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Decoding visual representations from human brain activity has emerged as a thriving research domain, particularly in the context of brain-computer interfaces. Our study presents an innovative method that employs knowledge distillation to train an EEG classifier and reconstruct images from the ImageNet and THINGS-EEG 2 datasets using only electroencephalography (EEG) data from participants who have viewed the images themselves (i.e. "brain decoding"). We analyzed EEG recordings from 6 participants for the ImageNet dataset and 10 for the THINGS-EEG 2 dataset, exposed to images spanning unique semantic categories. These EEG readings were converted into spectrograms, which were then used to train a convolutional neural network (CNN), integrated with a knowledge distillation procedure based on a pre-trained Contrastive Language-Image Pre-Training (CLIP)-based image classification teacher network. This strategy allowed our model to attain a top-5 accuracy of 87%, significantly outperforming a standard CNN and various RNN-based benchmarks. Additionally, we incorporated an image reconstruction mechanism based on pre-trained latent diffusion models, which allowed us to generate an estimate of the images that had elicited EEG activity. Therefore, our architecture not only decodes images from neural activity but also offers a credible image reconstruction from EEG only, paving the way for, e.g., swift, individualized feedback experiments., 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 © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Sex differences affect Parkinson's disease (PD) development and manifestation. Yet, current PD identification and treatments underuse these distinctions. Sex-focused PD literature often prioritizes prevalence rates over feature importance analysis. However, underlying aspects could make a feature significant for predicting PD, despite its score. Interactions between features require consideration, as do distinctions between scoring disparities and actual feature importance. For instance, a higher score in males for a certain feature doesn't necessarily mean it's less important for characterizing PD in females. This article proposes an explainable Machine Learning (ML) model to elucidate these underlying factors, emphasizing the importance of features. This insight could be critical for personalized medicine, suggesting the need to tailor data collection and analysis for males and females. The model identifies sex-specific differences in PD, aiding in predicting outcomes as "Healthy" or "Pathological". It adopts a system-level approach, integrating heterogeneous data - clinical, imaging, genetics, and demographics - to study new biomarkers for diagnosis. The explainable ML approach aids non-ML experts in understanding model decisions, fostering trust and facilitating interpretation of complex ML outcomes, thus enhancing usability and translational research. The ML model identifies muscle rigidity, autonomic and cognitive assessments, and family history as key contributors to PD diagnosis, with sex differences noted. The genetic variant SNCA-rs356181 may be more significant in characterizing PD in males. Interaction analysis reveals a greater occurrence of feature interplay among males compared to females. These disparities offer insights into PD pathophysiology and could guide the development of sex-specific diagnostic and therapeutic approaches., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: The autonomic response to transcutaneous auricular vagus nerve stimulation (taVNS) has been linked to the engagement of brainstem circuitry modulating autonomic outflow. However, the physiological mechanisms supporting such efferent vagal responses are not well understood, particularly in humans., Hypothesis: We present a paradigm for estimating directional brain-heart interactions in response to taVNS. We propose that our approach is able to identify causal links between the activity of brainstem nuclei involved in autonomic control and cardiovagal outflow., Methods: We adopt an approach based on a recent reformulation of Granger causality that includes permutation-based, nonparametric statistics. The method is applied to ultrahigh field (7T) functional magnetic resonance imaging (fMRI) data collected on healthy subjects during taVNS., Results: Our framework identified taVNS-evoked functional brainstem responses with superior sensitivity compared to prior conventional approaches, confirming causal links between taVNS stimulation and fMRI response in the nucleus tractus solitarii (NTS). Furthermore, our causal approach elucidated potential mechanisms by which information is relayed between brainstem nuclei and cardiovagal, i.e., high-frequency heart rate variability, in response to taVNS. Our findings revealed that key brainstem nuclei, known from animal models to be involved in cardiovascular control, exert a causal influence on taVNS-induced cardiovagal outflow in humans., Conclusion: Our causal approach allowed us to noninvasively evaluate directional interactions between fMRI BOLD signals from brainstem nuclei and cardiovagal outflow., Competing Interests: Declaration of competing interest None., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Resting-state functional magnetic resonance imaging (rs-fMRI) has been successfully employed to understand the organisation of the human brain. Typically, the brain is parcellated into regions of interest (ROIs) and modelled as a graph where each ROI represents a node and association measures between ROI-specific blood-oxygen-level-dependent (BOLD) time series are edges. Recently, graph neural networks (GNNs) have seen a surge in popularity due to their success in modelling unstructured relational data. The latest developments with GNNs, however, have not yet been fully exploited for the analysis of rs-fMRI data, particularly with regards to its spatio-temporal dynamics. In this paper, we present a novel deep neural network architecture which combines both GNNs and temporal convolutional networks (TCNs) in order to learn from both the spatial and temporal components of rs-fMRI data in an end-to-end fashion. In particular, this corresponds to intra-feature learning (i.e., learning temporal dynamics with TCNs) as well as inter-feature learning (i.e., leveraging interactions between ROI-wise dynamics with GNNs). We evaluate our model with an ablation study using 35,159 samples from the UK Biobank rs-fMRI database, as well as in the smaller Human Connectome Project (HCP) dataset, both in a unimodal and in a multimodal fashion. We also demonstrate that out architecture contains explainability-related features which easily map to realistic neurobiological insights. We suggest that this model could lay the groundwork for future deep learning architectures focused on leveraging the inherently and inextricably spatio-temporal nature of rs-fMRI data., 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 B.V.)

During aging, human white matter (WM) is subject to dynamic structural changes which have a deep impact on healthy and pathological evolution of the brain through the lifespan; characterizing this pattern is of key importance for understanding brain development, maturation, and aging as well as for studying its pathological alterations. Diffusion magnetic resonance imaging (MRI) can provide a quantitative assessment of the white-matter microstructural organization that characterizes these trajectories. Here, we use both conventional and advanced diffusion MRI in a cohort of 91 individuals (age range: 13-62 years) to study region- and sex-specific features of WM microstructural integrity in healthy aging. We focus on the age at which microstructural imaging parameters invert their development trend as the time point which marks the onset of microstructural decline in WM. Importantly, our results indicate that age-related brain changes begin earlier in males than females and affect more frontal regions-in accordance with evolutionary theories and numerous evidences across non-MRI domains. Advanced diffusion MRI reveals age-related WM modification patterns which cannot be detected using conventional diffusion tensor imaging., (Crown Copyright © 2019. Published by Elsevier Inc. All rights reserved.)

Primary open angle Glaucoma (POAG) is one of the most common causes of permanent blindness in the world. Recent studies have suggested the hypothesis that POAG is also a central nervous system disorder which may result in additional (i.e., extra-ocular) involvement. The aim of this study is to assess possible structural, whole-brain connectivity alterations in POAG patients. We evaluated 23 POAG patients and 15 healthy controls by combining multi-shell diffusion weighted imaging, multi-shell, multi-tissue probabilistic tractography, graph theoretical measures and a recently designed 'disruption index', which evaluates the global reorganization of brain networks. We also studied the associations between the whole-brain structural connectivity measures and indices of visual acuity including the field index (VFI) and two Optical Coherence Tomography (OCT) parameters, namely the Macula Ganglion Cell Layer (MaculaGCL) and Retinal Nerve Fiber Layer (RNFL) thicknesses. We found both global and local structural connectivity differences between POAG patients and controls, which extended well beyond the primary visual pathway and were localized in the left calcarine gyrus (clustering coefficient p = 0.036), left lateral occipital cortex (clustering coefficient p = 0.017, local efficiency p = 0.035), right lingual gyrus (clustering coefficient p = 0.009), and right paracentral lobule (clustering coefficient p = 0.009, local efficiency p = 0.018). Group-wise (clustering coefficient, p = 6.59∙10 -7 and local efficiency p = 6.23·10 -8 ) and subject-wise disruption indices (clustering coefficient, p = 0.018 and local efficiency, p = 0.01) also differed between POAG patients and controls. In addition, we found negative associations between RNFL thickness and local measures (clustering coefficient, local efficiency and strength) in the right amygdala (local efficiency p = 0.008, local strength p = 0.016), right inferior temporal gyrus (clustering coefficient p = 0.036, local efficiency p = 0.042), and right temporal pole (local strength p = 0.008). Overall, we show, in patients with POAG, a whole-brain structural reorganization that spans across a variety of brain regions involved in visual processing, motor control, and emotional/cognitive functions. We also identified a pattern of brain structural changes in relation to POAG clinical severity. Taken together, our findings support the hypothesis that the reduction in visual acuity from POAG can be driven by a combination of local (i.e., in the eye) and more extended (i.e., brain) effects., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Glaucoma is an optic neuropathy characterized by progressive loss of retinal ganglion cells with associated structural and functional changes of the optic nerve head and retinal nerve fiber layer. However, recent studies employing advanced neuroimaging techniques confirmed that glaucomatous damage is not limited to the eye but extends to the brain, affecting it also beyond the central visual pathways and disrupting brain network organization. We therefore posit that, while visual field changes play an important role in glaucoma-induced disability, central nervous pathways and mechanisms may play an important role in sustaining functional and daily living disability caused by the disease. Here we to summarize the current state of the art on the involvement of central brain circuits and possibly related disabilities in patients with glaucoma., Competing Interests: Disclosure statement The authors declare no potential conflicts of interest exist., (© 2020 Elsevier B.V. All rights reserved.)

Background and Aims: The aim of this study was to investigate possible associations among markers of mineralization, plaque instability and the main risk factors of atherosclerosis., Methods and Results: A Tissue MicroArray containing 52 samples of calcified carotid plaques from 52 symptomatic and asymptomatic patients were built. TMA serial sections were used to study the expression of inflammatory and mineralization markers (BMP-2, BMP-4, VDR, RANKL, Osteopontin, Sclerostin, β-catenin and calmodulin) by immunohistochemistry. Our data clearly demonstrated the expression of mineralization markers in atheromatic plaques. Indeed, with the exception of RANKL, all investigated markers were expressed in at least 60% of cases. Specifically, multivariate analysis displayed significant associations between both the expression of BMP-2 and the presence of unstable plaques as well as between the expression of β-catenin and the presence of stable plaques. We also found a significant inverse association between both a) the presence of hypertension and VDR and b) smoking habits and calmodulin expression. Finally, we noted a higher density of RANKL positive cells in plaques from diabetic patients as compared to non-diabetic ones and a significant positive association between hypertriglyceridemia and BMP-4 expression., Conclusion: Our results support the hypothesis that the process of atherosclerotic plaque calcification presents a number of similarities with the physiological processes that occur in bone, involving both osteoblasts- and osteoclasts-like arterial cells. Finally, the present study suggests that risk factors, such as hypertension, cigarette smoke and diabetes, can cause the destabilization of the atheromatic plaque acting on calcification process as well as inflammation., (Copyright © 2019 The Italian Society of Diabetology, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition, and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.)

Alzheimer's disease (AD) neuropathology is extremely heterogeneous, and the evolution from preclinical to mild cognitive impairment until dementia is driven by interacting genetic/biological mechanisms not fully captured by current clinical/research criteria. We characterized the heterogeneous "construct" of AD through a cerebrospinal fluid biomarker-guided stratification approach. We analyzed 5 validated pathophysiological cerebrospinal fluid biomarkers (Aβ 1-42 , t-tau, p-tau 181 , NFL, YKL-40) in 113 participants (healthy controls [N = 20], subjective memory complainers [N = 36], mild cognitive impairment [N = 20], and AD dementia [N = 37], age: 66.7 ± 10.4, 70.4 ± 7.7, 71.7 ± 8.4, 76.2 ± 3.5 years [mean ± SD], respectively) using Density-Based Spatial Clustering of Applications with Noise, which does not require a priori determination of the number of clusters. We found 5 distinct clusters (sizes: N = 38, 16, 24, 14, and 21) whose composition was independent of phenotypical groups. Two clusters showed biomarker profiles linked to neurodegenerative processes not associated with classical AD-related pathophysiology. One cluster was characterized by the neuroinflammation biomarker YKL-40. Combining nonlinear data aggregation with informative biomarkers can generate novel patient strata which are representative of cellular/molecular pathophysiology and may aid in predicting disease evolution and mechanistic drug response., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

According to the most recent epidemiological studies, breast cancer shows the highest incidence and the second leading cause of death in women. Cancer progression and metastasis are the main events related to poor survival of breast cancer patients. This can be explained by the presence of highly resistant to chemo- and radiotherapy stem cells in many breast tumor tissues. In this context, numerous studies highlighted the possible involvement of epithelial to mesenchymal transition phenomenon as biological program to generate cancer stem cells, and thus participate to both metastatic and drug resistance process. Therefore, the comprehension of mechanisms (both cellular and molecular) involved in breast cancer occurrence and progression can lay the foundation for the development of new diagnostic and therapeutical protocols. In this review, we reported the most important findings in the field of breast cancer highlighting the most recent data concerning breast tumor biology, diagnosis and therapy., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Background: Brainstem-focused mechanisms supporting transcutaneous auricular VNS (taVNS) effects are not well understood, particularly in humans. We employed ultrahigh field (7T) fMRI and evaluated the influence of respiratory phase for optimal targeting, applying our respiratory-gated auricular vagal afferent nerve stimulation (RAVANS) technique., Hypothesis: We proposed that targeting of nucleus tractus solitarii (NTS) and cardiovagal modulation in response to taVNS stimuli would be enhanced when stimulation is delivered during a more receptive state, i.e. exhalation., Methods: Brainstem fMRI response to auricular taVNS (cymba conchae) was assessed for stimulation delivered during exhalation (eRAVANS) or inhalation (iRAVANS), while exhalation-gated stimulation over the greater auricular nerve (GANctrl, i.e. earlobe) was included as control. Furthermore, we evaluated cardiovagal response to stimulation by calculating instantaneous HF-HRV from cardiac data recorded during fMRI., Results: Our findings demonstrated that eRAVANS evoked fMRI signal increase in ipsilateral pontomedullary junction in a cluster including purported NTS. Brainstem response to GANctrl localized a partially-overlapping cluster, more ventrolateral, consistent with spinal trigeminal nucleus. A region-of-interest analysis also found eRAVANS activation in monoaminergic source nuclei including locus coeruleus (LC, noradrenergic) and both dorsal and median raphe (serotonergic) nuclei. Response to eRAVANS was significantly greater than iRAVANS for all nuclei, and greater than GANctrl in LC and raphe nuclei. Furthermore, eRAVANS, but not iRAVANS, enhanced cardiovagal modulation, confirming enhanced eRAVANS response on both central and peripheral neurophysiological levels., Conclusion: 7T fMRI localized brainstem response to taVNS, linked such response with autonomic outflow, and demonstrated that taVNS applied during exhalation enhanced NTS targeting., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Proper placental development is crucial to establish a successful pregnancy. Defective placentation is the major cause of several pregnancy complications, including preeclampsia (PE). We have previously demonstrated that the secreted factor Epidermal Growth Factor-like Domain 7 (EGFL7) is expressed in trophoblast cells of the human placenta and that it regulates trophoblast migration and invasion, suggesting a role in placental development. In the present study, we demonstrate that circulating levels of EGFL7 are undetectable in nonpregnant women, increase during pregnancy and decline toward term. Close to term, circulating levels of EGFL7 are significantly higher in patients affected by PE when compared to normal pregnancies. Consistent with these results, villus explant cultures obtained from placentas affected by PE display increased release of EGFL7 in the culture medium when compared to those from normal placentas. Our results suggest that increased release of placenta-derived EGFL7 and increased circulating levels of EGFL7 are associated with the clinical manifestation of PE., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Irreversible white matter (WM) damage, including severe demyelination and axonal loss, is a main determinant of long-term disability in multiple sclerosis (MS). Non-invasive detection of changes in microstructural WM integrity in the disease is challenging since commonly used imaging metrics lack the necessary sensitivity, especially in the early phase of the disease. This study aims at assessing microstructural WM abnormalities in early-stage MS by using ultra-high gradient strength multi-shell diffusion MRI and the restricted signal fraction (FR) from the Composite Hindered and Restricted Model of Diffusion (CHARMED), a metric sensitive to the volume fraction of axons. In 22 early MS subjects (disease duration ≤5 years) and 15 age-matched healthy controls, restricted fraction estimates were obtained through the CHARMED model along with conventional Diffusion Tensor Imaging (DTI) metrics. All imaging parameters were compared cross-sectionally between the MS subjects and controls both in WM lesions and normal-appearing white matter (NAWM). We found a significant reduction in FR focally in WM lesions and widespread in the NAWM in MS patients relative to controls (corrected p < .05). Signal fraction changes in NAWM were not driven by perilesional tissue, nor were they influenced by proximity to the ventricles, challenging the hypothesis of an outside-in pathological process driven by CSF-mediated immune cytotoxic factors. No significant differences were found in conventional DTI parameters. In a cross-validated classification task, FR showed the largest effect size and outperformed all other diffusion imaging metrics in discerning lesions from contralateral NAWM. Taken together, our data provide evidence for the presence of widespread microstructural changes in the NAWM in early MS stages that are, at least in part, unrelated to focal demyelinating lesions. Interestingly, these pathological changes were not yet detectable by conventional diffusion imaging at this early disease stage, highlighting the sensitivity and value of multi-shell diffusion imaging for better characterizing axonal microstructure in MS., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: The development of bone metastasis from breast cancer results from a functional interaction between tumor cells and osteoclasts or osteoblasts. The main aim of this study was therefore to test the hypothesis that the appearance of breast osteoblast-like cells (BOLCs) in primary mammary lesions is a precursor (and hence an early predictor) of the formation of breast cancer metastases to bone., Patients and Methods: In this study, we collected 64 breast infiltrating carcinomas, 50 breast benignant lesions, and 10 biopsies of bone metastasis selected from patients with infiltrated carcinoma. Immunohistochemical, western blot, and ultrastructural analysis allowed us to investigate the presence of BOLCs in breast cancer lesions and metastatic sites., Results: We established the presence of a high amount of breast cancer cells that underwent mesenchymal transformation in infiltrating carcinomas. In addition, our results demonstrated that the microenvironment of breast cancer is very similar to the microenvironment of bone. We noted a significantly higher expression of BMP-2/4 and PTX3 in breast-infiltrating carcinomas compared with benign lesions. Moreover, we also identified numerous BOLCs positive to RANKL and Vitamin D receptor. Thanks to ultrastructural analysis, we also revealed the presence of BOLCs at the metastatic site., Conclusions: The identification of breast cancer cells with high affinity for a bone environment opens new perspectives on prevention and therapy of bone metastases from breast., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Objective: Previous studies have reported reduced cortical thickness and surface area and altered gyrification in frontal and temporal regions in adolescents with conduct disorder (CD). Although there is evidence that the clinical phenotype of CD differs between males and females, no studies have examined whether such sex differences extend to cortical and subcortical structure., Method: As part of a European multisite study (FemNAT-CD), structural magnetic resonance imaging (MRI) data were collected from 48 female and 48 male participants with CD and from 104 sex-, age-, and pubertal-status-matched controls (14-18 years of age). Data were analyzed using surface-based morphometry, testing for effects of sex, diagnosis, and sex-by-diagnosis interactions, while controlling for age, IQ, scan site, and total gray matter volume., Results: CD was associated with cortical thinning and higher gyrification in ventromedial prefrontal cortex in both sexes. Males with CD showed lower, and females with CD showed higher, supramarginal gyrus cortical thickness compared with controls. Relative to controls, males with CD showed higher gyrification and surface area in superior frontal gyrus, whereas the opposite pattern was seen in females. There were no effects of diagnosis or sex-by-diagnosis interactions on subcortical volumes. Results are discussed with regard to attention-deficit/hyperactivity disorder, depression, and substance abuse comorbidity, medication use, handedness, and CD age of onset., Conclusion: We found both similarities and differences between males and females in CD-cortical structure associations. This initial evidence that the pathophysiological basis of CD may be partly sex-specific highlights the need to consider sex in future neuroimaging studies and suggests that males and females may require different treatments., (Copyright © 2017 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: The hyperintensity of cerebral white matter (WM) in T2-weighted MR images of elderly subjects due to small vessel disease (SVD) is associated with variable clinical features including mild cognitive impairment (MCI), also termed subcortical vascular cognitive impairment (SVCI). The latter is typically characterized by psychomotor slowing, attention deficits, and executive dysfunctions. We hypothesized that functional brain changes might be associated with these distinctive cognitive deficits in patients with SVCI., Methods: Resting-state fMRI (rsfMRI) signal was assessed in conjunction with performance on the Montreal Cognitive Assessment battery (MoCA) and Stroop test in 67 subjects with MCI and moderate to severe extension of cerebral WM T2 hyperintensities qualifying for SVCI. We performed a whole-brain analysis of regional homogeneity (ReHo) of rsfMRI in conjunction with cognitive test scores., Results: We observed a significant (p<0.05) negative association between ReHo and MoCA scores, with higher ReHo in the left posterior cerebellum (crus I) of patients with greater global cognitive impairment, and a significant positive association between ReHo and Stroop scores, with higher ReHo in the middle cingulate cortex bilaterally of patients with worse executive functions., Conclusion: ReHo of rsfMRI is significantly correlated with measurements of the cognitive deficits which are distinctive of SVCI. The increased activity could have a maladaptive or compensatory significance towards specific aspects of cognition., (Copyright © 2016 Elsevier B.V. All rights reserved.)

The brain networks supporting nausea not yet understood. We previously found that while visual stimulation activated primary (V1) and extrastriate visual cortices (MT+/V5, coding for visual motion), increasing nausea was associated with increasing sustained activation in several brain areas, with significant co-activation for anterior insula (aIns) and mid-cingulate (MCC) cortices. Here, we hypothesized that motion sickness also alters functional connectivity between visual motion and previously identified nausea-processing brain regions. Subjects prone to motion sickness and controls completed a motion sickness provocation task during fMRI/ECG acquisition. We studied changes in connectivity between visual processing areas activated by the stimulus (MT+/V5, V1), right aIns and MCC when comparing rest (BASELINE) to peak nausea state (NAUSEA). Compared to BASELINE, NAUSEA reduced connectivity between right and left V1 and increased connectivity between right MT+/V5 and aIns and between left MT+/V5 and MCC. Additionally, the change in MT+/V5 to insula connectivity was significantly associated with a change in sympathovagal balance, assessed by heart rate variability analysis. No state-related connectivity changes were noted for the control group. Increased connectivity between a visual motion processing region and nausea/salience brain regions may reflect increased transfer of visual/vestibular mismatch information to brain regions supporting nausea perception and autonomic processing. We conclude that vection-induced nausea increases connectivity between nausea-processing regions and those activated by the nauseogenic stimulus. This enhanced low-frequency coupling may support continual, slowly evolving nausea perception and shifts toward sympathetic dominance. Disengaging this coupling may be a target for biobehavioral interventions aimed at reducing motion sickness severity., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Diffusional kurtosis imaging (DKI) has proven to be a promising diffusion-MRI technique whose first and most established applications are in neuroimaging. Recently, a number of preliminary studies have assessed the feasibility and potential usefulness of DKI in extra-cranial regions such as prostate, liver, kidney, bladder and breast. The stringent time constraints in most routine body MRI exams frequently mandate the acquisition of diffusion-weighted images (DWIs) with (only) three diffusion weighting directions (i.e. the main orthogonal directions). The aim of this study was to evaluate the potential error introduced in the estimation of the average of the three directional diffusional kurtosis values (K) by using, for each b-value, the geometric mean (trace-weighted image) of acquired DWIs (as is common practice in most diffusion-MRI studies of the body) instead of fitting the DKI model to DWIs acquired along each direction prior to averaging. By solving the DKI model analytically while imposing three orthogonal diffusion weighting directions and two non-null b-values (800 and 2000s/mm(2)), extensive simulations were performed for different K values (0-3) and a wide range of diffusion anisotropy values. The error in the estimates of K induced by geometrical averaging of DWIs was assessed and compared to the uncertainty in K caused by DWIs noise for low (20), medium (40) and high (80) signal-to-noise ratio (SNR) values. The simulations showed that geometrical averaging of the DWIs introduces a noticeable error in estimated K. While the error in K varies non-monotonically with K and with the degree of diffusion anisotropy, there is a trend of increasing absolute error with both increasing K and increasing degree of diffusion anisotropy. In particular, for values of K close to 1 and low/moderate (0-0.4) diffusion anisotropy degrees (typical of various body tissues), the absolute error in K can range up to 60% of K. In this case, at all SNR values (20, 40, 80), the absolute error in K can be greater than the uncertainty introduced by noise. In clinical body applications of DKI, the widespread and growing practice of using trace-weighted images to estimate K can introduce a substantial error, hence hampering interpretation of results as well as multi-center comparisons, and should therefore be avoided., (Copyright © 2015 Elsevier Inc. All rights reserved.)

The ability to image the whole brain through ever more subtle and specific methods/contrasts has come to play a key role in understanding the basis of brain abnormalities in several diseases. In magnetic resonance imaging (MRI), "diffusion" (i.e. the random, thermally-induced displacements of water molecules over time) represents an extraordinarily sensitive contrast mechanism, and the exquisite structural detail it affords has proven useful in a vast number of clinical as well as research applications. Since diffusion-MRI is a truly quantitative imaging technique, the indices it provides can serve as potential imaging biomarkers which could allow early detection of pathological alterations as well as tracking and possibly predicting subtle changes in follow-up examinations and clinical trials. Accordingly, diffusion-MRI has proven useful in obtaining information to better understand the microstructural changes and neurophysiological mechanisms underlying various neurodegenerative disorders. In this review article, we summarize and explore the main applications, findings, perspectives as well as challenges and future research of diffusion-MRI in various neurodegenerative disorders including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, Huntington's disease and degenerative ataxias., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Purpose: Previous studies have reported changes in gray matter volume in youths with conduct disorder (CD), although these differences are difficult to interpret as they may have been driven by alterations in cortical thickness, surface area (SA), or folding. The objective of this study was to use surface-based morphometry (SBM) methods to compare male youths with CD and age and sex-matched healthy controls (HCs) in cortical thickness, SA, and folding. We also tested for structural differences between the childhood-onset and adolescence-onset subtypes of CD and performed regression analyses to assess for relationships between CD symptoms and callous-unemotional (CU) traits and SBM-derived measures., Methods: We acquired structural neuroimaging data from 20 HCs and 36 CD participants (18 with childhood-onset CD and 18 with adolescence-onset CD) and analyzed the data using FreeSurfer., Results: Relative to HCs, youths with CD showed reduced cortical thickness in the superior temporal gyrus, reduced SA in the orbitofrontal cortex (OFC), and increased cortical folding in the insula. There were no significant differences between the childhood-onset and adolescence-onset CD subgroups in cortical thickness or SA, but several frontal and temporal regions showed increased cortical folding in childhood-onset relative to adolescence-onset CD participants. Both CD subgroups also showed increased cortical folding relative to HCs. CD symptoms were negatively correlated with OFC SA whereas CU traits were positively correlated with insula folding., Conclusions: Cortical thinning in the superior temporal gyrus may contribute to the social cognitive impairments displayed by youths with CD, whereas reduced OFC SA may lead to impairments in emotion regulation and reward processing in youths with CD. The increased cortical folding observed in the insula may reflect a maturational delay in this region and could mediate the link between CU traits and empathy deficits. Altered cortical folding was observed in childhood-onset and adolescence-onset forms of CD.

Recent advances in Magnetic Resonance Imaging (MRI) technology have brought new insight in central nervous system (CNS) manifestation of glaucoma. New MR techniques allowed to identify in vivo and noninvasively alterations along all the visual pathway in both early and late stages of the disease. Conventional neuroimaging still plays an important role, mostly in the anatomy description and in the differential diagnosis with space occupying lesions but it should be supported by other advanced MR techniques such as diffusion tensor imaging, functional imaging (BOLD-ASL), and magnetic resonance spectroscopy, which offer the possibility to investigate deep white matter tracts integrity and cortical gray matter changes. In a future perspective, MR quantification of CNS damage associated with glaucoma will be of pivotal importance for prognostic stratification and evaluation of neuroprotective therapy response., (© 2015 Elsevier B.V. All rights reserved.)

The periaqueductal gray (PAG), a brain area belonging to the descending pain modulatory system, plays a crucial role in pain perception. Little information is available on the relationship between PAG activation and perceived pain intensity. In this study, we acquired functional magnetic resonance imaging (fMRI) scans from the PAG during the cold pressor test, a model for tonic pain, in 12 healthy volunteers. fMRI data were acquired with a 12-channel head-coil and a 3-Tesla scanner and analyzed with Statistical Parametric Mapping (SPM8) software. During the cold pressor test, fMRI showed significant activation clusters in pain-related brain areas: bilateral middle and superior frontal gyrus, anterior cingulate cortex and thalamus, left insula, right inferior frontal gyrus, left inferior temporal gyrus and in the bilateral PAG (cluster level corrected threshold p<0.05). PAG activation correlated directly with the pain threshold and inversely with the participant's perceived pain intensity (cluster level corrected threshold (p<0.05). The cold pressor test consistently activated the PAG as well as other pain-related areas in the brain. Our study, showing that the greater the PAG activation the higher the pain threshold and the weaker the pain intensity perceived, highlights the key role of the PAG in inhibiting the pain afferent pathway function. Our findings might be useful for neuroimaging studies investigating PAG activation in patients with chronic idiopathic pain conditions possibly related to dysfunction in the descending pain modulatory system., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Background: Repetitive transcranial magnetic stimulation is increasingly used as a therapeutic tool in psychiatry and has been demonstrated to attenuate the activity of the stress hormone system. Stress-induced structural remodeling in the adult hippocampus may provide a cellular basis for understanding the impairment of neural plasticity in depressive illness. Accordingly, reversal of structural remodeling might be a desirable goal for antidepressant therapy. The present study investigated the effect of chronic psychosocial stress and concomitant repetitive transcranial magnetic stimulation treatment on stress hormone regulation and hippocampal neurogenesis., Methods: Adult male rats were submitted to daily psychosocial stress and repetitive transcranial magnetic stimulation (20 Hz) for 18 days. Cell proliferation in the dentate gyrus was quantified by using BrdU immunohistochemistry, and both the proliferation rate of progenitors and the survival rate of BrdU-labeled cells were evaluated. To characterize the activity of the hypothalamic-pituitary-adrenocortical system, plasma corticotropin and corticosterone concentrations were measured., Results: Chronic psychosocial stress resulted in a significant increase of stress hormone levels and potently suppressed the proliferation rate and survival of the newly generated hippocampal granule cells. Concomitant repetitive transcranial magnetic stimulation treatment normalized the stress-induced elevation of stress hormones; however, despite the normalized activity of the hypothalamic-pituitary-adrenocortical system, the decrement of hippocampal cell proliferation was only mildly attenuated by repetitive transcranial magnetic stimulation, while the survival rate of BrdU-labeled cells was further suppressed by the treatment., Conclusions: These results support the notion that attenuation of the hypothalamic-pituitary-adrenocortical system is an important mechanism underlying the clinically observed antidepressant effect of repetitive transcranial magnetic stimulation, whereas this experimental design did not reveal beneficial effects of repetitive transcranial magnetic stimulation on adult hippocampal neurogenesis.