Disruption of Semantic Network in Mild Alzheimer's Disease Revealed by Resting-State fMRI.

Subtle semantic deficits can be observed in Alzheimer's disease (AD) patients even in the early stages of the illness. In this work, we tested the hypothesis that the semantic control network is deregulated in mild AD patients. We assessed the integrity of the semantic control system using resting-state functional magnetic resonance imaging in a cohort of patients with mild AD (n = 38; mean mini-mental state examination = 20.5) and in a group of age-matched healthy controls (n = 19). Voxel-wise analysis spatially constrained in the left fronto-temporal semantic control network identified two regions with altered functional connectivity (FC) in AD patients, specifically in the pars opercularis (POp, BA44) and in the posterior middle temporal gyrus (pMTG, BA21). Using whole-brain seed-based analysis, we demonstrated that these two regions have altered FC even beyond the semantic control network. In particular, the pMTG displayed a wide-distributed pattern of lower connectivity to several brain regions involved in language-semantic processing, along with a possibly compensatory higher connectivity to the Wernicke's area. We conclude that in mild AD brain regions belonging to the semantic control network are abnormally connected not only within the network, but also to other areas known to be critical for language processing.

Temporal Information Entropy of the Blood-Oxygenation Level-Dependent Signals Increases in the Activated Human Primary Visual Cortex.

Time-domain analysis of blood-oxygenation level-dependent (BOLD) signals allows the identification of clusters of voxels responding to photic stimulation in primary visual cortex (V1). However, the characterization of information encoding into temporal properties of the BOLD signals of an activated cluster is poorly investigated. Here, we used Shannon entropy to determine spatial and temporal information encoding in the BOLD signal within the most strongly activated area of the human visual cortex during a hemifield photic stimulation. We determined the distribution profile of BOLD signals during epochs at rest and under stimulation within small (19-121 voxels) clusters designed to include only voxels driven by the stimulus as highly and uniformly as possible. We found consistent and significant increases (2-4% on average) in temporal information entropy during activation in contralateral but not ipsilateral V1, which was mirrored by an expected loss of spatial information entropy. These opposite changes coexisted with increases in both spatial and temporal mutual information (i.e., dependence) in contralateral V1. Thus, we showed that the first cortical stage of visual processing is characterized by a specific spatiotemporal rearrangement of intracluster BOLD responses. Our results indicate that while in the space domain BOLD maps may be incapable of capturing the functional specialization of small neuronal populations due to relatively low spatial resolution, some information encoding may still be revealed in the temporal domain by an increase of temporal information entropy.

Computational Flux Balance Analysis Predicts that Stimulation of Energy Metabolism in Astrocytes and their Metabolic Interactions with Neurons Depend on Uptake of K+ Rather than Glutamate.

Brain activity involves essential functional and metabolic interactions between neurons and astrocytes. The importance of astrocytic functions to neuronal signaling is supported by many experiments reporting high rates of energy consumption and oxidative metabolism in these glial cells. In the brain, almost all energy is consumed by the Na+/K+ ATPase, which hydrolyzes 1 ATP to move 3 Na+ outside and 2 K+ inside the cells. Astrocytes are commonly thought to be primarily involved in transmitter glutamate cycling, a mechanism that however only accounts for few % of brain energy utilization. In order to examine the participation of astrocytic energy metabolism in brain ion homeostasis, here we attempted to devise a simple stoichiometric relation linking glutamatergic neurotransmission to Na+ and K+ ionic currents. To this end, we took into account ion pumps and voltage/ligand-gated channels using the stoichiometry derived from available energy budget for neocortical signaling and incorporated this stoichiometric relation into a computational metabolic model of neuron-astrocyte interactions. We aimed at reproducing the experimental observations about rates of metabolic pathways obtained by 13C-NMR spectroscopy in rodent brain. When simulated data matched experiments as well as biophysical calculations, the stoichiometry for voltage/ligand-gated Na+ and K+ fluxes generated by neuronal activity was close to a 1:1 relationship, and specifically 63/58 Na+/K+ ions per glutamate released. We found that astrocytes are stimulated by the extracellular K+ exiting neurons in excess of the 3/2 Na+/K+ ratio underlying Na+/K+ ATPase-catalyzed reaction. Analysis of correlations between neuronal and astrocytic processes indicated that astrocytic K+ uptake, but not astrocytic Na+-coupled glutamate uptake, is instrumental for the establishment of neuron-astrocytic metabolic partnership. Our results emphasize the importance of K+ in stimulating the activation of astrocytes, which is relevant to the understanding of brain activity and energy metabolism at the cellular level.

Monoaminergic Control of Cellular Glucose Utilization by Glycogenolysis in Neocortex and Hippocampus.

Brainstem nuclei are the principal sites of monoamine (MA) innervation to major forebrain structures. In the cortical grey matter, increased secretion of MA neuromodulators occurs in response to a wealth of environmental and homeostatic challenges, whose onset is associated with rapid, preparatory changes in neural activity as well as with increases in energy metabolism. Blood-borne glucose is the main substrate for energy production in the brain. Once entered the tissue, interstitial glucose is equally accessible to neurons and astrocytes, the two cell types accounting for most of cellular volume and energy metabolism in neocortex and hippocampus. Astrocytes also store substantial amounts of glycogen, but non-stimulated glycogen turnover is very small. The rate of cellular glucose utilization in the brain is largely determined by hexokinase, which under basal conditions is more than 90 % inhibited by its product glucose-6-phosphate (Glc-6-P). During rapid increases in energy demand, glycogen is a primary candidate in modulating the intracellular level of Glc-6-P, which can occur only in astrocytes. Glycogenolysis can produce Glc-6-P at a rate higher than uptake and phosphorylation of glucose. MA neurotransmitter are released extrasinaptically by brainstem neurons projecting to neocortex and hippocampus, thus activating MA receptors located on both neuronal and astrocytic plasma membrane. Importantly, MAs are glycogenolytic agents and thus they are exquisitely suitable for regulation of astrocytic Glc-6-P concentration, upstream substrate flow through hexokinase and hence cellular glucose uptake. Conforming to such mechanism, Gerald A. Dienel and Nancy F. Cruz recently suggested that activation of noradrenergic locus coeruleus might reversibly block astrocytic glucose uptake by stimulating glycogenolysis in these cells, thereby anticipating the rise in glucose need by active neurons. In this paper, we further develop the idea that the whole monoaminergic system modulates both function and metabolism of forebrain regions in a manner mediated by glycogen mobilization in astrocytes.

Intrinsic patterns of coupling between correlation and amplitude of low-frequency fMRI fluctuations are disrupted in degenerative dementia mainly due to functional disconnection.

Low frequency fluctuations (LFFs) of the BOLD signal are a major discovery in the study of the resting brain with functional magnetic resonance imaging (fMRI). Two fMRI-based measures, functional connectivity (FC), a measure of signal synchronicity, and the amplitude of LFFs (ALFF), a measure of signal periodicity, have been proved to be sensitive to changes induced by several neurological diseases, including degenerative dementia. In spite of the increasing use of these measures, whether and how they are related to each other remains to be elucidated. In this work we used voxel-wise FC and ALFF computed in different frequency bands (slow-5: 0.01-0.027 Hz; slow-4: 0.027-0.073 Hz; and full-band: 0.01-0.073 Hz), in order to assess their relationship in healthy elderly as well as the relevant changes induced by Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI). We found that in healthy elderly subjects FC and ALFF are positively correlated in anterior and posterior cingulate cortex (full-band, slow-4 and slow-5), temporal cortex (full-band and slow-5), and in a set of subcortical regions (full-band and slow-4). These correlation patterns between FC and ALFF were absent in either AD or MCI patients. Notably, the loss of correlation between FC and ALFF in the AD group was primarily due to changes in FC rather than in ALFF. Our results indicate that degenerative dementia is characterized by a loss of global connection rather than by a decrease of fluctuation amplitude.

Does abnormal glycogen structure contribute to increased susceptibility to seizures in epilepsy?

Epilepsy is a family of brain disorders with a largely unknown etiology and high percentage of pharmacoresistance. The clinical manifestations of epilepsy are seizures, which originate from aberrant neuronal synchronization and hyperexcitability. Reactive astrocytosis, a hallmark of the epileptic tissue, develops into loss-of-function of glutamine synthetase, impairment of glutamate-glutamine cycle and increase in extracellular and astrocytic glutamate concentration. Here, we argue that chronically elevated intracellular glutamate level in astrocytes is instrumental to alterations in the metabolism of glycogen and leads to the synthesis of polyglucosans. Unaccessibility of glycogen-degrading enzymes to these insoluble molecules compromises the glycogenolysis-dependent reuptake of extracellular K(+) by astrocytes, thereby leading to increased extracellular K(+) and associated membrane depolarization. Based on current knowledge, we propose that the deterioration in structural homogeneity of glycogen particles is relevant to disruption of brain K(+) homeostasis and increased susceptibility to seizures in epilepsy.

On the impact of physiological noise in spinal cord functional MRI.

Functional magnetic resonance imaging (fMRI) techniques are widely exploited for the study of brain activation. In recent years, similar approaches have been attempted for the study of spinal cord function; however, obtaining good functional images of spinal cord still represents a technical and scientific challenge. Some of the main limiting factors can be classified under the broad category of "physiological noise," and are related to 1) the cerebrospinal fluid (CSF) flux in the subarachnoid space surrounding the spinal cord; 2) the cord motion itself; and 3) the small area of the cord, which makes it critical to have a high image resolution. In addition, the different magnetic susceptibility properties of tissues surrounding the spinal cord reduce the local homogeneity of the static magnetic field, causing image distortion, reduction of the effective resolution, and signal loss, all effects that are modulated by motion. For these reasons, a number of methods have been developed for the purpose of denoising spinal cord fMRI time series. In this work, after a short introduction on the relevant features of the spinal cord anatomy, we review the main sources of physiological noise in spinal cord fMRI and discuss the main approaches useful for its mitigation.

Physiological bases of the K+ and the glutamate/GABA hypotheses of epilepsy.

Epilepsy is a heterogeneous family of neurological disorders that manifest as seizures, i.e. the hypersynchronous activity of large population of neurons. About 30% of epileptic patients do not respond to currently available antiepileptic drugs. Decades of intense research have elucidated the involvement of a number of possible signaling pathways, however, at present we do not have a fundamental understanding of epileptogenesis. In this paper, we review the literature on epilepsy under a wide-angle perspective, a mandatory choice that responds to the recurrent and unanswered question about what is epiphenomenal and what is causal to the disease. While focusing on the involvement of K+ and glutamate/GABA in determining neuronal hyperexcitability, emphasis is given to astrocytic contribution to epileptogenesis, and especially to loss-of-function of astrocytic glutamine synthetase following reactive astrogliosis, a hallmark of epileptic syndromes. We finally introduce the potential involvement of abnormal glycogen synthesis induced by excess glutamate in increasing susceptibility to seizures.

Energy metabolism and glutamate-glutamine cycle in the brain: a stoichiometric modeling perspective.

BACKGROUND: The energetics of cerebral activity critically relies on the functional and metabolic interactions between neurons and astrocytes. Important open questions include the relation between neuronal versus astrocytic energy demand, glucose uptake and intercellular lactate transfer, as well as their dependence on the level of activity. RESULTS: We have developed a large-scale, constraint-based network model of the metabolic partnership between astrocytes and glutamatergic neurons that allows for a quantitative appraisal of the extent to which stoichiometry alone drives the energetics of the system. We find that the velocity of the glutamate-glutamine cycle (Vcyc) explains part of the uncoupling between glucose and oxygen utilization at increasing Vcyc levels. Thus, we are able to characterize different activation states in terms of the tissue oxygen-glucose index (OGI). Calculations show that glucose is taken up and metabolized according to cellular energy requirements, and that partitioning of the sugar between different cell types is not significantly affected by Vcyc. Furthermore, both the direction and magnitude of the lactate shuttle between neurons and astrocytes turn out to depend on the relative cell glucose uptake while being roughly independent of Vcyc. CONCLUSIONS: These findings suggest that, in absence of ad hoc activity-related constraints on neuronal and astrocytic metabolism, the glutamate-glutamine cycle does not control the relative energy demand of neurons and astrocytes, and hence their glucose uptake and lactate exchange.

Regulatory mechanisms for glycogenolysis and K+ uptake in brain astrocytes.

Recent advances in brain energy metabolism support the notion that glycogen in astrocytes is necessary for the clearance of neuronally-released K(+) from the extracellular space. However, how the multiple metabolic pathways involved in K(+)-induced increase in glycogen turnover are regulated is only partly understood. Here we summarize the current knowledge about the mechanisms that control glycogen metabolism during enhanced K(+) uptake. We also describe the action of the ubiquitous Na(+)/K(+) ATPase for both ion transport and intracellular signaling cascades, and emphasize its importance in understanding the complex relation between glycogenolysis and K(+) uptake.

Glucose metabolism down-regulates the uptake of 6-(N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl)amino)-2-deoxyglucose (6-NBDG) mediated by glucose transporter 1 isoform (GLUT1): theory and simulations using the symmetric four-state carrier model.

The non-metabolizable fluorescent glucose analogue 6-(N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl)amino)-2-deoxyglucose (6-NBDG) is increasingly used to study cellular transport of glucose. Intracellular accumulation of exogenously applied 6-NBDG is assumed to reflect concurrent gradient-driven glucose uptake by glucose transporters (GLUTs). Here, theoretical considerations are provided that put this assumption into question. In particular, depending on the microscopic parameters of the carrier proteins, theory proves that changes in glucose transport can be accompanied by opposite changes in flow of 6-NBDG. Simulations were carried out applying the symmetric four-state carrier model on the GLUT1 isoform, which is the only isoform whose kinetic parameters are presently available. Results show that cellular 6-NBDG uptake decreases with increasing rate of glucose utilization under core-model conditions, supported by literature, namely where the transporter is assumed to work in regime of slow reorientation of the free-carrier compared with the ligand-carrier complex. To observe an increase of 6-NBDG uptake with increasing rate of glucose utilization, and thus interpret 6-NBDG increase as surrogate of glucose uptake, the transporter must be assumed to operate in regime of slow ligand-carrier binding, a condition that is currently not supported by literature. Our findings suggest that the interpretation of data obtained with NBDG derivatives is presently ambiguous and should be cautious because the underlying transport kinetics are not adequately established.

Spatio-temporal anomalous diffusion imaging: results in controlled phantoms and in excised human meningiomas.

Recently, we measured two anomalous diffusion (AD) parameters: the spatial and the temporal AD indices, called γ and α, respectively, by using spectroscopic pulse gradient field methods. We showed that γ quantifies pseudo-superdiffusion processes, while α quantifies subdiffusion processes. Here, we propose γ and α maps obtained in a controlled heterogeneous phantom, comprised of packed micro-beads in water and in excised human meningiomas. In few words, α maps represent the multi-scale spatial distribution of the disorder degree in the system, while γ maps are influenced by local internal gradients, thus highlighting the interface between compartments characterized by different magnetic susceptibility. γ maps were already obtained by means of AD stretched exponential imaging and α-type maps have been recently achieved for fixed rat brain with the aim of highlighting the fractal dimension of specific brain regions. However, to our knowledge, the maps representative of the spatial distribution of α and γ obtained on the same controlled sample and in the same excised tissue have never been compared. Moreover, we show here, for the first time, that α maps are representative of the spatial distribution of the disorder degree of the system. In a first phase, γ and α maps of controlled phantom characterized by an ordered and a disordered rearrangement of packed micro-beads of different sizes in water and by different magnetic susceptibility (Δχ) between beads and water were obtained. In a second phase, we investigated excised human meningiomas of different consistency. Results reported here, obtained at 9.4T, show that α and γ maps are characterized by a different image contrast. Indeed, unlike γ maps, α maps are insensible to (Δχ) and they are sensible to the disorder degree of the microstructural rearrangement. These observations strongly suggest that AD indices α and γ reflect some additional microstructural information which cannot be obtained using conventional diffusion methods based on Gaussian diffusion. Moreover, α and γ maps obtained in excised meningiomas seem to provide more microstructural details above those obtained with conventional DTI analysis, which could be used to improve the classification of meningiomas based on their consistency.

The role of astrocytic glycogen in supporting the energetics of neuronal activity.

Energy homeostasis in the brain is maintained by oxidative metabolism of glucose, primarily to fulfil the energy demand associated with ionic movements in neurons and astrocytes. In this contribution we review the experimental evidence that grounds a specific role of glycogen metabolism in supporting the functional energetic needs of astrocytes during the removal of extracellular potassium. Based on theoretical considerations, we further discuss the hypothesis that the mobilization of glycogen in astrocytes serves the purpose to enhance the availability of glucose for neuronal glycolytic and oxidative metabolism at the onset of stimulation. Finally, we provide an evolutionary perspective for explaining the selection of glycogen as carbohydrate reserve in the energy-sensing machinery of cell metabolism.

Ictal haemodynamic changes in a patient affected by "subtle" Epilepsia Partialis Continua.

We report on a 64 year-old woman presenting with Epilepsia Partialis Continua (EPC) affecting the left hand since the age of 24 without neurological deficit. Structural MRI showed a region of focal cortical dysplasia (FCD) over the right central gyrus and lesions in the mesial frontal and occipital cortex secondary to perinatal hypoxic injury. Ictal spike haemodynamic mapping using simultaneous EEG-fMRI revealed significant BOLD signal changes prominent in the region of FCD (larger cluster), occipital cortex (global statistical maximum), prefrontal cortex and cerebellum. The cluster over FCD was in good agreement with the result of EEG source analysis. Our findings provide an interesting illustration of the ability of EEG-fMRI to reveal epileptogenic networks confirming the intrinsic epileptogenic properties of dysplastic neurons.

Phase stability in fMRI time series: effect of noise regression, off-resonance correction and spatial filtering techniques.

Although the majority of fMRI studies exploit magnitude changes only, there is an increasing interest regarding the potential additive information conveyed by the phase signal. This integrated part of the complex number furnished by the MR scanners can also be used for exploring direct detection of neuronal activity and for thermography. Few studies have explicitly addressed the issue of the available signal stability in the context of phase time-series, and therefore we explored the spatial pattern of frequency specific phase fluctuations, and evaluated the effect of physiological noise components (heart beat and respiration) on the phase signal. Three categories of retrospective noise reduction techniques were explored and the temporal signal stability was evaluated in terms of a physiologic noise model, for seven fMRI measurement protocols in eight healthy subjects at 3T, for segmented CSF, gray and white matter voxels. We confirmed that for most processing methods, an efficient use of the phase information is hampered by the fact that noise from physiological and instrumental sources contributes significantly more to the phase than to the magnitude instability. Noise regression based on the phase evolution of the central k-space point, RETROICOR, or an orthonormalized combination of these were able to reduce their impact, but without bringing phase stability down to levels expected from the magnitude signal. Similar results were obtained after targeted removal of scan-to-scan variations in the bulk magnetic field by the dynamic off-resonance in k-space (DORK) method and by the temporal off-resonance alignment of single-echo time series technique (TOAST). We found that spatial high-pass filtering was necessary, and in vivo a Gaussian filter width of 20mm was sufficient to suppress physiological noise and bring the phase fluctuations to magnitude levels. Stronger filters brought the fluctuations down to levels dictated by thermal noise contributions, and for 62.5mm(3) voxels the phase stability was as low as 5 mrad (0.27°). In conditions of low SNR(o) and high temporal sampling rate (short TR); we achieved an upper bound for the phase instabilities at 0.0017 ppm, which is close to the dHb contribution to the GM/WM phase contrast.

Semiautomated segmentation of the human spine based on echoplanar images.

The number of functional magnetic resonance imaging (fMRI) studies performed on the human spinal cord (SC) has considerably increased in recent years. The lack of a validated processing pipeline is, however, a significant obstacle to the spread of SC fMRI. One component likely to be involved in any such pipeline is the process of SC masking, analogous to brain extraction in cerebral fMRI. In general, SC masking has been performed manually, with the incumbent costs of being very time consuming and operator dependent. To overcome these drawbacks, we have developed a tailored semiautomatic method for segmenting echoplanar images (EPI) of human spine that is able to identify the spinal canal and the SC. The method exploits both temporal and spatial features of the EPI series and was tested and optimized on EPI images of cervical spine acquired at 3 T. The dependence of algorithm performance on the degree of EPI image distortion was assessed by computing the displacement warping field that best matched the EPI to the corresponding high-resolution T(2) images. Segmentation accuracy was above 80%, a significant improvement over values obtained with similar approaches, but not exploiting temporal information. Geometric distortion was found to explain about 50% of the variance of algorithm classification efficiency.

Modeling the contribution of neuron-astrocyte cross talk to slow blood oxygenation level-dependent signal oscillations.

A consistent and prominent feature of brain functional magnetic resonance imaging (fMRI) data is the presence of low-frequency (<0.1 Hz) fluctuations of the blood oxygenation level-dependent (BOLD) signal that are thought to reflect spontaneous neuronal activity. In this report we provide modeling evidence that cyclic physiological activation of astroglial cells produces similar BOLD oscillations through a mechanism mediated by intracellular Ca(2+) signaling. Specifically, neurotransmission induces pulses of Ca(2+) concentration in astrocytes, resulting in increased cerebral perfusion and neuroactive transmitter release by these cells (i.e., gliotransmission), which in turn stimulates neuronal activity. Noticeably, the level of neuron-astrocyte cross talk regulates the periodic behavior of the Ca(2+) wave-induced BOLD fluctuations. Our results suggest that the spontaneous ongoing activity of neuroglial networks is a potential source of the observed slow fMRI signal oscillations.

Non-Gaussian diffusion imaging: a brief practical review.

The departure from purely mono-exponential decay of the signal, as observed from brain tissue following a diffusion-sensitized sequence, has prompted the search for alternative models to characterize these unconventional water diffusion dynamics. Several approaches have been proposed in the last few years. While multi-exponential models have been applied to characterize brain tissue, several unresolved controversies about the interpretations of the results have motivated the search for alternative models that do not rely on the Gaussian diffusion hypothesis. In this brief review, diffusional kurtosis imaging (DKI) and anomalous diffusion imaging (ADI) techniques are addressed and compared with diffusion tensor imaging. Theoretical and experimental issues are briefly described to allow readers to understand similarities, differences and limitations of these two non-Gaussian models. However, since the ultimate goal is to improve specificity, sensitivity and spatial localization of diffusion MRI for the detection of brain diseases, special attention will be paid on the clinical feasibility of the proposed techniques as well as on the context of brain pathology investigations.

Why does the brain (not) have glycogen?

In the present paper we formulate the hypothesis that brain glycogen is a critical determinant in the modulation of carbohydrate supply at the cellular level. Specifically, we propose that mobilization of astrocytic glycogen after an increase in AMP levels during enhanced neuronal activity controls the concentration of glucose phosphates in astrocytes. This would result in modulation of glucose phosphorylation by hexokinase and upstream cell glucose uptake. This mechanism would favor glucose channeling to activated neurons, supplementing the already rich neuron-astrocyte metabolic and functional partnership with important implications for the energy compounds used to sustain neuronal activity. The hypothesis is based on recent modeling evidence suggesting that rapid glycogen breakdown can profoundly alter the short-term kinetics of glucose delivery to neurons and astrocytes. It is also based on review of the literature relevant to glycogen metabolism during physiological brain activity, with an emphasis on the metabolic pathways identifying both the origin and the fate of this glucose reserve.