Spontaneous Activity Patterns in Human Attention Networks Code for Hand Movements.

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 r 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 r 2 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.SIGNIFICANCE STATEMENT 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.

Indirect functional connectivity does not predict overall survival in glioblastoma.

BACKGROUND: 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). METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Convergence of Visual and Motor Awareness in Human Parietal Cortex.

OBJECTIVE: Brain lesions sometimes induce a failure of recognition of one's own deficits (anosognosia). Lack of deficit awareness may underlie damage of modality-specific systems, for example, visual cortex for visual anosognosia or motor/premotor cortex for motor anosognosia. However, focal lesions induce widespread remote structural and functional disconnection, and anosognosia, independent of modality, may also involve common neural mechanisms. METHODS: Here, we study the neural correlates of Anton syndrome (AS), anosognosia of blindness, and compare them with anosognosia for hemiplegia to test whether they share different or common mechanisms. We measured both local damage and patterns of structural-functional disconnection as predicted from healthy normative atlases. RESULTS: AS depends on bilateral striate and extrastriate occipital damage, and disconnection of ventral and dorsal frontoparietal regions involved in attention control. Visual and motor anosognosia each share damage of modality-specific regions, but also involve the disruption of white matter tracts, leading to functional disconnection within dorsal frontal-parietal regions that play critical roles in motor control, visuospatial attention, and multisensory integration. INTERPRETATION: These results reveal the unique shared combination of content-specific and supramodal mechanisms in anosognosia. ANN NEUROL 2023.

Prediction of misfolded proteins spreading in Alzheimer's disease using machine learning and spreading models.

The pervasive impact of Alzheimer's disease on aging society represents one of the main challenges at this time. Current investigations highlight 2 specific misfolded proteins in its development: Amyloid-$\beta$ and tau. Previous studies focused on spreading for misfolded proteins exploited simulations, which required several parameters to be empirically estimated. Here, we provide an alternative view based on 2 machine learning approaches which we compare with known simulation models. The first approach applies an autoregressive model constrained by structural connectivity, while the second is based on graph convolutional networks. The aim is to predict concentrations of Amyloid-$\beta$ 2 yr after a provided baseline. We also evaluate its real-world effectiveness and suitability by providing a web service for physicians and researchers. In experiments, the autoregressive model generally outperformed state-of-the-art models resulting in lower prediction errors. While it is important to note that a comprehensive prognostic plan cannot solely rely on amyloid beta concentrations, their prediction, achieved by the discussed approaches, can be valuable for planning therapies and other cures, especially when dealing with asymptomatic patients for whom novel therapies could prove effective.

Neurite Orientation Dispersion and Density Imaging in Multiple Sclerosis: A Systematic Review.

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.

Aberrant brain network connectivity in presymptomatic and manifest Huntington's disease: A systematic review.

Resting-state functional magnetic resonance imaging (rs-fMRI) has the potential to shed light on the pathophysiological mechanisms of Huntington's disease (HD), paving the way to new therapeutic interventions. A systematic literature review was conducted in three online databases according to PRISMA guidelines, using keywords for HD, functional connectivity, and rs-fMRI. We included studies investigating connectivity in presymptomatic (pre-HD) and manifest HD gene carriers compared to healthy controls, implementing seed-based connectivity, independent component analysis, regional property, and graph analysis approaches. Visual network showed reduced connectivity in manifest HD, while network/areas underpinning motor functions were consistently altered in both manifest HD and pre-HD, showing disease stage-dependent changes. Cognitive networks underlying executive and attentional functions showed divergent anterior-posterior alterations, possibly reflecting compensatory mechanisms. The involvement of these networks in pre-HD is still unclear. In conclusion, aberrant connectivity of the sensory-motor network is observed in the early stage of HD while, as pathology spreads, other networks might be affected, such as the visual and executive/attentional networks. Moreover, sensory-motor and executive networks exhibit hyper- and hypo-connectivity patterns following different spatiotemporal trajectories. These findings could potentially help to implement future huntingtin-lowering interventions.

Non-Invasive Brain Stimulation in Dementia: A Complex Network Story.

Non-invasive brain stimulation (NIBS) is emerging as a promising rehabilitation tool for a number of neurodegenerative diseases. However, the therapeutic mechanisms of NIBS are not completely understood. In this review, we will summarize NIBS results in the context of brain imaging studies of functional connectivity and metabolites to gain insight into the possible mechanisms underlying recovery. We will briefly discuss how the clinical manifestations of common neurodegenerative disorders may be related with aberrant connectivity within large-scale neural networks. We will then focus on recent studies combining resting-state functional magnetic resonance imaging with NIBS to delineate how stimulation of different brain regions induce complex network modifications, both at the local and distal level. Moreover, we will review studies combining magnetic resonance spectroscopy and NIBS to investigate how microscale changes are related to modifications of large-scale networks. Finally, we will re-examine previous NIBS studies in dementia in light of this network perspective. A better understanding of NIBS impact on the functionality of large-scale brain networks may be useful to design beneficial treatments for neurodegenerative disorders.

Brain networks stimulation in dementia: insights from functional imaging.

PURPOSE OF REVIEW: Noninvasive brain stimulation (NIBS) is increasingly used in the field of dementia as a therapeutic option; however, evidence of clinical efficacy is limited, and the mechanism of action remains unknown. This review summarizes how functional imaging could contribute to the design of targeted and effective NIBS interventions for dementia. RECENT FINDINGS: Resting-state functional magnetic resonance imaging (fMRI) has largely contributed to understanding brain dysfunction in dementia by identifying disease-specific networks. Resting-state fMRI might inform on a number of factors critical for the conduction of effective NIBS trials, such as definition of stimulation paradigms and choice of the stimulation target. In addition, fMRI may contribute to the understanding of the mechanisms of action of NIBS, and provide a tool to monitor treatment efficacy. SUMMARY: Functional imaging is a promising approach for the development of hypothesis-driven, targeted stimulation approaches in the field of dementia.

Glioblastoma and brain connectivity: the need for a paradigm shift.

Despite substantial advances in cancer treatment, for patients with glioblastoma prognosis remains bleak. The emerging field of cancer neuroscience reveals intricate functional interplays between glioblastoma and the cellular architecture of the brain, encompassing neurons, glia, and vessels. New findings underscore the role of structural and functional connections within hierarchical networks, known as the connectome. These connections contribute to the location, spread, and recurrence of a glioblastoma, and a patient's overall survival, revealing a complex interplay between the tumour and the CNS. This mounting evidence prompts a paradigm shift, challenging the perception of glioblastomas as mere foreign bodies within the brain. Instead, these tumours are intricately woven into the structural and functional fabric of the brain. This radical change in thinking holds profound implications for the understanding and treatment of glioblastomas, which could unveil new prognostic factors and surgical strategies and optimise radiotherapy. Additionally, a connectivity approach suggests that non-invasive brain stimulation could disrupt pathological neuron-glioma interactions within specific networks.

Behavioral and dysexecutive variant of Alzheimer's disease: Insights from structural and molecular imaging studies.

Frontal variant Alzheimer's disease (AD) manifests with either behavioral or dysexecutive syndromes. Recent efforts to gain a deeper understanding of this phenotype have led to a re-conceptualization of frontal AD. Behavioral (bAD) and dysexecutive (dAD) phenotypes could be considered subtypes, as suggested by both clinical and neuroimaging studies. In this review, we focused on imaging studies to highlight specific brain patterns in these two uncommon clinical AD phenotypes. Although studies did not compare directly these two variants, a common epicenter located in the frontal cortex could be inferred. On the contrary, 18F-FDG-PET findings suggested differing metabolic patterns, with bAD showing specific involvement of frontal regions and dAD exhibiting widespread alterations. Structural MRI findings confirmed this pattern, suggesting that degeneration might involve neural circuits associated with behavioral control in bAD and attentional networks in dAD. Furthermore, molecular imaging has identified different neocortical tau distribution in bAD and dAD patients compared to typical AD patients, although the distribution is remarkably heterogeneous. In contrast, Aß deposition patterns are less differentiated between these atypical variants and typical AD. Although preliminary, these findings underscore the complexity of AD frontal phenotypes and suggest that they represent distinct entities. Further research is essential to refine our understanding of the pathophysiological mechanisms in frontal AD.

Microstructural alterations in the locus coeruleus-entorhinal cortex pathway in Alzheimer's disease and frontotemporal dementia.

INTRODUCTION: We investigated in vivo the microstructural integrity of the pathway connecting the locus coeruleus to the transentorhinal cortex (LC-TEC) in patients with Alzheimer's disease (AD) and frontotemporal dementia (FTD). METHODS: Diffusion-weighted MRI scans were collected for 21 AD, 20 behavioral variants of FTD (bvFTD), and 20 controls. Fractional anisotropy (FA), mean, axial, and radial diffusivities (MD, AxD, RD) were computed in the LC-TEC pathway using a normative atlas. Atrophy was assessed using cortical thickness and correlated with microstructural measures. RESULTS: We found (i) higher RD in AD than controls; (ii) higher MD, RD, and AxD, and lower FA in bvFTD than controls and AD; and (iii) a negative association between LC-TEC MD, RD, and AxD, and entorhinal cortex (EC) thickness in bvFTD (all p < 0.050). DISCUSSION: LC-TEC microstructural alterations are more pronounced in bvFTD than AD, possibly reflecting neurodegeneration secondary to EC atrophy. Highlights: Microstructural integrity of LC-TEC pathway is understudied in AD and bvFTD.LC-TEC microstructural alterations are present in both AD and bvFTD.Greater LC-TEC microstructural alterations in bvFTD than AD.LC-TEC microstructural alterations in bvFTD are associated to EC neurodegeneration.

Different MRI structural processing methods do not impact functional connectivity computation.

Resting-state functional magnetic resonance imaging (rs-fMRI) has become an increasingly popular technique. This technique can assess several features of brain connectivity, such as inter-regional temporal correlation (functional connectivity), from which graph measures of network organization can be derived. However, these measures are prone to a certain degree of variability depending on the analytical steps during preprocessing. Many studies have investigated the effect of different preprocessing steps on functional connectivity measures; however, no study investigated whether different structural reconstructions lead to different functional connectivity metrics. Here, we evaluated the impact of different structural segmentation strategies on functional connectivity outcomes. To this aim, we compared different metrics computed after two different registration strategies. The first strategy used structural information from the 3D T1-weighted image (unimodal), while the second strategy implemented a multimodal approach, where an additional registration step used the information from the T2-weighted image. The impact of these different approaches was evaluated on a sample of 58 healthy adults. As expected, different approaches led to significant differences in structural measures (i.e., cortical thickness, volume, and gyrification index), with the maximum impact on the insula cortex. However, these differences were only slightly translated to functional metrics. We reported no differences in graph measures and seed-based functional connectivity maps, but slight differences in the insula when we compared the mean functional strength for each parcel. Overall, these results suggested that functional metrics are only slightly different when using a unimodal compared to a multimodal approach, while the structural output can be significantly affected.

Pupillary dynamics predict long-term outcome in a cohort of acute traumatic brain injury coma patients.

OBJECTIVE: Examining the size and reactivity of the pupils of traumatic brain injury coma patients is fundamental in the Neuro-intensive care unit (ICU). Pupil parameters on admission predict long-term clinical outcomes. However, little is known about the dynamics of pupillary parameters and their potential value for outcome prediction. METHODS: This study applied a time-course analysis of pupillary signals (size and photo-reactivity) in acute traumatic brain injury coma patients (n = 20) to predict outcome at 6 months. RESULTS: The time course of pupillary signals was informative in discriminating favorable (F) versus unfavorable (U) outcomes, with the highest correlation within the 1st week notwithstanding pharmacological sedation. Patients with favorable outcome at 6 months showed more consistent in time isochoric and photo-reactive pupils. In contrast, patients with an unfavorable outcome showed more variable measures that tended to stabilize toward pathological values. INTERPRETATION: Time-dependent tracking of pupils' size and reactivity is a promising application for ICU monitoring and long-term prognosis. These findings support the usefulness of automatic tools for the dynamic, quantitative, and objective measurements of pupils.

How both positive and burdensome caregiver experiences are associated with care recipient cognitive performance: Evidence from the National Health and Aging Trends Study and National Study of Caregiving.

Introduction: Being an informal caregiver to a person with chronic disease, including persons living with dementia (PLWD), is a big role to take on and many caregivers experience both substantial burden and emotional reward related to caregiving. Care recipient factors (e.g., behavioral symptoms) are associated with caregiver experience. However, the relationship between caregiver and care recipient is bidirectional, so it is likely that caregiver factors impact the care recipient, though few studies have investigated this. Methods: In the 2017 round of the National Health and Aging Trends Study (NHATS) and National Study of Caregiving (NSOC), we studied 1,210 care dyads--170 PLWD dyads and 1,040 without dementia dyads. Care recipients completed immediate and delayed word list memory tasks, the Clock Drawing Test, and a self-rated memory rating, while caregivers were interviewed about their caregiving experiences using a 34-item questionnaire. Using principal component analysis, we created a caregiver experience score with three components-Practical Care Burden, Positive Care Experiences, and Emotional Care Burden. We then investigated the cross-sectional association between caregiver experience components and care recipient cognitive test performance using linear regression models adjusted for age, sex, education, race, and depressive and anxiety symptoms. Results: Among PLWD dyads, a higher caregiver Positive Care Experiences score was associated with better care recipient performance on the delayed word recall (B = 0.20, 95% CI 0.05, 0.36) and Clock Draw (B = 0.12, 95% CI 0.01, 0.24) tests while higher Emotional Care Burden score was associated with worse self-rated memory score (B = -0.19, 95% CI -0.39, -0.003). Among participants without dementia, higher Practical Care Burden score was associated with poorer care recipient performance on the immediate (B = -0.07, 95% CI -0.12, -0.01) and delayed (B = -0.10, 95% CI -0.16, -0.05) word recall tests. Discussion: These findings support the concept that caregiving is bidirectional within the dyad and that positive variables can positively impact both members of the dyad. This suggests that caregiving interventions should target the caregiver and recipient both individually and as a unit, with the goal of holistically improving outcomes for both.

The pollutome-connectome axis: a putative mechanism to explain pollution effects on neurodegeneration.

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.