A multi-contrast MRI study of microstructural brain damage in patients with mild cognitive impairment.

OBJECTIVES: The aim of this study was to investigate pathological mechanisms underlying brain tissue alterations in mild cognitive impairment (MCI) using multi-contrast 3 T magnetic resonance imaging (MRI). METHODS: Forty-two MCI patients and 77 healthy controls (HC) underwent T1/T2* relaxometry as well as Magnetization Transfer (MT) MRI. Between-groups comparisons in MRI metrics were performed using permutation-based tests. Using MRI data, a generalized linear model (GLM) was computed to predict clinical performance and a support-vector machine (SVM) classification was used to classify MCI and HC subjects. RESULTS: Multi-parametric MRI data showed microstructural brain alterations in MCI patients vs HC that might be interpreted as: (i) a broad loss of myelin/cellular proteins and tissue microstructure in the hippocampus (p ≤ 0.01) and global white matter (p < 0.05); and (ii) iron accumulation in the pallidus nucleus (p ≤ 0.05). MRI metrics accurately predicted memory and executive performances in patients (p ≤ 0.005). SVM classification reached an accuracy of 75% to separate MCI and HC, and performed best using both volumes and T1/T2*/MT metrics. CONCLUSION: Multi-contrast MRI appears to be a promising approach to infer pathophysiological mechanisms leading to brain tissue alterations in MCI. Likewise, parametric MRI data provide powerful correlates of cognitive deficits and improve automatic disease classification based on morphometric features.

Experience-based Auditory Predictions Modulate Brain Activity to Silence as Do Real Sounds.

Interactions between stimuli's acoustic features and experience-based internal models of the environment enable listeners to compensate for the disruptions in auditory streams that are regularly encountered in noisy environments. However, whether auditory gaps are filled in predictively or restored a posteriori remains unclear. The current lack of positive statistical evidence that internal models can actually shape brain activity as would real sounds precludes accepting predictive accounts of filling-in phenomenon. We investigated the neurophysiological effects of internal models by testing whether single-trial electrophysiological responses to omitted sounds in a rule-based sequence of tones with varying pitch could be decoded from the responses to real sounds and by analyzing the ERPs to the omissions with data-driven electrical neuroimaging methods. The decoding of the brain responses to different expected, but omitted, tones in both passive and active listening conditions was above chance based on the responses to the real sound in active listening conditions. Topographic ERP analyses and electrical source estimations revealed that, in the absence of any stimulation, experience-based internal models elicit an electrophysiological activity different from noise and that the temporal dynamics of this activity depend on attention. We further found that the expected change in pitch direction of omitted tones modulated the activity of left posterior temporal areas 140-200 msec after the onset of omissions. Collectively, our results indicate that, even in the absence of any stimulation, internal models modulate brain activity as do real sounds, indicating that auditory filling in can be accounted for by predictive activity.

In-vivo brain neuroimaging provides a gateway for integrating biological and clinical biomarkers of Alzheimer's disease.

PURPOSE OF REVIEW: Only 5% of the Alzheimer's cases are explained by genetic mutations, whereas the remaining 95% are sporadic. The pathophysiological mechanisms underlying sporadic Alzheimer's disease are not well understood, suggesting a complex multifactorial cause. This review summarizes the recent findings on research aiming to show how biomarkers can be used for revealing the underlying mechanisms of preclinical stage Alzheimer's disease and help in their diagnosis. RECENT FINDINGS: The undisputed successful publicly accessible repositories provide longitudinal brain images, clinical, genetic and proteomic information of Alzheimer's disease. By combining with increasingly sophisticated data analysis methods, it is a great opportunity for searching new biomarkers. Innovative studies validated theoretical models of disease progression demonstrating the sequential ordering of well-established biomarkers. Novel observations shed light on the interaction between biomarkers to confirm that disease progression is related to multiple pathological factors. A typical example is the tau-associated neuronal toxicity that can be additionally potentiated by amyloid β peptides. To increase further the complexity, studies report specific impact of common genetic variants that can be traced from childhood through middle age up to the symptomatic onset of Alzheimer's disease. SUMMARY: The discovery of efficient therapies to prevent the disease or modify the progression of disease requires a more thorough understanding of the underlying biological processes. Neuroimaging, genetic and proteomic biomarkers for Alzheimer's disease are critically discussed and proposed to be included in clinical descriptions and diagnostic guidelines.

Brain metastases in gastro-oesophageal adenocarcinoma: insights into the role of the human epidermal growth factor receptor 2 (HER2).

BACKGROUND: Gastro-oesophageal adenocarcinomas rarely metastasize to the central nervous system (CNS). The role of the human epidermal growth factor receptor 2 (HER2) in patients with these cancers and CNS involvement is presently unknown. PATIENTS AND METHODS: A multicentre registry was established to collect data from patients with gastro-oesophageal adenocarcinomas and CNS involvement both retrospectively and prospectively. Inclusion in the study required a predefined clinical data set, a central neuro-radiological or histopathological confirmation of metastatic CNS involvement and central assessment of HER2 by immunohistochemistry (IHC) and in situ hybridisation (ISH). In addition, expression of E-cadherin and DNA mismatch repair (MMR) proteins were assessed by IHC. RESULTS: One hundred patients fulfilled the inclusion criteria. The population's median age was 59 years (interquartile range: 54-68), of which 85 (85%) were male. Twenty-five patients were of Asian and 75 of Caucasian origin. HER2 status was positive in 36% (95% CI: 26.6-46.2) of cases. Median time from initial diagnosis to the development of brain metastases (BMets) or leptomeningeal carcinomatosis (LC) was 9.9 months (95% CI: 8.5-15.0). Median overall survival from diagnosis was 16.9 months (95% CI: 14.0-20.7) and was not related to the HER2 status. E-cadherin loss was observed in 9% of cases and loss of expression in at least one DNA MMR proteins in 6%. CONCLUSIONS: The proportion of a positive HER2 status in patients with gastro-oesophageal adenocarcinoma and CNS involvement was higher than expected. The impact of anti-HER2 therapies should be studied prospectively.

Task-Driven Activity Reduces the Cortical Activity Space of the Brain: Experiment and Whole-Brain Modeling.

How a stimulus or a task alters the spontaneous dynamics of the brain remains a fundamental open question in neuroscience. One of the most robust hallmarks of task/stimulus-driven brain dynamics is the decrease of variability with respect to the spontaneous level, an effect seen across multiple experimental conditions and in brain signals observed at different spatiotemporal scales. Recently, it was observed that the trial-to-trial variability and temporal variance of functional magnetic resonance imaging (fMRI) signals decrease in the task-driven activity. Here we examined the dynamics of a large-scale model of the human cortex to provide a mechanistic understanding of these observations. The model allows computing the statistics of synaptic activity in the spontaneous condition and in putative tasks determined by external inputs to a given subset of brain regions. We demonstrated that external inputs decrease the variance, increase the covariances, and decrease the autocovariance of synaptic activity as a consequence of single node and large-scale network dynamics. Altogether, these changes in network statistics imply a reduction of entropy, meaning that the spontaneous synaptic activity outlines a larger multidimensional activity space than does the task-driven activity. We tested this model's prediction on fMRI signals from healthy humans acquired during rest and task conditions and found a significant decrease of entropy in the stimulus-driven activity. Altogether, our study proposes a mechanism for increasing the information capacity of brain networks by enlarging the volume of possible activity configurations at rest and reliably settling into a confined stimulus-driven state to allow better transmission of stimulus-related information.

An efficient total variation algorithm for super-resolution in fetal brain MRI with adaptive regularization.

Although fetal anatomy can be adequately viewed in new multi-slice MR images, many critical limitations remain for quantitative data analysis. To this end, several research groups have recently developed advanced image processing methods, often denoted by super-resolution (SR) techniques, to reconstruct from a set of clinical low-resolution (LR) images, a high-resolution (HR) motion-free volume. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has been quite attracted by Total Variation energies because of their ability in edge preserving but only standard explicit steepest gradient techniques have been applied for optimization. In a preliminary work, it has been shown that novel fast convex optimization techniques could be successfully applied to design an efficient Total Variation optimization algorithm for the super-resolution problem. In this work, two major contributions are presented. Firstly, we will briefly review the Bayesian and Variational dual formulations of current state-of-the-art methods dedicated to fetal MRI reconstruction. Secondly, we present an extensive quantitative evaluation of our SR algorithm previously introduced on both simulated fetal and real clinical data (with both normal and pathological subjects). Specifically, we study the robustness of regularization terms in front of residual registration errors and we also present a novel strategy for automatically select the weight of the regularization as regards the data fidelity term. Our results show that our TV implementation is highly robust in front of motion artifacts and that it offers the best trade-off between speed and accuracy for fetal MRI recovery as in comparison with state-of-the art methods.

Comparison of accelerated T1-weighted whole-brain structural-imaging protocols.

Imaging in neuroscience, clinical research and pharmaceutical trials often employs the 3D magnetisation-prepared rapid gradient-echo (MPRAGE) sequence to obtain structural T1-weighted images with high spatial resolution of the human brain. Typical research and clinical routine MPRAGE protocols with ~1mm isotropic resolution require data acquisition time in the range of 5-10min and often use only moderate two-fold acceleration factor for parallel imaging. Recent advances in MRI hardware and acquisition methodology promise improved leverage of the MR signal and more benign artefact properties in particular when employing increased acceleration factors in clinical routine and research. In this study, we examined four variants of a four-fold-accelerated MPRAGE protocol (2D-GRAPPA, CAIPIRINHA, CAIPIRINHA elliptical, and segmented MPRAGE) and compared clinical readings, basic image quality metrics (SNR, CNR), and automated brain tissue segmentation for morphological assessments of brain structures. The results were benchmarked against a widely-used two-fold-accelerated 3T ADNI MPRAGE protocol that served as reference in this study. 22 healthy subjects (age=20-44yrs.) were imaged with all MPRAGE variants in a single session. An experienced reader rated all images of clinically useful image quality. CAIPIRINHA MPRAGE scans were perceived on average to be of identical value for reading as the reference ADNI-2 protocol. SNR and CNR measurements exhibited the theoretically expected performance at the four-fold acceleration. The results of this study demonstrate that the four-fold accelerated protocols introduce systematic biases in the segmentation results of some brain structures compared to the reference ADNI-2 protocol. Furthermore, results suggest that the increased noise levels in the accelerated protocols play an important role in introducing these biases, at least under the present study conditions.

Roaring lions and chirruping lemurs: How the brain encodes sound objects in space.

The dual-stream model of auditory processing postulates separate processing streams for sound meaning and for sound location. The present review draws on evidence from human behavioral and activation studies as well as from lesion studies to argue for a position-linked representation of sound objects that is distinct both from the position-independent representation within the ventral/What stream and from the explicit sound localization processing within the dorsal/Where stream.

Brain glucose sensing in homeostatic and hedonic regulation.

Glucose homeostasis as well as homeostatic and hedonic control of feeding is regulated by hormonal, neuronal, and nutrient-related cues. Glucose, besides its role as a source of metabolic energy, is an important signal controlling hormone secretion and neuronal activity, hence contributing to whole-body metabolic integration in coordination with feeding control. Brain glucose sensing plays a key, but insufficiently explored, role in these metabolic and behavioral controls, which when deregulated may contribute to the development of obesity and diabetes. The recent introduction of innovative transgenic, pharmacogenetic, and optogenetic techniques allows unprecedented analysis of the complexity of central glucose sensing at the molecular, cellular, and neuronal circuit levels, which will lead to a new understanding of the pathogenesis of metabolic diseases.

Structural Brain Connectivity in School-Age Preterm Infants Provides Evidence for Impaired Networks Relevant for Higher Order Cognitive Skills and Social Cognition.

Extreme prematurity and pregnancy conditions leading to intrauterine growth restriction (IUGR) affect thousands of newborns every year and increase their risk for poor higher order cognitive and social skills at school age. However, little is known about the brain structural basis of these disabilities. To compare the structural integrity of neural circuits between prematurely born controls and children born extreme preterm (EP) or with IUGR at school age, long-ranging and short-ranging connections were noninvasively mapped across cortical hemispheres by connection matrices derived from diffusion tensor tractography. Brain connectivity was modeled along fiber bundles connecting 83 brain regions by a weighted characterization of structural connectivity (SC). EP and IUGR subjects, when compared with controls, had decreased fractional anisotropy-weighted SC (FAw-SC) of cortico-basal ganglia-thalamo-cortical loop connections while cortico-cortical association connections showed both decreased and increased FAw-SC. FAw-SC strength of these connections was associated with poorer socio-cognitive performance in both EP and IUGR children.

Third International Congress on Epilepsy, Brain, and Mind: Part 2.

Epilepsy is both a disease of the brain and the mind. Here, we present the second of two papers with extended summaries of selected presentations of the Third International Congress on Epilepsy, Brain and Mind (April 3-5, 2014; Brno, Czech Republic). Humanistic, biologic, and therapeutic aspects of epilepsy, particularly those related to the mind, were discussed. The extended summaries provide current overviews of epilepsy, cognitive impairment, and treatment, including brain functional connectivity and functional organization; juvenile myoclonic epilepsy; cognitive problems in newly diagnosed epilepsy; SUDEP including studies on prevention and involvement of the serotoninergic system; aggression and antiepileptic drugs; body, mind, and brain, including pain, orientation, the "self-location", Gourmand syndrome, and obesity; euphoria, obsessions, and compulsions; and circumstantiality and psychiatric comorbidities.

Programming Hippocampal Neural Stem/Progenitor Cells into Oligodendrocytes Enhances Remyelination in the Adult Brain after Injury.

Demyelinating diseases are characterized by a loss of oligodendrocytes leading to axonal degeneration and impaired brain function. Current strategies used for the treatment of demyelinating disease such as multiple sclerosis largely rely on modulation of the immune system. Only limited treatment options are available for treating the later stages of the disease, and these treatments require regenerative therapies to ameliorate the consequences of oligodendrocyte loss and axonal impairment. Directed differentiation of adult hippocampal neural stem/progenitor cells (NSPCs) into oligodendrocytes may represent an endogenous source of glial cells for cell-replacement strategies aiming to treat demyelinating disease. Here, we show that Ascl1-mediated conversion of hippocampal NSPCs into mature oligodendrocytes enhances remyelination in a diphtheria-toxin (DT)-inducible, genetic model for demyelination. These findings highlight the potential of targeting hippocampal NSPCs for the treatment of demyelinated lesions in the adult brain.

Avaliação de foco epileptogênico do lobo temporal: correlação entre SPECT ictal, ressonância magnética e ressonância magnética com espectroscopia de prótons

O objetivo deste trabalho foi determinar a existência de concordância entre os métodos radioisotópico e radiológico e, em caso positivo, avaliar a utilidade do SPECT ictal na determinação do foco epileptogênico. Foram realizados SPECT ictal, ressonância magnética (RM) e ressonância magnética com espectroscopia de prótons (RME) em seis pacientes com epilepsia de lobo temporal refratária. O SPECT ictal foi realizado após a retirada das drogas antiepilépticas durante monitoramento por vídeo-EEG, utilizando-se o 99mTc-ECD, administrado aos pacientes no início da crise. As imagens de RM foram obtidas em T1, T2 e FLAIR, com cortes de 3 e 5 mm de espessura, e a RME foi realizada com técnica PRESS, com voxel único posicionado no hipocampo, bilateralmente. A análise estatística incluiu os valores de Kappa (k), erro-padrão (ep) e o nível de significância (p) para a lateralização do foco. Os achados foram analisados com base na localização por EEG da descarga ictal, no tempo de duração da crise (109-280 s; média: 152 s) e no tempo de administração do traçador (30-262 s; média: 96 s). Obtivemos dados correlatos em quatro pacientes (67%), com valores de k = 0,67, ep = 0,38 e p = 0,041. Concluímos que existe concordância entre SPECT ictal, RM e RME, e a utilidade do procedimento radioisotópico está relacionada aos casos em que o EEG não é diagnóstico e quando há discordância ou indefinição diagnóstica na análise comparativa entre EEG, RM e RME.

Neuroenergetic Response to Prolonged Cerebral Glucose Depletion after Severe Brain Injury and the Role of Lactate.

Lactate may represent a supplemental fuel for the brain. We examined cerebral lactate metabolism during prolonged brain glucose depletion (GD) in acute brain injury (ABI) patients monitored with cerebral microdialysis (CMD). Sixty episodes of GD (defined as spontaneous decreases of CMD glucose from normal to low [<1.0 mmol/L] for at least 2 h) were identified among 26 patients. During GD, we found a significant increase of CMD lactate (from 4±2.3 to 5.4±2.9 mmol/L), pyruvate (126.9±65.1 to 172.3±74.1 μmol/L), and lactate/pyruvate ratio (LPR; 27±6 to 35±9; all, p<0.005), while brain oxygen and blood lactate remained normal. Dynamics of lactate and glucose supply during GD were further studied by analyzing the relationships between blood and CMD samples. There was a strong correlation between blood and brain lactate when LPR was normal (r=0.56; p<0.0001), while an inverse correlation (r=-0.11; p=0.04) was observed at elevated LPR >25. The correlation between blood and brain glucose also decreased from r=0.62 to r=0.45. These findings in ABI patients suggest increased cerebral lactate delivery in the absence of brain hypoxia when glucose availability is limited and support the concept that lactate acts as alternative fuel.