Diffusion-weighted imaging has been applied to investigate alterations in multiple sclerosis (MS). In the last years, advanced diffusion models were used to identify subtle changes and early lesions ...in MS. Among these models, neurite orientation dispersion and density imaging (NODDI) is an emerging approach, quantifying specific neurite morphology in both grey (GM) and white matter (WM) tissue and increasing the specificity of diffusion imaging. In this systematic review, we summarized the NODDI findings in MS. A search was conducted on PubMed, Scopus, and Embase, which yielded a total number of 24 eligible studies. Compared to healthy tissue, these studies identified consistent alterations in NODDI metrics involving WM (neurite density index), and GM lesions (neurite density index), or normal-appearing WM tissue (isotropic volume fraction and neurite density index). Despite some limitations, we pointed out the potential of NODDI in MS to unravel microstructural alterations. These results might pave the way to a deeper understanding of the pathophysiological mechanism of MS. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 3.
Lesion network mapping (LNM) is a popular framework to assess clinical syndromes following brain injury. The classical approach involves embedding lesions from patients into a normative functional ...connectome and using the corresponding functional maps as proxies for disconnections. However, previous studies indicated limited predictive power of this approach in behavioral deficits. We hypothesized similarly low predictiveness for overall survival (OS) in glioblastoma (GBM).
A retrospective dataset of patients with GBM was included (n = 99). Lesion masks were registered in the normative space to compute disconnectivity maps. The brain functional normative connectome consisted in data from 173 healthy subjects obtained from the Human Connectome Project. A modified version of the LNM was then applied to core regions of GBM masks. Linear regression, classification, and principal component (PCA) analyses were conducted to explore the relationship between disconnectivity and OS. OS was considered both as continuous and categorical (low, intermediate, and high survival) variable.
The results revealed no significant associations between OS and network disconnection strength when analyzed at both voxel-wise and classification levels. Moreover, patients stratified into different OS groups did not exhibit significant differences in network connectivity patterns. The spatial similarity among the first PCA of network maps for each OS group suggested a lack of distinctive network patterns associated with survival duration.
Compared with indirect structural measures, functional indirect mapping does not provide significant predictive power for OS in patients with GBM. These findings are consistent with previous research that demonstrated the limitations of indirect functional measures in predicting clinical outcomes, underscoring the need for more comprehensive methodologies and a deeper understanding of the factors influencing clinical outcomes in this challenging disease.
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•This study challenges the predictive power of network mapping in glioblastoma.•We found a lack of distinctive functional network patterns associated with survival.•The clinical value of indirect brain functional tools needs further investigation.
Recent evidence suggests that, in the absence of any task, spontaneous brain activity patterns and connectivity in the visual and motor cortex code for natural stimuli and actions, respectively. ...These "resting-state" activity patterns may underlie the maintenance and consolidation (replay) of information states coding for ecological stimuli and behaviors. In this study, we examine whether replay patterns occur in resting-state activity in association cortex grouped into high-order cognitive networks not directly processing sensory inputs or motor outputs. Fifteen participants (7 females) performed four hand movements during an fMRI study. Three movements were ecological. The fourth movement as control was less ecological. Before and after the task scans, we acquired resting-state fMRI scans. The analysis examined whether multivertex task activation patterns for the four movements computed at the cortical surface in different brain networks resembled spontaneous activity patterns measured at rest. For each movement, we computed a vector of
values indicating the strength of the similarity between the mean task activation pattern and frame-by-frame resting-state patterns. We computed a cumulative distribution function of
values and used the 90th percentile cutoff value for comparison. In the dorsal attention network, resting-state patterns were more likely to match task patterns for the ecological movements than the control movement. In contrast, rest-task pattern correlation was more likely for less ecological movement in the ventral attention network. These findings show that spontaneous activity patterns in human attention networks code for hand movements.
fMRI indirectly measures neural activity noninvasively. Resting-state (spontaneous) fMRI signals measured in the absence of any task resemble signals evoked by task performance both in topography and inter-regional (functional) connectivity. However, the function of spontaneous brain activity is unknown. We recently showed that spatial activity patterns evoked by visual and motor tasks in visual and motor cortex, respectively, occur at rest in the absence of any stimulus or response. Here we show that activity patterns related to hand movements replay at rest in frontoparietal regions of the human attention system. These findings show that spontaneous activity in the human cortex may mediate the maintenance and consolidation of information states coding for ecological stimuli and behaviors.
High quality of sleep may mitigate the impact of pathophysiological mechanisms in mild cognitive impairment (MCI) through functional connectivity reorganization of neural networks underlying higher ...cognitive functions. Thirty-eight patients with MCI stratified into high and low quality of sleep in accordance with a self-reported questionnaire for sleep habits, and 38 controls underwent resting-state functional magnetic resonance imaging. Independent component analysis was used to reconstruct the default mode network and frontoparietal network (FPN). High quality of sleep was associated with increased FPN connectivity among patients with MCI. Moreover, a positive coupling of connectivity between networks was found in MCI reporting high quality of sleep, congruently with the pattern observed in controls, whereas this coupling was disrupted in MCI with low quality of sleep. An association between FPN connectivity and language scores was observed in MCI. These findings suggest a relationship between sleep quality and FPN connectivity in MCI that may underlie compensatory mechanisms to overcome advancing neurodegeneration.
•Sleep is associated with frontoparietal network in mild cognitive impairment.•Brain network functional coupling and sleep quality are related.•Sleep might underlie compensatory mechanisms through frontoparietal connectivity.
The pathophysiology of migraine as a headache disorder is still undetermined. Diffusion tensor imaging (DTI) has significantly improved our knowledge about brain microstructure in this disease. Here, ...we aimed to systematically review DTI studies in migraine and survey the sources of heterogeneity by investigating diffusion parameter changes associated with clinical characteristics and migraine subtypes. Microstructural changes, as revealed by widespread alteration of diffusion metrics in white matter (WM) tracts, subcortical and cortical regions, were reported by several migraine DTI studies. Specifically, we reported changes in the corpus callosum, thalamic radiations, corona radiata, and brain stem. These alterations showed high variability across migraine cycle phases. Additionally, migraine associated with depressive/anxiety symptoms revealed significant changes in the corpus callosum, internal capsule, and superior longitudinal fasciculus. No significant WM microstructural differences were observed between migraine patients with and without aura. Overall, differences between chronic and episodic migraine showed inconsistency across studies. Migraine is associated with microstructural changes in widespread regions including thalamic radiations, corpus callosum, and brain stem. These alterations can highlight neuronal damage and neuronal plasticity mechanisms either following pain stimulations occurring in migraine cycle or as a compensatory response to pain in chronic migraine. Longitudinal studies applying advanced modalities may shed new light on the underlying microstructural changes in migraine subtypes.
Alzheimer's disease (AD) is characterized by different clinical entities. Although AD phenotypes share a common molecular substrate (i.e., amyloid beta and tau accumulation), several ...clinicopathological differences exist. Brain functional networks might provide a macro-scale scaffolding to explain this heterogeneity. In this review, we summarize the evidence linking different large-scale functional network abnormalities to distinct AD phenotypes. Specifically, executive deficits in early-onset AD link with the dysfunction of networks that support sustained attention and executive functions. Posterior cortical atrophy relates to the breakdown of visual and dorsal attentional circuits, while the primary progressive aphasia variant of AD may be associated with the dysfunction of the left-lateralized language network. Additionally, network abnormalities might provide in vivo signatures for distinguishing proteinopathies that mimic AD, such as TAR DNA binding protein 43 related pathologies. These network differences vis-a-vis clinical syndromes are more evident in the earliest stage of AD. Finally, we discuss how these findings might pave the way for new tailored interventions targeting the most vulnerable brain circuit at the optimal time window to maximize clinical benefits.
•We reviewed brain connectivity in atypical variants of Alzheimer’s disease.•Network-symptom coupling is reported in AD clinical phenotypes.•Network alterations is a candidate biomarker for proteinopathies that mimic AD.•Network connectivity fingerprints may help to guide interventions in AD.
The study of pollutant effects is extremely important to address the epochal challenges we are facing, where world populations are increasingly moving from rural to urban centers, revolutionizing our ...world into an urban world. These transformations will exacerbate pollution, thus highlighting the necessity to unravel its effect on human health. Epidemiological studies have reported that pollution increases the risk of neurological diseases, with growing evidence on the risk of neurodegenerative disorders. Air pollution and water pollutants are the main chemicals driving this risk. These chemicals can promote inflammation, acting in synergy with genotype vulnerability. However, the biological underpinnings of this association are unknown. In this review, we focus on the link between pollution and brain network connectivity at the macro-scale level. We provide an updated overview of epidemiological findings and studies investigating brain network changes associated with pollution exposure, and discuss the mechanistic insights of pollution-induced brain changes through neural networks. We explain, in detail, the pollutome-connectome axis that might provide the functional substrate for pollution-induced processes leading to cognitive impairment and neurodegeneration. We describe this model within the framework of two pollutants, air pollution, a widely recognized threat, and polyfluoroalkyl substances, a large class of synthetic chemicals which are currently emerging as new neurotoxic source.
•Pollution is a critical risk factor for dementia.•Pollution increases inflammation acting in concert with genotype vulnerability.•Air pollution-induced inflammation can spread along functional brain pathways.•Chemical-induced effects alter cell signaling spreading through network pathways.
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