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Objective: Our aim was to map the in vivo human functional connectivity of several brainstem nuclei with the rest of the brain by using seed-based correlation of ultra-high magnetic field functional magnetic resonance imaging (fMRI) data., Materials and Methods: We used the recently developed template of 11 brainstem nuclei derived from multi-contrast structural MRI at 7 Tesla as seed regions to determine their connectivity to the rest of the brain. To achieve this, we used the increased contrast-to-noise ratio of 7-Tesla fMRI compared with 3 Tesla and time-efficient simultaneous multi-slice imaging to cover the brain with high spatial resolution (1.1-mm isotropic nominal resolution) while maintaining a short repetition time (2.5 s)., Results: The delineated Pearson's correlation-based functional connectivity diagrams (connectomes) of 11 brainstem nuclei of the ascending arousal, motor, and autonomic systems from 12 controls are presented and discussed in the context of existing histology and animal work., Conclusion: Considering that the investigated brainstem nuclei play a crucial role in several vital functions, the delineated preliminary connectomes might prove useful for future in vivo research and clinical studies of human brainstem function and pathology, including disorders of consciousness, sleep disorders, autonomic disorders, Parkinson's disease, and other motor disorders.

Through their dynamical interplay, the brain and the heart ensure fundamental homeostasis and mediate a number of physiological functions as well as their disease-related aberrations. Although a vast number of ad hoc analytical and computational tools have been recently applied to the non-invasive characterization of brain and heart dynamic functioning, little attention has been devoted to combining information to unveil the interactions between these two physiological systems. This theme issue collects contributions from leading experts dealing with the development of advanced analytical and computational tools in the field of biomedical signal and image processing. It includes perspectives on recent advances in 7 T magnetic resonance imaging as well as electroencephalogram, electrocardiogram and cerebrovascular flow processing, with the specific aim of elucidating methods to uncover novel biological and physiological correlates of brain-heart physiology and physiopathology., (© 2016 The Author(s).)

The causal, directed interactions between brain regions at rest (brain-brain networks) and between resting-state brain activity and autonomic nervous system (ANS) outflow (brain-heart links) have not been completely elucidated. We collected 7 T resting-state functional magnetic resonance imaging (fMRI) data with simultaneous respiration and heartbeat recordings in nine healthy volunteers to investigate (i) the causal interactions between cortical and subcortical brain regions at rest and (ii) the causal interactions between resting-state brain activity and the ANS as quantified through a probabilistic, point-process-based heartbeat model which generates dynamical estimates for sympathetic and parasympathetic activity as well as sympathovagal balance. Given the high amount of information shared between brain-derived signals, we compared the results of traditional bivariate Granger causality (GC) with a globally conditioned approach which evaluated the additional influence of each brain region on the causal target while factoring out effects concomitantly mediated by other brain regions. The bivariate approach resulted in a large number of possibly spurious causal brain-brain links, while, using the globally conditioned approach, we demonstrated the existence of significant selective causal links between cortical/subcortical brain regions and sympathetic and parasympathetic modulation as well as sympathovagal balance. In particular, we demonstrated a causal role of the amygdala, hypothalamus, brainstem and, among others, medial, middle and superior frontal gyri, superior temporal pole, paracentral lobule and cerebellar regions in modulating the so-called central autonomic network (CAN). In summary, we show that, provided proper conditioning is employed to eliminate spurious causalities, ultra-high-field functional imaging coupled with physiological signal acquisition and GC analysis is able to quantify directed brain-brain and brain-heart interactions reflecting central modulation of ANS outflow., (© 2016 The Author(s).)

The influence of cardiac activity on the viscoelastic properties of intracranial tissue is one of the mechanisms through which brain-heart interactions take place, and is implicated in cerebrovascular disease. Cerebrovascular disease risk is not fully explained by current risk factors, including arterial compliance. Cerebrovascular compliance is currently estimated indirectly through Doppler sonography and magnetic resonance imaging (MRI) measures of blood velocity changes. In order to meet the need for novel cerebrovascular disease risk factors, we aimed to design and validate an MRI indicator of cerebrovascular compliance based on direct endogenous measures of blood volume changes. We implemented a fast non-gated two-dimensional MRI pulse sequence based on echo-planar imaging (EPI) with ultra-short repetition time (approx. 30-50 ms), which stepped through slices every approximately 20 s. We constrained the solution of the Bloch equations for spins moving faster than a critical speed to produce an endogenous contrast primarily dependent on spin volume changes, and an approximately sixfold signal gain compared with Ernst angle acquisitions achieved by the use of a 90° flip angle. Using cardiac and respiratory peaks detected on physiological recordings, average cardiac and respiratory MRI pulse waveforms in several brain compartments were obtained at 7 Tesla, and used to derive a compliance indicator, the pulsatility volume index (pVI). The pVI, evaluated in larger cerebral arteries, displayed significant variation within and across vessels. Multi-echo EPI showed the presence of significant pulsatility effects in both S0 and [Formula: see text] signals, compatible with blood volume changes. Lastly, the pVI dynamically varied during breath-holding compared with normal breathing, as expected for a compliance indicator. In summary, we characterized and performed an initial validation of a novel MRI indicator of cerebrovascular compliance, which might prove useful to investigate brain-heart interactions in cerebrovascular disease and other disorders., (© 2016 The Author(s).)

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.)

Purpose: An increasing number of studies have aimed to compare diffusion tensor imaging (DTI)-related parameters [e.g., mean diffusivity (MD), fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD)] to complementary new indexes [e.g., mean kurtosis (MK)/radial kurtosis (RK)/axial kurtosis (AK)] derived through diffusion kurtosis imaging (DKI) in terms of their discriminative potential about tissue disease-related microstructural alterations. Given that the DTI and DKI models provide conceptually and quantitatively different estimates of the diffusion tensor, which can also depend on fitting routine, the aim of this study was to investigate model- and algorithm-dependent differences in MD/FA/RD/AD and anisotropy mode (MO) estimates in diffusion-weighted imaging of human brain white matter., Methods: The authors employed (a) data collected from 33 healthy subjects (20-59 yr, F: 15, M: 18) within the Human Connectome Project (HCP) on a customized 3 T scanner, and (b) data from 34 healthy subjects (26-61 yr, F: 5, M: 29) acquired on a clinical 3 T scanner. The DTI model was fitted to b-value =0 and b-value =1000 s/mm(2) data while the DKI model was fitted to data comprising b-value =0, 1000 and 3000/2500 s/mm(2) [for dataset (a)/(b), respectively] through nonlinear and weighted linear least squares algorithms. In addition to MK/RK/AK maps, MD/FA/MO/RD/AD maps were estimated from both models and both algorithms. Using tract-based spatial statistics, the authors tested the null hypothesis of zero difference between the two MD/FA/MO/RD/AD estimates in brain white matter for both datasets and both algorithms., Results: DKI-derived MD/FA/RD/AD and MO estimates were significantly higher and lower, respectively, than corresponding DTI-derived estimates. All voxelwise differences extended over most of the white matter skeleton. Fractional differences between the two estimates [(DKI - DTI)/DTI] of most invariants were seen to vary with the invariant value itself as well as with MK/RK/AK values, indicating substantial anatomical variability of these discrepancies. In the HCP dataset, the median voxelwise percentage differences across the whole white matter skeleton were (nonlinear least squares algorithm) 14.5% (8.2%-23.1%) for MD, 4.3% (1.4%-17.3%) for FA, -5.2% (-48.7% to -0.8%) for MO, 12.5% (6.4%-21.2%) for RD, and 16.1% (9.9%-25.6%) for AD (all ranges computed as 0.01 and 0.99 quantiles). All differences/trends were consistent between the discovery (HCP) and replication (local) datasets and between estimation algorithms. However, the relationships between such trends, estimated diffusion tensor invariants, and kurtosis estimates were impacted by the choice of fitting routine., Conclusions: Model-dependent differences in the estimation of conventional indexes of MD/FA/MO/RD/AD can be well beyond commonly seen disease-related alterations. While estimating diffusion tensor-derived indexes using the DKI model may be advantageous in terms of mitigating b-value dependence of diffusivity estimates, such estimates should not be referred to as conventional DTI-derived indexes in order to avoid confusion in interpretation as well as multicenter comparisons. In order to assess the potential and advantages of DKI with respect to DTI as well as to standardize diffusion-weighted imaging methods between centers, both conventional DTI-derived indexes and diffusion tensor invariants derived by fitting the non-Gaussian DKI model should be separately estimated and analyzed using the same combination of fitting routines.

Background and Purpose: Imaging biomarkers of disease progression are desirable in inherited ataxias. MRI has demonstrated brain damage in Friedreich ataxia (FRDA) in form of regional atrophy of the medulla, peridentate cerebellar white matter (WM) and superior cerebellar peduncles (visible in T1-weighted images) and of change of microstructural characteristics of WM tracts of the brainstem, cerebellar peduncles, cerebellum, and supratentorial structures (visible through diffusion-weighted imaging). We explored the potential of brain MR morphometry and diffusion tensor imaging (DTI) to track the progression of neurodegeneration in FRDA., Methods: Eight patients (5F, 3M; age 13.4-41.2 years) and 8 healthy controls (2F, 6M; age 26.2-48.3 years) underwent 2 MRI examinations (mean 3.9 and 4.1 years apart, respectively) on the same 1.5T scanner. The protocol included 3D T1-weighted images and axial diffusion-weighted images (b-value 1,000 s/mm(2)) for calculating maps of fractional anisotropy, mean, axial and radial diffusivity, and mode of anisotropy. Tensor-based morphometry was used to investigate regional volume changes and tract-based spatial statistics was used to investigate microstructural changes in WM tracts., Results: Longitudinal analyses showed no differences in regional volume changes but a significant difference in axial diffusivity changes in cerebral and corpus callosum WM of patients as compared to controls (mean longitudinal rate of change for axial diffusivity: -.02 × 10(-3) mm(2)/s/year in patients vs. .01 × 10(-3) mm(2)/s/year in controls). No correlation with number of triplets, disease duration, and worsening of the clinical deficit was observed., Conclusion: DTI can track brain microstructural changes in FRDA and can be considered a potential biomarker of disease progression., (Copyright © 2015 by the American Society of Neuroimaging.)

Objective: To compare heart rate variability (HRV) parameters in newly diagnosed and untreated temporal lobe epilepsy (TLE) between the interictal, preictal, ictal, and postictal states., Methods: HRV parameters were extracted from single-lead electrocardiography data collected during video-electroencephalography (EEG) recordings from 14 patients with newly diagnosed TLE in a resting, awake, and supine state. HRV parameters in the time and frequency domains included low frequency (LF), high frequency (HF), standard deviation of all consecutive R wave intervals (SDNN), and square root of the mean of the sum of the squares of differences between adjacent R wave intervals (RMSSD). Cardiovagal index (CVI), cardiosympathetic index (CSI), and approximate entropy (ApEn) were also studied., Results: Frequency domain analysis showed significantly higher preictal, ictal, and postictal LF/HF ratio compared to the interictal state. Similarly, the LF component increased progressively and was significantly higher during the ictal state compared to interictal and preictal states. RR interval values were lower in the ictal state compared to basal and preictal states and in the postictal state compared to the preictal state. Interictal RMSSD was significantly higher compared to all other states, and ictal SDNN was significantly higher compared to all other states. Ictal CSI was significantly higher compared to preictal and interictal states, whereas preictal CVI was lower than in basal and ictal states. In addition, ictal ApEn was significantly lower than interictal and preictal ApEn. Interictal CVI was lower in left TLE compared to right TLE. In addition, in left TLE, ictal CVI was higher than interictal CVI, whereas in right TLE, CVI was lower in the preictal state compared to all other states., Significance: Our data suggest an ictal sympathetic overdrive with partial recovery in the postictal state. Higher sympathetic tone and vagal tone imbalance may induce early autonomic dysfunction and increase cardiovascular risk in patients affected by TLE., (Wiley Periodicals, Inc. © 2016 International League Against Epilepsy.)

Background and Purpose: Parkinson's disease (PD) is a progressive neurodegenerative disorder with motor and non-motor symptoms, including cognitive deficits. Several magnetic resonance imaging approaches have been applied to investigate brain atrophy in PD. The aim of this study was to detect early structural cortical and subcortical changes in de novo PD whilst distinguishing cognitive status, clinical phenotype and motor laterality., Methods: Eighteen de novo PD with mild cognitive impairment (PD-MCI), 18 de novo PD without MCI (PD-NC) and 18 healthy control subjects were evaluated. In the PD-MCI group, nine were tremor dominant and nine were postural instability gait disorder (PIGD) phenotype; 11 had right-sided symptom dominance and seven had left-sided symptom dominance. FreeSurfer was used to measure cortical thickness/folding, subcortical structures and to study group differences as well as the association with clinical and neuropsychological data., Results: Parkinson's disease with MCI showed regional thinning in the right frontal, right middle temporal areas and left insula compared to PD-NC. A reduction of the volume of the left and right thalamus and left hippocampus was found in PD-MCI compared to PD-NC. PD-MCI PIGD showed regional thinning in the right inferior parietal area compared to healthy controls. A decreased volume of the left thalamus was reported in PD-MCI with right-sided symptom dominance compared to PD-NC and PD-MCI with left-sided symptom dominance., Conclusions: When MCI was present, PD patients showed a fronto-temporo-parietal pattern of cortical thinning. This cortical pattern does not appear to be influenced by motor laterality, although one-sided symptom dominance may contribute to volumetric reduction of specific subcortical structures., (© 2015 EAN.)

Brainstem nuclei (Bn) in humans play a crucial role in vital functions, such as arousal, autonomic homeostasis, sensory and motor relay, nociception, sleep, and cranial nerve function, and they have been implicated in a vast array of brain pathologies. However, an in vivo delineation of most human Bn has been elusive because of limited sensitivity and contrast for detecting these small regions using standard neuroimaging methods. To precisely identify several human Bn in vivo, we employed a 7 Tesla scanner equipped with multi-channel receive-coil array, which provided high magnetic resonance imaging sensitivity, and a multi-contrast (diffusion fractional anisotropy and T2-weighted) echo-planar-imaging approach, which provided complementary contrasts for Bn anatomy with matched geometric distortions and resolution. Through a combined examination of 1.3 mm(3) multi-contrast anatomical images acquired in healthy human adults, we semi-automatically generated in vivo probabilistic Bn labels of the ascending arousal (median and dorsal raphe), autonomic (raphe magnus, periaqueductal gray), and motor (inferior olivary nuclei, two subregions of the substantia nigra compatible with pars compacta and pars reticulata, two subregions of the red nucleus, and, in the diencephalon, two subregions of the subthalamic nucleus) systems. These labels constitute a first step toward the development of an in vivo neuroimaging template of Bn in standard space to facilitate future clinical and research investigations of human brainstem function and pathology. Proof-of-concept clinical use of this template is demonstrated in a minimally conscious patient with traumatic brainstem hemorrhages precisely localized to the raphe Bn involved in arousal.

There is evolving evidence that individuals categorized with subjective cognitive decline (SCD) are potentially at higher risk for developing objective and progressive cognitive impairment compared to cognitively healthy individuals without apparent subjective complaints. Interestingly, SCD, during advancing preclinical Alzheimer's disease (AD), may denote very early, subtle cognitive decline that cannot be identified using established standardized tests of cognitive performance. The substantial heterogeneity of existing SCD-related research data has led the Subjective Cognitive Decline Initiative (SCD-I) to accomplish an international consensus on the definition of a conceptual research framework on SCD in preclinical AD. In the area of biological markers, the cerebrospinal fluid signature of AD has been reported to be more prevalent in subjects with SCD compared to healthy controls; moreover, there is a pronounced atrophy, as demonstrated by magnetic resonance imaging, and an increased hypometabolism, as revealed by positron emission tomography, in characteristic brain regions affected by AD. In addition, SCD individuals carrying an apolipoprotein ɛ4 allele are more likely to display AD-phenotypic alterations. The urgent requirement to detect and diagnose AD as early as possible has led to the critical examination of the diagnostic power of biological markers, neurophysiology, and neuroimaging methods for AD-related risk and clinical progression in individuals defined with SCD. Observational studies on the predictive value of SCD for developing AD may potentially be of practical value, and an evidence-based, validated, qualified, and fully operationalized concept may inform clinical diagnostic practice and guide earlier designs in future therapy trials.

Glioblastoma multiforme (GBM) is the most common and deadliest primary brain tumor, driving patients to death within 15 months after diagnosis (short term survivors, ST), with the exception of a small fraction of patients (long term survivors, LT) surviving longer than 36 months. Here we present deep sequencing data showing that peritumoral (P) areas differ from healthy white matter, but share with their respective frankly tumoral (C) samples, a number of mRNAs and microRNAs representative of extracellular matrix remodeling, TGFβ and signaling, of the involvement of cell types different from tumor cells but contributing to tumor growth, such as microglia or reactive astrocytes. Moreover, we provide evidence about RNAs differentially expressed in ST vs LT samples, suggesting the contribution of TGF-β signaling in this distinction too. We also show that the edited form of miR-376c-3p is reduced in C vs P samples and in ST tumors compared to LT ones. As a whole, our study provides new insights into the still puzzling distinction between ST and LT tumors, and sheds new light onto that "grey" zone represented by the area surrounding the tumor, which we show to be characterized by the expression of several molecules shared with the proper tumor mass.

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.)

Liver transplantation remains the only curative treatment option for a variety of end-stage liver diseases. Prediction of major adverse events following surgery has traditionally focused on static predictors that are known prior to surgery. The effects of intraoperative management can now be explored due to the archiving of high-resolution monitoring data. We extracted intraoperative hemodynamic trend data of 55 patients undergoing orthotopic liver transplantation (OLT) and computed 12 features from the systolic arterial blood pressure (ABP), cardiac index, central venous pressure (CVP), and stroke volume variation (SVV) signals. Using a logistic regression classifier with a leave-one-out cross-validation procedure, we selected subsets of these features to predict mortality up to 180 days after surgery. Best performance was achieved with a combination of 3 features - median absolute deviation (MAD) of ABP, median CVP, and time spent with SVV <; 10% - reaching an area under the receiver-operating characteristic (or c-statistic) of 0.808. Odds ratios (OR) computed from the coefficients of the multivariate logistic regression model constructed from these features showed that greater time spent with SVV <; 10% (OR = 0.981 min(-1), p = 0.001) and greater MAD of systolic ABP (OR = 0.696 mmHg(-1), p = 0.026) were significantly associated with survival. Adding preoperative measures such as age and serum concentrations of albumin, bilirubin, and creatinine failed to improve performance of the prediction model. These results show that the course of intraoperative hemodynamics can predict 180-day mortality after OLT.

We used 7T fMRI with simultaneous physiological signals acquisitions to investigate the causal interactions from resting state brain activity to autonomic nervous system (ANS) outflow as quantified through a probabilistic heartbeat model. Given the highly redundant nature of brain-derived signals, we compare the results of traditional bivariate Granger Causality (GC) to a globally conditioned approach which evaluates the additional influence of each brain region on ANS activity while factoring out effects concomitantly mediated by other brain regions. The bivariate approach results in an unrealistically large number of spurious causal brain-heart links. In contrast, using the globally conditioned approac, we demonstrate the existence of significant selective causal links between cortical/subcortical brain regions and ANS outflow for sympathetic and parasympathetic modulation as well as sympathovagal balance, with a prominent involvement of frontal, parietal, and cerebellar regions and Sensory Motor, Default Mode, Left and Right executive networks. Provided proper conditioning is employed to eliminate spurious causalities, 7T functional imaging coupled with physiological signal acquisition and GC analysis is able to quantify directed brain-heart interactions reflecting central modulation of ANS outflow.

Vascular mild cognitive impairment (VMCI) is a disorder in which multimodal MRI can add significant value by combining diffusion tensor imaging (DTI) with brain morphometry. In this study we implemented and compared machine learning techniques for multimodal classification between 58 VMCI patients and 29 healthy subjects as well as for discrimination (within the VMCI group) between patients with different cognitive performances. For each subject, a cortical feature vector was constructed based on cortical parcellation and cortical and subcortical volumetric segmentation and a DTI feature vector was formed by combining descriptive statistical metrics related to the distribution of DTI invariants within white matter. We employed both a sequential minimal optimization and a functional tree classifier, using feature selection and 10-fold cross-validation, and compared their performances in monomodal and multimodal classification for both classification problems (healthy subjects vs VMCI and prediction of cognitive performance). While monomodal classification resulted in satisfactory performance in most cases, turning from monomodal to multimodal classification resulted in an improvement of the performance in the discrimination between VMCI patients with low cognitive performance and healthy subjects by up to 10% in sensitivity (leaving specificity unchanged). We therefore are able to confirm the usefulness of machine learning techniques in discriminating diseased states based on neuroimaging data.

Background: Major depression (MD) is a common psychiatric disorder in multiple sclerosis (MS). Despite the negative impact of MD on the quality of life of MS patients, little is known about its underlying brain mechanisms., Objective: We studied the whole-brain connectivity patterns that were associated with MD in MS. Alterations were mainly expected within limbic circuits., Methods: Diffusion tensor imaging data were collected in 20 MS patients with MD, 22 non-depressed MS patients and 16 healthy controls. We used deterministic tractography and graph analysis to study the white-matter connectivity patterns that characterized MS patients with MD., Results: We found that MD in MS was associated with increased local path length in the right hippocampus and right amygdala. Further analyses revealed that these effects were driven by an increased shortest distance between both the right hippocampus and right amygdala and a series of regions including the dorsolateral and ventrolateral prefrontal cortex, orbitofrontal cortex, sensory-motor cortices and supplementary motor area., Conclusion: Our data provide strong support for neurobiological accounts positing that MD in MS is mediated by abnormal 'communications' within limbic circuits. We also found evidence that MD in MS may be linked with connectivity alterations at the limbic-motor interface, a group of regions that translates emotions into survival-oriented behaviors., (© The Author(s), 2015.)

Background and Purpose: The ability of DTI to track the progression of microstructural damage in patients with inherited ataxias has not been explored so far. We performed a longitudinal DTI study in patients with spinocerebellar ataxia type 2., Materials and Methods: Ten patients with spinocerebellar ataxia type 2 and 16 healthy age-matched controls were examined twice with DTI (mean time between scans, 3.6 years [patients] and 3.3 years [controls]) on the same 1.5T MR scanner. Using tract-based spatial statistics, we analyzed changes in DTI-derived indices: mean diffusivity, axial diffusivity, radial diffusivity, fractional anisotropy, and mode of anisotropy., Results: At baseline, the patients with spinocerebellar ataxia type 2, as compared with controls, showed numerous WM tracts with significantly increased mean diffusivity, axial diffusivity, and radial diffusivity and decreased fractional anisotropy and mode of anisotropy in the brain stem, cerebellar peduncles, cerebellum, cerebral hemisphere WM, corpus callosum, and thalami. Longitudinal analysis revealed changes in axial diffusivity and mode of anisotropy in patients with spinocerebellar ataxia type 2 that were significantly different than those in the controls. In patients with spinocerebellar ataxia type 2, axial diffusivity was increased in WM tracts of the right cerebral hemisphere and the corpus callosum, and the mode of anisotropy was extensively decreased in hemispheric cerebral WM, corpus callosum, internal capsules, cerebral peduncles, pons and left cerebellar peduncles, and WM of the left paramedian vermis. There was no correlation between the progression of changes in DTI-derived indices and clinical deterioration., Conclusions: DTI can reveal the progression of microstructural damage of WM fibers in the brains of patients with spinocerebellar ataxia type 2, and mode of anisotropy seems particularly sensitive to such changes. These results support the potential of DTI-derived indices as biomarkers of disease progression., (© 2015 by American Journal of Neuroradiology.)

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.

Introduction: Kennedy's disease (KD) is a progressive degenerative disorder affecting lower motor neurons. We investigated the correlation between disease severity and whole brain white matter microstructure, including upper motor neuron tracts, by using diffusion-tensor imaging (DTI) in eight patients with KD in whom disease severity was evaluated using the Amyotrophic Lateral Sclerosis Functional Rating Scale (ALSFRS)., Methods: From DTI acquisitions we obtained maps of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (L1) and radial diffusivities (L2, L3). We then employed tract-based spatial statistics (TBSS) to investigate within-patient correlations of DTI invariants with ALSFRS and disease duration (DD)., Results: We found a significant correlation between low ALSFRS and 1) low FA values in association commissural and projection fibers, and 2) high L3 values in commissural tracts and fronto-parietal white matter. Additionally, we found a significant association between longer DD and 1) low FA in the genu and body of corpus callosum, association fibers and midbrain and 2) high L1 in projection and association tracts., Conclusions: The associations between clinical variables and white matter microstructural changes in areas thought to be spared by the disease process support the hypothesis of a multisystem involvement in the complex pathogenic mechanisms responsible for the clinical disability of these patients., (© The Author(s) 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.)

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.)

Background and Purpose: Montreal Cognitive Assessment (MoCA) has been proposed as a screening tool in vascular cognitive impairment. Diffusion tensor imaging is sensitive to white matter microstructural damage. We investigated if diffusion tensor imaging-derived indices are more strongly associated with performances on MoCA or on the widely used mini mental state examination in patients with mild cognitive impairment and small vessel disease., Methods: Mild cognitive impairment patients with moderate/severe degrees of white matter hyperintensities on MRI were enrolled. Lacunar infarcts, cortical atrophy, medial temporal lobe atrophy and median values of mean diffusivity and fractional anisotropy of the cerebral white matter were studied and correlated with cognitive tests performances., Results: Seventy-six patients (mean age 75.1±6.8 years, mean years of education 8.0±4.3) were assessed. In univariate analyses, a significant association of both MoCA and mini mental state examination scores with age, education, cortical atrophy, and medial temporal lobe atrophy was found, whereas mean diffusivity and fractional anisotropy were associated with MoCA. In partial correlation analyses, adjusting for all demographic and neuroimaging variables, both mean diffusivity and fractional anisotropy were associated only with MoCA (mean diffusivity: r= -0.275, P=0.023; fractional anisotropy: r=0.246, P=0.043)., Conclusions: In patients with mild cognitive impairment and small vessel disease, diffusion tensor imaging-measured white matter microstructural damage is more related to MoCA than mini mental state examination performances. MoCA is suited for the cognitive screening of patients with small vessel disease., (© 2014 American Heart Association, Inc.)

The presence of brain atrophy and its progression in early Parkinson's disease (PD) are still a matter of debate, particularly in patients without cognitive impairment. The aim of this longitudinal study was to assess whether PD patients who remain cognitively intact develop progressive atrophic changes in the early stages of the disease. For this purpose, we employed high-resolution T1-weighted MR imaging to compare 22 drug-naïve de novo PD patients without cognitive impairment to 17 age-matched control subjects, both at baseline and at three-year follow-up. We used tensor-based morphometry to explore the presence of atrophic changes at baseline and to compute yearly atrophy rates, after which we performed voxel-wise group comparisons using threshold-free cluster enhancement. At baseline, we did not observe significant differences in regional atrophy in PD patients with respect to control subjects. In contrast, PD patients showed significantly higher yearly atrophy rates in the prefrontal cortex, anterior cingulum, caudate nucleus, and thalamus when compared to control subjects. Our results indicate that even cognitively preserved PD patients show progressive cortical and subcortical atrophic changes in regions related to cognitive functions and that these changes are already detectable in the early stages of the disease., (Copyright © 2014 Wiley Periodicals, Inc.)

Purpose: To explore gender, age-related, and regional differences of magnetization transfer ratio (MTR) of brain cortical and subcortical gray matter (GM)., Materials and Methods: In all, 102 healthy subjects (51 women and 51 men; range 25-84 years) were examined with 3-mm thick MT images. We assessed MTR in automatically segmented GM structures including frontal, parietal-insular, temporal, and occipital cortex, caudate, pallidus and putamen, and cerebellar cortex. A general linear model analysis was conducted to ascertain the linear and quadratic relationship among the MTR and gender, age, and anatomical structure., Results: The effect of gender was borderline (P = 0.07) in all GM structures (with higher MTR values in men), whereas age showed a significant linear as well as quadratic effect in all cortical and subcortical GM structures (P ≤ 0.001). Quadratic age-related decrease in MTR began at about 40 years of age. Mean and standard deviation (SD) of MTR had the following decreasing order: thalamus (58.3 + 0.8), pallidus (56.8 ± 1.3), caudate (55.5 ± 1.6) and putamen (54.6 ± 1.1); temporal (56.8 ± 0.9), parietal-insular (56.8 ± 1.1), frontal (56.5 ± 1.1), occipital (55.4 ± 1.0) and cerebellar (53.2 ± 1.0) cortex. In post-hoc testing, all regional pairwise differences were statistically significant except pallidus vs. temporal or parietal-insular cortex, caudate vs. occipital cortex, frontal vs. parietal-insular or temporal cortex., Conclusion: MTR of the cortical and subcortical brain GM structures decreases quadratically after midlife and shows significant regional differences., (© 2013 Wiley Periodicals, Inc.)

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.)

The aim of this study was to identify potential diagnostic markers of Hereditary Spastic Paraplegia (HSP). We investigated the white matter features of spastic gait (SPG)11- and SPG4-linked HSP, using diffusion tensor imaging performed with a 3-Tesla (3T) scanner. We examined four patients with SPG11 mutations, three with SPG4 mutations, and 26 healthy controls. We obtained maps of fractional anisotropy (FA) and mean diffusivity (MD), which we analyzed through both region of interest -based approach and tract-based spatial statistics (TBSS). Compared with healthy controls, SPG11 patients presented increased MD and decreased FA in the semioval centers, frontal and peritrigonal white matter, posterior limb of the internal capsule, and throughout the corpus callosum. Similar alterations were seen in the SPG4 patients at the levels of the semioval centers, the posterior limb of the internal capsule, the left cerebral pedicle, the genu and trunk of the corpus callosum, and the peritrigonal white matter on the left. No MD or FA alterations were observed in the cerebellar white matter. In a direct comparison, white matter alterations were more pronounced and widespread in HSP-SPG11 than in HSP-SPG4 patients. Joint TBSS analysis of all three groups confirmed significant widespread alterations of FA and MD values in the supratentorial white matter. This noninvasive study documented the presence of altered diffusivity in white matter in both forms of HSP, which could represent an important diagnostic marker of HSP. The association of reduced FA and increased MD in this patient population supports the interpretation of HPG as a neurodegenerative disorder.

The term leuko-araiosis (LA) describes a common chronic affection of the cerebral white matter (WM) in the elderly due to small vessel disease with variable clinical correlates. To explore whether severity of LA entails some adaptive reorganization in the cerebral cortex we evaluated with functional MRI (fMRI) the cortical activation pattern during a simple motor task in 60 subjects with mild cognitive impairment and moderate or severe (moderate-to-severe LA group, n = 46) and mild (mild LA group, n = 14) LA extension on visual rating. The microstructural damage associated with LA was measured on diffusion tensor data by computation of the mean diffusivity (MD) of the cerebral WM and by applying tract based spatial statistics (TBSS). Subjects were examined with fMRI during continuous tapping of the right dominant hand with task performance measurement. Moderate-to-severe LA group showed hyperactivation of left primary sensorimotor cortex (SM1) and right cerebellum. Regression analyses using the individual median of WM MD as explanatory variable revealed a posterior shift of activation within the left SM1 and hyperactivation of the left SMA and paracentral lobule and of the bilateral cerebellar crus. These data indicate that brain activation is modulated by increasing severity of LA with a local remapping within the SM1 and increased activity in ipsilateral nonprimary sensorimotor cortex and bilateral cerebellum. These potentially adaptive changes as well lack of contralateral cerebral hemisphere hyperactivation are in line with sparing of the U fibers and brainstem and cerebellar WM tracts and the emerging microstructual damage of the corpus callosum revealed by TBSS with increasing severity of LA., (Copyright © 2012 Wiley Periodicals, Inc.)

Spinocerebellar ataxia type 2 (SCA2) is the second most frequent autosomal dominant inherited ataxia worldwide. We investigated the capability of magnetic resonance imaging (MRI) to track in vivo progression of brain atrophy in SCA2 by examining twice 10 SCA2 patients (mean interval 3.6 years) and 16 age- and gender-matched healthy controls (mean interval 3.3 years) on the same 1.5 T MRI scanner. We used T1-weighted images and tensor-based morphometry (TBM) to investigate volume changes and the Inherited Ataxia Clinical Rating Scale to assess the clinical deficit. With respect to controls, SCA2 patients showed significant higher atrophy rates in the midbrain, including substantia nigra, basis pontis, middle cerebellar peduncles and posterior medulla corresponding to the gracilis and cuneatus tracts and nuclei, cerebellar white matter (WM) and cortical gray matter (GM) in the inferior portions of the cerebellar hemisphers. No differences in WM or GM volume loss were observed in the supratentorial compartment. TBM findings did not correlate with modifications of the neurological deficit. In conclusion, MRI volumetry using TBM is capable of demonstrating the progression of pontocerebellar atrophy in SCA2, supporting a possible role of MRI as biomarker in future trials.

Breast imaging represents a relatively recent and promising field of application of quantitative diffusion-MRI techniques. In view of the importance of guaranteeing and assessing its reliability in clinical as well as research settings, the aim of this study was to specifically characterize how the main MR scanner system-related factors affect quantitative measurements in diffusion-MRI of the breast. In particular, phantom acquisitions were performed on three 1.5 T MR scanner systems by different manufacturers, all equipped with a dedicated multi-channel breast coil as well as acquisition sequences for diffusion-MRI of the breast. We assessed the accuracy, inter-scan and inter-scanner reproducibility of the mean apparent diffusion coefficient measured along the main orthogonal directions () as well as of diffusion-tensor imaging (DTI)-derived mean diffusivity (MD) measurements. Additionally, we estimated spatial non-uniformity of (NU) and MD (NUMD) maps. We showed that the signal-to-noise ratio as well as overall calibration of high strength diffusion gradients system in typical acquisition sequences for diffusion-MRI of the breast varied across MR scanner systems, introducing systematic bias in the measurements of diffusion indices. While and MD values were not appreciably different from each other, they substantially varied across MR scanner systems. The mean of the accuracies of measured and MD was in the range [-2.3%,11.9%], and the mean of the coefficients of variation for and MD measurements across MR scanner systems was 6.8%. The coefficient of variation for repeated measurements of both and MD was < 1%, while NU and NUMD values were <4%. Our results highlight that MR scanner system-related factors can substantially affect quantitative diffusion-MRI of the breast. Therefore, a specific quality control program for assessing and monitoring the performance of MR scanner systems for diffusion-MRI of the breast is highly recommended at every site, especially in multicenter and longitudinal studies.

Background and Purpose: Manually drawn VOI-based analysis shows a decrease in magnetization transfer ratio in the hippocampus of patients with Alzheimer disease. We investigated with whole-brain voxelwise analysis the regional changes of the magnetization transfer ratio in patients with mild Alzheimer disease and patients with amnestic mild cognitive impairment., Materials and Methods: Twenty patients with mild Alzheimer disease, 27 patients with amnestic mild cognitive impairment, and 30 healthy elderly control subjects were examined with high-resolution T1WI and 3-mm-thick magnetization transfer images. Whole-brain voxelwise analysis of magnetization transfer ratio maps was performed by use of Statistical Parametric Mapping 8 software and was supplemented by the analysis of the magnetization transfer ratio in FreeSurfer parcellation-derived VOIs., Results: Voxelwise analysis showed 2 clusters of significantly decreased magnetization transfer ratio in the left hippocampus and amygdala and in the left posterior mesial temporal cortex (fusiform gyrus) of patients with Alzheimer disease as compared with control subjects but no difference between patients with amnestic mild cognitive impairment and either patients with Alzheimer disease or control subjects. VOI analysis showed that the magnetization transfer ratio in the hippocampus and amygdala was significantly lower (bilaterally) in patients with Alzheimer disease when compared with control subjects (ANOVA with Bonferroni correction, at P < .05). Mean magnetization transfer ratio values in the hippocampus and amygdala in patients with amnestic mild cognitive impairment were between those of healthy control subjects and those of patients with mild Alzheimer disease. Support vector machine-based classification demonstrated improved classification performance after inclusion of magnetization transfer ratio-related features, especially between patients with Alzheimer disease versus healthy subjects., Conclusions: Bilateral but asymmetric decrease of magnetization transfer ratio reflecting microstructural changes of the residual GM is present not only in the hippocampus but also in the amygdala in patients with mild Alzheimer disease.

The aim of this paper is to compare baroreflex sensitivity (BRS) following anesthesia induction via propofol to pre-induction baseline values through a systematic and mathematically robust analysis. Several mathematical methods for BRS quantification were applied to pre-operative and intra-operative data collected from patients undergoing major surgery, in order to track the trend in BRS variations following anesthesia induction, as well as following the onset of mechanical ventilation. Finally, a comparison of BRS trends in chronic hypertensive patients (CH) with respect to non hypertensive (NH) patients was performed. 10 NH and 7 CH patients undergoing major surgery with American Society of Anesthesiologists classification score 2.5 ± 0.5 and 2.6 ± 0.5 respectively, were enrolled in the study. A Granger causality test was carried out to verify the causal relationship between RR interval duration and systolic blood pressure (SBP), and four different mathematical methods were used to estimate the BRS: (1) ratio between autospectra of RR and SBP, (2) transfer function, (3) sequence method and (4) bivariate closed loop model. Three different surgical epochs were considered: baseline, anesthetic procedure and post-intubation. In NH patients, propofol administration caused a decrease in arterial blood pressure (ABP), due to its vasodilatory effects, and a reduction of BRS, while heart rate (HR) remained unaltered with respect to baseline values before induction. A larger decrease in ABP was observed in CH patients when compared to NH patients, whereas HR remained unaltered and BRS was found to be lower than in the NH group at baseline, with no significant changes in the following epochs when compared to baseline. To our knowledge, this is the first study in which the autonomic response to propofol induction in CH and NH patients was compared. The analysis of BRS through a mathematically rigorous procedure in the perioperative period could result in the availability of additional information to guide therapy and anesthesia in uncontrolled hypertensive patients, which are prone to a higher rate of hypotension events occurring during general anesthesia induction.

Dopaminergic therapy in Parkinson's disease (PD) can improve some cognitive functions while worsening others. These opposite effects might reflect different levels of residual dopamine in distinct parts of the striatum, although the underlying mechanisms remain poorly understood. We used functional magnetic resonance imaging (fMRI) to address how apomorphine, a potent dopamine agonist, influences brain activity associated with working memory in PD patients with variable levels of nigrostriatal degeneration, as assessed via dopamine-transporter (DAT) scan. Twelve PD patients underwent two fMRI sessions (Off-, On-apomorphine) and one DAT-scan session. Twelve sex-, age-, and education-matched healthy controls underwent one fMRI session. The core fMRI analyses explored: (1) the main effect of group; (2) the main effect of treatment; and (3) linear and nonlinear interactions between treatment and DAT levels. Relative to controls, PD-Off patients showed greater activations within posterior attentional regions (e.g., precuneus). PD-On versus PD-Off patients displayed reduced left superior frontal gyrus activation and enhanced striatal activation during working-memory task. The relation between DAT levels and striatal responses to apomorphine followed an inverted-U-shaped model (i.e., the apomorphine effect on striatal activity in PD patients with intermediate DAT levels was opposite to that observed in PD patients with higher and lower DAT levels). Previous research in PD demonstrated that the nigrostriatal degeneration (tracked via DAT scan) is associated with inverted-U-shaped rearrangements of postsynaptic D2-receptors sensitivity. Hence, it can be hypothesized that individual differences in DAT levels drove striatal responses to apomorphine via D2-receptor-mediated mechanisms.

Hippocampus volumetry currently is the best-established imaging biomarker for AD. However, the effect of multicenter acquisition on measurements of hippocampus volume needs to be explicitly considered when it is applied in large clinical trials, for example by using mixed-effects models to take the clustering of data within centers into account. The marker needs further validation in respect of the underlying neurobiological substrate and potential confounds such as vascular disease, inflammation, hydrocephalus, and alcoholism, and with regard to clinical outcomes such as cognition but also to demographic and socioeconomic outcomes such as mortality and institutionalization. The use of hippocampus volumetry for risk stratification of predementia study samples will further increase with the availability of automated measurement approaches. An important step in this respect will be the development of a standard hippocampus tracing protocol that harmonizes the large range of presently available manual protocols. In the near future, regionally differentiated automated methods will become available together with an appropriate statistical model, such as multivariate analysis of deformation fields, or techniques such as cortical-thickness measurements that yield a meaningful metrics for the detection of treatment effects. More advanced imaging protocols, including DTI, DSI, and functional MRI, are presently being used in monocenter and first multicenter studies. In the future these techniques will be relevant for the risk stratification in phase IIa type studies (small proof-of-concept trials). By contrast, the application of the broader established structural imaging biomarkers, such as hippocampus volume, for risk stratification and as surrogate end point is already today part of many clinical trial protocols. However, clinical care will also be affected by these new technologies. Radiologic expert centers already offer “dementia screening” for well-off middle-aged people who undergo an MRI scan with subsequent automated, typically VBM-based analysis, and determination of z-score deviation from a matched control cohort. Next-generation scanner software will likely include radiologic expert systems for automated segmentation, deformation-based morphometry, and multivariate analysis of anatomic MRI scans for the detection of a typical AD pattern. As these developments will start to change medical practice, first for selected subject groups that can afford this type of screening but later eventually also for other cohorts, clinicians must become aware of the potentials and limitations of these technologies. It is decidedly unclear to date how a middle-aged cognitively intact subject with a seemingly AD-positive MRI scan should be clinically advised. There is no evidence for individual risk prediction and even less for specific treatments. Thus, the development of preclinical diagnostic imaging poses not only technical but also ethical problems that must be critically discussed on the basis of profound knowledge. From a neurobiological point of view, the main determinants of cognitive impairment in AD are the density of synapses and neurons in distributed cortical and subcortical networks. MRI-based measures of regional gray matter volume and associated multivariate analysis techniques of regional interactions of gray matter densities provide insight into the onset and temporal dynamics of cortical atrophy as a close proxy for regional neuronal loss and a basis of functional impairment in specific neuronal networks. From the clinical point of view, clinicians must bear in mind that patients do not suffer from hippocampus atrophy or disconnection but from memory impairment, and that dementia screening in asymptomatic subjects should not be used outside of clinical studies., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Sporadic Alzheimer's disease (AD) is a prevalent, complex and chronically progressive brain disease. Its course is non-linear, dynamic, adaptive to maladaptive, and compensatory to decompensatory, affecting large-scale neural networks through a plethora of mechanistic and signaling pathway alterations that converge into regional and cell type-specific neurodegeneration and, finally, into clinically overt cognitive and behavioral decline. This decline includes reductions in the activities of daily living, quality of life, independence, and life expectancy. Evolving lines of research suggest that epigenetic mechanisms may play a crucial role during AD development and progression. Epigenetics designates molecular mechanisms that alter gene expression without modifications of the genetic code. This topic includes modifications on DNA and histone proteins, the primary elements of chromatin structure. Accumulating evidence has revealed the relevant processes that mediate epigenetic modifications and has begun to elucidate how these processes are apparently dysregulated in AD. This evidence has led to the clarification of the roles of specific classes of therapeutic compounds that affect epigenetic pathways and characteristics of the epigenome. This insight is accompanied by the development of new methods for studying the global patterns of DNA methylation and chromatin alterations. In particular, high-throughput sequencing approaches, such as next-generation DNA sequencing techniques, are beginning to drive the field into the next stage of development. In parallel, genetic imaging is beginning to answer additional questions through its ability to uncover genetic variants, with or without genome-wide significance, that are related to brain structure, function and metabolism, which impact disease risk and fundamental network-based cognitive processes. Neuroimaging measures can further be used to define AD systems and endophenotypes. The integration of genetic neuroimaging methods with epigenetic markers in humans appears promising. This evolving development may lead to a new research discipline - imaging epigenetics - that will provide deeper insight into the causative pathogenetic and pathophysiological pathways through which genes and environment interrelate during life and impact human brain development, physiology, aging and disease. This knowledge may open doors for the development of novel biomarkers and preventive and disease-modifying treatments.

Objective: This study describes changes in heart rate (HR) and HR variability (HRV) related to clinical onset of seizures in nocturnal frontal lobe epilepsy (NFLE) in order to determine whether signs of autonomic activation precede onset of seizure motor manifestations, which was selected as seizure onset (SO). Further, to clarify the nature (epileptic or physiologic) of the changes in autonomic cardiac control presumed to precede SO, time-dependent variations in HR and HRV related to physiological cortical arousals associated with motor activity (phases of transitory activation, PAT) were also investigated., Methods: HR and HRV spectral power, quantified by means of wavelet transform, were analyzed in relation to the onset of motor manifestations in 45 NFLE seizures and 45 PAT derived from whole night video-polysomnographic recordings of ten patients and of ten control subjects, respectively., Results: Analysis of HRV showed a shift of sympathetic/parasympathetic cardiac control toward a sympathetic predominance in the 10s immediately preceding SO, while changes in HR were evident only one second before SO. This sympathetic activation was not associated with a sleep-wake transition or changes in respiratory activity, both of which occurred concurrently with SO. Similar changes in HR and HRV were observed in the 10s before the motor and electroencephalographic onset of PAT., Conclusions: Our study demonstrates that a similar autonomic activation precedes the motor manifestations of NFLE seizures and physiological arousal. This autonomic activation could represent part of the arousal response, which could be implicated in the occurrence of both seizure and arousal motor manifestations., (Copyright © 2012 Elsevier B.V. All rights reserved.)

The significant potential for early and accurate detection of Alzheimer's disease (AD) through neuroimaging data is becoming increasingly attractive in view of the possible advent of drugs which are able to modify or delay disease progression. In this paper, we aimed at developing an effective machine learning scheme which leverages structural magnetic resonance imaging features in order to identify and discriminate individuals affected by mild AD on a single subject basis. Selected features included one- and two-way combinations of subcortical and cortical volumes as well as cortical thickness and curvature of numerous brain regions which are known to be vulnerable to AD. Additionally, several feature combinations were fed into support vector machines (SVMs) as well as Naïve Bayes classifiers in order to compare scheme accuracy. The most efficient combination of features and classification scheme, which employed both subcortical and cortical volumes feature vectors and a SVM classifier, was able to distinguish mild AD patients from healthy controls with 86% accuracy (82% sensitivity and 90% specificity). While this investigation is of preliminary nature, and further efforts are currently underway towards automated feature selection, best classifier determination and parameter optimization, our results appear very promising in terms of automated high-accuracy discrimination of disease stages which cannot easily be distinguished though routine clinical investigation.

Background: Marcus Gunn jaw-winking synkinesis (MGJWS) is characterized by eyelid ptosis, which disappears during jaw movement. Familial MGJWS is an extremely rare condition. Some authors suggested that MGJWS is due to neural misdirection in the brainstem whereas others suggested that aberrant reinnervation or ephapse may be responsible for synkinetic activity. Pathogenesis of this condition is therefore still unclear., Methodology/principal Findings: To investigate pathogenetic mechanism in familial MGJWS we performed neurophysiological (EMG, Blink Reflex, Recovery cycle of the R2 component of the blink reflex, Masseter inhibitory reflex, BAEPS and kinematic analysis) and neuroradiological (MRI, Diffusion Tensor Imaging) investigations in a member of a multigenerational family with autosomal dominant Marcus Gunn jaw-winking synkinesis (MGJWS). Kinematic analysis of eyelid and jaw movements disclosed a similar onset and offset of the eyelid and jaw in both the opening and closing phases. The excitability of brainstem circuits, as assessed by the blink reflex recovery cycle and recovery index, was normal. Diffusion Tensor Imaging revealed reduced fractional anisotropy within the midbrain tegmentum., Conclusions/significance: Kinematic and MRI findings point to a brainstem structural abnormality in our familial MGJWS patient thus supporting the hypothesis of a neural misdirection of trigeminal motor axons to the elevator palpebralis muscle.

The majority of studies on fluid responsiveness is focused on volume expansion maneuvers in intensive care unit (ICU), while fewer studies have analyzed the same problem during major surgery. Among them, the results are contrasting. The aim of this work was to compare the performance of different hemodynamic indices in the prediction of cardiac output variations following fast fluid infusion. The study was limited to a particular type of major surgery, i.e. liver transplantation and hepatectomy. Our results showed that pulse pressure variation (PPV) estimated according to the definition, i.e. within single respiratory cycles, and PPV estimated by PiCCO monitor system are coherent and very similar. Moreover, PPV and stroke volume variation (SVV) produced good values of sensitivity and specificity in separating the subjects into responsive and non responsive to maneuvers.

This paper presents the analysis of autonomic nervous system (ANS) control of heart rate (HR) and of cardiac baroreflex sensitivity (BRS) in patients undergoing general anesthesia for major surgery through spectral analysis techniques and with the Granger causality approach that take into account the causal relationships between HR and arterial blood pressure (ABP) variability. Propofol produced a general decrease in ABP due to its vasodilatory effects, a reduction in BRS, while HR remained unaltered with respect to baseline values before induction of anesthesia. The bivariate model suggests that the feedback pathway of cardiac baroreflex could be blunted by propofol induced anesthesia and that the feedforward pathway could be unaffected by anesthesia.

Transcranial Magnetic Stimulation offers enormous potential for noninvasive brain stimulation. While it is known that brain tissue significantly "reshapes" induced field and charge distributions, most modeling investigations to-date have focused on single-subject data with limited generality. Further, the effects of the significant uncertainties which exist in the simulation (i.e. brain conductivity distributions) and stimulation (e.g. coil positioning and orientations) setup have not been quantified. In this study, we construct a high-resolution anisotropic head model in standard ICBM space, which can be used as a population-representative standard for bioelectromagnetic simulations. Further, we employ Monte-Carlo simulations in order to quantify how uncertainties in conductivity values propagate all the way to induced field and currents, demonstrating significant, regionally dependent dispersions in values which are commonly assumed "ground truth". This framework can be leveraged in order to quantify the effect of any type of uncertainty in noninvasive brain stimulation and bears relevance in all applications of TMS, both investigative and therapeutic.

Purpose: Diffusion tensor imaging (DTI) is highly sensitive to noise and improvement of radiofrequency coil technology represents a straightforward way for augmenting signal-to-noise ratio (SNR) performance in magnetic resonance imaging (MRI) scanners. The aim of this study was to characterize the dependence of DTI measurements of fractional anisotropy (FA) and mean diffusivity (MD) on the choice of head coil, comparing two head coils with different functional designs and sensitivities., Methods: Fourteen healthy subjects underwent DTI acquisitions at 1.5 T. Every subject was scanned twice, using a standard quadrature birdcage head coil (coil-A) and an eight-channel array head coil (coil-B). FA and MD maps, estimated using both the linear least squares (LLS) and nonlinear least squares (NLLS) methods, were nonlinearly normalized into a standard space. Then, volumetric regions of interest encompassing typical white and gray matter structures [splenium of the corpus callosum (SCC), internal capsule (IC), cerebral peduncles (CP), middle cerebellar peduncles (MCP), globus pallidus (GP), thalamus (TH), caudate (CA), and putamen (PU)] were analyzed. Significant differences and trends of variation in DTI measurements were assessed by the Wilcoxon test for paired samples with and without Bonferroni correction for multiple comparisons, respectively., Results: The overall SNR of coil-B was 30% higher than that of coil-A. When comparing DTI measurements (coil-B versus coil-A), mean FA values (SCC, IC, and TH), mean MD values (IC, CP, GP, and TH), FA standard deviation (CP, MCP, GP, and CA), and MD standard deviation (IC, CP, TH, and PU) resulted decreased (significant difference, p(cor) < 0.05, or trend of variation, P(uncor) < 0.05) in several gray and white matter regions of the human brain. With the exception of CP, the results in terms of revealed significant difference or trend of variation were independent of the method (LLS and NLLS) used for estimating the diffusion tensor., Conclusions: In various gray and white matter structures, the eight-channel array head coil yielded more precise and accurate measurements of DTI derived indices compared to the standard quadrature birdcage head coil.

In critical care patient management, extensive and invasive patient monitoring is routinely performed in order to quantify patient status in view of therapeutic interventions. Little quantitative integration is performed when collecting information from multiple monitors, and processing algorithms are often based on little physiological understanding. Mechanistic modeling can offer insight into the mechanisms underlying patient stability and sensitivity to alterations in physiological variables. Starting from existing models, we construct an integrated model which combines detailed neural cardiovascular regulation with realistic circulation modeling, using Monte-Carlo techniques for reparameterisation when merging the two models. The combined model is analyzed in terms of its dynamical stability and sensitivity to parameter perturbations under simulated conditions of fluid deficit, anaesthesia, and dilatative cardiomyopathy. The results exemplify how a structural model can serve as a quantitative guide in assessing how different underlying patient states can alter the haemodynamics impact of external therapeutic intervention.

This paper presents the analysis of the autonomic nervous system (ANS) control and cardiac baroreflex sensitivity in patients undergoing general anesthesia for major surgery, with the goal of evaluating the effects of anesthesia bolus induction with propofol on autonomic control of heart rate (HR) and arterial blood pressure (ABP). The increase in baroreflex gain in the LF band observed through two different methods hints at the fact that the baroreflex may increase heart period (HP) following a transient ABP decrease, but its response displays a larger amplitude, to compensate for the blunting of the sympathetic action on heart rate and vascular resistance.

In this paper, we propose the use of black box models for the system identification of the cardiopulmonary baroreflex control of arterial resistance and of ventricular contractility and of arterial baroreflex control of heart rate (HR) from invasive, continuous measurements of arterial blood pressure (ABP) and central venous pressure (CVP), and non invasive, continuous recordings of ECG and respiration. Two crucial phases of the abdominal aortic aneurism (AAA) repair were investigated: the clamping and declamping of aorta. The objective of the present work is to evaluate and to test the ability to monitor baroreflex responses to clamping and declamping maneuvers preceding and following aneurism removal.

Background: Transcranial magnetic stimulation (TMS) is an attractive research and possibly therapeutic tool for non-invasive central nervous system stimulation. However, relatively little is known about the direction, magnitude and distribution of induced electric field and current flows in tissue, and optimal setup characteristics as well as appropriate sham stimulation conditions remain largely undetermined, hampering reproducibility., Methods: We reconstruct the conductive phenomena induced by TMS by implementing digitized coil geometry and realistic stimulator parameters and solving the electromagnetic problem over an MRI-based, realistic head model of 1mm resolution. Findings are validated by recording motor evoked potentials from the right abductor pollicis brevis muscle from healthy subjects stimulated in a stereotaxic framework., Results: Several commonly used sham stimulation configurations elicit conductive patterns which achieve up to 40% of the strength of real stimulation. Also, variations in coil position of the order of a 7 degrees tilt, which are expected to occur in non-stereotaxic stimulation, can alter the stimulation intensity by up to 25%., Conclusions: In accordance with our findings, several clinical studies observe measurable effects during sham stimulation or no significant difference between sham and real stimulation, and the sensitivity of stimulation intensity to tiny coil rotations affords a partial explanation for the poor reproducibility and partial disagreements observed across clinical TMS studies. Knowledge of coil and stimulator specifications alone is hence not sufficient to control stimulation conditions, and a stereotaxic setup coupled with individually adjusted field solvers appear essential in performing reliable TMS studies.

Peripheral arterial elastic properties are greatly affected by cardiovascular as well as other pathologies, and their assessment can provide useful diagnostic indicators. The photoplethysmographic technique can provide finger blood volume and pressure waveforms non-invasively, which can then be processed statically or beat-to-beat to characterize parameters of the vessel wall mechanics. We employ an occlusion-deflation protocol in 48 healthy volunteers to study peripheral artery compliance-related indices over positive and negative transmural pressure values as well as under the influence of a valid vasoconstrictor (cigarette smoking). We calculate beat-to-beat indices (compliance index CI, distensibility index DI, three viscoelastic model parameters (compliance C, viscosity R and inertia L), pressure-volume loop areas A and damping factor DF as well as symmetrical (C(max)) and asymmetrical (C(A)(max)) static compliance estimates, and their distributions over transmural pressure. All distributions are bell-shaped and centred on negative transmural pressure values. Distribution heights were significantly lower in the smoking group (w.r.t. the non-smoking group) for C, CI, DI and significantly higher in R and DF. The estimated volume signal time lag was also significantly lower in the smoking group. Left and right distribution widths were significantly different in all parameters/groups but DI (both groups), C(A)(max), A (smoking group) and L (non-smoking group), and positions of maxima/minima were significantly altered in C(A)(max), R and DF. C, DF and CI are seen to be most sensitive under this protocol, while C(max) and C(A)(max) are seen to be insensitive. These quantities provide complementary, time- and transmural pressure-dependent information about arterial wall mechanics, and the choice of index should depend on the physiological conditions at hand as well as relevant time resolution and transmural pressure range.