In vivo assessment of use-dependent brain plasticity--beyond the "one trick pony" imaging strategy.

This article has been written as a comment to Dr Thomas and Dr Baker's article "Teaching an adult brain new tricks: A critical review of evidence for training-dependent structural plasticity in humans". We deliberately expand on the key question about the biological substrates underlying use-dependent brain plasticity rather than reiterating the authors' main points of criticism already addressed in more general way by previous publications in the field. The focus here is on the following main issues: i) controversial brain plasticity findings in voxel-based morphometry studies are partially due to the strong dependency of the widely used T1-weighted imaging protocol on varying magnetic resonance contrast contributions; ii) novel concepts in statistical analysis allow one to directly infer topological specificity of structural brain changes associated with plasticity. We conclude that iii) voxel-based quantification of relaxometry derived parameter maps could provide a new perspective on use-dependent plasticity by characterisation of brain tissue property changes beyond the estimation of volume and cortical thickness changes. In the relevant sections we respond to the concerns raised by Dr Thomas and Dr Baker from the perspective of the proposed data acquisition and analysis strategy.

Early EEG correlates of neuronal injury after brain anoxia.

OBJECTIVES: EEG and serum neuron-specific enolase (NSE) are used for outcome prognostication in patients with postanoxic coma; however, it is unclear if EEG abnormalities reflect transient neuronal dysfunction or neuronal death. To assess this question, EEG abnormalities were correlated with NSE. Moreover, NSE cutoff values and hypothermic EEG features related with poor outcome were explored.¦METHODS: In a prospective cohort of 61 adults treated with therapeutic hypothermia (TH) after cardiac arrest (CA), multichannel EEG recorded during TH was assessed for background reactivity and continuity, presence of epileptiform transients, and correlated with serum NSE collected at 24-48 hours after CA. Demographic, clinical, and functional outcome data (at 3 months) were collected and integrated in the analyses.¦RESULTS: In-hospital mortality was 41%, and 82% of survivors had good neurologic outcome at 3 months. Serum NSE and EEG findings were strongly correlated (Spearman rho = 0.45; p < 0.001). Median NSE peak values were higher in patients with unreactive EEG background (p < 0.001) and discontinuous patterns (p = 0.001). While all subjects with nonreactive EEG died, 5 survivors (3 with good outcome) had NSE levels >33 μg/L.¦CONCLUSION: The correlation between EEG during TH and serum NSE levels supports the hypothesis that early EEG alterations reflect permanent neuronal damage. Furthermore, this study confirms that absent EEG background reactivity and presence of epileptiform transients are robust predictors of poor outcome after CA, and that survival with good neurologic recovery is possible despite serum NSE levels> 33 μg/L. This underscores the importance of multimodal assessments in this setting.

Expression of brain-derived neurotrophic factor is not modulated by chronic mild stress in the rat hippocampus and amygdala.

Accumulating evidence supports a role for brain-derived neurotrophic factor (BDNF) in depression. However, most of these studies have been performed in animal models that have a low face validity with regard to the human disease. Here, we examined the regulation of BDNF expression in the hippocampus and amygdala of rats subjected to the chronic mild stress (CMS) model of depression, a paradigm that induces anhedonia, a core symptom of depression. We found that exposure of rats to the CMS paradigm did not modulate BDNF mRNA expression in the hippocampus and amygdala. In addition, chronic administration of imipramine, which reversed CMS-induced anhedonia, did not alter BDNF mRNA expression in these limbic structures.

Automatic quality assessment in structural brain magnetic resonance imaging

MRI has evolved into an important diagnostic technique in medical imaging. However, reliability of the derived diagnosis can be degraded by artifacts, which challenge both radiologists and automatic computer-aided diagnosis. This work proposes a fully-automatic method for measuring image quality of three-dimensional (3D) structural MRI. Quality measures are derived by analyzing the air background of magnitude images and are capable of detecting image degradation from several sources, including bulk motion, residual magnetization from incomplete spoiling, blurring, and ghosting. The method has been validated on 749 3D T(1)-weighted 1.5T and 3T head scans acquired at 36 Alzheimer's Disease Neuroimaging Initiative (ADNI) study sites operating with various software and hardware combinations. Results are compared against qualitative grades assigned by the ADNI quality control center (taken as the reference standard). The derived quality indices are independent of the MRI system used and agree with the reference standard quality ratings with high sensitivity and specificity (>85%). The proposed procedures for quality assessment could be of great value for both research and routine clinical imaging. It could greatly improve workflow through its ability to rule out the need for a repeat scan while the patient is still in the magnet bore.

Use of anisotropic modelling in electrical impedance tomography: description of method and preliminary assessment of utility in imaging brain function in the adult human head.

Electrical Impedance Tomography (EIT) is an imaging method which enables a volume conductivity map of a subject to be produced from multiple impedance measurements. It has the potential to become a portable non-invasive imaging technique of particular use in imaging brain function. Accurate numerical forward models may be used to improve image reconstruction but, until now, have employed an assumption of isotropic tissue conductivity. This may be expected to introduce inaccuracy, as body tissues, especially those such as white matter and the skull in head imaging, are highly anisotropic. The purpose of this study was, for the first time, to develop a method for incorporating anisotropy in a forward numerical model for EIT of the head and assess the resulting improvement in image quality in the case of linear reconstruction of one example of the human head. A realistic Finite Element Model (FEM) of an adult human head with segments for the scalp, skull, CSF, and brain was produced from a structural MRI. Anisotropy of the brain was estimated from a diffusion tensor-MRI of the same subject and anisotropy of the skull was approximated from the structural information. A method for incorporation of anisotropy in the forward model and its use in image reconstruction was produced. The improvement in reconstructed image quality was assessed in computer simulation by producing forward data, and then linear reconstruction using a sensitivity matrix approach. The mean boundary data difference between anisotropic and isotropic forward models for a reference conductivity was 50%. Use of the correct anisotropic FEM in image reconstruction, as opposed to an isotropic one, corrected an error of 24 mm in imaging a 10% conductivity decrease located in the hippocampus, improved localisation for conductivity changes deep in the brain and due to epilepsy by 4-17 mm, and, overall, led to a substantial improvement on image quality. This suggests that incorporation of anisotropy in numerical models used for image reconstruction is likely to improve EIT image quality.

Assessment of metabolic fluxes in the mouse brain in vivo using 1H-[13C] NMR spectroscopy at 14.1 Tesla.

(13)C magnetic resonance spectroscopy (MRS) combined with the administration of (13)C labeled substrates uniquely allows to measure metabolic fluxes in vivo in the brain of humans and rats. The extension to mouse models may provide exclusive prospect for the investigation of models of human diseases. In the present study, the short-echo-time (TE) full-sensitivity (1)H-[(13)C] MRS sequence combined with high magnetic field (14.1 T) and infusion of [U-(13)C6] glucose was used to enhance the experimental sensitivity in vivo in the mouse brain and the (13)C turnover curves of glutamate C4, glutamine C4, glutamate+glutamine C3, aspartate C2, lactate C3, alanine C3, γ-aminobutyric acid C2, C3 and C4 were obtained. A one-compartment model was used to fit (13)C turnover curves and resulted in values of metabolic fluxes including the tricarboxylic acid (TCA) cycle flux VTCA (1.05 ± 0.04 μmol/g per minute), the exchange flux between 2-oxoglutarate and glutamate Vx (0.48 ± 0.02 μmol/g per minute), the glutamate-glutamine exchange rate V(gln) (0.20 ± 0.02 μmol/g per minute), the pyruvate dilution factor K(dil) (0.82 ± 0.01), and the ratio for the lactate conversion rate and the alanine conversion rate V(Lac)/V(Ala) (10 ± 2). This study opens the prospect of studying transgenic mouse models of brain pathologies.

Mild guanidinoacetate increase under partial guanidinoacetate methyltransferase deficiency strongly affects brain cell development.

Among cerebral creatine deficiency syndromes, guanidinoacetate methyltransferase (GAMT) deficiency can present the most severe symptoms, and is characterized by neurocognitive dysfunction due to creatine deficiency and accumulation of guanidinoacetate in the brain. So far, every patient was found with negligible GAMT activity. However, GAMT deficiency is thought under-diagnosed, in particular due to unforeseen mutations allowing sufficient residual activity avoiding creatine deficiency, but enough guanidinoacetate accumulation to be toxic. With poorly known GAA-specific neuropathological mechanisms, we developed an RNAi-induced partial GAMT deficiency in organotypic rat brain cell cultures. As expected, the 85% decrease of GAMT protein was insufficient to cause creatine deficiency, but generated guanidinoacetate accumulation causing axonal hypersprouting and decrease in natural apoptosis, followed by induction of non-apoptotic cell death. Specific guanidinoacetate-induced effects were completely prevented by creatine co-treatment. We show that guanidinoacetate accumulation without creatine deficiency is sufficient to affect CNS development, and suggest that additional partial GAMT deficiencies, which may not show the classical brain creatine deficiency, may be discovered through guanidinoacetate measurement.

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.

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.