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Studying brain development poses significant methodological challenges when working with vulnerable newborn infant populations. Non-invasive and wearable optical brain imaging technologies may allow for the cot-side study of newborn infants in clinical settings. This has particularly important implications for preterm infants in intensive care, for whom traditional neuroimaging techniques are not readily feasible. Wearable high-density diffuse optical tomography (HD-DOT) has emerged as a promising technology in this pursuit. In this thesis, I describe the development and application of wearable HD-DOT for newborn infants in clinical settings. Specifically, this technology is applied to study the features of functional brain connectivity (FC) associated with neonatal sleep states, active sleep and quiet sleep, in both term-born and preterm infants. HD-DOT is also electromechanically combined with electroencephalography (EEG) to concurrently study haemodynamic cortical and electrical cortical brain activity in the preterm infant. As a result of the constraints posed by lock-down conditions and a pause on clinical studies during the COVID-19 pandemic, the HD- DOT device is also used to study resting state functional connectivity (RSFC) in the adult brain in the home setting. Findings from this work demonstrate the potential of wearable HD-DOT, and combined EEG-HD-DOT, for the cot-side study of cerebral function during sleep in newborn infants, as well as at-home neuroimaging of resting-state networks in adults. This work was supervised by: Dr. Topun Austin, Department of Paediatrics, University of Cambridge, and Dr. Robert J. Cooper, Department of Medical Physics and Biomedical Engineering, UCL.

Purpose of review Within the past decade tremendous advances have occurred in our understanding of dyslexia. Recent findings Reliable data now validate the definition of dyslexia as an unexpected difficulty in reading in an individual who has the ability to be a much better reader. That dyslexia is unexpected is now codified in US federal law (PL 115-391). Replicated studies using functional brain imaging have documented a neural signature for dyslexia. Epidemiologic, longitudinal data now demonstrate that dyslexia is highly prevalent, affecting 20% of the population, affecting boys and girls equally. These data further demonstrate that the achievement gap between dyslexic and typical readers is now evident as early as first grade and persists. Evidence-based, efficient, inexpensive screening tools now offer the possibility of universal screening to identify children at risk for dyslexia as early as first grade. Specialized schools which focus on dyslexic students provide welcoming communities, ensuring that dyslexic children will not only survive but thrive. Summary Taken together, these findings indicate that we must act and act now to ensure that this 21st century knowledge of dyslexia is disseminated to educators, policy makers, and most of all to parents of dyslexic children.

Background: Interoceptive properties of food may influence emotional state and its neural basis, as shown for fatty acids but remains unstudied for carbohydrates. Objectives: To study the effects o...

This study examined global resting‐state functional connectivity of neural oscillations in individuals with chronic tinnitus and normal and impaired hearing. We tested the hypothesis that distinct neural oscillatory networks are engaged in tinnitus with and without hearing loss. In both tinnitus groups, with and without hearing loss, we identified multiple frequency band‐dependent regions of increased and decreased global functional connectivity. We also found that the auditory domain of tinnitus severity, assayed by the Tinnitus Functional Index, was associated with global functional connectivity in both auditory and nonauditory regions. These findings provide candidate biomarkers to target and monitor treatments for tinnitus with and without hearing loss.

Nowadays, we are witnessing the increasing scholarly attention to neuroscience achievements in the context of the law. However, the complexity of the brain cognitive functions and the performance limits of current neuroscience techniques for discovering the secrets of the brain on one hand, and the need for neuro-litigation development with ethical-legal constraints, on the other hand, caused some limits in ‘law and neuroscience’. What credit can be given to neuroscience today in full development? Can functional brain imaging have a place in criminal procedures to assess liability and dangerousness, for example? We will consider the limits of the techniques as well as the possible progress of the legislation in this field. These questions justify the creation of a new interdisciplinary concept: Neurolaw or Law applied to neuroscience.

Epidemiological and clinical gender differences in obsessive-compulsive disorder (OCD) have been reported; however, gender differences in brain functional connectivity and the relationship between resting brain functional imaging and clinical symptoms has not been studied in OCD.A total of 62 drug-naive patients with OCD (31 males, 31 females) and 60 healthy controls (HCs) (30 males, 30 females) matched for age, sex, and education underwent magnetic resonance imaging. Amplitude of low-frequency fluctuations (ALFF) over the whole brain and seed-based connectivity analyses were evaluated to examine the intrinsic cerebral activity of the subjects. Additionally, associations between functional connectivity and clinical features were analysed.Compared to male OCD (mOCD) patients, female OCD (fOCD) patients showed higher ALFF values in the right parahippocampal gyrus. Compared to HCs, fOCD patients showed significantly decreased functional connectivity between the right parahippocampal gyrus and whole brain to the right posterior central gyrus/precentral gyrus/superior temporal gyrus/barycentric lobule and left anterior cuneus. Abnormal functional connectivity was negatively correlated with the Yale-Brown Obsessive-Compulsive Scale, Beck Depression Inventory-II, and Beck Anxiety Inventory total scores.Our results suggest that the right parahippocampal gyrus, which is related to executive control and emotional regulation, may show gender differences in OCD.

Movies, audio stories, and virtual reality are increasingly used as stimuli for functional brain imaging. Such naturalistic paradigms are in sharp contrast to the tradition of experimental reductionism in neuroscience research. Being complex, dynamic, and diverse, naturalistic stimuli set up a more ecologically relevant condition and induce highly reproducible brain responses across a wide range of spatiotemporal scales. Here, we review recent technical advances and scientific findings on imaging the brain under naturalistic stimuli. Then we elaborate on the premise of using naturalistic paradigms for multi-scale, multi-modal, and high-throughput functional characterization of the human brain. We further highlight the growing potential of using deep learning models to infer neural information processing from brain responses to naturalistic stimuli. Lastly, we advocate large-scale collaborations to combine brain imaging and recording data across experiments, subjects, and labs that use the same set of naturalistic stimuli.

The pathophysiology of primary burning mouth syndrome (BMS) has been extensively debated but is poorly understood despite a large number of hypotheses attempting to explain its etiopathogenic mechanisms. The aim of the present work was to systematically review papers that could provide arguments in favour of the neuropathic and psychogenic components of primary BMS for a better understanding of the disease. This systematic review (SR) was registered in PROSPERO (CRD42021224160). The search was limited to articles in English or French from 1990 to 01 December 2020. A total of 113 articles were considered for data extraction. We divided them into four subgroups: pharmacological and nonpharmacological management studies (n = 23); neurophysiological studies (n = 35); biohistopathological studies (n = 25); and questionnaire-based studies (n = 30). Several of these studies have shown neuropathic involvement at various levels of the neuraxis in BMS with the contribution of quantitative sensory testing (QST), functional brain imaging, and biohistopathological or pharmacologic studies. On the other hand, the role of psychological factors in BMS has also been the focus of several studies and has shown a link with psychiatric disorders such as anxiety and/or depression symptoms. Depending on the patient, the neuropathic and psychogenic components may exist simultaneously, with a preponderance of one or the other, or exist individually. These two components cannot be dissociated to define BMS. Consequently, BMS may be considered nociplastic pain.

Chronic pain is a major public health problem in the United States costing $635 billion annually. Hospitalizations for chronic pain in childhood have increased almost tenfold in the last decade, without breakthroughs in novel treatment strategies. Findings from brain imaging studies using structural and resting-state fMRI could potentially help personalize treatment to address this costly and prevalent health problem by identifying the underlying brain pathways that contribute, facilitate, and maintain chronic pain. The aim of this review is to synthesize structural and resting-state network pathology identified by recent brain imaging studies in pediatric chronic pain populations and discuss the potential impact of chronic pain on cortical development. Sex-differences, as well as treatment effects on these cortical alterations associated with symptom changes, are also summarized. This area of research is still in its infancy with currently limited evidence available from a small number of studies, some of which suffer from limitations such as small sample size and suboptimal methodology. The identification of brain signatures of chronic pain in children may help to develop new pathways for future research as well as treatment strategies.

Objectives Evidence of plastic changes in tinnitus has been demonstrated in functional brain imaging. Although repetitive transcranial magnetic stimulation (rTMS) has been shown to decrease steady-state auditory evoked fields (SSAEFs) in tinnitus, the long-term consequence remained unknown. In addition, association between plastic changes as reflected by hemispheric asymmetry and tinnitus handicap inventory (THI) before and after rTMS have not been addressed. Methods Twelve tinnitus patients received rTMS and 12 received sham stimulation. Another 12 healthy participants served as the normal hearing controls. Patients responded to the THI before the 1st session and at one month after the final session of rTMS/sham stimulation. Changes in brain activity were assessed by measuring SSAEFs. Results SSAEFs remained decreased one month after rTMS compared to before treatment, along with a significant reduction in THI score. There was no significant effect between the index of hemispheric asymmetry and THI score. Conclusions The current study objectively demonstrated the long-term effects of rTMS on tinnitus using SSAEFs. A longitudinal study to develop an index using SSAEFs to assess the subjective severity of tinnitus is warranted. Significance This study suggests the possible use of SSAEFs to assess the long-term effects of rTMS on tinnitus.

Background/Study context: Posture and gait are complex sensorimotor functions affected by age. These difficulties are particularly apparent when performing cognitively demanding tasks. Characterizing the functional organization of brain networks involved in these associations remains a challenge because of the incompatibility of brain imagery techniques with gross body movements. The present study aimed at testing whether resting-state functional connectivity of sensorimotor networks is associated with posture and gait performance recorded offline, in young and older adults.Young (n = 12, mean = 24.1 y/o) and older (n = 14, mean = 65.6 y/o) healthy adults were tested for stability of their posture and gait. Four hours later, anatomical and functional brain imaging data were collected with Magnetic Resonance Imaging (MRI). Bilateral precentral and postcentral gyri were used as seeds in a graph theory analysis focused on global and local efficiency. The possible association between these data and posture and gait performance was examined.Both samples presented similar sensorimotor graphs, but with different global and local efficiencies (small world properties). The association between the networks' graph measures and posture and gait performance also differed across groups: local efficiency was correlated with gait stability in challenging conditions in older adults, but not in young adults.This exploratory study suggests that combining analyses of functional networks and offline body movement may provide important information about motor function. In older adults, the association between graph properties of the sensorimotor network and gait performance in challenging conditions may be indicative of compensatory processes. Prospective studies involving more subjects with a larger age range are warranted.

A prominent goal of neuroscience is to improve our understanding of how brain structure and activity interact to produce perception, emotion, behavior, and cognition. The brain’s network activity is inherently organized in distinct spatiotemporal patterns that span scales from nanometer-sized synapses to meter-long nerve fibers and millisecond intervals between electrical signals to decades of memory storage. There is currently no single imaging method that alone can provide all the relevant information, but intelligent combinations of complementary techniques can be effective. Here, we thus present the latest advances in biomedical and biological engineering on photoacoustic neuroimaging in the context of complementary imaging techniques. A particular focus is placed on recent advances in whole-brain photoacoustic imaging in rodent models and its influential role in bridging the gap between fluorescence microscopy and more non-invasive techniques such as magnetic resonance imaging (MRI). We consider current strategies to address persistent challenges, particularly in developing molecular contrast agents, and conclude with an overview of potential future directions for photoacoustic neuroimaging to provide deeper insights into healthy and pathological brain processes.

Supplemental Digital Content is Available in the Text. We report an increased slow-to-fast alpha power ratio of neurophysiological activity in chronic pain from known pain-processing areas, among others., Introduction: Objective disease markers are a key for diagnosis and personalized interventions. In chronic pain, such markers are still not available, and therapy relies on individual patients' reports. However, several pain studies have reported group-based differences in functional magnetic resonance imaging, electroencephalography, and magnetoencephalography (MEG). Objectives: We aimed to explore spectral differences in resting-state MEG brain signals between patients with chronic pain and pain-free controls and to characterize the cortical and subcortical regions involved. Methods: We estimated power spectral density over 5 minutes of resting-state MEG recordings in patients with chronic pain and controls and derived 7 spectral features at the sensor and source levels: alpha peak frequency, alpha power ratio (power 7–9 Hz divided by power 9–11 Hz), and average power in theta, alpha, beta, low-gamma, and high-gamma bands. We performed nonparametric permutation t tests (false discovery rate corrected) to assess between-group differences in these 7 spectral features. Results: Twenty-one patients with chronic pain and 25 controls were included. No significant group differences were found in alpha peak frequency or average power in any frequency band. The alpha power ratio was significantly higher (P < 0.05) in patients with chronic pain at both the sensor and brain source levels. The brain regions showing significantly higher ratios included the occipital, parietal, temporal and frontal lobe areas, insular and cingulate cortex, and right thalamus. Conclusion: The alpha power ratio is a simple, promising signal marker of chronic pain, affecting an expansive range of cortical and subcortical regions, including known pain-processing areas.

To elucidate the expression mechanisms of brain functions, we have developed an ultrathin fluorescence endoscope imaging system (U-FEIS) that can image cells in the brain at any depth while minimizing the invasion. The endoscope part of U-FEIS consists of a GRIN lens and a 10,000-pixel image fiber with a diameter of 450 μm. The specialized microscope of U-FEIS is within 30 cm square and includes lenses and optical filters optimized for the endoscope. Using U-FEIS, we successfully visualized neurons expressing GFP with single-cell resolution and recorded the multineuronal activities in vitro and in vivo. U-FEIS can also perform imaging and optical stimulation simultaneously. Therefore, U-FEIS should be a powerful optical tool in neuroscience research.

In the last 20 years, functional magnetic resonance imaging (fMRI) has been extensively used to investigate system-level abnormalities in the brain of patients with obsessive-compulsive disorder (OCD). In this chapter, we start by reviewing the studies assessing regional brain differences between patients with OCD and healthy controls in task-based fMRI. Specifically, we review studies on executive functioning and emotional processing, protocols in which these patients have been described to show alterations at the behavioral level, as well as research using symptom provocation protocols. Next, we review studies on brain connectivity alterations, focusing on resting-state studies evaluating disruptions in fronto-subcortical functional connectivity and in cortical networks. Likewise, we also review research on effective connectivity, which, different from functional connectivity, allows for ascertaining the directionality of inter-regional connectivity alterations. We conclude by reviewing the most significant findings on a topic of translational impact, such as the use of different fMRI measurements to predict response across a variety of treatment approaches. Overall, results suggest that there exists a pattern of regions, involving, but not limited to, different nodes of the cortico-striatal-thalamo-cortical circuits, showing robust evidence of functional alteration across studies, although the nature of the alterations critically depends on the specific tasks and their particular demands. Moreover, such findings have been, to date, poorly translated into clinical practice. It is suggested that this may be partially accounted for by the difficulty to integrate into a common framework results obtained under a wide variety of analysis approaches.

Significance: We propose a customized animal-specific head cap and an near-infrared spectroscopy (NIRS) system to obtain NIRS signals in mobile small animals. NIRS studies in mobile small animals provide a feasible solution for comprehensive brain function studies. Aim: We aim to develop and validate a multichannel NIRS system capable of performing functional brain imaging along with a closed-box stimulation kit for small animals in mobile conditions. Approach: The customized NIRS system uses light-weight long optical fibers, along with a customized light-weight head cap to securely attach the optical fibers to the mouse. A customized stimulation box was designed to perform various stimuli in a controlled environment. The system performance was tested in a visual stimulation task on eight anesthetized mice and eight freely moving mice. Results: Following the visual stimulation task, we observed a significant stimulation-related oxyhemoglobin (HbO) increase in the visual cortex of freely moving mice during the task. In contrast, HbO concentration did not change significantly in the visual cortex of anesthetized mice. Conclusions: We demonstrate the feasibility of a wearable, multichannel NIRS system for small animals in a less confined experimental design.

Over the last twenty five years, advances in the collection and analysis of functional magnetic resonance imaging (fMRI) data have enabled new insights into the brain basis of human health and disease. Individual behavioral variation can now be visualized at a neural level as patterns of connectivity among brain regions. As such, functional brain imaging is enhancing our understanding of clinical psychiatric disorders by revealing ties between regional and network abnormalities and psychiatric symptoms. Initial success in this arena has recently motivated collection of larger datasets which are needed to leverage fMRI to generate brain-based biomarkers to support the development of precision medicines. Despite numerous methodological advances and enhanced computational power, evaluating the quality of fMRI scans remains a critical step in the analytical framework. Before analysis can be performed, expert reviewers visually inspect individual raw scans and preprocessed derivatives to determine viability of the data. This Quality Control (QC) process is labor intensive, and the inability to adequately automate at large scale has proven to be a limiting factor in clinical neuroscience fMRI research. In this paper, we present a novel method for automating the QC of fMRI scans. We train machine learning classifiers using features derived from brain MR images to predict the “quality” of those images, which is based on the ground truth of an expert’s opinion. Specifically, we emphasize the importance of these classifiers’ ability to generalize their predictions across data collected in different studies. To address this, we propose a novel approach entitled “FMRI preprocessing Log mining for Automated, Generalizable Quality Control” (FLAG-QC), in which features derived from mining runtime logs are used to train the classifier. We show that classifiers trained on FLAG-QC features perform much better (AUC = 0.79) than previously proposed feature sets (AUC = 0.56) when testing their ability to generalize across studies.

Modern functional neuroimaging techniques can be dated to the 1960s, although humans have been trying to understand the functional organization of the brain for millennia. Precursors of modern techniques were quite crude and date roughly to the 19th century. Rapid technological advances during the end of the 20th century provided researchers with tools capable of measuring hemodynamic activity within the brain, such as changes in blood flow and metabolism, and these techniques quickly became core methodological approaches in the disciplines of cognitive and clinical neuroscience. Notably, clinicians and researchers were significantly aided in their ability to examine diffuse neural networks underlying complex cognitive functions such as working memory, learning, and attention in normal subjects and patient populations. Although the clinical application of functional neuroimaging methodologies have been limited to date, research in this area is rapidly growing and empirical support exists for effective use of techniques such as fMRI and PET, for instance, in presurgical mapping and early detection of Alzheimer’s disease.

This work reviews recent advances in technologies for functional magnetic resonance imaging (fMRI) of the human brain and highlights the push for higher functional specificity based on increased spatial resolution and specific MR contrasts to reveal previously undetectable functional properties of small-scale cortical structures. We discuss how the combination of MR hardware, advanced acquisition techniques and various MR contrast mechanisms have enabled recent advances in functional neuroimaging. However, these advanced fMRI practices have only been applied to a handful of neuroscience questions to date, with the majority of the neuroscience community still using conventional imaging techniques. We thus discuss upcoming challenges and possibilities for fMRI technology development in human neuroscience. We hope that readers interested in functional brain imaging acquire an understanding of current and novel developments and potential future applications, even if they don't have a background in MR physics or engineering. We summarize the capabilities of standard fMRI acquisition schemes with pointers to relevant literature and comprehensive reviews and introduce more recent developments.

Noninvasive functional brain imaging with magnetoencephalography (MEG) is regularly used to map the eloquent cortex associated with somatosensory, motor, auditory, visual, and language processing before a surgical resection to determine if the functional areas have been reorganized. Most tasks can also be performed in the pediatric population. To acquire an optimal MEG study for any of these modalities, the patient needs to be well rested and attending to the stimulation.

Background The active alkaloid in Betel quid is arecoline. Consumption of betel quid is associated with both acute effects and longer-term addictive effects. Despite growing evidence that betel quid use is linked with altered brain function and connectivity, the neurobiology of this psychoactive substance in initial acute chewing, and long-term dependence, is not clear. Methods In this observational study, functional magnetic resonance imaging in a resting-state was performed in 24 male betel quid-dependent chewers and 28 male controls prior to and promptly after betel quid chewing. Network-based statistics were employed to determine significant differences in functional connectivity between brain networks for both acute effects and in long-term betel users versus controls. A support vector machine was employed for pattern classification analysis. Results Before chewing betel quid, higher functional connectivity in betel quid-dependent chewers than in controls was found between the temporal, parietal and frontal brain regions (right medial orbitofrontal cortex, right lateral orbital frontal cortex, right angular gyrus, bilateral inferior temporal gyrus, superior parietal gyrus, and right medial superior frontal gyrus). In controls, the effect of betel quid chewing was significantly increased functional connectivity between the subcortical regions (caudate, putamen, pallidum, and thalamus), and the visual cortex (superior occipital gyrus and right middle occipital gyrus). Conclusion These findings show that individuals who chronically use betel quid have higher functional connectivity than controls of the orbitofrontal cortex, and inferior temporal and angular gyri. Acute effects of betel quid are to increase the functional connectivity of some visual cortical areas (which may relate to the acute symptoms) and the basal ganglia and thalamus.

Our team has recently shown the SNR and depth-sensitivity advantages of using 1064 nm light for diffuse correlation spectroscopy as well as the challenges of commercially available single-photon detectors at this wavelength. We will review two strategies for custom readout integrated circuit designs that simultaneously target lower pixel dead times and lower afterpulsing probabilities. Both designs use macropixels comprising many detectors, each having a programmable hold-off time. We will compare simulated autocorrelations for our detector models and compare predicted performance against commercial InGaAs/InP detectors.

Arterial spin labeling (ASL) enables noninvasive, quantitative MRI measurements of tissue perfusion and has a broad range of applications including functional brain imaging. ASL can concurrently measure perfusion and blood oxygenation-level-dependent (BOLD) signal changes, which proves useful for investigating the brain’s physiology in health and disease. However, ASL suffers from limited temporal resolution and has a lower signal-to-noise ratio (SNR) compared to conventional BOLD imaging. Therefore, most of the ASL research to date has focused on improving its SNR and temporal resolution. In this chapter, the functioning, advantages, disadvantages, and application areas of ASL are summarized. Further, the acquisition approaches and imaging parameters that influence ASL’s SNR and temporal resolution are reviewed. Finally, the effects of labeling schemes, background suppression, and readout approaches, as well as the potential of ultrahigh magnetic fields and acceleration techniques, are discussed. The ASL technical developments described here are key to its utilization increase in both neuroscience research and clinical applications.

Advances in brain–gut investigation techniques have been influential in the progress, and vastly improved understanding of functional gastrointestinal disorders in the Rome IV era. In this chapter, we consider the development of technologies including non-invasive brain stimulation, cortical evoked potentials, models of pain processing, functional brain imaging and vagal tone measurement. We summarize the key findings to date from studies using these techniques and their role in our current understanding and future utility in functional gastrointestinal and motility disorders.

Parkinson's disease (PD) and atypical parkinsonisms are progressive, untreatable neurodegenerative syndromes that commonly affect elderly people. In their early stages they may be misdiagnosed because their clinical presentation overlaps. Functional brain imaging, especially positron-emission tomography with radioligand 18F-fluorodeoxyglucose (18F-FDG-PET) has broadened our knowledge about the pathophysiology of parkinsonian syndromes and improved clinicians' diagnostic accuracy. For clinical diagnostic purposes, 18F-FDG-PET brain images are usually examined by visual inspection; however, its evaluation accuracy may be improved by the use of various univariate and multivariate statistical mapping approaches. Parkinson's disease-related pattern (PDRP) is a characteristic metabolic brain pattern identified in PD patients that involves the key nodes of the cortico-striatopallidal-thalamo-cortical circuits and related cerebello-cortical pathways. It has been identified using multivariate image analyses based on spatial covariance mapping. PDRP and other syndrome-specific metabolic patterns are repeatedly proving to be robust and reliable metabolic biomarkers of various parkinsonian syndromes.

Modern neuroimaging techniques provide us with unique views on brain structure and function; i.e., how the brain is wired, and where and when activity takes place. Data acquired using these techniques can be analyzed in terms of its network structure to reveal organizing principles at the systems level. Graph representations are versatile models where nodes are associated to brain regions and edges to structural or functional connections. Structural graphs model neural pathways in white matter, which are the anatomical backbone between regions. Functional graphs are built based on functional connectivity, which is a pairwise measure of statistical interdependency between pairs of regional activity traces. Therefore, most research to date has focused on analyzing these graphs reflecting structure or function. Graph signal processing (GSP) is an emerging area of research where signals recorded at the nodes of the graph are studied atop the underlying graph structure. An increasing number of fundamental operations have been generalized to the graph setting, allowing to analyze the signals from a new viewpoint. Here, we review GSP for brain imaging data and discuss their potential to integrate brain structure, contained in the graph itself, with brain function, residing in the graph signals. We review how brain activity can be meaningfully filtered based on concepts of spectral modes derived from brain structure. We also derive other operations such as surrogate data generation or decompositions informed by cognitive systems. In sum, GSP offers a novel framework for the analysis of brain imaging data.

Miniature pig as a model for translational therapy – Vagal stimulation and metabolic syndrome Therapeutic innovation against morbid obesity requires alternate animal models such as the diet induced obese miniature pig. While it does not develop the panel of diseases associated with obesity such as diabetes, atherosclerosis and metabolic syndrome, central and peripheral nervous signals are altered similar to humans. These peculiarities make the porcine model of significant interest to study the consequences of chronic vagal stimulation (VNS) on the recovery of the nervous traffic between the gut and the brain. VNS reduced food intake and increased resting energy expenditure resulting in a reduction of weight gain. Insulin sensitivity was recovered as a consequence of improved glucose uptake of key organs for glucose homeostasis. These effects were the consequence of a direct and indirect modulation of limbic networks via a further improvement of mesolimbic dopamine trafficking., L’innovation thérapeutique dans la lutte contre l’obésité morbide chez l’homme se heurte aux limites du modèle rongeur et justifie l’utilisation du porc miniature rendu obèse par une alimentation pléthorique. Ce dernier ne développe aucune des comorbidités décrites chez l’homme : diabète, troubles cardiovasculaires et syndrome métabolique, mais il présente toutes les altérations nerveuses centrale et périphérique identifiées chez le patient. C’est pourquoi, il représente un modèle particulièrement pertinent pour évaluer les conséquences de la stimulation vagale chronique visant à rétablir le trafic nerveux entre le tube digestif et le cerveau. Cette pratique réduit durablement, chez le porc, l’ingestion et accroit le métabolisme intermédiaire conduisant à une réduction de la prise de poids. Elle rétablit la sensibilité à l’insuline au niveau de l’organisme entier et des organes clés de l’homéostasie glucidique. Ces effets résultent d’une modulation directe et indirecte des réseaux limbiques via la normalisation du trafic dopaminergique mésolimbique., Malbert Charles-Henri. Porc miniature modèle pour l’innovation thérapeutique – stimulation vagale et syndrome métabolique. In: Bulletin de l'Académie Vétérinaire de France tome 171 n°3, 2018. pp. 194-201.

Functional Near-Infrared Spectroscopy (fNIRS) maps human brain function by measuring and imaging local changes in hemoglobin concentrations in the brain that arise from the modulation of cerebral blood flow and oxygen metabolism by neural activity. Since its advent over 20 years ago, researchers have exploited and continuously advanced the ability of near infrared light to penetrate through the scalp and skull in order to non-invasively monitor changes in cerebral hemoglobin concentrations that reflect brain activity. We review recent advances in signal processing and hardware that significantly improve the capabilities of fNIRS by reducing the impact of confounding signals to improve statistical robustness of the brain signals and by enhancing the density, spatial coverage, and wearability of measuring devices respectively. We then summarize the application areas that are experiencing rapid growth as fNIRS begins to enable routine functional brain imaging.

Developing efficient brain imaging technologies by combining a high spatiotemporal resolution and a large penetration depth is a key step for better understanding the neurovascular interface that emerges as a main pathway to neurodegeneration in many pathologies such as dementia. This review focuses on the advances in two complementary techniques: multi-photon laser scanning microscopy (MPLSM) and functional ultrasound imaging (fUSi). MPLSM has become the gold standard for in vivo imaging of cellular dynamics and morphology, together with cerebral blood flow. fUSi is an innovative imaging modality based on Doppler ultrasound, capable of recording vascular brain activity over large scales (i.e., tens of cubic millimeters) at unprecedented spatial and temporal resolution for such volumes (up to 10 μm pixel size at 10 kHz). By merging these two technologies, researchers may have access to a more detailed view of the various processes taking place at the neurovascular interface. MPLSM and fUSi are also good candidates for addressing the major challenge of real-time delivery, monitoring, and in vivo evaluation of drugs in neuronal tissue

This article concerns optimal experimental designs for neuroimaging studies in which the pioneering functional magnetic resonance imaging (fMRI) technology is used to investigate functions of the human brain. We develop analytical results for identifying designs that allow precise estimates of the contrasts between hemodynamic response functions (HRFs), each describing the effect of a mental stimulus over time. We also provide systematic methods for constructing optimal and very efficient designs, and show that fMRI designs obtained by relabeling the symbols of m -sequences can be very efficient in comparing the HRFs.

Background: Resting state MRI (rsfMRI) is a method of functional brain imaging that can be used to evaluate regional functional connectivity (FC) when a participant is at rest, not responding to ta...

The human brain undergoes significant functional and structural changes in the first decades of life, as the foundations for human cognition are laid down. However, non-invasive imaging techniques to investigate brain function throughout neurodevelopment are limited due to growth in head-size with age and substantial head movement in young participants. Experimental designs to probe brain function are also limited by the unnatural environment typical brain imaging systems impose. However, developments in quantum technology allowed fabrication of a new generation of wearable magnetoencephalography (MEG) technology with the potential to revolutionise electrophysiological measures of brain activity. Here we demonstrate a lifespan-compliant MEG system, showing recordings of high fidelity data in toddlers, young children, teenagers and adults. We show how this system can support new types of experimental paradigm involving naturalistic learning. This work reveals a new approach to functional imaging, providing a robust platform for investigation of neurodevelopment in health and disease.

The human brain undergoes significant functional and structural changes in the first decades of life, as the foundations for human cognition are laid down. However, non-invasive imaging techniques to investigate brain function throughout neurodevelopment are limited due to growth in head-size with age and substantial head movement in young participants. Experimental designs to probe brain function are also limited by the unnatural environment typical brain imaging systems impose. However, developments in quantum technology allowed fabrication of a new generation of wearable magnetoencephalography (MEG) technology with the potential to revolutionise electrophysiological measures of brain activity. Here we demonstrate a lifespan-compliant MEG system, showing recordings of high fidelity data in toddlers, young children, teenagers and adults. We show how this system can support new types of experimental paradigm involving naturalistic learning. This work reveals a new approach to functional imaging, providing a robust platform for investigation of neurodevelopment in health and disease., Magnetoencephalography (MEG) recordings are sensitive to movement and therefore are especially challenging with young participants. Here the authors develop a wearable MEG system based on a modified bicycle helmet, which enables reliable recordings in toddlers, children, teenagers and adults.

While structural network analysis consolidated the hypothesis of cerebral small vessel disease (SVD) being a disconnection syndrome, little is known about functional changes on the level of brain networks. In patients with genetically defined SVD (CADASIL, n = 41) and sporadic SVD (n = 46), we independently tested the hypothesis that functional networks change with SVD burden and mediate the effect of disease burden on cognitive performance, in particular slowing of processing speed. We further determined test–retest reliability of functional network measures in sporadic SVD patients participating in a high‐frequency (monthly) serial imaging study (RUN DMC—InTENse, median: 8 MRIs per participant). Functional networks for the whole brain and major subsystems (i.e., default mode network, DMN; fronto‐parietal task control network, FPCN; visual network, VN; hand somatosensory‐motor network, HSMN) were constructed based on resting‐state multi‐band functional MRI. In CADASIL, global efficiency (a graph metric capturing network integration) of the DMN was lower in patients with high disease burden (standardized beta = −.44; p [corrected] = .035) and mediated the negative effect of disease burden on processing speed (indirect path: std. beta = −.20, p = .047; direct path: std. beta = −.19, p = .25; total effect: std. beta = −.39, p = .02). The corresponding analyses in sporadic SVD showed no effect. Intraclass correlations in the high‐frequency serial MRI dataset of the sporadic SVD patients revealed poor test–retest reliability and analysis of individual variability suggested an influence of age, but not disease burden, on global efficiency. In conclusion, our results suggest that changes in functional connectivity networks mediate the effect of SVD‐related brain damage on cognitive deficits. However, limited reliability of functional network measures, possibly due to age‐related comorbidities, impedes the analysis in elderly SVD patients.

A revolution in functional brain imaging techniques is in progress in the field of neurosciences. Optical imaging techniques, such as high-density diffuse optical tomography (HD-DOT), in which source-detector pairs of probes are placed on subjects’ heads, provide better portability than conventional functional magnetic resonance imaging (fMRI) equipment. However, these techniques remain costly and can only acquire images at up to a few measurements per square centimetre, even when multiple detector probes are employed. In this study, we demonstrate functional brain imaging using a compact and affordable setup that employs nanosecond-order pulsed ordinary laser diodes and a time-extracted image sensor with superimposition capture of scattered components. Our technique can simply and easily attain a high density of measurement points without requiring probes to be attached, and can directly capture two-dimensional functional brain images. We have demonstrated brain activity imaging using a phantom that mimics the optical properties of an adult human head, and with a human subject, have measured cognitive brain activation while the subject is solving simple arithmetical tasks.

Iterative interactions between functional brain imaging in humans and mechanistic research in other animals hold great promise for understanding and treating mental health and neurological disorders. One way to accelerate discovery in this domain is to develop a unified, widely accepted vocabulary for describing structural and functional localization in the mammalian brain. To facilitate generation of such a defined nomenclature we begun by creating a table for direct mapping between terms for describing cerebral cortex parcellation according to six schemes in human, three schemes in mouse, and two schemes in rat. Use, refinement, and expansion of this model could lead to the development of a standardized structural neuroscience terminology, such as those long employed successfully in fields like chemistry, electrical engineering, and the naming of species.

The review considers modern ideas about the clinic and pathogenesis of minimal hepatic encephalopathy (MHE). It is discussed the present of cognitive impairment in this category of patients. The data of functional MRI are analyzed, and these results allow taking a fresh look at the origin of clinical disorders in this condition. The importance of cerebral connections disruption is emphasized. It is focused on the fact that in the functioning of the central nervous system the spontaneous activity of the brain has a significant importance. Separately is analyzed “the resting state”. It is concluded that MHE, despite its minimal manifestations, is a clinically significant condition requiring attention of a specialists. With that, it is often not diagnosed on time in clinical practice, which could lead to more severe damage of the cerebral functions. As evidenced by the data obtained at the present time, quite extensive changes in the neuronal activity are underlid of the cognitive deficit.

The miniaturized one-photon epi-fluorescence microscopy (miniscopy) has emerged as a powerful tool for in vivo functional brain imaging. Here, we report a computational method to improve the image quality of miniscopy.