Development of projections from auditory to visual areas in the cat.

In newborn kittens, cortical auditory areas (including AI and AII) send transitory projections to ipsi- and contralateral visual areas 17 and 18. These projections originate mainly from neurons in supragranular layers but also from a few in infragranular layers (Innocenti and Clarke: Dev. Brain Res. 14:143-148, '84; Clarke and Innocenti: J. Comp. Neurol. 251:1-22, '86). The postnatal development of these projections was studied with injections of anterograde tracers (wheat germ agglutinin-horseradish peroxidase [WGA-HRP]) in AI and AII and of retrograde tracers (WGA-HRP, fast blue, diamidino yellow, rhodamine-labeled latex beads) in areas 17 and 18. It was found that the projections are nearly completely eliminated in development, this, by the end of the first postnatal month. Until then, most of the transitory axons seem to remain confined to the white matter and the depth of layer VI; a few enter it further but do not appear to form terminal arbors. As for other transitory cortical projections the disappearance of the transitory axons seems not to involve death of their neurons of origin. In kittens older than 1 month and in normal adult cats, retrograde tracer injections restricted to, or including, areas 17 and 18 label only a few neurons in areas AI and AII. Unlike the situation in the kitten, nearly all of these are restricted to layers V and VI. A similar distribution of neurons projecting from auditory to visual areas is found in adult cats bilaterally enucleated at birth, which suggests that the postnatal elimination of the auditory-to-visual projection is independent of visual experience and more generally of information coming from the retina.

Differential impact of lacunes and microvascular lesions on poststroke depression.

BACKGROUND AND PURPOSE: Previous studies have postulated that poststroke depression (PSD) might be related to cumulative vascular brain pathology rather than to the location and severity of a single macroinfarct. We performed a detailed analysis of all types of microvascular lesions and lacunes in 41 prospectively documented and consecutively autopsied stroke cases. METHODS: Only cases with first-onset depression <2 years after stroke were considered as PSD in the present series. Diagnosis of depression was established prospectively using DSM-IV criteria for major depression. Neuropathological evaluation included bilateral semiquantitative assessment of microvascular ischemic pathology and lacunes; statistical analysis included Fisher exact test, Mann-Whitney U test, and regression models. RESULTS: Macroinfarct site was not related to the occurrence of PSD for any of the locations studied. Thalamic and basal ganglia lacunes occurred significantly more often in PSD cases. Higher lacune scores in basal ganglia, thalamus, and deep white matter were associated with an increased PSD risk. In contrast, microinfarct and diffuse or periventricular demyelination scores were not increased in PSD. The combined lacune score (thalamic plus basal ganglia plus deep white matter) explained 25% of the variability of PSD occurrence. CONCLUSIONS: The cumulative vascular burden resulting from chronic accumulation of lacunar infarcts within the thalamus, basal ganglia, and deep white matter may be more important than single infarcts in the prediction of PSD.

Severe Postnatally Acquired Cytomegalovirus Infection Presenting with Colitis, Pneumonitis and Sepsis-Like Syndrome in an Extremely Low Birthweight Infant

Few cases of severe postnatally acquired cytomegalovirus (CMV) infection are reported in premature infants. We report on an extremely low birthweight (ELBW) preterm infant who presented with a sepsis-like syndrome and multiple organ involvement, notably pneumonitis and colitis. The course of infection was assessed by repeated analysis of urine, tracheal aspirates and blood. The patient was given intravenous ganciclovir. The clinical course was rapidly favorable. Development of neutropenia led to the discontinuation of the antiviral treatment after 28 days. Follow-up showed moderate white matter anomalies on cerebral MRI, a transient hypoacusis and a mild developmental delay at 18 months of corrected age. To the best of our knowledge, this is the first description of a severe combination of pneumonitis and colitis in postnatal CMV infection. Many issues remain controversial and are discussed. We propose that antiviral treatment should be considered in severe postnatal CMV infection in ELBW patients.

Characterizing the connectome in schizophrenia with diffusion spectrum imaging.

Schizophrenia is a complex psychiatric disorder characterized by disabling symptoms and cognitive deficit. Recent neuroimaging findings suggest that large parts of the brain are affected by the disease, and that the capacity of functional integration between brain areas is decreased. In this study we questioned (i) which brain areas underlie the loss of network integration properties observed in the pathology, (ii) what is the topological role of the affected regions within the overall brain network and how this topological status might be altered in patients, and (iii) how white matter properties of tracts connecting affected regions may be disrupted. We acquired diffusion spectrum imaging (a technique sensitive to fiber crossing and slow diffusion compartment) data from 16 schizophrenia patients and 15 healthy controls, and investigated their weighted brain networks. The global connectivity analysis confirmed that patients present disrupted integration and segregation properties. The nodal analysis allowed identifying a distributed set of brain nodes affected in the pathology, including hubs and peripheral areas. To characterize the topological role of this affected core, we investigated the brain network shortest paths layout, and quantified the network damage after targeted attack toward the affected core. The centrality of the affected core was compromised in patients. Moreover the connectivity strength within the affected core, quantified with generalized fractional anisotropy and apparent diffusion coefficient, was altered in patients. Taken together, these findings suggest that the structural alterations and topological decentralization of the affected core might be major mechanisms underlying the schizophrenia dysconnectivity disorder. Hum Brain Mapp, 36:354-366, 2015. © 2014 Wiley Periodicals, Inc.

Understanding diffusion MR imaging techniques: from scalar diffusion-weighted imaging to diffusion tensor imaging and beyond.

The complex structural organization of the white matter of the brain can be depicted in vivo in great detail with advanced diffusion magnetic resonance (MR) imaging schemes. Diffusion MR imaging techniques are increasingly varied, from the simplest and most commonly used technique-the mapping of apparent diffusion coefficient values-to the more complex, such as diffusion tensor imaging, q-ball imaging, diffusion spectrum imaging, and tractography. The type of structural information obtained differs according to the technique used. To fully understand how diffusion MR imaging works, it is helpful to be familiar with the physical principles of water diffusion in the brain and the conceptual basis of each imaging technique. Knowledge of the technique-specific requirements with regard to hardware and acquisition time, as well as the advantages, limitations, and potential interpretation pitfalls of each technique, is especially useful.

Is the macromolecule signal tissue-specific in healthy human brain? A (1)H MRS study at 7 Tesla in the occipital lobe.

PURPOSE: The macromolecule signal plays a key role in the precision and the accuracy of the metabolite quantification in short-TE (1) H MR spectroscopy. Macromolecules have been reported at 1.5 Tesla (T) to depend on the cerebral studied region and to be age specific. As metabolite concentrations vary locally, information about the profile of the macromolecule signal in different tissues may be of crucial importance. METHODS: The aim of this study was to investigate, at 7T for healthy subjects, the neurochemical profile differences provided by macromolecule signal measured in two different tissues in the occipital lobe, predominantly composed of white matter tissue or of grey matter tissue. RESULTS: White matter-rich macromolecule signal was relatively lower than the gray matter-rich macromolecule signal from 1.5 to 1.8 ppm and from 2.3 to 2.5 ppm with mean difference over these regions of 7% and 12% (relative to the reference peak at 0.9 ppm), respectively. The neurochemical profiles, when using either of the two macromolecule signals, were similar for 11 reliably quantified metabolites (CRLB < 20%) with relatively small concentration differences (< 0.3 μmol/g), except Glu (± 0.8 μmol/g). CONCLUSION: Given the small quantification differences, we conclude that a general macromolecule baseline provides a sufficiently accurate neurochemical profile in occipital lobe at 7T in healthy human brain.

Delirium and cognitive decline: more than a coincidence.

PURPOSE OF REVIEW: To review the recent findings on the relationships between delirium and cognitive decline in the elderly. RECENT FINDINGS: Current advances in the field include substantial new evidence that delirium increases the risk of dementia in patients without previous cognitive impairment and accelerates cognitive decline in patients with Alzheimer's disease. Findings on cognitive trajectories and domains affected contribute to better understanding of the clinical nature of cognitive impairment after delirium. Volume loss and disruption of white matter integrity may represent early MRI markers for long-term cognitive impairment. Neurodegenerative and low-level chronic inflammatory processes predispose to exaggerated response to incident stimuli that may precipitate both acute brain dysfunction and persisting cerebral damage. SUMMARY: Still little is known about the relationship between delirium and cognitive trajectories in the elderly, and the underlying pathophysiological mechanisms. The association of neurodegenerative and inflammatory processes appears to play an important role in the pathogenesis and the clinical course of cognitive impairment after delirium. The hypothetical role of several other factors remains to be clarified. Further clinical studies are needed to evaluate whether prevention and treatment approaches that proved to be useful to reduce delirium incidence and severity may also improve long-term outcomes, and prevent cognitive decline.

Temporal evolution of MR perfusion in neonatal hypoxic-ischemic encephalopathy

PURPOSE: To illustrate the evolution of brain perfusion-weighted magnetic resonance imaging (PWI-MRI) in severe neonatal hypoxic-ischemic (HI) encephalopathy, and its possible relation to further neurodevelopmental outcome. MATERIALS AND METHODS: Two term neonates with HI encephalopathy underwent an early and a late MRI, including PWI. They were followed until eight months of age. A total of three "normal controls" were also included. Perfusion maps were obtained, and relative cerebral blood flow (rCBF) and cerebral blood volume (rCBV) values were measured. RESULTS: Compared to normal neonates, a hyperperfusion (increased rCBF and rCBV) was present on early scans in the whole brain. On late scans, hyperperfusion persisted in cortical gray matter (normalization of rCBF and rCBV ratios in white matter and basal ganglia, but not in cortical gray matter). Diffusion-weighted imaging (DWI) was normalized, and extensive lesions became visible on T2-weighted images. Both patients displayed very abnormal outcome: Patient 2 with the more abnormal early and late hyperperfusion being the worst. CONCLUSION: PWI in HI encephalopathy did not have the same temporal evolution as DWI, and remained abnormal for more than one week after injury. This could be a marker of an ongoing mechanism underlying severe neonatal HI encephalopathy. Evolution of PWI might help to predict further neurodevelopmental outcome.

Overlap Between Common Genetic Polymorphisms Underpinning Kidney Traits and Cardiovascular Disease Phenotypes: The CKDGen Consortium.

BACKGROUND: Chronic kidney disease is associated with cardiovascular disease. We tested for evidence of a shared genetic basis to these traits. STUDY DESIGN: We conducted 2 targeted analyses. First, we examined whether known single-nucleotide polymorphisms (SNPs) underpinning kidney traits were associated with a series of vascular phenotypes. Additionally, we tested whether vascular SNPs were associated with markers of kidney damage. Significance was set to 1.5×10(-4) (0.05/325 tests). SETTING & PARTICIPANTS: Vascular outcomes were analyzed in participants from the AortaGen (20,634), CARDIoGRAM (86,995), CHARGE Eye (15,358), CHARGE IMT (31,181), ICBP (69,395), and NeuroCHARGE (12,385) consortia. Tests for kidney outcomes were conducted in up to 67,093 participants from the CKDGen consortium. PREDICTOR: We used 19 kidney SNPs and 64 vascular SNPs. OUTCOMES & MEASUREMENTS: Vascular outcomes tested were blood pressure, coronary artery disease, carotid intima-media thickness, pulse wave velocity, retinal venular caliber, and brain white matter lesions. Kidney outcomes were estimated glomerular filtration rate and albuminuria. RESULTS: In general, we found that kidney disease variants were not associated with vascular phenotypes (127 of 133 tests were nonsignificant). The one exception was rs653178 near SH2B3 (SH2B adaptor protein 3), which showed direction-consistent association with systolic (P = 9.3 ×10(-10)) and diastolic (P = 1.6 ×10(-14)) blood pressure and coronary artery disease (P = 2.2 ×10(-6)), all previously reported. Similarly, the 64 SNPs associated with vascular phenotypes were not associated with kidney phenotypes (187 of 192 tests were nonsignificant), with the exception of 2 high-correlated SNPs at the SH2B3 locus (P = 1.06 ×10(-07) and P = 7.05 ×10(-08)). LIMITATIONS: The combined effect size of the SNPs for kidney and vascular outcomes may be too low to detect shared genetic associations. CONCLUSIONS: Overall, although we confirmed one locus (SH2B3) as associated with both kidney and cardiovascular disease, our primary findings suggest that there is little overlap between kidney and cardiovascular disease risk variants in the overall population. The reciprocal risks of kidney and cardiovascular disease may not be genetically mediated, but rather a function of the disease milieu itself.

Quantitative morphometry analysis of the fetal brain using clinical MR imaging

In vivo fetal magnetic resonance imaging provides aunique approach for the study of early human braindevelopment [1]. In utero cerebral morphometry couldpotentially be used as a marker of the cerebralmaturation and help to distinguish between normal andabnormal development in ambiguous situations. However,this quantitative approach is a major challenge becauseof the movement of the fetus inside the amniotic cavity,the poor spatial resolution provided by very fast MRIsequences and the partial volume effect. Extensiveefforts are made to deal with the reconstruction ofhigh-resolution 3D fetal volumes based on severalacquisitions with lower resolution [2,3,4]. Frameworkswere developed for the segmentation of specific regionsof the fetal brain such as posterior fossa, brainstem orgerminal matrix [5,6], or for the entire brain tissue[7,8], applying the Expectation-Maximization MarkovRandom Field (EM-MRF) framework. However, many of theseprevious works focused on the young fetus (i.e. before 24weeks) and use anatomical atlas priors to segment thedifferent tissue or regions. As most of the gyraldevelopment takes place after the 24th week, acomprehensive and clinically meaningful study of thefetal brain should not dismiss the third trimester ofgestation. To cope with the rapidly changing appearanceof the developing brain, some authors proposed a dynamicatlas [8]. To our opinion, this approach however faces arisk of circularity: each brain will be analyzed /deformed using the template of its biological age,potentially biasing the effective developmental delay.Here, we expand our previous work [9] to proposepost-processing pipeline without prior that allow acomprehensive set of morphometric measurement devoted toclinical application. Data set & Methods: Prenatal MRimaging was performed with a 1-T system (GE MedicalSystems, Milwaukee) using single shot fast spin echo(ssFSE) sequences (TR 7000 ms, TE 180 ms, FOV 40 x 40 cm,slice thickness 5.4mm, in plane spatial resolution1.09mm). For each fetus, 6 axial volumes shifted by 1 mmwere acquired under motherâeuro?s sedation (about 1min pervolume). First, each volume is segmentedsemi-automatically using region-growing algorithms toextract fetal brain from surrounding maternal tissues.Inhomogeneity intensity correction [10] and linearintensity normalization are then performed. Brain tissues(CSF, GM and WM) are then segmented based on thelow-resolution volumes as presented in [9]. Ahigh-resolution image with isotropic voxel size of 1.09mm is created as proposed in [2] and using B-splines forthe scattered data interpolation [11]. Basal gangliasegmentation is performed using a levet setimplementation on the high-resolution volume [12]. Theresulting white matter image is then binarized and givenas an input in FreeSurfer software(http://surfer.nmr.mgh.harvard.edu) to providetopologically accurate three-dimensional reconstructionsof the fetal brain according to the local intensitygradient. References: [1] Guibaud, Prenatal Diagnosis29(4) (2009). [2] Rousseau, Acad. Rad. 13(9), 2006. [3]Jiang, IEEE TMI 2007. [4] Warfield IADB, MICCAI 2009. [5]Claude, IEEE Trans. Bio. Eng. 51(4) 2004. [6] Habas,MICCAI 2008. [7] Bertelsen, ISMRM 2009. [8] Habas,Neuroimage 53(2) 2010. [9] Bach Cuadra, IADB, MICCAI2009. [10] Styner, IEEE TMI 19(39 (2000). [11] Lee, IEEETrans. Visual. And Comp. Graph. 3(3), 1997. [12] BachCuadra, ISMRM 2010.

Structured sparsity for spatially coherent fibre orientation estimation in diffusion MRI.

We propose a novel formulation to solve the problem of intra-voxel reconstruction of the fibre orientation distribution function (FOD) in each voxel of the white matter of the brain from diffusion MRI data. The majority of the state-of-the-art methods in the field perform the reconstruction on a voxel-by-voxel level, promoting sparsity of the orientation distribution. Recent methods have proposed a global denoising of the diffusion data using spatial information prior to reconstruction, while others promote spatial regularisation through an additional empirical prior on the diffusion image at each q-space point. Our approach reconciles voxelwise sparsity and spatial regularisation and defines a spatially structured FOD sparsity prior, where the structure originates from the spatial coherence of the fibre orientation between neighbour voxels. The method is shown, through both simulated and real data, to enable accurate FOD reconstruction from a much lower number of q-space samples than the state of the art, typically 15 samples, even for quite adverse noise conditions.

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.

Advances in MRI-based computational neuroanatomy: from morphometry to in-vivo histology.

PURPOSE OF REVIEW: Current computational neuroanatomy based on MRI focuses on morphological measures of the brain. We present recent methodological developments in quantitative MRI (qMRI) that provide standardized measures of the brain, which go beyond morphology. We show how biophysical modelling of qMRI data can provide quantitative histological measures of brain tissue, leading to the emerging field of in-vivo histology using MRI (hMRI). RECENT FINDINGS: qMRI has greatly improved the sensitivity and specificity of computational neuroanatomy studies. qMRI metrics can also be used as direct indicators of the mechanisms driving observed morphological findings. For hMRI, biophysical models of the MRI signal are being developed to directly access histological information such as cortical myelination, axonal diameters or axonal g-ratio in white matter. Emerging results indicate promising prospects for the combined study of brain microstructure and function. SUMMARY: Non-invasive brain tissue characterization using qMRI or hMRI has significant implications for both research and clinics. Both approaches improve comparability across sites and time points, facilitating multicentre/longitudinal studies and standardized diagnostics. hMRI is expected to shed new light on the relationship between brain microstructure, function and behaviour, both in health and disease, and become an indispensable addition to computational neuroanatomy.

Microstructure of the superior longitudinal fasciculus predicts stimulation-induced interference with on-line motor control.

A cortical visuomotor network, comprising the medial intraparietal sulcus (mIPS) and the dorsal premotor area (PMd), encodes the sensorimotor transformations required for the on-line control of reaching movements. How information is transmitted between these two regions and which pathways are involved, are less clear. Here, we use a multimodal approach combining repetitive transcranial magnetic stimulation (rTMS) and diffusion tensor imaging (DTI) to investigate whether structural connectivity in the 'reaching' circuit is associated to variations in the ability to control and update a movement. We induced a transient disruption of the neural processes underlying on-line motor adjustments by applying 1Hz rTMS over the mIPS. After the stimulation protocol, participants globally showed a reduction of the number of corrective trajectories during a reaching task that included unexpected visual perturbations. A voxel-based analysis revealed that participants exhibiting higher fractional anisotropy (FA) in the second branch of the superior longitudinal fasciculus (SLF II) suffered less rTMS-induced behavioral impact. These results indicate that the microstructural features of the white matter bundles within the parieto-frontal 'reaching' circuit play a prominent role when action reprogramming is interfered. Moreover, our study suggests that the structural alignment and cohesion of the white matter tracts might be used as a predictor to characterize the extent of motor impairments.

Structured sparsity through reweighting and application to diffusion MRI

We consider the problem of multiple correlated sparse signals reconstruction and propose a new implementation of structured sparsity through a reweighting scheme. We present a particular application for diffusion Magnetic Resonance Imaging data and show how this procedure can be used for fibre orientation reconstruction in the white matter of the brain. In that framework, our structured sparsity prior can be used to exploit the fundamental coherence between fibre directions in neighbour voxels. Our method approaches the ℓ0 minimisation through a reweighted ℓ1-minimisation scheme. The weights are here defined in such a way to promote correlated sparsity between neighbour signals.