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Background: Advances in analytical methods have recently paved the way to Alzheimer's disease (AD) biomarkers testing in blood along with the more established CSF testing. To ensure a forthcoming application of this low-invasive diagnostic that might allow to recognize early onset of dementia, appropriate pathological cut-points need to be defined., Methods: In this cross-sectional study we measured blood and CSF neurofilament light chain (NFL), phosphorylated tau (pTau 181), Amyloid-β1-42 (AB 1-42) and Amyloid-β1-40 (AB 1-40) on a fully automated chemiluminescent platform (Lumipulse, Fujirebio) in 80 cognitively impaired patients and 55 cognitively unimpaired subjects. Clinical cut points were calculated with receiver-operator characteristic (ROC) curve analysis and a head-to-head comparison of blood and CSF testing was performed., Results: Blood NFL best discriminant thresholds to distinguish neurodegenerative diseases from controls varied age-dependently, being 19 and 33 pg/mL in subjects 50-65 years and > 65 years respectively. AD was best framed by AB 1-42/1-40 ratio < 0.079 and ptau181 > 1 pg/mL. Though a strong correlation for all biomarkers, only blood AB ratio was equal to CSF testing for AD diagnosis., Conclusions: The specific context of use might be considered to define the cut-offs of blood biomarkers of neurodegenerative diseases. Future efforts towards reference materials for each AD blood biomarker will improve clinical cut-offs., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: [G.M., C.G., C.C., A.C., G.S., M.Z., S.M., C.F.Z., M.P., M.C., D.B. declarations of interest: none. M.Pu. reports travel grants, consultancy, and board membership from Almirall, Teva, Sanofi Genzyme, Merck Serono, Biogen Italy, Novartis, Bristol Myers Squibb, Janssen, Sandoz and Alexion. P.G. reports grant, consultancy, and board membership for Almirall, Teva, Sanofi Genzyme, Merck Serono, Biogen Italy, Novartis, Roche, Bristol Myers Squibb, Janssen, Sandoz and Alexion. E. P. reports payments or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events from Biogen and Roche; support for attending meetings and/or travels from Roche, Biogen, and Alexion; payments for participation on a Data Safety Monitoring Board or Advisory Board from Alexion, UCB Biopharma, and Sanofi. A.A. has received compensation for consultancy and speaker related activities from UCB, Britannia, AbbVie, Zambon, Bial, Neuroderm, Theravance Biopharma, Roche; he receives research support from Horizon 2020 - Ministry of Education University and Research (MIUR), Ministry of Health, Cariparo Foundation, Fondazione Grigioni per il Morbo di Parkinson.]., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Introduction: Neuropsychological studies infer brain-behavior relationships from focal lesions like stroke and tumors. However, these pathologies impair brain function through different mechanisms even when they occur at the same brain's location. The aim of this study was to compare the profile of cognitive impairment in patients with brain tumors vs. stroke and examine the correlation with lesion location in each pathology., Methods: Patients with first time stroke (n = 77) or newly diagnosed brain tumors (n = 76) were assessed with a neuropsychological battery. Their lesions were mapped with MRI scans. Test scores were analyzed using principal component analysis (PCA) to measure their correlation, and logistic regression to examine differences between pathologies. Next, with ridge regression we examined whether lesion features (location, volume) were associated with behavioral performance., Results: The PCA showed a similar cognitive impairment profile in tumors and strokes with three principal components (PCs) accounting for about half of the individual variance. PC1 loaded on language, verbal memory, and executive/working memory; PC2 loaded on general performance, visuo-spatial attention and memory, and executive functions; and, PC3 loaded on calculation, reading and visuo-spatial attention. The average lesion distribution was different, and lesion location was correlated with cognitive deficits only in stroke. Logistic regression found language and calculation more affected in stroke, and verbal memory and verbal fluency more affected in tumors., Conclusions: A similar low dimensional set of behavioral impairments was found both in stroke and brain tumors, even though each pathology caused some specific deficits in different domains. The lesion distribution was different for stroke and tumors and correlated with behavioral impairment only in stroke., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

The default mode (DMN) and the salience (SN) networks show functional hypo-connectivity in Alzheimer's disease (AD) and the behavioral variant of frontotemporal dementia (bvFTD), respectively, along with patterns of hyper-connectivity. We tested the clinical and neurobiological effects of noninvasive stimulation over these networks in 45 patients (AD and bvFTD) who received either anodal (target network: DMN in AD, SN in bvFTD) or cathodal stimulation (target network: SN in AD, DMN in bvFTD). We evaluated changes in clinical, cognitive, functional and structural connectivity, and perfusion measures. In both patient groups, cathodal stimulation was followed by behavioral improvement, whereas anodal stimulation led to cognitive improvement. Neither functional connectivity nor perfusion showed significant effects. A significant interaction between DMN and SN functional connectivity changes and stimulation protocol was reported in AD. These results suggest a protocol-dependent response, whereby the protocols studied show divergent effects on cognitive and clinical measures, along with a divergent modulatory pattern of connectivity in AD., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Gliomas are commonly characterized by neurocognitive deficits that strongly impact patients' and caregivers' quality of life. Surgical resection is the mainstay of therapy, and it can also cause cognitive impairment. An important clinical problem is whether patients who undergo surgery will show post-surgical cognitive impairment above and beyond that present before surgery. The relevant rognostic factors are largely unknown. This study aims to quantify the cognitive impairment in glioma patients 1-week after surgery and to compare different pre-surgical information (i.e., cognitive performance, tumor volume, grading, and lesion topography) towards predicting early post-surgical cognitive outcome. We retrospectively recruited a sample of N = 47 patients affected by high-grade and low-grade glioma undergoing brain surgery for tumor resection. Cognitive performance was assessed before and immediately after (∼1 week) surgery with an extensive neurocognitive battery. Multivariate linear regression models highlighted the combination of predictors that best explained post-surgical cognitive impairment. The impact of surgery on cognitive functioning was relatively small (i.e., 85% of test scores across the whole sample indicated no decline), and pre-operative cognitive performance was the main predictor of early post-surgical cognitive outcome above and beyond information from tumor topography and volume. In fact, structural lesion information did not significantly improve the accuracy of prediction made from cognitive data before surgery. Our findings suggest that post-surgery neurocognitive deficits are only partially explained by preoperative brain damage. The present results suggest the possibility to make reliable, individualized, and clinically relevant predictions from relatively easy-to-obtain information., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier Inc.)

Diffusion-based biophysical models have been used in several recent works to study the microenvironment of brain tumours. While the pathophysiological interpretation of the parameters of these models remains unclear, their use as signal representations may yield useful biomarkers for monitoring the treatment and the progression of this complex and heterogeneous disease. Up to now, however, no study was devoted to assessing the mathematical stability of these approaches in cancerous brain regions. To this end, we analyzed in 11 brain tumour patients the fitting results of two microstructure models (Neurite Orientation Dispersion and Density Imaging and the Spherical Mean Technique) and of a signal representation (Diffusion Kurtosis Imaging) to compare the reliability of their parameter estimates in the healthy brain and in the tumoral lesion. The framework of our between-tissue analysis included the computation of 1) the residual sum of squares as a goodness-of-fit measure 2) the standard deviation of the models' derived metrics and 3) models' sensitivity functions to analyze the suitability of the employed protocol for parameter estimation in the different microenvironments. Our results revealed no issues concerning the fitting of the models in the tumoral lesion, with similar goodness of fit and parameter precisions occurring in normal appearing and pathological tissues. Lastly, with the aim of highlight possible biomarkers, in our analysis we briefly discuss the correlation between the metrics of the three techniques, identifying groups of indices which are significantly collinear in all tissues and thus provide no additional information when jointly used in data-driven analyses., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Most neuroimaging studies of post-stroke recovery rely on analyses derived from standard node-centric functional connectivity to map the distributed effects in stroke patients. Here, given the importance of nonlocal and diffuse damage, we use an edge-centric approach to functional connectivity in order to provide an alternative description of the effects of this disorder. These techniques allow for the rendering of metrics such as normalized entropy, which describes the diversity of edge communities at each node. Moreover, the approach enables the identification of high amplitude co-fluctuations in fMRI time series. We found that normalized entropy is associated with stroke lesion severity and continually increases across the time of patients' recovery. Furthermore, high amplitude co-fluctuations not only relate to the lesion severity but are also associated with patients' level of recovery. The current study is the first edge-centric application for a clinical population in a longitudinal dataset and demonstrates how a different perspective for functional data analysis can further characterize topographic modulations of brain dynamics., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Understanding the effect of focal lesions (stroke) on brain structure-function traditionally relies on behavioral analyses and correlation with neuroimaging data. Here we use structural disconnection maps from individual lesions to derive a causal mechanistic generative whole-brain model able to explain both functional connectivity alterations and behavioral deficits induced by stroke. As compared to other models that use only the local lesion information, the similarity to the empirical fMRI connectivity increases when the widespread structural disconnection information is considered. The presented model classifies behavioral impairment severity with higher accuracy than other types of information (e.g.: functional connectivity). We assessed topological measures that characterize the functional effects of damage. With the obtained results, we were able to understand how network dynamics change emerge, in a nontrivial way, after a stroke injury of the underlying complex brain system. This type of modeling, including structural disconnection information, helps to deepen our understanding of the underlying mechanisms of stroke lesions., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Beyond causing local ischemia and cell damage at the site of injury, stroke strongly affects long-range anatomical connections, perturbing the functional organization of brain networks. Several studies reported functional connectivity abnormalities parallelling both behavioral deficits and functional recovery across different cognitive domains. FC alterations suggest that long-range communication in the brain is altered after stroke. However, standard FC analyses cannot reveal the directionality and time scale of inter-areal information transfer. We used resting-state fMRI and covariance-based Granger causality analysis to quantify network-level information transfer and its alteration in stroke. Two main large-scale anomalies were observed in stroke patients. First, inter-hemispheric information transfer was significantly decreased with respect to healthy controls. Second, stroke caused inter-hemispheric asymmetries, as information transfer within the affected hemisphere and from the affected to the intact hemisphere was significantly reduced. Both anomalies were more prominent in resting-state networks related to attention and language, and they correlated with impaired performance in several behavioral domains. Overall, our findings support the hypothesis that stroke provokes asymmetries between the affected and spared hemisphere, with different functional consequences depending on which hemisphere is lesioned., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

Lesion studies are an important tool for cognitive neuroscientists and neurologists. However, while brain lesion studies have traditionally aimed to localize neurological symptoms to specific anatomical loci, a growing body of evidence indicates that neurological diseases such as stroke are best conceptualized as brain network disorders. While researchers in the fields of neuroscience and neurology are therefore increasingly interested in quantifying the effects of focal brain lesions on the white matter connections that form the brain's structural connectome, few dedicated tools exist to facilitate this endeavor. Here, we present the Lesion Quantification Toolkit, a publicly available MATLAB software package for quantifying the structural impacts of focal brain lesions. The Lesion Quantification Toolkit uses atlas-based approaches to estimate parcel-level grey matter lesion loads and multiple measures of white matter disconnection severity that include tract-level disconnection measures, voxel-wise disconnection maps, and parcel-wise disconnection matrices. The toolkit also estimates lesion-induced increases in the lengths of the shortest structural paths between parcel pairs, which provide information about changes in higher-order structural network topology. We describe in detail each of the different measures produced by the toolkit, discuss their applications and considerations relevant to their use, and perform example analyses using real behavioral data collected from sub-acute stroke patients. We show that analyses performed using the different measures produced by the toolkit produce results that are highly consistent with results that have been reported in the prior literature, and we demonstrate the consistency of results obtained from analyses conducted using the different disconnection measures produced by the toolkit. We anticipate that the Lesion Quantification Toolkit will empower researchers to address research questions that would be difficult or impossible to address using traditional lesion analyses alone, and ultimately, lead to advances in our understanding of how white matter disconnections contribute to the cognitive, behavioral, and physiological consequences of focal brain lesions., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Focal brain lesions can lend insight into the causal neuroanatomical substrate of depression in the human brain. However, studies of lesion location have led to inconsistent results., Methods: Five independent datasets with different lesion etiologies and measures of postlesion depression were collated (N = 461). Each 3-dimensional lesion location was mapped to a common brain atlas. We used voxel lesion symptom mapping to test for associations between depression and lesion locations. Next, we computed the network of regions functionally connected to each lesion location using a large normative connectome dataset (N = 1000). We used these lesion network maps to test for associations between depression and connected brain circuits. Reproducibility was assessed using a rigorous leave-one-dataset-out validation. Finally, we tested whether lesion locations associated with depression fell within the same circuit as brain stimulation sites that were effective for improving poststroke depression., Results: Lesion locations associated with depression were highly heterogeneous, and no single brain region was consistently implicated. However, these same lesion locations mapped to a connected brain circuit, centered on the left dorsolateral prefrontal cortex. Results were robust to leave-one-dataset-out cross-validation. Finally, our depression circuit derived from brain lesions aligned with brain stimulation sites that were effective for improving poststroke depression., Conclusions: Lesion locations associated with depression fail to map to a specific brain region but do map to a specific brain circuit. This circuit may have prognostic utility in identifying patients at risk for poststroke depression and therapeutic utility in refining brain stimulation targets., (Copyright © 2019 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Objective: To test efficacy and tolerability of edaravone in patients with amyotrophic lateral sclerosis (ALS) originating from North-Eastern Italy., Methods: We compared 3-month and 6-month changes of ALSFRS-R score, FVC value, and MRC score of 31 consecutive patients with ALS who were treated with edaravone to those of 50 historical ALS patients who were not treated with edaravone., Results: No significant difference for any functional measures was found between the two groups at each time point as compared to baseline. In treated patients, we also observed creatinine values to significantly decrease at 3 and 6 months (p = 0.0078 and 0.030, respectively) and ALSAQ5 score to significantly increase (i.e. worse quality of life) at 3 and 6 months (p = 0.0005 and 0.0078, respectively). Yet, we observed an overall safety of the medication over the 6-month period of observation., Conclusions: Our retrospective study suggests no benefit of edaravone on ALS in populations of Caucasian ancestry., (Copyright © 2019 Elsevier B.V. All rights reserved.)

We report on the results of a multimodal imaging study involving behavioral assessments, evoked and resting-state BOLD fMRI, and DTI in chronic mTBI subjects. We found that larger task-evoked BOLD activity in the MT+/LO region in extra-striate visual cortex correlated with mTBI and PTSD symptoms, especially light sensitivity. Moreover, higher FA values near the left optic radiation (OR) were associated with both light sensitivity and higher BOLD activity in the MT+/LO region. The MT+/LO region was localized as a region of abnormal functional connectivity with central white matter regions previously found to have abnormal physiological signals during visual eye movement tracking (Astafiev et al., 2015). We conclude that mTBI symptoms and light sensitivity may be related to excessive responsiveness of visual cortex to sensory stimuli. This abnormal sensitivity may be related to chronic remodeling of white matter visual pathways acutely injured.

A barrier in the diagnosis of mild traumatic brain injury (mTBI) stems from the lack of measures that are adequately sensitive in detecting mild head injuries. MRI and CT are typically negative in mTBI patients with persistent symptoms of post-concussive syndrome (PCS), and characteristic difficulties in sustaining attention often go undetected on neuropsychological testing, which can be insensitive to momentary lapses in concentration. Conversely, visual tracking strongly depends on sustained attention over time and is impaired in chronic mTBI patients, especially when tracking an occluded target. This finding suggests deficient internal anticipatory control in mTBI, the neural underpinnings of which are poorly understood. The present study investigated the neuronal bases for deficient anticipatory control during visual tracking in 25 chronic mTBI patients with persistent PCS symptoms and 25 healthy control subjects. The task was performed while undergoing magnetoencephalography (MEG), which allowed us to examine whether neural dysfunction associated with anticipatory control deficits was due to altered alpha, beta, and/or gamma activity. Neuropsychological examinations characterized cognition in both groups. During MEG recordings, subjects tracked a predictably moving target that was either continuously visible or randomly occluded (gap condition). MEG source-imaging analyses tested for group differences in alpha, beta, and gamma frequency bands. The results showed executive functioning, information processing speed, and verbal memory deficits in the mTBI group. Visual tracking was impaired in the mTBI group only in the gap condition. Patients showed greater error than controls before and during target occlusion, and were slower to resynchronize with the target when it reappeared. Impaired tracking concurred with abnormal beta activity, which was suppressed in the parietal cortex, especially the right hemisphere, and enhanced in left caudate and frontal-temporal areas. Regional beta-amplitude demonstrated high classification accuracy (92%) compared to eye-tracking (65%) and neuropsychological variables (80%). These findings show that deficient internal anticipatory control in mTBI is associated with altered beta activity, which is remarkably sensitive given the heterogeneity of injuries.

Background: Functional imaging and lesion studies have associated willed behavior with the anterior cingulate cortex (ACC). Abulia is a syndrome characterized by apathy and deficiency of motivated behavior. Abulia is most frequently associated with ACC damage, but also occurs following damage to subcortical nuclei (striatum, globus pallidus, thalamic nuclei). We present resting state functional connectivity MRI (fcMRI) data from an individual who suffered a stroke leading to abulia. We hypothesized that, although structural imaging revealed no damage to the patient's ACC, fcMRI would uncover aberrant function in this region and in the relevant cortical networks., Methods: Resting state correlations in the patient's gray matter were compared to those of age-matched controls. Using a novel method to identify abnormal patterns of functional connectivity in single subjects, we identified areas and networks with aberrant connectivity., Results: Networks associated with memory (default mode network) and executive function (cingulo-opercular network) were abnormal. The patient's anterior cingulate was among the areas showing aberrant functional connectivity. In a rescan 3 years later, deficits remained stable and fcMRI findings were replicated., Conclusions: These findings suggest that the aberrant functional connectivity mapping approach described may be useful for linking stroke symptoms to disrupted network connectivity.

Objective: We examined whether depression and anxiety disorders in early childhood were associated with changes in resting state functional connectivity (RSFC) of the ventral attention network (VAN), and whether RSFC in the VAN was associated with alterations in attention specific to these disorders. Important clinical features of these illnesses, including changes in attention toward novel stimuli and changes in attention to stimuli of negative valence (threat/sad bias), indirectly implicate the VAN., Method: We collected resting state functional magnetic resonance imaging data in children aged 8 to 12 years. Data were volume censored to reduce artifact from submillimeter movement, resulting in analyzable data from 30 children with a history of depression and/or anxiety and 42 children with no psychiatric history. We compared pairwise RSFC among the following VAN regions: right ventro-lateral prefrontal cortex (VLPFC), right posterior superior temporal gyrus (pSTG), and right ventral supramarginal gyrus (vSMG). We also collected measures of threat bias and current clinical symptoms., Results: Children with a history of depression and/or anxiety had reduced RSFC among the regions of the VAN compared to children with no psychiatric history. The magnitude of VAN RSFC was correlated with measures of attention bias toward threat but not with current depressive, internalizing, or externalizing symptoms. No RSFC changes were detected between groups among homotopic left hemisphere regions., Conclusions: Disruption in the VAN may be an early feature of depression and anxiety disorders. VAN changes were associated with attention bias and clinical history but not with current symptoms of depression and anxiety., (Copyright © 2013 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.)

How epilepsy affects brain functional networks remains poorly understood. Here we investigated resting state functional connectivity of the temporal region in temporal lobe epilepsy. Thirty-two patients with unilateral temporal lobe epilepsy underwent resting state blood-oxygenation level dependent functional magnetic resonance imaging. We defined regions of interest a priori focusing on structures involved, either structurally or metabolically, in temporal lobe epilepsy. These structures were identified in each patient based on their individual anatomy. Our principal findings are decreased local and inter-hemispheric functional connectivity and increased intra-hemispheric functional connectivity ipsilateral to the seizure focus compared to normal controls. Specifically, several regions in the affected temporal lobe showed increased functional coupling with the ipsilateral insula and immediately neighboring subcortical regions. Additionally there was significantly decreased functional connectivity between regions in the affected temporal lobe and their contralateral homologous counterparts. Intriguingly, decreased local and inter-hemispheric connectivity was not limited or even maximal for the hippocampus or medial temporal region, which is the typical seizure onset region. Rather it also involved several regions in temporal neo-cortex, while also retaining specificity, with neighboring regions such as the amygdala remaining unaffected. These findings support a view of temporal lobe epilepsy as a disease of a complex functional network, with alterations that extend well beyond the seizure onset area, and the specificity of the observed connectivity changes suggests the possibility of a functional imaging biomarker for temporal lobe epilepsy.