Publications by authors named "Stefania Ferraro"

Background: The lack of clearly defined neuromodulation targets has contributed to the inconsistent results of real-time fMRI-based neurofeedback (rt-fMRI-NF) for the treatment of chronic pain. Functional neurosurgery (funcSurg) approaches have shown more consistent effects in reducing pain in patients with severe chronic pain.

Objective: This study aims to redefine rt-fMRI-NF targets for chronic pain management informed by funcSurg studies.

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Posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) are common stress-related psychiatric disorders. Genetic and neurobiology research has supported the viewpoint that PTSD and MDD may possess common and disorder-specific underlying mechanisms. In this systematic review, we summarize evidence for the similarities and differences in brain functional and structural features of MDD, PTSD, and their comorbidity, as well as the effects of extensively used therapies in patients with comorbid PTSD and MDD (PTSD + MDD).

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Background: Mindfulness practice has gained interest in the management of Chronic Migraine associated with Medication Overuse Headache (CM-MOH). Mindfulness is characterized by present-moment self-awareness and relies on attention control and emotion regulation, improving headache-related pain management. Mindfulness modulates the Default Mode Network (DMN), Salience Network (SN), and Fronto-Parietal Network (FPN) functional connectivity.

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Background: The involvement of specific basal ganglia-thalamocortical circuits in response inhibition has been extensively mapped in animal models. However, the pivotal nodes and directed causal regulation within this inhibitory circuit in humans remains controversial.

Objective: The main aim of the present study was to determine the causal information flow and critical nodes in the basal ganglia-thalamocortical inhibitory circuits and also to examine whether these are modulated by biological factors (i.

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Maternal phenylketonuria (mPKU) is a pathologic condition occurring in the fetus of a mother with PKU that is caused by prolonged elevated intrauterine blood phenylalanine (Phe) levels, which can lead to congenital abnormalities and mental retardation of newborns. Management of PKU during pregnancy can be challenging as protein substitutes may exacerbate nausea, vomiting, and gastrointestinal symptoms. To report the successful management of four PKU pregnant women.

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Background And Purpose: Thalamic alterations have been reported as a major feature in presymptomatic and symptomatic patients carrying the C9orf72 mutation across the frontotemporal dementia-amyotrophic lateral sclerosis (ALS) spectrum. Specifically, the pulvinar, a high-order thalamic nucleus and timekeeper for large-scale cortical networks, has been hypothesized to be involved in C9orf72-related neurodegenerative diseases. We investigated whether pulvinar volume can be useful for differential diagnosis in ALS C9orf72 mutation carriers and noncarriers and how underlying functional connectivity changes affect this region.

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In the past 2 decades, several attempts have been made to promote a correct diagnosis and possible restorative interventions in patients suffering from disorders of consciousness. Sensory stimulation has been proved to be useful in sustaining the level of arousal/awareness and to improve behavioural responsiveness with a significant effect on oro-motor functions. Recently, action observation has been proposed as a stimulation strategy in patients with disorders of consciousness, based on neurophysiological evidence that the motor cortex can be activated not only during action execution but also when actions are merely observed in the absence of motor output, or during listening to action sounds and speech.

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Objective: The resting-state functional connectome has not been extensively investigated in amyotrophic lateral sclerosis (ALS) spectrum disease, in particular in relationship with patients' genetic status.

Methods: Here we studied the network-to-network connectivity of 19 ALS patients carrying the C9orf72 hexanucleotide repeat expansion (C9orf72+), 19 ALS patients not affected by C9orf72 mutation (C9orf72-), and 19 ALS-mimic patients (ALSm) well-matched for demographic and clinical variables.

Results: When compared with ALSm, we observed greater connectivity of the default mode and frontoparietal networks with the visual network for C9orf72+ patients (P = 0.

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Background: Despite hypothalamus has long being considered to be involved in the pathophysiology of cluster headache, the inconsistencies of previous neuroimaging studies and a limited understanding of the hypothalamic areas involved, impede a comprehensive interpretation of its involvement in this condition.

Methods: We used an automated algorithm to extract hypothalamic subunit volumes from 105 cluster headache patients (57 chronic and 48 episodic) and 59 healthy individuals; after correcting the measures for the respective intracranial volumes, we performed the relevant comparisons employing logist regression models. Only for subunits that emerged as abnormal, we calculated their correlation with the years of illness and the number of headache attacks per day, and the effects of lithium treatment.

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Reward processing dysfunctions are considered a candidate mechanism underlying anhedonia and apathy in depression. Neuroimaging studies have documented that neurofunctional alterations in mesocorticolimbic circuits may neurally mediate these dysfunctions. However, common and distinct neurofunctional alterations during motivational and hedonic evaluation of monetary and natural rewards in depression have not been systematically examined.

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Purpose: The use of topological metrics to derive quantitative descriptors from structural connectomes is receiving increasing attention but deserves specific studies to investigate their reproducibility and variability in the clinical context. This work exploits the harmonization of diffusion-weighted acquisition for neuroimaging data performed by the Italian Neuroscience and Neurorehabilitation Network initiative to obtain normative values of topological metrics and to investigate their reproducibility and variability across centers.

Methods: Different topological metrics, at global and local level, were calculated on multishell diffusion-weighted data acquired at high-field (e.

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Initiatives for the collection of harmonized MRI datasets are growing continuously, opening questions on the reliability of results obtained in multi-site contexts. Here we present the assessment of the brain anatomical variability of MRI-derived measurements obtained from T1-weighted images, acquired according to the Standard Operating Procedures, promoted by the RIN-Neuroimaging Network. A multicentric dataset composed of 77 brain T1w acquisitions of young healthy volunteers (mean age = 29.

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Objective: C9orf72 mutation carriers with different neurological phenotypes show cortical and subcortical atrophy in multiple different brain regions, even in pre-symptomatic phases. Despite there is a substantial amount of knowledge, small sample sizes, clinical heterogeneity, as well as different choices of image analysis may hide anatomical abnormalities that are unique to amyotrophic lateral sclerosis (ALS) patients with this genotype or that are indicative of the C9orf72-specific trait overlain in fronto-temporal dementia patients.

Methods: Brain structural and resting state functional magnetic imaging was obtained in 24 C9orf72 positive (ALSC9+) ALS patients paired for burden disease with 24 C9orf72 negative (ALSC9-) ALS patients.

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Background And Aims: Fear of missing out (FOMO) promotes the desire or urge to stay continuously connected with a social reference group and updated on their activities, which may result in escalating and potentially addictive smartphone and social media use. The present study aimed to determine whether the neurobiological basis of FOMO encompasses core regions of the reward circuitry or social brain, and associations with levels of problematic smartphone or social media use.

Methods: We capitalized on a dimensional neuroimaging approach to examine cortical thickness and subcortical volume associations in a sample of healthy young individuals (n = 167).

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Aim: When studying brain networks in patients with Disorders of Consciousness (DoC), it is important to evaluate the structural integrity of networks in addition to their functional activity. Here, we investigated whether structural MRI, together with clinical variables, can be useful for diagnostic purposes and whether a quantitative analysis is feasible in a group of chronic DoC patients.

Methods: We studied 109 chronic patients with DoC and emerged from DoC with structural MRI: 65 in vegetative state/unresponsive wakefulness state (VS/UWS), 34 in minimally conscious state (MCS), and 10 with severe disability.

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Major depression (MDD) and generalized anxiety disorder (GAD) have become one of the leading global causes of disability and both are characterized by marked interpersonal and social impairments. However, despite high comorbidity and overlapping social-emotional deficits, it remains unclear whether MDD and GAD share a common neural basis during interpersonal processing. In the present study, we combined an emotional face processing paradigm with fMRI and dimensional and categorical analyses in a sample of unmedicated MDD and GAD patients (N = 72) as well as healthy controls (N = 35).

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Article Synopsis
  • * Researchers analyzed gray and white matter changes in the cervical spinal cord of 44 ALS patients and found that at the early stage (King's stage 1), atrophy was primarily in gray matter, while later stages involved both gray and white matter.
  • * A model suggested that significant gray matter atrophy occurs 7 to 20 months before clinical symptoms appear, indicating that spinal cord MRI could be a valuable tool for monitoring ALS progression.
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Purpose: Generating big-data is becoming imperative with the advent of machine learning. RIN-Neuroimaging Network addresses this need by developing harmonized protocols for multisite studies to identify quantitative MRI (qMRI) biomarkers for neurological diseases. In this context, image quality control (QC) is essential.

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The autonomic nervous system regulates dynamic body adaptations to internal and external environment changes. Capitalizing on two different algorithms (that differ in empirical assumptions), we scrutinized the meta-analytic convergence of human neuroimaging studies investigating the neural basis of peripheral autonomic signal processing. Among the selected studies, we identified 42 records reporting 44 different experiments and testing 758 healthy individuals.

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Quantitative Susceptibility Mapping (QSM) is an MRI-based technique allowing the non-invasive quantification of iron content and myelination in the brain. The RIN - Neuroimaging Network established an optimized and harmonized protocol for QSM across ten sites with 3T MRI systems from three different vendors to enable multicentric studies. The assessment of the reproducibility of this protocol is crucial to establish susceptibility as a quantitative biomarker.

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Fundamental and clinical neuroscience has benefited tremendously from the development of automated computational analyses. In excess of 600 human neuroimaging papers using Voxel-based Morphometry (VBM) are now published every year and a number of different automated processing pipelines are used, although it remains to be systematically assessed whether they come up with the same answers. Here we examined variability between four commonly used VBM pipelines in two large brain structural datasets.

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Background: Converging evidence suggests that anatomical and functional mesocorticolimbic abnormalities support the chronicization of pain disorders.

Methods: We mapped structural and functional alterations of the mesocorticolimbic system in a sample of chronic cluster headache patients (n = 28) in comparison to age and sex-matched healthy individuals (n = 28) employing structural MRI and resting-state functional MRI.

Results: Univariate logistic regression models showed that several of the examined structures/areas (i.

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Neuroimaging studies often lack reproducibility, one of the cardinal features of the scientific method. Multisite collaboration initiatives increase sample size and limit methodological flexibility, therefore providing the foundation for increased statistical power and generalizable results. However, multisite collaborative initiatives are inherently limited by hardware, software, and pulse and sequence design heterogeneities of both clinical and preclinical MRI scanners and the lack of benchmark for acquisition protocols, data analysis, and data sharing.

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Resting-state fMRI (rs-fMRI) is a widely used technique to investigate the residual brain functions of patients with Disorders of Consciousness (DoC). Nonetheless, it is unclear how the networks that are more associated with primary functions, such as the sensory-motor, medial/lateral visual and auditory networks, contribute to clinical assessment. In this study, we examined the rs-fMRI lower-order networks alongside their structural MRI data to clarify the corresponding association with clinical assessment.

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Article Synopsis
  • The study applied various entropy measures, specifically Lempel-Ziv complexity, amplitude coalition entropy (ACE), and synchrony coalition entropy (SCE), to EEG signals from 32 patients with different chronic disorders of consciousness.
  • It found that differences in theta and alpha band activity could effectively classify patients between minimal consciousness state (MCS) and vegetative state/unresponsive wakefulness state (VS/UWS), particularly in the left hemisphere and midline regions.
  • ACE was the most effective measure for highlighting significant differences, indicating that higher entropy values in MCS correlated with better consciousness preservation, as shown by the patients' scores on the coma recovery scale revised (CRS-R).
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