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The estimation of incidentally encoded durations of time intervals (retrospective duration processing) is thought to rely on the retrieval of contextual information associated with a sequence of events, automatically encoded in medial temporal lobe regions. “Time cells” have been described in the hippocampus (HC), encoding the temporal progression of events and their duration. However, whether the HC supports explicit retrospective duration judgments in humans, and which neural dynamics are involved, is still poorly understood. Here we used resting-state fMRI to test the relation between variations in intrinsic connectivity patterns of the HC, and individual differences in retrospective duration processing, assessed using a novel task involving the presentation of ecological stimuli. Results showed that retrospective duration discrimination performance predicted variations in the intrinsic connectivity of the bilateral HC with the right precentral gyrus; follow-up exploratory analyses suggested a role of the CA1 and CA4/DG subfields in driving the observed pattern. Findings provide insights on neural networks associated with implicit processing of durations in the second range.

Sleep is a universal and evolutionarily conserved behavior among many animal species, yet we do not have a fundamental understanding of why animals need to sleep. What we do know, however, is that sleep is critical for behavioral performance during the waking period and for long-term brain health. Here we provide an overview of some putative mechanisms that mediate the restorative effects of sleep, namely metabolic biosynthesis, fluid perfusion, and synaptic homeostasis. We then review recent experimental findings that advance the possibility of inducing sleep-like slow-wave activity (SWA) during wakefulness or enhance SWA during sleep in a top-down manner using noninvasive brain stimulation. SWA induction and SWA enhancement are believed to recapitulate the beneficial effects of sleep independent of the actual state of the subjects. If confirmed, these observations will change the way in which we investigate the neural correlates of sleep, thus paving the way for comprehending and actively controlling its restorative function.

Autobiographical memory includes a representation of personal life events with a unique spatiotemporal context (episodic autobiographical memory) and factual self-knowledge (personal semantics). Whereas “experience-far” personal semantics have undergone complete abstraction, “experience-near” personal semantics are still linked to a spatiotemporal context. The representation of one's own past involves an autobiographical knowledge base, in the form of a personal timeline, along which autobiographical information is temporally organized into different lifetime periods. Commonalities and differences between brain networks supporting this temporal organization for autobiographical information with different contextual specificity, however, have not been investigated to date. Here, we used task-based fMRI to assess neural substrates of temporal ordering along the personal timeline for real autobiographical episodic and experience-near personal semantic memories. Within a distributed network, the left calcarine cortex was more strongly activated for episodic autobiographical memory than personal semantics, whereas the left ventromedial pFC and right posterior cingulate cortex (PCC), angular gyrus (AG), and anterior middle temporal gyrus (aMTG) showed stronger activation for personal semantics than episodic autobiographical memory. Findings were confirmed by analyses in independently derived ROIs. Generalized psychophysiological interaction analyses between the same regions showed that, during personal semantics compared with episodic autobiographical memory, memory category modulated activity in the left PCC and right PCC, AG, and aMTG. Findings provide insights on how personal events and facts are represented in the timescale of years, suggesting that the temporal organization of autobiographical memory exploits properties of situation models developed within posteromedial, lateral parietal, and medial prefrontal regions.

Processing of incoming sensory stimulation triggers an increase of cerebral perfusion and blood oxygenation (neurovascular response) as well as an alteration of the metabolic neurochemical profile (neurometabolic response). Here, we show in human primary visual cortex (V1) that perceived and unperceived isoluminant chromatic flickering stimuli designed to have similar neurovascular responses as measured by blood oxygenation level-dependent functional magnetic resonance imaging (BOLD-fMRI) have markedly different neurometabolic responses as measured by proton functional magnetic resonance spectroscopy (1H-fMRS). In particular, a significant regional buildup of lactate, an index of aerobic glycolysis, and glutamate, an index of malate–aspartate shuttle, occurred in V1 only when the flickering was perceived, without any relation with other behavioral or physiological variables. Whereas the BOLD-fMRI signal in V1, a proxy for input to V1, was insensitive to flickering perception by design, the BOLD-fMRI signal in secondary visual areas was larger during perceived than unperceived flickering, indicating increased output from V1. These results demonstrate that the upregulation of energy metabolism induced by visual stimulation depends on the type of information processing taking place in V1, and that 1H-fMRS provides unique information about local input/output balance that is not measured by BOLD-fMRI.

Over the last two decades, it has been established that glucose metabolic fluxes in neurons and astrocytes are proportional to the rates of the glutamate/GABA-glutamine neurotransmitter cycles in close to 1:1 stoichiometries across a wide range of functional energy demands. However, there is presently no mechanistic explanation for these relationships. We present here a theoretical meta-analysis that tests whether the brain’s unique compartmentation of glycogen metabolism in the astrocyte and the requirement for neuronal glucose homeostasis lead to the observed stoichiometries. We found that blood-brain barrier glucose transport can be limiting during activation and that the energy demand could only be met if glycogenolysis supports neuronal glucose metabolism by replacing the glucose consumed by astrocytes, a mechanism we call Glucose Sparing by Glycogenolysis (GSG). The predictions of the GSG model are in excellent agreement with a wide range of experimental results from rats, mice, tree shrews, and humans, which were previously unexplained. Glycogenolysis and glucose sparing dictate the energy available to support neuronal activity, thus playing a fundamental role in brain function in health and disease.

Visuospatial attention is strongly lateralized, with the right hemisphere commonly exhibiting stronger activation and connectivity patterns than the left hemisphere during attentive processes. However, whether such asymmetry influences inter-hemispheric information transfer and behavioral performance is not known. Here we used a region of interest (ROI) and network-based approach to determine steady-state fMRI functional connectivity (FC) in the whole cerebral cortex during a leftward/rightward covert visuospatial attention task. We found that the global FC topology between either ROIs or networks was independent on the attended side. The side of attention significantly modulated FC strength between brain networks, with leftward attention primarily involving the connections of the right visual network with dorsal and ventral attention networks in both the left and right hemisphere. High hemispheric functional segregation significantly correlated with faster target detection response times (i.e., better performance). Our findings suggest that the dominance of the right hemisphere in visuospatial attention is associated with an hemispheric functional segregation that is beneficial for behavioral performance.

Processing of incoming sensory stimulation triggers an increase of cerebral perfusion and blood oxygenation (neurovascular response) as well as an alteration of the metabolic neurochemical profile (neurometabolic response). Here we show that perceived and unperceived isoluminant chromatic flickering stimuli designed to have similar neurovascular responses as measured by blood oxygenation level dependent functional MRI (BOLD-fMRI) in primary visual cortex (V1) have markedly different neurometabolic responses as measured by functional MRS. In particular, a significant regional buildup of lactate, an index of aerobic glycolysis, and glutamate, an index of malate-aspartate shuttle, occurred in V1 only when the flickering is perceived, without any relation with behavioral or physiological variables. Wheras the BOLD-fMRI signal in V1, a proxy for input to V1, was insensitive to flickering perception by design, the BOLD-fMRI signal in secondary visual areas was larger during perceived than unperceived flickering indicating increased output from V1. These results indicate that the upregulation of energy metabolism induced by visual stimulation depends on the type of information processing taking place in V1, and that 1H-fMRS provides unique information about local input/output balance that is not measured by BOLD-fMRI.Significance statementVisual perception has a measurable metabolic effect in the primary visual cortex (V1). Here we show that the upregulation of energy metabolism induced by isoluminant chromatic flickering depends on subjective visual perception. Within V1, perceived and unperceived stimuli that are contrast-matched to elicit similar blood-oxygenation level-dependent fMRI response are associated with clearly distinct neurochemical profiles. Specifically, regional accumulations of lactate (an index of aerobic glycolysis) and glutamate (an index of malate-aspartate shuttle) only develop during perceived stimuli, together with a larger activation of secondary visual areas. Our results imply a dissociation between metabolic and functional response, and indicate that that the upregulation of energy metabolism induced by visual stimulation depends on the type of information processing taking place in V1.

Skull-stripping and region segmentation are fundamental steps in preclinical magnetic resonance imaging (MRI) studies, and these common procedures are usually performed manually. We present Multi-task U-Net (MU-Net), a convolutional neural network designed to accomplish both tasks simultaneously. MU-Net achieved higher segmentation accuracy than state-of-the-art multi-atlas segmentation methods with an inference time of 0.35 seconds and no pre-processing requirements. We evaluated the performance of our network in the presence of skip connections and recently proposed framing connections, finding the simplest network to be the most effective. We tested MU-Net with an unusually large dataset combining several independent studies consisting of 1,782 mouse brain MRI volumes of both healthy and Huntington animals, and measured average Dice scores of 0.906 (striati), 0.937 (cortex), and 0.978 (brain mask). These high evaluation scores demonstrate that MU-Net is a powerful tool for segmentation and skull-stripping, decreasing inter and intra-rater variability of manual segmentation. The MU-Net code and the trained model are publicly available at https://github.com/Hierakonpolis/MU-Net.

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.

In the present study, we aimed at determining the metabolic responses of the human visual cortex during the presentation of chromatic and achromatic stimuli, known to preferentially activate two separate clusters of neuronal populations (called “blobs” and “interblobs”) with distinct sensitivity to color or luminance features. Since blobs and interblobs have different cytochrome-oxidase (COX) content and micro-vascularization level (i.e., different capacities for glucose oxidation), different functional metabolic responses during chromatic vs. achromatic stimuli may be expected. The stimuli were optimized to evoke a similar load of neuronal activation as measured by the bold oxygenation level dependent (BOLD) contrast. Metabolic responses were assessed using functional 1H MRS at 7 T in 12 subjects. During both chromatic and achromatic stimuli, we observed the typical increases in glutamate and lactate concentration, and decreases in aspartate and glucose concentration, that are indicative of increased glucose oxidation. However, within the detection sensitivity limits, we did not observe any difference between metabolic responses elicited by chromatic and achromatic stimuli. We conclude that the higher energy demands of activated blobs and interblobs are supported by similar increases in oxidative metabolism despite the different capacities of these neuronal populations.

Phasic changes in eye's pupil diameter have been repeatedly observed during cognitive, emotional and behavioral activity in mammals. Although pupil diameter is known to be associated with noradrenergic firing in the pontine Locus Coeruleus (LC), thus far the causal chain coupling spontaneous pupil dynamics to specific cortical brain networks remains unknown. In the present study, we acquired steady-state blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) data combined with eye-tracking pupillometry from fifteen healthy subjects that were trained to maintain a constant attentional load. Regression analysis revealed widespread visual and sensorimotor BOLD-fMRI deactivations correlated with pupil diameter. Furthermore, we found BOLD-fMRI activations correlated with pupil diameter change rate within a set of brain regions known to be implicated in selective attention, salience, error-detection and decision-making. These regions included LC, thalamus, posterior cingulate cortex (PCC), dorsal anterior cingulate and paracingulate cortex (dACC/PaCC), orbitofrontal cortex (OFC), and right anterior insular cortex (rAIC). Granger-causality analysis performed on these regions yielded a complex pattern of interdependence, wherein LC and pupil dynamics were far apart in the network and separated by several cortical stages. Functional connectivity (FC) analysis revealed the ubiquitous presence of the superior frontal gyrus (SFG) in the networks identified by the brain regions correlated to the pupil diameter change rate. No significant correlations were observed between pupil dynamics, regional activation and behavioral performance. Based on the involved brain regions, we speculate that pupil dynamics reflects brain processing implicated in changes between self- and environment-directed awareness.

One of the most common tasks in small rodents MRI pipelines is the voxel-wise segmentation of the volume in multiple classes. While many segmentation schemes have been developed for the human brain, fewer are available for rodent MRI, often by adaptation from human neuroimaging. Common methods include atlas-based and clustering schemes. The former labels the target volume by registering one or more pre-labeled atlases using a deformable registration method, in which case the result depends on the quality of the reference volumes, the registration algorithm and the label fusion approach, if more than one atlas is employed. The latter is based on an expectation maximization procedure to maximize the variance between voxel categories, and is often combined with Markov Random Fields and the atlas based approach to include spatial information, priors, and improve the classification accuracy. Our primary goal is to critically review the state of the art of rat and mouse segmentation of neuro MRI volumes and compare the available literature on popular, readily and freely available MRI toolsets, including SPM, FSL and ANTs, when applied to this task in the context of common pre-processing steps. Furthermore, we will briefly address the emerging Deep Learning methods for the segmentation of medical imaging, and the perspectives for applications to small rodents.

Idiopathic rapid eye movement sleep behavior disorder (iRBD) is a condition that often evolves into Parkinson's disease (PD). Therefore, by monitoring iRBD it is possible to track the neurodegeneration of individuals who may progress to PD. Here we aimed at piloting the characterization of brain tissue properties in mid-brain subcortical regions of 10 healthy subjects, 8 iRBD, and 9 early-diagnosed PD. We used a battery of magnetic resonance imaging (MRI) contrasts at 3 T, including adiabatic and non-adiabatic rotating frame techniques developed by our group, along with diffusion tensor imaging (DTI) and resting-state fMRI. Adiabatic T1ρ and T2ρ, and non-adiabatic RAFF4 (Relaxation Along a Fictitious Field in the rotating frame of rank 4) were found to have lower coefficient of variations and higher sensitivity to detect group differences as compared to DTI parameters such as fractional anisotropy and mean diffusivity. Significantly longer T1ρ were observed in the amygdala of PD subjects vs. controls, along with a trend of lower functional connectivity as measured by regional homogeneity, thereby supporting the notion that amygdalar dysfunction occurs in PD. Significant abnormalities in reward networks occurred in iRBD subjects, who manifested lower network strength of the accumbens. In agreement with previous studies, significantly longer T1ρ occurred in the substantia nigra compacta of PD vs. controls, indicative of neuronal degeneration, while regional homogeneity was lower in the substantia nigra reticulata. Finally, other trend-level findings were observed, i.e., lower RAFF4 and T2ρ in the midbrain of iRBD subjects vs. controls, possibly indicating changes in non-motor features as opposed to motor function in the iRBD group. We conclude that rotating frame relaxation methods along with functional connectivity measures are valuable to characterize iRBD and PD subjects, and with proper validation in larger cohorts may provide pathological signatures of iRBD and PD.

Brain activity at rest is characterized by widely distributed and spatially specific patterns of synchronized low-frequency blood-oxygenation level-dependent (BOLD) fluctuations, which correspond to physiologically relevant brain networks. This network behaviour is known to persist also during task execution, yet the details underlying task-associated modulations of within- and between-network connectivity are largely unknown. In this study we exploited a multi-parametric and multi-scale approach to investigate how low-frequency fluctuations adapt to a sustained n-back working memory task. We found that the transition from the resting state to the task state involves a behaviourally relevant and scale-invariant modulation of synchronization patterns within both task-positive and default mode networks. Specifically, decreases of connectivity within networks are accompanied by increases of connectivity between networks. In spite of large and widespread changes of connectivity strength, the overall topology of brain networks is remarkably preserved. We show that these findings are strongly influenced by connectivity at rest, suggesting that the absolute change of connectivity (i.e., disregarding the baseline) may be not the most suitable metric to study dynamic modulations of functional connectivity. Our results indicate that a task can evoke scale-invariant, distributed changes of BOLD fluctuations, further confirming that low frequency BOLD oscillations show a specialized response and are tightly bound to task-evoked activation. The human brain is organized in functional networks, characterized by long range functional connections between brain areas. This network behavior is modulated by the execution of tasks. In our work, we show that modulations associated to a task are massive and widespread, but changes are scale invariant and the overall topology of the networks is well preserved under stimulation, confirming that the functional networks are intrinsic features of the human brain function. We found also that the amplitude of the massive change we observed is heavily influenced by the degree of connectivity at rest, indicating that the magnitude of connectivity change is not an independent metric for the assessment of functional network dynamics.

Idiopathic rapid eye movement sleep behavior disorder (iRBD) is a condition that often evolves into Parkinson’s disease (PD). Therefore, by monitoring iRBD it is possible to track the neurodegeneration of individuals who may progress to PD. Here we aimed at piloting the characterization of brain tissue properties in mid-brain subcortical regions of 10 healthy subjects, 8 iRBD, and 9 early-diagnosed PD. We used a battery of magnetic resonance imaging (MRI) contrasts at 3 T, including adiabatic and non-adiabatic rotating frame techniques developed by our group, along with diffusion tensor imaging and resting-state fMRI. Adiabatic T1 and T2, and non-adiabatic RAFF4 (Relaxation Along a Fictitious Field in the rotating frame of rank 4) were found to have lower coefficient of variations and higher sensitivity to detect group differences as compared to DTI parameters such as fractional anisotropy and mean diffusivity. Significantly longer T1 were observed in the amygdala of PD subjects versus controls, along with a trend of lower functional connectivity as measured by network regional homogeneity, thereby supporting the notion that amygdalar dysfunction occurs in PD. Significant abnormalities in reward networks occurred in iRBD subjects, who manifested lower network strength of the accumbens. In agreement with previous studies, significantly longer T1 occurred in the substantia nigra compacta of PD versus controls, indicative of neuronal degeneration, while regional homogeneity was lower in the network of the substantia nigra reticulata. Finally, other trend-level findings were observed, i.e., lower RAFF4 and T2 in the midbrain of iRBD subjects vs controls, possibly indicating changes in non-motor features as opposed to motor function in the iRBD group. We conclude that rotating frame relaxation methods along with functional connectivity measures are valuable to characterize iRBD and PD subjects, and with proper validation in larger cohorts may provide pathological signatures of iRBD and PD.

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.

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.

Fractal analysis is a powerful method for the morphological study of complex systems that is increasingly applied to biomedical images. Spatial resolution and image segmentation are crucial for the discrimination of tissue structures at the multiscale level. In this work, we have applied fractal analysis to high-resolution X-ray phase contrast micro-tomography (XrPC&mu, T) images in both uninjured and injured tissue of a mouse spinal cord. We estimated the fractal dimension (FD) using the box-counting method on tomographic slices segmented at different threshold levels. We observed an increased FD in the ipsilateral injured hemicord compared with the contralateral uninjured tissue, which was almost independent of the chosen threshold. Moreover, we found that images exhibited the highest fractality close to the global histogram threshold level. Finally, we showed that the FD estimate largely depends on the image histogram regardless of tissue appearance. Our results demonstrate that the pre-processing of XrPC&mu, T images is critical to fractal analysis and the estimation of FD.

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.

Nowadays hybrid PET/MRI systems and magnetic resonance spectroscopy (MRS) with high field strength are becoming more widespread not only in research applications but also in clinical practice. The aim of this paper is to review the current roles of high-field PET/MRI and high-field magnetic resonance spectroscopy (MRS) in the clinical setting and their applications in research. A non-systematic literature search of the Medline and Cochrane Library databases was performed up to September 2012. Bibliographies of retrieved articles and review articles were also examined. Only those articles reporting complete data of clinical and research relevance for the present review (i.e., diagnosis, therapeutic response monitoring) were selected. The advent of higher field strengths (3-T and above), and thus, higher spectral resolution, increased the potentiality and the diffusion of MRS evaluations. This review article is divided into two major parts. The first considers the potential clinical and research roles of MRS at 3-T and of hybrid system PET/MRI, particularly with regard to simultaneous PET/MRI systems which provide some major advantages over the conventional PET/CT systems (such as identical position of the patient during image acquisition, no radiation burden from the MRI part, more structural, functional and molecular imaging at the same time). The second part provides detailed information about the use of ultra-high-field MRS and MRI (7-T) integrated with PET. The fusion of biological information (PET) and morpho-metabolic patterns (MRI–MRS) shows promise for obtaining early diagnosis, coherent follow-up and the desired response to therapy.

The available estimate of the energy expended for signaling in rat neocortex is refined to examine the separate contribution of spiking and synaptic activity as a function of average neuronal firing rate. By taking into account a phenomenological model of short-term synaptic plasticity, we show that the transition from low to high cortical activity is accompanied by a substantial increase in relative energy consumed by action potentials vs. synaptic potentials. This consideration might be important for a deeper understanding of how information is represented in the cortex and which metabolic pathways are upregulated to sustain cortical activity.

For many years, a tenet of cerebral metabolism held that glucose was the obligate energy substrate of the mammalian brain and that neuronal oxidative metabolism represented the majority of this glucose utilization. In 1994, Pellerin and Magistretti formulated the astrocyte-neuron lactate shuttle (ANLS) hypothesis, in which astrocytes, not neurons, metabolized glucose, with subsequent transport of the glycolytically derived lactate to fuel the energy needs of the neuron during neurotransmission. By considering the concentrations and kinetic characteristics of the nutrient transporter proteins, Simpson et al later supported the opposite view, in which lactate flows from neurons to astrocytes, thus leading to the neuron-astrocyte lactate shuttle (NALS). Most recently, a commentary was published in this journal attempting to discredit the NALS. This challenge has stimulated the present response in which we detail the inaccuracies of the commentary and further model several different possibilities. Although our simulations continue to support the predominance of neuronal glucose utilization during activation and neuronal to astrocytic lactate flow, the most important result is that, regardless of the direction of the flow, the overall contribution of lactate to cerebral glucose metabolism is found to be so small as to make this ongoing debate ‘much ado about nothing'.

Functional Magnetic Resonance Imaging (fMRI) based on Blood Oxygenation Level Dependent (BOLD) contrast has become one of the most powerful tools in neuroscience research. On the other hand, fMRI approaches have seen limited use in the study of spinal cord and subcortical brain regions (such as the brainstem and portions of the diencephalon). Indeed obtaining good BOLD signal in these areas still represents a technical and scientific challenge, due to poor control of physiological noise and to a limited overall quality of the functional series. A solution can be found in the combination of optimized experimental procedures at acquisition stage, and well-adapted artifact mitigation procedures in the data processing. In this framework, we studied two different data processing strategies to reduce physiological noise in cortical and subcortical brain regions and in the spinal cord, based on the aCompCor and RETROICOR denoising tools respectively. The study, performed in healthy subjects, was carried out using an ad hoc isometric motor task. We observed an increased signal to noise ratio in the denoised functional time series in the spinal cord and in the subcortical brain region.

In this paper, we combined several mathematical models of cerebral metabolism and nutrient transport to investigate the energetic significance of metabolite trafficking within the brain parenchyma during a 360-secs activation. Glycolytic and oxidative cellular metabolism were homogeneously modeled between neurons and astrocytes, and the stimulation-induced neuronal versus astrocytic Na+ inflow was set to 3:1. These assumptions resemble physiologic conditions and are supported by current literature. Simulations showed that glucose diffusion to the interstitium through basal lamina dominates the provision of the sugar to both neurons and astrocytes, whereas astrocytic endfeet transfer less than 4% of the total glucose supplied to the tissue. Neuronal access to paracellularly diffused glucose prevails even after halving (doubling) the ratio of neuronal versus astrocytic glycolytic (oxidative) metabolism, as well as after reducing the neuronal versus astrocytic Na+ inflow to a nonphysiologic value of 1:1. Noticeably, displaced glucose equivalents as intercellularly shuttled lactate account for ∼6% to 7% of total brain glucose uptake, an amount comparable with the concomitant drainage of the monocarboxylate by the bloodstream. Overall, our results suggest that the control of carbon recruitment for neurons and astrocytes is exerted at the level of glucose uptake rather than that of lactate shuttle.

Faults in vascular (VN) and neuronal networks of spinal cord are responsible for serious neurodegenerative pathologies. Because of inadequate investigation tools, the lacking knowledge of the complete fine structure of VN and neuronal system represents a crucial problem. Conventional 2D imaging yields incomplete spatial coverage leading to possible data misinterpretation, whereas standard 3D computed tomography imaging achieves insufficient resolution and contrast. We show that X-ray high-resolution phase-contrast tomography allows the simultaneous visualization of three-dimensional VN and neuronal systems of ex-vivo mouse spinal cord at scales spanning from millimeters to hundreds of nanometers, with nor contrast agent nor sectioning and neither destructive sample-preparation. We image both the 3D distribution of micro-capillary network and the micrometric nerve fibers, axon-bundles and neuron soma. Our approach is very suitable for pre-clinical investigation of neurodegenerative pathologies and spinal-cord-injuries, in particular to resolve the entangled relationship between VN and neuronal system.

The purpose of this study was to investigate short-time metabolic variations related to continuous epileptic activity elicited by fixation-off sensitivity (FOS). Time-resolved magnetic resonance spectroscopy was performed on a patient on whom previous clinical findings clearly indicated presence of FOS. The epileptic focus was localized with a simultaneous electroencephalographic and functional magnetic resonance imaging study. The results showed a linear increase of the sum of glutamate and glutamine with time of paroxysmal activity in epileptic focus and much greater concentration of choline-containing compounds in focus than in the contralateral side.

Noninvasive functional studies on human spinal cord by means of magnetic resonance imaging (MRI) are gaining attention because of the promising applications in the study of healthy and injured central nervous system. The findings obtained are generally consistent with the anatomic knowledge based on invasive methods, but the origin and specificity of functional contrast is still debated. In this paper, a review of current knowledge and major issues about functional MRI (fMRI) in the human spinal cord is presented, with emphasis on the main methodological and technical problems and on forthcoming applications as clinical tool.

In the present work, an arteriovenous malformation was taken as a pathological model for studying task-related flow decreases during a motor task. Combined Blood Oxygen Level Dependent (BOLD)-perfusion experiments were applied in order to evaluate the relative sensitivity of these techniques to task-related reductions in cerebral blood flow (CBF). Results shows that, by matching the sensitivity of the methods (which exhibit a different contrast-to-noise ratio) in the primary motor cortex, the spatial extent of the regions of decreased perfusion signal is larger than those of the BOLD signal reduction. The above finding suggests that perfusion imaging, that already represents a gold standard method in the detection of vascular phenomena, may estimate task-related flow decreases in a functional time-series better than BOLD.

In this article, a review is made of the current knowledge concerning the physiology and metabolism of neuronal activity, as provided by the application of NMR approaches in vivo. The evidence furnished by other functional spectroscopic and imaging techniques, such as PET and optical methods, are also discussed. In spite of considerable amounts of studies presented in the literature, several controversies concerning the mechanisms underlying brain function still remain, mainly due to the difficult assessment of the single vascular and metabolic dynamics which generally influence the functional signals. In this framework, methodological and technical improvements are required to provide new and reliable experimental elements, which can support or eventually modify the current models of activation.

The metabolic events of neuronal energetics during functional activity are still partially unexplained. In particular, lactate (and not glucose) was recently proposed as the main substrate for neurons during activity [Proc Natl Acad Sci USA 91 (1994) 10625] . By means of proton magnetic resonance spectroscopy, lactate was reported to increase during the first minutes of prolonged stimulation Prichard et al 1991 , Sappey-Marinier et al 1992 , Frahm et al 1996 , but the studies reported thus far suffered from low temporal resolution. In the present study we used a time-resolved proton magnetic resonance spectroscopy strategy in order to analyse the evolution of lactate during the early seconds following a brief visual stimulation (event-related design). A significant decrease in lactate concentration was observed 5 s after the stimulation, while a recovering of the baseline was observed at 12 s.

Prostate cancer (PC) is one of the most common diseases in western countries and a leading cause of cancer death. A variety of treatment options are available but a precise disease characterization is needed: evaluation of cancer location, size, and extent and an indication of tumor aggressiveness. The current standard for diagnosing PC is transrectal ultrasound guided sextant biopsy. A novel multidisciplinary approach is required. Imaging may play a key role provided that dedicated prostate imagers and procedures are available: considerable improvements have been achieved in diagnosis with the Magnetic Resonance Imaging (MRI) and nuclear medicine (Positron Emission Tomography (PET) and Single Photon Emission Computed Tomography (SPECT)) techniques. Nevertheless, due to sub-optimal prostate imaging geometries with these generic large instruments preventing separation of the signal from surrounding organs, the sensitivity, spatial resolution and lesion contrast detected are lower compared to what can be potentially achievable with optimized dedicated prostate imagers and procedures. Fully exploiting the Time Of Flight (TOF) capability would allow not only to increase the Signal-to-Noise ratio (SNR) / Noise Equivalent Count Rate (NECR) but also to get rid of the huge background coming from neighboring organs i.e. the bladder. Recently a new research project was initiated by a large INFN collaboration, and a “TOF-PET and MRI for prostate cancer diagnosis and follow up experiment” (TOPEM) was financed as a 3-year experiment by the Italian “INFN Commissione Scientifica Nazionale V” with the goal of designing, building and testing in phantom tests an endorectal PET-TOF probe compatible with MRI.

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.

Several brain regions exhibit a sustained negative BOLD response (NBR) during specific tasks, as assessed with functional magnetic resonance imaging. The origin of the NBR and the relationships between the vascular/metabolic dynamics and the underlying neural activity are highly debated. Converging evidence indicates that NBR, in human and non-human primates, can be interpreted in terms of decrease in neuronal activity under its basal level, rather than a purely vascular phenomenon. However, the scarcity of direct experimental evidence suggests caution and encourages the ongoing utilization of multimodal approaches in the investigation of this effect.

A consistent and prominent feature of brain functional magnetic resonance imaging (fMRI) data is the presence of low-frequency (2+ signaling. Specifically, neurotransmission induces pulses of Ca2+ 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 Ca2+ 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.

Purpose: To compare the effects of anisotropic and Gaussian smoothing on the outcomes of diffusion tensor imaging (DTI) voxel-based (VB) analyses in the clinic, in terms of signal-to-noise ratio (SNR) enhancement and directional information and boundary structures preservation. Materials and Methods: DTI data of 30 Alzheimer's disease (AD) patients and 30 matched control subjects were obtained at 3T. Fractional anisotropy (FA) maps with variable degrees and quality (Gaussian and anisotropic) of smoothing were created and compared with an unsmoothed dataset. The two smoothing approaches were evaluated in terms of SNR improvements, capability to separate differential effects between patients and controls by a standard VB analysis, and level of artifacts introduced by the preprocessing. Results: Gaussian smoothing regionally biased the FA values and introduced a high variability of results in clinical analysis, greatly dependent on the kernel size. On the contrary, anisotropic smoothing proved itself capable of enhancing the SNR of images and maintaining boundary structures, with only moderate dependence of results on smoothing parameters. Conclusion: Our study suggests that anisotropic smoothing is more suitable in DTI studies; however, regardless of technique, a moderate level of smoothing seems to be preferable considering the artifacts introduced by this manipulation.

In this study, we assess white matter microstructural deficit correlates of apathy level in 20 patients with amnestic mild cognitive impairment by means of diffusion tensor imaging. Mean diffusivity correlated positively with apathy level in the right temporal portion of the uncinate, middle longitudinal and inferior longitudinal fasciculi and in the parathalamic white matter, the fornix and the posterior cingulum of the right hemisphere. Fractional anisotropy results confirmed evidence of disconnection associated with apathy in all white matter areas except the middle longitudinal fasciculus. These results support the view that alterations in the neural mechanisms underlying apathy level occur in the early phase of degenerative dementias.

Parkinson's disease is a neurological disorder associated with the disfunction of dopaminergic pathways of the basal ganglia, mainly resulting in a progressive alteration in the execution of voluntary movements. We present a functional magnetic resonance imaging (fMRI) study on cortical activations during simple motor task performance, in six early–stage hemiparkinsonian patients and seven healthy volunteers. We acquired data in three sessions, during which subjects performed the task with right or left hand, or bimanually. We observed consistent bilateral activations in cingulate cortex and dorsolateral prefrontal cortex of Parkinsonian subjects during the execution of the task with the affected hand. In addition, patients showed both larger and stronger activations in motor cortex of the affected hemisphere with respect to the healthy hemisphere. Compared with the control group, patients showed a hyperactivation of the dorsolateral prefrontal cortex of the affected hemisphere. We concluded that a presymptomatic reorganization of the motor system is likely to occur in Parkinson's disease at earlier stages than previously hypothesized. Moreover, our results support fMRI as a sensitive technique for revealing the initial involvement of motor cortex areas at the debut of this degenerative disorder.

Functional magnetic resonance imaging (fMRI) has emerged during the last decade as the main non-invasive technique for the investigation of human brain function. More recently, fMRI was also proposed for functional studies of the human spinal cord, but with controversial results. In fact, the functional contrast is not well-characterized, and even its origin has been challenged. In the present work, we characterized the temporal features of the functional signal evoked in the human spinal cord by a motor task, studied with an approach based on time-locked averaging of functional time series of different durations. Based on the results here reported, we defined an impulse-response function (irf) able to explain the functional response for motor tasks in the interval of 15-42 s of duration, thus suggesting the linearity of the phenomenon in this interval. Conversely, with stimulation durations ranging between 3 and 9 s, the functional signal was not detectable, and was under the level predicted by a linear behavior, suggesting deviation from linearity during short stimulations. The impulse-response function appeared slower than in the brain, peaking at about 9 s after its beginning. The observed contrast was generally larger than in the brain, on the order of about 5.4% of baseline signal at 1.5 T. The findings further suggested that the physiological origin of T(2) weighted functional imaging is similar in the spinal cord and in the brain.

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.

The aim of the present study was to analyze blood oxygenation level-dependent (BOLD) signal variation during an apnea-based task in order to assess the capability of a functional magnetic resonance imaging (MRI) procedure to estimate cerebral vascular dynamic effects. We measured BOLD contrast by hierarchical cluster analysis in healthy subjects undergoing an fMRI experiment, in which the task paradigm was one phase of inspirational apnea (IA). By processing the time courses of the fMRI experiment, analysis was performed only on a subclass of all the possible signal patterns; basically, root mean square and absolute variation differences have been calculated. Considering the baseline value obtained by computing the mean value of the initial rest period as reference, particular voxels showed relative important variations during the IA task and during the recovery phase following the IA. We focused our interest on the signal response of voxels that would correspond mainly to white and gray matter regions and that also may be affected by the proximity of large venous vessels. The results are presented as maps of space-temporal distribution of time series variations with two levels of hierarchical clustering among voxels with low to high initial response. Furthermore, we have presented a clustering of the signal response delay, conducting to a partition and identification of specified brain sites. (c) 2006 Elsevier Inc. All rights reserved.

The aim of our work was to evaluate the feasibility of in vivo single-voxel quantitative proton MR spectroscopy in order to identify possible alterations in the main metabolite concentrations due to some metabolic dysfunctions in the cerebellum of patients suffering from a particular form of migraine called “with aura.” Measurements of metabolite levels in the cerebellum disclosed reduced choline values (normalized both to N-acetyl-aspartate and creatine) in the patient group with respect to the age-matched control group. Our interest in this pathology is motivated by the fact that there are no available specific biochemical markers for migraine characterization, and the current diagnostic only takes advantage of the medical history and the clinical examination.

The metabolic events underlying neuronal activity still remain the object of intense debate, in spite of the considerable amount of information provided from different experimental techniques. Indeed, several attempts at linking the cellular metabolic phenomena with the macroscopic physiological changes have not yet attained foolproof conclusions. The difficulties in drawing definitive conclusions are due primarily to the heterogeneity of the experimental procedures used in different laboratories, and also given the impossibility of extrapolating the findings obtained under stationary conditions (prolonged stimulation) to dynamic and transient phenomena. Recently, lactate has received much attention, following its proposal by Pellerin and Magistretti (1994; Proc. Natl. Acad. Sci. USA 91:10625-10629), instead of glucose, as the main substrate for neurons during activity. Several challenging aspects suggest the return to a more conventional view of neuronal metabolism, in which neurons are able to metabolize ambient glucose directly as their major substrate, also during activation.

Proton magnetic resonance spectroscopy (1H-MRS) has been used in a number of studies to noninvasively assess the temporal changes of lactate in the activated human brain. However, the results have not been consistent. The aim of the present study was to test the sensitivity of 1H-MRS during functional experiments at the highest magnetic field currently available for human studies (7 T). Stability and reproducibility of the measurements were evaluated from LCModel analysis of time series of spectra measured during a visual stimulation paradigm and by examination of the difference between spectra obtained at rest and during activation. The sensitivity threshold to detect concentration changes was 0.2 μmol/g for most of the quantified metabolites. The possible variations of metabolite concentrations during visual stimulation were within the same range (±0.2 μmol/g). In addition, the influence of a small line-narrowing effect due to the blood oxygenation level-dependent (BOLD) T2* changes on the estimated concentrations was simulated. Quantification of metabolites was, in general, not affected beyond 1% by line-width changes within 0.5 Hz. © 2006 Elsevier Inc. All rights reserved.