determine DBS locations used as seeds for probabilistic tractography to cortical and subcortical targets within the motor circuitry. Lastly, we evaluated the relationship between brain microstructural characteristics of DBS-targeted brain network terminals and postoperative clinical outcomes. Results: The proposed framework showed robust performance for identifying the DBS electrode positions. Connectivity profiles between the primary motor cortex (M1), supplementary motor area (SMA), and DBS locations were strongly associated with the stimulation intensity needed for the optimal clinical outcome. Local diffusion properties of the modulated pathways were related to DBS outcomes. STN-DBS motor symptom improvement was highly associated with cortical thickness in the middle frontal and superior frontal cortices, but not with subcortical volumetry. Conclusion: These data suggest that STN-DBS outcomes largely rely on the modulatory interference from cortical areas, particularly M1 and SMA, to DBS locations. [ABSTRACT FROM AUTHOR]

Background: Movement execution is impaired in patients with Parkinson's disease. Evolving neurodegeneration leads to altered connectivity between distinct regions of the brain and altered activity at interconnected areas. How connectivity alterations influence complex movements like drawing spirals in Parkinson's disease patients remains largely unexplored. Objective: We investigated whether deteriorations in interregional connectivity relate to impaired execution of drawing. Methods: Twenty-nine patients and 31 age-matched healthy control participants drew spirals with both hands on a digital graphics tablet, and the regularity of drawing execution was evaluated by sample entropy. We recorded resting-state fMRI and task-related EEG, and calculated the time-resolved partial directed coherence to estimate effective connectivity for both imaging modalities to determine the extent and directionality of interregional interactions. Results: Movement performance in Parkinson's disease patients was characterized by increased sample entropy, corresponding to enhanced irregularities in task execution. Effective connectivity between the motor cortices of both hemispheres, derived from resting-state fMRI, was significantly reduced in Parkinson's disease patients in comparison to controls. The connectivity strength in the nondominant to dominant hemisphere direction in both modalities was inversely correlated with irregularities during drawing, but not with the clinical state. Conclusion: Our findings suggest that interhemispheric connections are affected both at rest and during drawing movements by Parkinson's disease. This provides novel evidence that disruptions of interhemispheric information exchange play a pivotal role for impairments of complex movement execution in Parkinson's disease patients. [ABSTRACT FROM AUTHOR]

Background: Deep brain stimulation (DBS) is an effective evidence-based therapy for dystonia. However, no unequivocal predictors of therapy responses exist. We investigated whether patients optimally responding to DBS present distinct brain network organization and structural patterns.Methods: From a German multicenter cohort of 82 dystonia patients with segmental and generalized dystonia who received DBS implantation in the globus pallidus internus, we classified patients based on the clinical response 3 years after DBS. Patients were assigned to the superior-outcome group or moderate-outcome group, depending on whether they had above or below 70% motor improvement, respectively. Fifty-one patients met MRI-quality and treatment response requirements (mean age, 51.3 ± 13.2 years; 25 female) and were included in further analysis. From preoperative MRI we assessed cortical thickness and structural covariance, which were then fed into network analysis using graph theory. We designed a support vector machine to classify subjects for the clinical response based on individual gray-matter fingerprints.Results: The moderate-outcome group showed cortical atrophy mainly in the sensorimotor and visuomotor areas and disturbed network topology in these regions. The structural integrity of the cortical mantle explained about 45% of the DBS stimulation amplitude for optimal response in individual subjects. Classification analyses achieved up to 88% of accuracy using individual gray-matter atrophy patterns to predict DBS outcomes.Conclusions: The analysis of cortical integrity, informed by group-level network properties, could be developed into independent predictors to identify dystonia patients who benefit from DBS. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

Neuroinflammation is a pathophysiological hallmark of multiple sclerosis and has a close mechanistic link to neurodegeneration. Although this link is potentially targetable, robust translatable models to reliably quantify and track neuroinflammation in both mice and humans are lacking. The choroid plexus (ChP) plays a pivotal role in regulating the trafficking of immune cells from the brain parenchyma into the cerebrospinal fluid (CSF) and has recently attracted attention as a key structure in the initiation of inflammatory brain responses. In a translational framework, we here address the integrity and multidimensional characteristics of the ChP under inflammatory conditions and question whether ChP volumes could act as an interspecies marker of neuroinflammation that closely interrelates with functional impairment. Therefore, we explore ChP characteristics in neuroinflammation in patients with multiple sclerosis and in two experimental mouse models, cuprizone diet-related demyelination and experimental autoimmune encephalomyelitis. We demonstrate that ChP enlargement--reconstructed from MRI--is highly associated with acute disease activity, both in the studied mouse models and in humans. A close dependency of ChP integrity and molecular signatures of neuroinflammation is shown in the performed transcriptomic analyses. Moreover, pharmacological modulation of the blood-CSF barrier with natalizumab prevents an increase of the ChP volume. ChP enlargement is strongly linked to emerging functional impairment as depicted in the mouse models and in multiple sclerosis patients. Our findings identify ChP characteristics as robust and translatable hallmarks of acute and ongoing neuroinflammatory activity in mice and humans that could serve as a promising interspecies marker for translational and reverse-translational approaches. [ABSTRACT FROM AUTHOR]

Objective: The objective of this study was to determine the ability of 7T‐MRI for characterizing brain tissue integrity in early relapsing‐remitting MS patients compared to conventional 3T‐MRI and to investigate whether 7T‐MRI improves the performance for detecting cortical gray matter neurodegeneration and its associated network reorganization dynamics. Methods: Seven early relapsing‐remitting MS patients and seven healthy individuals received MRI at 7T and 3T, whereas 30 and 40 healthy controls underwent separate 3T‐ and 7T‐MRI sessions, respectively. Surface‐based cortical thickness (CT) and gray‐to‐white contrast (GWc) measures were used to model morphometric networks, analyzed with graph theory by means of modularity, clustering coefficient, path length, and small‐worldness. Results: 7T‐MRI had lower CT and higher GWc compared to 3T‐MRI in MS. CT and GWc measures robustly differentiated MS from controls at 3T‐MRI. 7T‐ and 3T‐MRI showed high regional correspondence for CT (r = 0.72, P = 2e‐78) and GWc (r = 0.83, P = 5.5e‐121) in MS patients. MS CT and GWc morphometric networks at 7T‐MRI showed higher modularity, clustering coefficient, and small‐worldness than 3T, also compared to controls. Interpretation: 7T‐MRI allows to more precisely quantify morphometric alterations across the cortical mantle and captures more sensitively MS‐related network reorganization. Our findings open new avenues to design more accurate studies quantifying brain tissue loss and test treatment effects on tissue repair. [ABSTRACT FROM AUTHOR]

Growing evidence suggests that decreased functional connectivity in cortical networks precedes clinical stages of Alzheimer's disease (AD), although our knowledge about cerebral and biological correlates of this phenomenon is limited. To shed light on this issue, we have investigated whether resting-state oscillatory connectivity patterns in healthy older (HO) and amnestic mild cognitive impairment (aMCI) subjects are related to anatomical grey matter (GM) and functional (2-[18F]fluoro-2-deoxy- d-glucose (FDG)-PET) changes of neuroelectric sources of alpha rhythms, and/or to changes in plasma amyloid-beta (Aβ) and serum lipid levels, blood markers tied to AD pathogenesis and aging-related cognitive decline. We found that aMCI subjects showed decreased levels of cortical connectivity, reduced FDG-PET intake of the precuneus, and GM atrophy of the thalamus, together with higher levels of Aβ and apolipoprotein B (ApoB) compared to HO. Interestingly, levels of high-density lipoprotein (HDL) cholesterol were positively correlated with the strength of neural-phase coupling in aMCI subjects, and increased triglycerides accompanied bilateral GM loss in the precuneus of aMCI subjects. Together, these findings provide peripheral blood correlates of reduced resting-state cortical connectivity in aMCI, supported by anatomo-functional changes in cerebral sources of alpha rhythms. This framework constitutes an integrated approach to assess functional changes in cortical networks through neuroimaging and peripheral blood markers during early stages of neurodegeneration. [ABSTRACT FROM AUTHOR]

Adapting actions to changing goals and environments is central to intelligent behavior. There is evidence that the basal ganglia play a crucial role in reinforcing or adapting actions depending on their outcome. However, the corresponding electrophysiological correlates in the basal ganglia and the extent to which these causally contribute to action adaptation in humans is unclear. Here, we recorded electrophysiological activity and applied bursts of electrical stimulation to the subthalamic nucleus, a core area of the basal ganglia, in 16 patients with Parkinson's disease (PD) on medication using temporarily externalized deep brain stimulation (DBS) electrodes. Patients as well as 16 age- and gender-matched healthy participants attempted to produce forces as close as possible to a target force to collect a maximum number of points. The target force changed over trials without being explicitly shown on the screen so that participants had to infer target force based on the feedback they received after each movement. Patients and healthy participants were able to adapt their force according to the feedback they received (P < 0.001). At the neural level, decreases in subthalamic beta (13 to 30 Hz) activity reflected poorer outcomes and stronger action adaptation in 2 distinct time windows (Pcluster-corrected < 0.05). Stimulation of the subthalamic nucleus reduced beta activity and led to stronger action adaptation if applied within the time windows when subthalamic activity reflected action outcomes and adaptation (Pcluster-corrected < 0.05). The more the stimulation volume was connected to motor cortex, the stronger was this behavioral effect (Pcorrected = 0.037). These results suggest that dynamic modulation of the subthalamic nucleus and interconnected cortical areas facilitates adaptive behavior. This study shows that activity in the subthalamic nucleus reflects action outcomes and consequent adaptation in humans. This can be modified through bursts of electrical stimulation, with the potential to restore healthy brain function in people with neurological disorders like Parkinson's disease. [ABSTRACT FROM AUTHOR]

Our current knowledge about the anatomical substrate of impaired resting-state cortical oscillatory coupling in mild cognitive impairment is still rudimentary. Here, we show that both resting-state oscillatory coupling and its anatomical correlates clearly distinguish healthy older (HO) adults from individuals with amnestic mild cognitive impairment (aMCI). aMCI showed failures in neural-phase coupling of resting-state electroencephalographic alpha activity mostly evident between fronto-temporal and parietal regions. As oligomers of amyloid-beta (Aβ) are linked to synaptic dysfunction in Alzheimer's disease (AD), we further investigated whether plasma concentrations of these oligomers (Aβ and Aβ) accounted for impaired patterns of oscillatory coupling in aMCI. Results revealed that decreased plasma Aβ was associated with augmented coupling of parieto-temporal regions in HO subjects, but no relationship was found in aMCI. Oscillatory coupling of frontal regions was also significantly reduced in aMCI carriers of the ε4 allele of the Apolipoprotein E (ApoE) compared to ε4 noncarriers, although neither neuroanatomical nor plasma Aβ changes accounted for this difference. However, the abnormal pattern of oscillatory coupling in aMCI was negatively related to volume of the angular gyrus, and positively related to volume of the precuneus and the splenium of the corpus callosum. Previous evidence suggests that all these regions are neuropathological targets of AD. The current study takes that scenario one step further, suggesting that this anatomical damage could be responsible for disrupted cortical oscillatory coupling in aMCI. Together, these data shed light on how the MCI status modifies anatomo-functional relationships underlying coordination of large-scale cortical systems in the resting-state. [ABSTRACT FROM AUTHOR]

7 Tesla MRI will soon be helpful to guide clinical practice in multiple sclerosis centres - No Magnetic resonance imaging (MRI) has gained an essential role in state-of-the-art research and clinical practice for neuroimmunological conditions and especially multiple sclerosis (MS) by providing important information on focal inflammation with demyelination and structural alterations with atrophy and neurodegeneration. In light of the present discussion, from a technical and economic point, it is very likely that UHF MRI will not become part of the clinical practice and multicenter clinical studies examining patients with MS in the very near future. [Extracted from the article]

Abstract: Little attention has been paid to cortical integrity in patients with minimal hepatic encephalopathy (MHE), although cognitive functions affected in early stages of liver disease are mainly allocated in different neocortical structures. Here we used cortical surface-based analysis techniques to investigate if patterns of cortical thinning accompany the mildest form of HE. To aim this goal, cortical thickness obtained from high-resolution 3T magnetic resonance imaging (MRI) was measured in patients with no MHE (NMHE), MHE, and healthy controls. Further correlation analyses were performed to examine whether scores in the critical flicker frequency (CFF) test, and blood ammonia levels accounted for the loss of cortical integrity in different stages of liver disease. Finally, we assessed group differences in volume of different subcortical regions and their potential relationships with CFF scores/blood ammonia levels. Results showed a focal thinning of the superior temporal cortex and precuneus in MHE patients when compared with NMHE and controls. Relationships between blood ammonia levels and cortical thickness of the calcarine sulcus accounted for impaired visual judgment in patients with MHE when compared to NMHE. Regression analyses between cortical thickness and CFF predicted differences between controls and the two groups of HE patients, but failed to discriminate between patients with NMHE and MHE. Taking together, these findings provide the first report of cortical thinning in MHE patients, and they yield novel insights into the neurobiological basis of cognitive impairment associated with early stages of liver diseases. [Copyright &y& Elsevier]

Background: Anxiety, often seen as comorbidity in multiple sclerosis (MS), is a frequent neuropsychiatric symptom and essentially affects the overall disease burden. Here, we aimed to decipher anxiety-related networks functionally connected to atrophied areas in patients suffering from MS.Methods: Using 3-T MRI, anxiety-related atrophy maps were generated by correlating longitudinal cortical thinning with the severity of anxiety symptoms in MS patients. To determine brain regions functionally connected to these maps, we applied a technique termed "atrophy network mapping". Thereby, the anxiety-related atrophy maps were projected onto a large normative connectome (n = 1000) performing seed-based functional connectivity. Finally, an instructed threat paradigm was conducted with regard to neural excitability and effective connectivity, using transcranial magnetic stimulation combined with high-density electroencephalography.Results: Thinning of the left dorsal prefrontal cortex was the only region that was associated with higher anxiety levels. Atrophy network mapping identified functional involvement of bilateral prefrontal cortex as well as amygdala and hippocampus. Structural equation modeling confirmed that the volumes of these brain regions were significant determinants that influence anxiety symptoms in MS. We additionally identified reduced information flow between the prefrontal cortex and the amygdala at rest, and pathologically increased excitability in the prefrontal cortex in MS patients as compared to controls.Conclusion: Anxiety-related prefrontal cortical atrophy in MS leads to a specific network alteration involving structures that resemble known neurobiological anxiety circuits. These findings elucidate the emergence of anxiety as part of the disease pathology and might ultimately enable targeted treatment approaches modulating brain networks in MS. [ABSTRACT FROM AUTHOR]

Deep brain stimulation (DBS) has developed over the last twenty years into a highly effective evidenced-based treatment option for neuropsychiatric disorders. Moreover, it has become a fascinating tool to provide illustrative insights into the functioning of brain networks. New anatomical and pathophysiological models of DBS action have accelerated our understanding of neurological and psychiatric disorders and brain functioning. The description of the brain networks arose through the unique ability to illustrate long-range interactions between interconnected brain regions as derived from state-of-the-art neuroimaging (structural, diffusion, and functional MRI) and the opportunity to record local and large-scale brain activity at millisecond temporal resolution (microelectrode recordings, local field potential, electroencephalography, and magnetoencephalography). In the first part of this review, we describe how neuroimaging techniques have led to current understanding of DBS effects, by identifying and refining the DBS targets and illustrate the actual view on the relationships between electrode locations and clinical effects. One step further, we discuss how neuroimaging has shifted the view of localized DBS effects to a modulation of specific brain circuits, which has been possible from the combination of electrode location reconstructions with recently introduced network imaging methods. We highlight how these findings relate to clinical effects, thus postulating neuroimaging as a key factor to understand the mechanisms of DBS action on behavior and clinical effects. In the second part, we show how invasive electrophysiology techniques have been efficiently integrated into the DBS set-up to precisely localize the neuroanatomical targets of DBS based on distinct region-specific patterns of neural activity. Next, we show how multi-site electrophysiological recordings have granted a real-time window into the aberrant brain circuits within and beyond DBS targets to quantify and map the dynamic properties of rhythmic oscillations. We also discuss how DBS alters the transient synchrony states of oscillatory networks in temporal and spatial domains during resting, task-based and motion conditions, and how this modulation of brain states ultimately shapes the functional response. Finally, we show how a successful decoding and management of electrophysiological proxies (beta bursts, phase-amplitude coupling) of aberrant brain circuits was translated into adaptive DBS stimulation paradigms for a targeted and state-dependent invasive electrical neuromodulation. • Neuroimaging and neurophysiology drive the conceptual understanding and further development of deep brain stimulation. • Invasive neuromodulation necessitates an a priori detailed characterisation of targeted networks. • Targeted neuromodulation advance brain imaging studies for probing causal interregional interactions and brain states shifts. [ABSTRACT FROM AUTHOR]

Objective: Fatigue is a frequent and severe symptom in multiple sclerosis (MS), but its pathophysiological origin remains incompletely understood. We aimed to examine the predictive value of subcortical gray matter volumes for fatigue severity at disease onset and after 4 years by applying structural equation modeling (SEM). Methods: This multicenter cohort study included 601 treatment‐naive patients with MS after the first demyelinating event. All patients underwent a standardized 3T magnetic resonance imaging (MRI) protocol. A subgroup of 230 patients with available clinical follow‐up data after 4 years was also analyzed. Associations of subcortical volumes (included into SEM) with MS‐related fatigue were studied regarding their predictive value. In addition, subcortical regions that have a central role in the brain network (hubs) were determined through structural covariance network (SCN) analysis. Results: Predictive causal modeling identified volumes of the caudate (s [standardized path coefficient] = 0.763, p = 0.003 [left]; s = 0.755, p = 0.006 [right]), putamen (s = 0.614, p = 0.002 [left]; s = 0.606, p = 0.003 [right]) and pallidum (s = 0.606, p = 0.012 [left]; s = 0.606, p = 0.012 [right]) as prognostic factors for fatigue severity in the cross‐sectional cohort. Moreover, the volume of the pons was additionally predictive for fatigue severity in the longitudinal cohort (s = 0.605, p = 0.013). In the SCN analysis, network hubs in patients with fatigue worsening were detected in the putamen (p = 0.008 [left]; p = 0.007 [right]) and pons (p = 0.0001). Interpretation: We unveiled predictive associations of specific subcortical gray matter volumes with fatigue in an early and initially untreated MS cohort. The colocalization of these subcortical structures with network hubs suggests an early role of these brain regions in terms of fatigue evolution. ANN NEUROL 2022;91:192–202 [ABSTRACT FROM AUTHOR]

Threat detection is essential for protecting individuals from adverse situations, in which a network of amygdala, limbic regions and dorsomedial prefrontal cortex (dmPFC) regions are involved in fear processing. Excitability regulation in the dmPFC might be crucial for fear processing, while abnormal patterns could lead to mental illness. Notwithstanding, non-invasive paradigms to measure excitability regulation during fear processing in humans are missing. To address this challenge we adapted an approach for excitability characterization, combining electroencephalography (EEG) and transcranial magnetic stimulation (TMS) over the dmPFC during an instructed fear paradigm, to dynamically dissect its role in fear processing. Event-related (ERP) and TMS-evoked potentials (TEP) were analyzed to trace dmPFC excitability. We further linked the excitability regulation patterns to individual MRI-derived gray matter structural integrity of the fear network. Increased cortical excitability was demonstrated to threat (T) processing in comparison to no-threat (NT), reflected by increased amplitude of evoked potentials. Furthermore, TMS at dmPFC enhanced the evoked responses during T processing, while the structural integrity of the dmPFC and amygdala predicted the excitability regulation patterns to fear processing. The dmPFC takes a special role during fear processing by dynamically regulating excitability. The applied paradigm can be used to non-invasively track response abnormalities to threat stimuli in healthy subjects or patients with mental disorders. [ABSTRACT FROM AUTHOR]

Background and Objective: Status epilepticus in poststroke epilepsy is a challenging condition because of multiple vascular comorbidities and the advanced age of patients. Data on third-generation antiseizure medication (ASM) in this condition are limited. The aim of this study was to evaluate the efficacy of third-generation ASMs in the second- or third-line therapy of benzodiazepine-refractory status epilepticus in poststroke epilepsy following acute ischemic stroke. Methods: Data on the effectiveness of third-generation ASMs in patients with status epilepticus in poststroke epilepsy were gathered from two German Stroke Registries and the Mainz Epilepsy Registry. We included only cases with epilepsy remote to the ischemic event. No patients with acute symptomatic seizures were included. The following third-generation ASMs were included: brivaracetam, lacosamide, eslicarbazepine, perampanel, topiramate, and zonisamide. The assessment of effectiveness was based on seizure freedom within 48 h since the start of therapy with the respective ASM. Seizure freedom was evaluated both clinically (clinical evaluation at least three times per day) and by daily electroencephalogram records. Results: Of the 138 patients aged 70.8 ± 8.1 years with benzodiazepine-refractory status epilepticus in ischemic poststroke epilepsy, 33 (23.9%) were treated with lacosamide, 24 (17.4%) with brivaracetam, 23 (16.7%) with eslicarbazepine, 21 (15.2%) with perampanel, 20 (14.5%) with topiramate, and 17 (12.3%) with zonisamide. Seizure freedom within 48 h was achieved in 66.7% of patients with lacosamide, 65.2% with eslicarbazepine, 38.1% with perampanel, 37.5% with brivaracetam, 35.0% with topiramate, and 35.3% with zonisamide (p < 0.05 for comparison of lacosamide or eslicarbazepine to other ASMs). Conclusions: Based on these data, lacosamide and eslicarbazepine might be more favorable in the treatment of refractory status epilepticus in poststroke epilepsy, when administered as second- or third-line ASMs before anesthesia. Because of the fact that these ASMs share the same mechanism of action (slow inactivation of sodium channels), our findings could motivate further research on the role that this pharmaceutical mechanism of action has in the treatment of poststroke epilepsy. Clinical Trial Registration: This study was registered at ClinicalTrials.gov (NCT05267405). [ABSTRACT FROM AUTHOR]

Amyloid deposition and neurofibrillary degeneration in Alzheimer's disease specifically affect discrete neuronal systems, but the underlying mechanisms that render some brain regions more vulnerable to Alzheimer's disease pathology than others remain largely unknown. Here we studied molecular properties underlying these distinct regional vulnerabilities by analysing Alzheimer's disease-typical neuroimaging patterns of amyloid deposition and neurodegeneration in relation to regional gene expression profiles of the human brain. Graded patterns of brain-wide vulnerability to amyloid deposition and neurodegeneration in Alzheimer's disease were estimated by contrasting multimodal amyloid-sensitive PET and structural MRI data between patients with Alzheimer's disease dementia (n = 76) and healthy controls (n = 126) enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Regional gene expression profiles were derived from brain-wide microarray measurements provided by the Allen brain atlas of the adult human brain transcriptome. In a hypothesis-driven analysis focusing on the genes coding for the amyloid precursor (APP) and tau proteins (MAPT), regional expression levels of APP were positively correlated with the severity of regional amyloid deposition (r = 0.44, P = 0.009), but not neurodegeneration (r = 0.01, P = 0.96), whereas the opposite pattern was observed for MAPT (neurodegeneration: r = 0.46, P = 0.006; amyloid: r = 0.08, P = 0.65). Using explorative gene set enrichment analysis, amyloid-vulnerable regions were found to be characterized by relatively low expression levels of gene sets implicated in protein synthesis and mitochondrial respiration. By contrast, neurodegeneration-vulnerable regions were characterized by relatively high expression levels of gene sets broadly implicated in neural plasticity, with biological functions ranging from neurite outgrowth and synaptic contact over intracellular signalling cascades to proteoglycan metabolism. At the individual gene level this data-driven analysis further corroborated the association between neurodegeneration and MAPT expression, and additionally identified associations with known tau kinases (CDK5, MAPK1/ERK2) alongside components of their intracellular (Ras-ERK) activation pathways. Sensitivity analyses showed that these pathology-specific imaging-genetic associations were largely robust against changes in some of the methodological parameters, including variation in the brain donor sample used for estimating regional gene expression profiles, and local variations in the Alzheimer's disease-typical imaging patterns when these were derived from an independent patient cohort (BioFINDER study). These findings highlight that the regionally selective vulnerability to Alzheimer's disease pathology relates to specific molecular-functional properties of the affected neural systems, and that the implicated biochemical pathways largely differ for amyloid accumulation versus neurodegeneration. The data provide novel insights into the complex pathophysiological mechanisms of Alzheimer's disease and point to pathology-specific treatment targets that warrant further exploration in independent studies. [ABSTRACT FROM AUTHOR]

Purpose: To predict the occurrence of a second clinical event in patients with a CIS suggestive of MS, from baseline magnetic resonance imaging (MRI), by means of a pattern recognition approach. Methods: Two hundred sixty-six patients with a CIS were recruited from four participating centers. Over a follow-up of 3 years, 130 patients had a second clinical episode and 136 did not. Grey matter and white matter T1-hypointensities masks segmented from 3D T1-weighted images acquired on 3 T scanners were used as features for the classification approach. Differences between CIS that remained CIS and those that developed a second event were assessed at a global level and at a regional level, arranging the regions according to their contribution to the classification model. Results: All classification metrics were around or even below 50% for both global and regional approaches. Accuracies did not change when T1-hypointensity maps were added to the model; just the specificity was increased up to 80%. Among the 30 regions with the largest contribution, 26 were grey matter and 4 were white matter regions. For grey matter, regions contributing showed either a larger or a smaller volume in the group of patients that remained CIS, compared to those with a second event. The volume of T1-hypointensities was always larger for the group that presented a second event. Conclusions: Prediction of a second clinical event in CIS patients from baseline MRI seems to present a highly heterogeneous pattern, leading to very low classification accuracies. Adding the T1-hypointensity maps does not seem to improve the accuracy of the classification model. [ABSTRACT FROM AUTHOR]

Background: Research in rodents identified specific neuron populations encoding information for spatial navigation with particularly high density in the medial part of the entorhinal cortex (ERC), which may be homologous with Brodmann area 34 (BA34) in the human brain.Objective: The aim of this study was to test whether impaired spatial navigation frequently occurring in mild cognitive impairment (MCI) is specifically associated with neurodegeneration in BA34.Methods: The study included baseline data of MCI patients enrolled in the Alzheimer's Disease Neuroimaging Initiative with high-resolution structural MRI, brain FDG PET, and complete visuospatial ability scores of the Everyday Cognition test (VS-ECog) within 30 days of PET. A standard mask of BA34 predefined in MNI space was mapped to individual native space to determine grey matter volume and metabolic activity in BA34 on MRI and on (partial volume corrected) FDG PET, respectively. The association of the VS-ECog sum score with grey matter volume and metabolic activity in BA34, APOE4 carrier status, age, education, and global cognition (ADAS-cog-13 score) was tested by linear regression. BA28, which constitutes the lateral part of the ERC, was used as control region.Results: The eligibility criteria led to inclusion of 379 MCI subjects. The VS-ECog sum score was negatively correlated with grey matter volume in BA34 (β= -0.229, p = 0.022) and age (β= -0.124, p = 0.036), and was positively correlated with ADAS-cog-13 (β= 0.175, p = 0.003). None of the other predictor variables contributed significantly.Conclusion: Impairment of spatial navigation in MCI is weakly associated with BA34 atrophy. [ABSTRACT FROM AUTHOR]

Background: Multiple sclerosis (MS) is an autoimmune disease of the central nervous system (CNS), characterized by inflammatory and neurodegenerative processes. Despite demyelination being a hallmark of the disease, how it relates to neurodegeneration has still not been completely unraveled, and research is still ongoing into how these processes can be tracked non-invasively. Magnetic resonance imaging (MRI) derived brain network characteristics, which closely mirror disease processes and relate to functional impairment, recently became important variables for characterizing immune-mediated neurodegeneration; however, their histopathological basis remains unclear.Methods: In order to determine the MRI-derived correlates of myelin dynamics and to test if brain network characteristics derived from diffusion tensor imaging reflect microstructural tissue reorganization, we took advantage of the cuprizone model of general demyelination in mice and performed longitudinal histological and imaging analyses with behavioral tests. By introducing cuprizone into the diet, we induced targeted and consistent demyelination of oligodendrocytes, over a period of 5 weeks. Subsequent myelin synthesis was enabled by reintroduction of normal food.Results: Using specific immune-histological markers, we demonstrated that 2 weeks of cuprizone diet induced a 52% reduction of myelin content in the corpus callosum (CC) and a 35% reduction in the neocortex. An extended cuprizone diet increased myelin loss in the CC, while remyelination commenced in the neocortex. These histologically determined dynamics were reflected by MRI measurements from diffusion tensor imaging. Demyelination was associated with decreased fractional anisotropy (FA) values and increased modularity and clustering at the network level. MRI-derived modularization of the brain network and FA reduction in key anatomical regions, including the hippocampus, thalamus, and analyzed cortical areas, were closely related to impaired memory function and anxiety-like behavior.Conclusion: Network-specific remyelination, shown by histology and MRI metrics, determined amelioration of functional performance and neuropsychiatric symptoms. Taken together, we illustrate the histological basis for the MRI-driven network responses to demyelination, where increased modularity leads to evolving damage and abnormal behavior in MS. Quantitative information about in vivo myelination processes is mirrored by diffusion-based imaging of microstructural integrity and network characteristics. [ABSTRACT FROM AUTHOR]

Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease leading to gray matter atrophy and brain network reconfiguration as a response to increasing tissue damage. We evaluated whether white matter network reconfiguration appears subsequently to gray matter damage, or whether the gray matter degenerates following alterations in white matter networks. MRI data from 83 patients with clinically isolated syndrome and early relapsing–remitting MS were acquired at two time points with a follow‐up after 1 year. White matter network integrity was assessed based on probabilistic tractography performed on diffusion‐weighted data using graph theoretical analyses. We evaluated gray matter integrity by computing cortical thickness and deep gray matter volume in 94 regions at both time points. The thickness of middle temporal cortex and the volume of deep gray matter regions including thalamus, caudate, putamen, and brain stem showed significant atrophy between baseline and follow‐up. White matter network dynamics, as defined by modularity and distance measure changes over time, were predicted by deep gray matter volume of the atrophying anatomical structures. Initial white matter network properties, on the other hand, did not predict atrophy. Furthermore, gray matter integrity at baseline significantly predicted physical disability at 1‐year follow‐up. In a sub‐analysis, deep gray matter volume was significantly related to cognitive performance at baseline. Hence, we postulate that atrophy of deep gray matter structures drives the adaptation of white matter networks. Moreover, deep gray matter volumes are highly predictive for disability progression and cognitive performance. [ABSTRACT FROM AUTHOR]

Dopamine dysfunction is associated with a wide range of neuropsychiatric disorders commonly treated pharmacologically or invasively. Recent studies provide evidence for a nonpharmacological and noninvasive alternative that allows similar manipulation of the dopaminergic system: transcranial direct current stimulation (tDCS). In rodents, tDCS has been shown to increase neural activity in subcortical parts of the dopaminergic system, and recent studies in humans provide evidence that tDCS over prefrontal regions induces striatal dopamine release and affects reward-related behavior. Based on these findings, we used fMRI in healthy human participants and measured the fractional amplitude of low-frequency fluctuations to assess spontaneous neural activity strength in regions of the mesostriatal dopamine system before and after tDCS over prefrontal regions (n = 40,22 females). In a second study, we examined the effect of a single dose of the dopamine precursor levodopa (l-DOPA) on mesostriatal fractional amplitude of low-frequency fluctuation values in male humans (n = 22) and compared the results between both studies. We found that prefrontal tDCS and l-DOPA both enhance neural activity in core regions of the dopaminergic system and show similar subcortical activation patterns. We furthermore assessed the spatial similarity of whole-brain statistical parametric maps, indicating tDCS- and L-DOPA-induced activation, and >100 neuronal receptor gene expression maps based on transcriptional data from the Allen Institute for Brain Science. In line with a specific activation of the dopaminergic system, we found that both interventions predominantly activated regions with high expression levels of the dopamine receptors D2 and D3. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Network science in combination with graph theory is becoming an important approach to model tissue organization in MS. • Connectivity disruption and loss of network efficiency have led to the notion of MS as a so-called disconnection syndrome. • Early adaptive network response might represent an important hallmark of the disease to counteract chronic damage. • Functional and structural network properties could become biomarkers for monitoring the disease course. Abstract Network science provides powerful access to essential organizational principles of the human brain. It has been applied in combination with graph theory to characterize brain connectivity patterns. In multiple sclerosis (MS), analysis of the brain networks derived from either structural or functional imaging provides new insights into pathological processes within the gray and white matter. Beyond focal lesions and diffuse tissue damage, network connectivity patterns could be important for closely tracking and predicting the disease course. In this review, we describe concepts of graph theory, highlight novel issues of tissue reorganization in acute and chronic neuroinflammation and address pitfalls with regard to network analysis in MS patients. We further provide an outline of functional and structural connectivity patterns observed in MS, spanning from disconnection and disruption on one hand to adaptation and compensation on the other. Moreover, we link network changes and their relation to clinical disability based on the current literature. Finally, we discuss the perspective of network science in MS for future research and postulate its role in the clinical framework. [ABSTRACT FROM AUTHOR]

Background: Currently, no unequivocal predictors of disease evolution exist in patients with multiple sclerosis (MS). Cortical atrophy measurements are, however, closely associated with cumulative disability. Objective: Here, we aim to forecast longitudinal magnetic resonance imaging (MRI)-driven cortical atrophy and clinical disability from cerebrospinal fluid (CSF) markers. Methods: We analyzed CSF fractions of albumin and immunoglobulins (Ig) A, G, and M and their CSF to serum quotients. Results: Widespread atrophy was highly associated with increased baseline CSF concentrations and quotients of albumin and IgA. Patients with increased CSFIgA and CSFIgM showed higher functional disability at follow-up. Conclusion: CSF markers of blood–brain barrier integrity and specific immune response forecast emerging gray matter pathology and disease progression in MS. [ABSTRACT FROM AUTHOR]

Fatemah A. Sakr and Michel J. Grothe contributed equally to this work. B Correction: Alz Res Therapy 11, 15 (2019) b B https://doi.org/10.1186/s13195-019-0466-3 b Following the publication of the original article [[1]] the authors reported that members of "Alzheimer Precision Medicine Initiative (APMI)" are not visible in the collaborator list indexed. [Extracted from the article]

We determined the effect of cortical amyloid load using 18 F-florbetapir PET on cognitive performance and gray matter structural integrity derived from MRI in 318 cognitively normally performing older people with subjective memory impairment from the INSIGHT-preAD cohort using multivariate partial least squares regression. Amyloid uptake was associated with reduced gray matter structural integrity in hippocampus, entorhinal and cingulate cortex, middle temporal gyrus, prefrontal cortex, and lentiform nucleus ( p < 0.01, permutation test). Higher amyloid load was associated with poorer global cognitive performance, delayed recall and attention ( p < 0.05), independently of its effects on gray matter connectivity. These findings agree with the assumption of a two-stage effect of amyloid on cognition, (1) an early direct effect in the preclinical stages of Alzheimer's disease and (2) a delayed effect mediated by downstream effects of amyloid accumulation, such as gray matter connectivity decline. [ABSTRACT FROM AUTHOR]

Juvenile myoclonic epilepsy (JME) is the most common syndrome within the idiopathic generalized epilepsy spectrum, manifested by myoclonic and generalized tonic-clonic seizures and spike-and-wave discharges (SWDs) on electroencephalography (EEG). Currently, the pathophysiological concepts addressing SWD generation in JME are still incomplete. In this work, we characterize the temporal and spatial organization of functional networks and their dynamic properties as derived from high-density EEG (hdEEG) recordings and MRI in 40 JME patients (25.4 ± 7.6 years, 25 females). The adopted approach allows for the construction of a precise dynamic model of ictal transformation in JME at the cortical and deep brain nuclei source levels. We implement Louvain algorithm to attribute brain regions with similar topological properties to modules during separate time windows before and during SWD generation. Afterwards, we quantify how modular assignments evolve and steer through different states towards the ictal state by measuring characteristics of flexibility and controllability. We find antagonistic dynamics of flexibility and controllability within network modules as they evolve towards and undergo ictal transformation. Prior to SWD generation, we observe concomitantly increasing flexibility (F(1,39) = 25.3, corrected p < 0.001) and decreasing controllability (F(1,39) = 55.3, p < 0.001) within the fronto-parietal module in γ- band. On a step further, during interictal SWDs as compared to preceding time windows, we notice decreasing flexibility (F(1,39) = 11.9, p < 0.001) and increasing controllability (F(1,39) = 10.1, p < 0.001) within the fronto-temporal module in γ- band. During ictal SWDs as compared to prior time windows, we demonstrate significantly decreasing flexibility (F(1,14) = 31.6; p < 0.001) and increasing controllability (F(1,14) = 44.7, p < 0.001) within the basal ganglia module. Furthermore, we show that flexibility and controllability within the fronto-temporal module of the interictal SWDs relate to seizure frequency and cognitive performance in JME patients. Our results demonstrate that detection of network modules and quantification of their dynamic properties is relevant to track the generation of SWDs. The observed flexibility and controllability dynamics reflect the reorganization of de−/synchronized connections and the ability of evolving network modules to reach a seizure-free state, respectively. These findings may advance the elaboration of network-based biomarkers and more targeted therapeutic neuromodulatory approaches in JME. • JME patients display distinct and overlapping network communities before and during SWDs. • Flexibility and controllability exhibit antagonistic dynamics before and during SWDs. • Flexibility and controllability dynamics are detectable in γ - and β-bands. • Detection of network communities and their properties is relevant to track SWD generation. [ABSTRACT FROM AUTHOR]

Brain connectivity profiles seeding from deep brain stimulation (DBS) electrodes have emerged as informative tools to estimate outcome variability across DBS patients. Given the limitations of acquiring and processing patient-specific diffusion-weighted imaging data, a number of studies have employed normative atlases of the human connectome. To date, it remains unclear whether patient-specific connectivity information would strengthen the accuracy of such analyses. Here, we compared similarities and differences between patient-specific, disease-matched and normative structural connectivity data and their ability to predict clinical improvement. Data from 33 patients suffering from Parkinson's Disease who underwent surgery at three different centers were retrospectively collected. Stimulation-dependent connectivity profiles seeding from active contacts were estimated using three modalities, namely patient-specific diffusion-MRI data, age- and disease-matched or normative group connectome data (acquired in healthy young subjects). Based on these profiles, models of optimal connectivity were calculated and used to estimate clinical improvement in out of sample data. All three modalities resulted in highly similar optimal connectivity profiles that could largely reproduce findings from prior research based on this present novel multi-center cohort. In a data-driven approach that estimated optimal whole-brain connectivity profiles, out-of-sample predictions of clinical improvements were calculated. Using either patient-specific connectivity (R = 0.43 at p = 0.001), an age- and disease-matched group connectome (R = 0.25, p = 0.048) and a normative connectome based on healthy/young subjects (R = 0.31 at p = 0.028), significant predictions could be made. Our results of patient-specific connectivity and normative connectomes lead to similar main conclusions about which brain areas are associated with clinical improvement. Still, although results were not significantly different, they hint at the fact that patient-specific connectivity may bear the potential of explaining slightly more variance than group connectomes. Furthermore, use of normative connectomes involves datasets with high signal-to-noise acquired on specialized MRI hardware, while clinical datasets as the ones used here may not exactly match their quality. Our findings support the role of DBS electrode connectivity profiles as a promising method to investigate DBS effects and to potentially guide DBS programming. [ABSTRACT FROM AUTHOR]

Background: Current methods of amyloid PET interpretation based on the binary classification of global amyloid signal fail to identify early phases of amyloid deposition. A recent analysis of 18F-florbetapir PET data from the Alzheimer's disease Neuroimaging Initiative cohort suggested a hierarchical four-stage model of regional amyloid deposition that resembles neuropathologic estimates and can be used to stage an individual's amyloid burden in vivo. Here, we evaluated the validity of this in vivo amyloid staging model in an independent cohort of older people with subjective memory complaints (SMC). We further examined its potential association with subtle cognitive impairments in this population at elevated risk for Alzheimer's disease (AD). Methods: The monocentric INSIGHT-preAD cohort includes 318 cognitively intact older individuals with SMC. All individuals underwent 18F-florbetapir PET scanning and extensive neuropsychological testing. We projected the regional amyloid uptake signal into the previously proposed hierarchical staging model of in vivo amyloid progression. We determined the adherence to this model across all cases and tested the association between increasing in vivo amyloid stage and cognitive performance using ANCOVA models. Results: In total, 156 participants (49%) showed evidence of regional amyloid deposition, and all but 2 of these (99%) adhered to the hierarchical regional pattern implied by the in vivo amyloid progression model. According to a conventional binary classification based on global signal (SUVRCereb = 1.10), individuals in stages III and IV were classified as amyloid-positive (except one in stage III), but 99% of individuals in stage I and even 28% of individuals in stage II were classified as amyloid-negative. Neither in vivo amyloid stage nor conventional binary amyloid status was significantly associated with cognitive performance in this preclinical cohort. Conclusions: The proposed hierarchical staging scheme of PET-evidenced amyloid deposition generalizes well to data from an independent cohort of older people at elevated risk for AD. Future studies will determine the prognostic value of the staging approach for predicting longitudinal cognitive decline in older individuals at increased risk for AD. [ABSTRACT FROM AUTHOR]