Functional mapping of the human visual cortex by magnetic resonance imaging

Simultaneous metabolic and functional imaging of the brain using SPICE

PURPOSE

To enable simultaneous high-resolution mapping of brain function and metabolism.

METHODS

An encoding scheme was designed for interleaved acquisition of functional MRI (fMRI) data in echo volume imaging trajectories and MR spectroscopic imaging (MRSI) data in echo-planar spectroscopic imaging trajectories. The scheme eliminates water and lipid suppression and utilizes free induction decay signals to encode both functional and metabolic information with ultrashort TE, short TR, and sparse sampling of k , t -space. A subspace-based image reconstruction method was introduced for processing both the fMRI and MRSI data. The complementary information in the fMRI and MRSI data sets was also utilized to improve image reconstruction in the presence of intrascan head motion, field drift, and tissue susceptibility changes.

RESULTS

In-vivo experimental results were obtained from healthy human subjects in resting-state fMRI/MRSI experiments. In these experiments, the proposed method was able to simultaneously acquire metabolic and functional information from the brain in high resolution. For scans of 6.5 minutes, we achieved 3.0 × 3.0 × 1.8 mm³ spatial resolution for fMRI, 1.9 × 2.5 × 3.0 mm³ nominal spatial resolution for MRSI, and 1.9 × 1.9 × 1.8 mm³ nominal spatial resolution for quantitative susceptibility maps.

CONCLUSION

This work demonstrates the feasibility of simultaneous high-resolution mapping of brain function and metabolism with improved spatial resolution and synergistic image reconstruction.

The Titrated Monetary Incentive Delay Task: Sensitivity, convergent and divergent validity, and neural correlates in an RDoC sample

INTRODUCTION

Neuropsychological tests are designed to assay brain function via performance measurements. Many tests corresponding to visual and motor cortex function have been validated. Tests probing reward circuitry, including the ventral striatum (VS), could benefit assessment of numerous neurological and psychiatric disorders in which reward or VS function is disturbed. The present study sought to examine convergent and divergent validity of our modified, titrated version of the Monetary Incentive Delay Task, such that it may in the future stand as a validated neuropsychological test for reward function.

METHOD

Participants were 132 individuals with a history of mood disturbance (HMD) and 43 healthy comparisons, ages 18-30 years. In addition to a standard neuropsychological battery and symptom measures, participants completed a modified version of the Monetary Incentive Delay Task (T-MIDT) during functional magnetic resonance imaging (fMRI), which involved a multistage titration procedure to incrementally increase or decrease the response window time per each participant's psychomotor speed and optimize individual performance.

RESULTS

Across groups after titration, performance on the T-MIDT diverged from measures of processing speed, attention, and spatial working memory, but not inhibitory control. Performance in the HMD group was differentially correlated with executive function measures before and after titration. The reward circuit (e.g., subcortical, insular, medial prefrontal) was activated during reward anticipation.

CONCLUSION

The present findings provide preliminary evidence that the T-MIDT measures a construct distinct from many executive functions and that individualized titration of the task parameters is critical in parsing reward from executive function. The T-MIDT correlated with residual mood symptoms in individuals with remitted depression or bipolar disorder, implying that behavioral or brain activation group differences are only to be observed in the active state of illness.

After-effects of self-control: The reward responsivity hypothesis

Exercising self-control can be phenomenologically aversive. Insofar as individuals strive to maintain a positive emotional state, one consequence of exercising self-control may thus be a temporarily tuning toward or amplification of reward-related impulses (perhaps arising to countermand the aversive feelings that stem from self-control). Reward-relevant after-effects are relatively underappreciated in self-control research. In the current paper, we review theory and research pertaining to the idea that exercising self-control increases reward responsivity. First, we review theoretical models of self-control focusing on the relationship between control systems and reward systems. Second, we review behavioral studies regarding the effects of exercising self-control on subsequent reactivity to food, money, drugs, and positive emotional images. Third, we review findings from functional neuroimaging and electroencephalographic research pertaining to the reward responsivity hypothesis. We then call for additional research to integrate how, when, and under what circumstances self-control exertion influences reward processing. Such an endeavor will help to advance research and theory on self-control by offering a more precise characterization of the dynamic interactions between control systems and reward systems.

Optogenetic fMRI interrogation of brain-wide central vestibular pathways

Blood oxygen level-dependent functional MRI (fMRI) constitutes a powerful neuroimaging technology to map brain-wide functions in response to specific sensory or cognitive tasks. However, fMRI mapping of the vestibular system, which is pivotal for our sense of balance, poses significant challenges. Physical constraints limit a subject's ability to perform motion- and balance-related tasks inside the scanner, and current stimulation techniques within the scanner are nonspecific to delineate complex vestibular nucleus (VN) pathways. Using fMRI, we examined brain-wide neural activity patterns elicited by optogenetically stimulating excitatory neurons of a major vestibular nucleus, the ipsilateral medial VN (MVN). We demonstrated robust optogenetically evoked fMRI activations bilaterally at sensorimotor cortices and their associated thalamic nuclei (auditory, visual, somatosensory, and motor), high-order cortices (cingulate, retrosplenial, temporal association, and parietal), and hippocampal formations (dentate gyrus, entorhinal cortex, and subiculum). We then examined the modulatory effects of the vestibular system on sensory processing using auditory and visual stimulation in combination with optogenetic excitation of the MVN. We found enhanced responses to sound in the auditory cortex, thalamus, and inferior colliculus ipsilateral to the stimulated MVN. In the visual pathway, we observed enhanced responses to visual stimuli in the ipsilateral visual cortex, thalamus, and contralateral superior colliculus. Taken together, our imaging findings reveal multiple brain-wide central vestibular pathways. We demonstrate large-scale modulatory effects of the vestibular system on sensory processing.

A Brief History of Simulation Neuroscience

Our knowledge of the brain has evolved over millennia in philosophical, experimental and theoretical phases. We suggest that the next phase is simulation neuroscience. The main drivers of simulation neuroscience are big data generated at multiple levels of brain organization and the need to integrate these data to trace the causal chain of interactions within and across all these levels. Simulation neuroscience is currently the only methodology for systematically approaching the multiscale brain. In this review, we attempt to reconstruct the deep historical paths leading to simulation neuroscience, from the first observations of the nerve cell to modern efforts to digitally reconstruct and simulate the brain. Neuroscience began with the identification of the neuron as the fundamental unit of brain structure and function and has evolved towards understanding the role of each cell type in the brain, how brain cells are connected to each other, and how the seemingly infinite networks they form give rise to the vast diversity of brain functions. Neuronal mapping is evolving from subjective descriptions of cell types towards objective classes, subclasses and types. Connectivity mapping is evolving from loose topographic maps between brain regions towards dense anatomical and physiological maps of connections between individual genetically distinct neurons. Functional mapping is evolving from psychological and behavioral stereotypes towards a map of behaviors emerging from structural and functional connectomes. We show how industrialization of neuroscience and the resulting large disconnected datasets are generating demand for integrative neuroscience, how the scale of neuronal and connectivity maps is driving digital atlasing and digital reconstruction to piece together the multiple levels of brain organization, and how the complexity of the interactions between molecules, neurons, microcircuits and brain regions is driving brain simulation to understand the interactions in the multiscale brain.

Discovering hierarchical common brain networks via multimodal deep belief network

Studying a common architecture reflecting both brain's structural and functional organizations across individuals and populations in a hierarchical way has been of significant interest in the brain mapping field. Recently, deep learning models exhibited ability in extracting meaningful hierarchical structures from brain imaging data, e.g., fMRI and DTI. However, deep learning models have been rarely used to explore the relation between brain structure and function yet. In this paper, we proposed a novel multimodal deep believe network (DBN) model to discover and quantitatively represent the hierarchical organizations of common and consistent brain networks from both fMRI and DTI data. A prominent characteristic of DBN is that it is capable of extracting meaningful features from complex neuroimaging data with a hierarchical manner. With our proposed DBN model, three hierarchical layers with hundreds of common and consistent brain networks across individual brains are successfully constructed through learning a large dimension of representative features from fMRI/DTI data.

High-density diffuse optical tomography for imaging human brain function

This review describes the unique opportunities and challenges for noninvasive optical mapping of human brain function. Diffuse optical methods offer safe, portable, and radiation free alternatives to traditional technologies like positron emission tomography or functional magnetic resonance imaging (fMRI). Recent developments in high-density diffuse optical tomography (HD-DOT) have demonstrated capabilities for mapping human cortical brain function over an extended field of view with image quality approaching that of fMRI. In this review, we cover fundamental principles of the diffusion of near infrared light in biological tissue. We discuss the challenges involved in the HD-DOT system design and implementation that must be overcome to acquire the signal-to-noise necessary to measure and locate brain function at the depth of the cortex. We discuss strategies for validation of the sensitivity, specificity, and reliability of HD-DOT acquired maps of cortical brain function. We then provide a brief overview of some clinical applications of HD-DOT. Though diffuse optical measurements of neurophysiology have existed for several decades, tremendous opportunity remains to advance optical imaging of brain function to address a crucial niche in basic and clinical neuroscience: that of bedside and minimally constrained high fidelity imaging of brain function.

Development of Dedicated Brain PET Imaging Devices: Recent Advances and Future Perspectives

Whole-body PET scanners are not optimized for imaging small structures in the human brain. Several PET devices specifically designed for this task have been proposed either for stand-alone operation or as MR-compatible inserts. The main distinctive features of some of the most recent concepts and their performance characteristics, with a focus on spatial resolution and sensitivity, are reviewed. The trade-offs between the various performance characteristics, desired capabilities, and cost that need to be considered when designing a dedicated brain scanner are presented. Finally, the aspirational goals for future-generation scanners, some of the factors that have contributed to the current status, and how recent advances may affect future developments in dedicated brain PET instrumentation are briefly discussed.

Manganese oxide-carbon quantum dots nano-composites for fluorescence/magnetic resonance (T1) dual mode bioimaging, long term cell tracking, and ROS scavenging

Multimodal long-term imaging probes with capability of extracting complementary information are highly important in biomedical engineering for disease diagnosis and monitoring of therapeutics distribution. However, most of the theranostics probes used are transient and have inherent problem of toxicity mostly related to generation of free radicals. In current study, a simple microwave assisted synthesis of multimodal imaging nanoprobe (T1 contrast in MR/fluorescence) is reported via doping carbon quantum dots into manganese oxide nanoparticles. The nanostructures were characterized by US-Vis spectroscopy, fluorescence spectroscopy, FTIR, Raman spectroscopy, TEM, XRD, AFM and XPS. The average particle size was observed to be around 20-40 nm with a height of 7-9 nm and approximate quantum yield of 0.23. The nanostructures were useful for bio imaging and cell tracking via fluorescence microscopy up to 12 generations with nominal cytotoxicity. The material was capable of scavenging free radicals from cellular microenvironment and downregulate gene expression of free radical scavenging enzymes. The material has significant relaxivity (r1) value of 3.98 mM^-1.sec^-1 at 1.5 T. It was also observed to create significant contrast with high circulation time (30 min) and renal clearance property. The histological analysis of kidney and liver sections were observed to have no significant toxicity from the nanostructure.

Brain networks and their relevance for stroke rehabilitation

Stroke has long been regarded as focal disease with circumscribed damage leading to neurological deficits. However, advances in methods for assessing the human brain and in statistics have enabled new tools for the examination of the consequences of stroke on brain structure and function. Thereby, it has become evident that stroke has impact on the entire brain and its network properties and can therefore be considered as a network disease. The present review first gives an overview of current methodological opportunities and pitfalls for assessing stroke-induced changes and reorganization in the human brain. We then summarize principles of plasticity after stroke that have emerged from the assessment of networks. Thereby, it is shown that neurological deficits do not only arise from focal tissue damage but also from local and remote changes in white-matter tracts and in neural interactions among wide-spread networks. Similarly, plasticity and clinical improvements are associated with specific compensatory structural and functional patterns of neural network interactions. Innovative treatment approaches have started to target such network patterns to enhance recovery. Network assessments to predict treatment response and to individualize rehabilitation is a promising way to enhance specific treatment effects and overall outcome after stroke.

Imaging localized neuronal activity at fast time scales through biomechanics

Mapping neuronal activity noninvasively is a key requirement for in vivo human neuroscience. Traditional functional magnetic resonance (MR) imaging, with a temporal response of seconds, cannot measure high-level cognitive processes evolving in tens of milliseconds. To advance neuroscience, imaging of fast neuronal processes is required. Here, we show in vivo imaging of fast neuronal processes at 100-ms time scales by quantifying brain biomechanics noninvasively with MR elastography. We show brain stiffness changes of ~10% in response to repetitive electric stimulation of a mouse hind paw over two orders of frequency from 0.1 to 10 Hz. We demonstrate in mice that regional patterns of stiffness modulation are synchronous with stimulus switching and evolve with frequency. For very fast stimuli (100 ms), mechanical changes are mainly located in the thalamus, the relay location for afferent cortical input. Our results demonstrate a new methodology for noninvasively tracking brain functional activity at high speed.

Multimodal integration of diffusion MRI for better characterization of tissue biology

The contrast in diffusion-weighted MR images is due to variations of diffusion properties within the examined specimen. Certain microstructural information on the underlying tissues can be inferred through quantitative analyses of the diffusion-sensitized MR signals. In the first part of the paper, we review two types of approach for characterizing diffusion MRI signals: Bloch's equations with diffusion terms, and statistical descriptions. Specifically, we discuss expansions in terms of cumulants and orthogonal basis functions, the confinement tensor formalism and tensor distribution models. Further insights into the tissue properties may be obtained by integrating diffusion MRI with other techniques, which is the subject of the second part of the paper. We review examples involving magnetic susceptibility, structural tensors, internal field gradients, transverse relaxation and functional MRI. Integrating information provided by other imaging modalities (MR based or otherwise) could be a key to improve our understanding of how diffusion MRI relates to physiology and biology.

Kernel machine tests of association between brain networks and phenotypes

Applications of quantitative network analysis to functional brain connectivity have become popular in the last decade due to their ability to describe the general topological principles of brain networks. However, many issues arise when standard statistical analysis techniques are applied to functional magnetic resonance imaging (fMRI) connectivity maps. Frequently, summary measures of these maps, such as global efficiency and clustering coefficients, collapse the changing structures of graph topology from many scales to one. This can result in a loss of whole-brain spatio-temporal pattern information that may be significant in association and prediction analyses. Drawing from the electrical engineering field, the resistance perturbation distance is a quantification of similarity between graphs on the same vertex set that has been shown to identify changes in dynamic graphs, such as those from fMRI, while not being computationally expensive or result in a loss of information. This work proposes a novel kernel-based regression scheme that incorporates the resistance perturbation distance to better understand the association with biological phenotypes from fMRI using both simulated and real datasets.

Neural responses to children's faces: Test-retest reliability of structural and functional MRI

INTRODUCTION

Functional MRI (fMRI) is commonly used to investigate the neural mechanisms underlying psychological processes and behavioral responses. However, to draw well-founded conclusions from fMRI studies, more research on the reliability of fMRI is needed.

METHODS

We invited a sample of 41 female students to participate in two identical fMRI sessions, separated by 5 weeks on average. To investigate the potential effect of left-handedness on the stability of neural activity, we oversampled left-handed participants (N = 20). Inside the scanner, we presented photographs of familiar and unfamiliar children's faces preceded by neutral and threatening primes to the participants. We calculated intraclass correlations (ICCs) to investigate the test-retest reliability of peak activity in areas that showed significant activity during the first session (primary visual cortex, fusiform face area, inferior frontal gyrus, and superior temporal gyrus). In addition, we examined how many trials were needed to reliably measure the effects.

RESULTS

Across all participants, only fusiform face area activity in response to faces showed good test-retest reliability (ICC = 0.71). All other test-retest reliabilities were low (0.01 ≤ ICC ≤ 0.35). Reliabilities varied only slightly with increasing numbers of trials, with no consistent increase in ICCs. Test-retest reliabilities for left-handed participants (0.28 ≤ ICC ≤0.66) were generally somewhat higher than for right-handed participants (-0.13 ≤ ICC ≤0.75), but not statistically significant.

CONCLUSION

Our study shows good test-retest reliability for fusiform facer area activity in response to faces, but low test-retest reliability for other contrasts and areas.

Spatial source phase: A new feature for identifying spatial differences based on complex-valued resting-state fMRI data

Spatial source phase, the phase information of spatial maps extracted from functional magnetic resonance imaging (fMRI) data by data-driven methods such as independent component analysis (ICA), has rarely been studied. While the observed phase has been shown to convey unique brain information, the role of spatial source phase in representing the intrinsic activity of the brain is yet not clear. This study explores the spatial source phase for identifying spatial differences between patients with schizophrenia (SZs) and healthy controls (HCs) using complex-valued resting-state fMRI data from 82 individuals. ICA is first applied to preprocess fMRI data, and post-ICA phase de-ambiguity and denoising are then performed. The ability of spatial source phase to characterize spatial differences is examined by the homogeneity of variance test (voxel-wise F-test) with false discovery rate correction. Resampling techniques are performed to ensure that the observations are significant and reliable. We focus on two components of interest widely used in analyzing SZs, including the default mode network (DMN) and auditory cortex. Results show that the spatial source phase exhibits more significant variance changes and higher sensitivity to the spatial differences between SZs and HCs in the anterior areas of DMN and the left auditory cortex, compared to the magnitude of spatial activations. Our findings show that the spatial source phase can potentially serve as a new brain imaging biomarker and provide a novel perspective on differences in SZs compared to HCs, consistent with but extending previous work showing increased variability in patient data.

MRI techniques to measure arterial and venous cerebral blood volume

The measurement of cerebral blood volume (CBV) has been the topic of numerous neuroimaging studies. To date, however, most in vivo imaging approaches can only measure CBV summed over all types of blood vessels, including arterial, capillary and venous vessels in the microvasculature (i.e. total CBV or CBVtot). As different types of blood vessels have intrinsically different anatomy, function and physiology, the ability to quantify CBV in different segments of the microvascular tree may furnish information that is not obtainable from CBVtot, and may provide a more sensitive and specific measure for the underlying physiology. This review attempts to summarize major efforts in the development of MRI techniques to measure arterial (CBVa) and venous CBV (CBVv) separately. Advantages and disadvantages of each type of method are discussed. Applications of some of the methods in the investigation of flow-volume coupling in healthy brains, and in the detection of pathophysiological abnormalities in brain diseases such as arterial steno-occlusive disease, brain tumors, schizophrenia, Huntington's disease, Alzheimer's disease, and hypertension are demonstrated. We believe that the continual development of MRI approaches for the measurement of compartment-specific CBV will likely provide essential imaging tools for the advancement and refinement of our knowledge on the exquisite details of the microvasculature in healthy and diseased brains.

Structural connectome alterations in patients with disorders of consciousness revealed by 7-tesla magnetic resonance imaging

Although the functional connectivity of patients with disorders of consciousness (DOC) has been widely examined, less is known about brain white matter connectivity. The aim of this study was to explore structural network alterations for the diagnosis and prognosis of patients with chronic DOC. Eleven DOC patients and 11 sex- and age-matched controls were included in the study. Participants underwent diffusion magnetic resonance imaging (MRI) and T1-weighted structural MRI at 7 tesla (7 T). Graph-theoretical analysis and network-based statistics were used to analyze the group differences. Two patients were scanned twice for a longitudinal study to examine the relationship between connectome metrics and the patients' prognoses. Compared with healthy controls, DOC patients showed significantly elevated transitivity (p < .001), local efficiency (p = .009), and clustering coefficient (p = .039). When comparing the connectome metrics within the three groups (healthy controls, minimally conscious state (MCS), and vegetative state/unresponsive wakefulness syndrome (VS/UWS)), significant group differences were observed in transitivity (p < .001) and local efficiency (p = .031). Significantly increased transitivity was observed in vegetative state/unresponsive wakefulness syndrome compared with minimally conscious state (p = .0217, Bonferroni corrected). Transitivity showed significant negative correlations with the Coma Recovery Scale-Revised score (r = -0.6902, p = .023), consistent with the longitudinal study results. A subnetwork with significantly decreased structural connections was identified using network-based statistical analysis comparing DOC patients with healthy controls, which was mainly located in the frontal cortex, limbic system, and occipital and parietal lobes. This preliminary study suggests that graph theoretical approaches for assessing white matter connectivity may enable various states of DOC to be distinguished. Of the metrics analyzed, transitivity had a critical role in distinguishing the diagnostic groups. Larger cohorts will be necessary to confirm the predictive value of 7 T MRI in the prognosis of DOC patients.

Effects of flow changes on radiotracer binding: Simultaneous measurement of neuroreceptor binding and cerebral blood flow modulation

The potential effects of changes in blood flow on the delivery and washout of radiotracers has been an ongoing question in PET bolus injection studies. This study provides practical insight into this topic by experimentally measuring cerebral blood flow (CBF) and neuroreceptor binding using simultaneous PET/MRI. Hypercapnic challenges (7% CO₂) were administered to non-human primates in order to induce controlled increases in CBF, measured with pseudo-continuous arterial spin labeling. Simultaneously, dopamine D₂/D₃ receptor binding of [¹¹C]raclopride or [¹⁸F]fallypride was monitored with dynamic PET. Experiments showed that neither time activity curves nor quantification of binding through binding potentials ( BP_ND) were measurably affected by CBF increases, which were larger than two-fold. Simulations of experimental procedures showed that even large changes in CBF should have little effect on the time activity curves of radiotracers, given a set of realistic assumptions. The proposed method can be applied to experimentally assess the flow sensitivity of other radiotracers. Results demonstrate that CBF changes, which often occur due to behavioral tasks or pharmacological challenges, do not affect PET [¹¹C]raclopride or [¹⁸F]fallypride binding studies and their quantification. The results from this study suggest flow effects may have limited impact on many PET neuroreceptor tracers with similar properties.

Layer-specific connectivity revealed by diffusion-weighted functional MRI in the rat thalamocortical pathway

Investigating neural activity from a global brain perspective in-vivo has been in the domain of functional Magnetic Resonance Imaging (fMRI) over the past few decades. The intricate neurovascular couplings that govern fMRI's blood-oxygenation-level-dependent (BOLD) functional contrast are invaluable in mapping active brain regions, but they also entail significant limitations, such as non-specificity of the signal to active foci. Diffusion-weighted functional MRI (dfMRI) with relatively high diffusion-weighting strives to ameliorate this shortcoming as it offers functional contrasts more intimately linked with the underlying activity. Insofar, apart from somewhat smaller activation foci, dfMRI's contrasts have not been convincingly shown to offer significant advantages over BOLD-driven fMRI, and its activation maps relied on significant modelling. Here, we study whether dfMRI could offer a better representation of neural activity in the thalamocortical pathway compared to its (spin-echo (SE)) BOLD counterpart. Using high-end forepaw stimulation experiments in the rat at 9.4 T, and with significant sensitivity enhancements due to the use of cryocoils, we show for the first time that dfMRI signals exhibit layer specificity, and, additionally, display signals in areas devoid of SE-BOLD responses. We find that dfMRI signals in the thalamocortical pathway cohere with each other, namely, dfMRI signals in the ventral posterolateral (VPL) thalamic nucleus cohere specifically with layers IV and V in the somatosensory cortex. These activity patterns are much better correlated (compared with SE-BOLD signals) with literature-based electrophysiological recordings in the cortex as well as thalamus. All these findings suggest that dfMRI signals better represent the underlying neural activity in the pathway. In turn, these advanatages may have significant implications towards a much more specific and accurate mapping of neural activity in the global brain in-vivo.

Transverse NMR relaxation in biological tissues

Transverse NMR relaxation is a fundamental physical phenomenon underpinning a wide range of MRI-based techniques, essential for non-invasive studies in biology, physiology and neuroscience, as well as in diagnostic imaging. Biophysically, transverse relaxation originates from a number of distinct scales - molecular (nanometers), cellular (micrometers), and macroscopic (millimeter-level MRI resolution). Here we review the contributions to the observed relaxation from each of these scales, with the main focus on the cellular level of tissue organization, commensurate with the diffusion length of spin-carrying molecules. We discuss how the interplay between diffusion and spin dephasing in a spatially heterogeneous tissue environment leads to a non-monoexponential time-dependent transverse relaxation signal that contains important biophysical information about tissue microstructure.

Disentangling Multispectral Functional Connectivity With Wavelets

The field of brain connectomics develops our understanding of the brain's intrinsic organization by characterizing trends in spontaneous brain activity. Linear correlations in spontaneous blood-oxygen level dependent functional magnetic resonance imaging (BOLD-fMRI) fluctuations are often used as measures of functional connectivity (FC), that is, as a quantity describing how similarly two brain regions behave over time. Given the natural spectral scaling of BOLD-fMRI signals, it may be useful to represent BOLD-fMRI as multiple processes occurring over multiple scales. The wavelet domain presents a transform space well suited to the examination of multiscale systems as the wavelet basis set is constructed from a self-similar rescaling of a time and frequency delimited kernel. In the present study, we utilize wavelet transforms to examine fluctuations in whole-brain BOLD-fMRI connectivity as a function of wavelet spectral scale in a sample (N = 31) of resting healthy human volunteers. Information theoretic criteria measure relatedness between spectrally-delimited FC graphs. Voxelwise comparisons of between-spectra graph structures illustrate the development of preferential functional networks across spectral bands.

Feasibility of functional MRI at ultralow magnetic field via changes in cerebral blood volume

We investigate the feasibility of performing functional MRI (fMRI) at ultralow field (ULF) with a Superconducting QUantum Interference Device (SQUID), as used for detecting magnetoencephalography (MEG) signals from the human head. While there is negligible magnetic susceptibility variation to produce blood oxygenation level-dependent (BOLD) contrast at ULF, changes in cerebral blood volume (CBV) may be a sensitive mechanism for fMRI given the five-fold spread in spin-lattice relaxation time (T₁) values across the constituents of the human brain. We undertook simulations of functional signal strength for a simplified brain model involving activation of a primary cortical region in a manner consistent with a blocked task experiment. Our simulations involve measured values of T₁ at ULF and experimental parameters for the performance of an upgraded ULFMRI scanner. Under ideal experimental conditions we predict a functional signal-to-noise ratio of between 3.1 and 7.1 for an imaging time of 30 min, or between 1.5 and 3.5 for a blocked task experiment lasting 7.5 min. Our simulations suggest it may be feasible to perform fMRI using a ULFMRI system designed to perform MRI and MEG in situ.

MRI-based assessment of function and dysfunction in myelinated axons

Repetitive electrical activity produces microstructural alteration in myelinated axons, which may afford the opportunity to noninvasively monitor function of myelinated fibers in peripheral nervous system (PNS)/CNS pathways. Microstructural changes were assessed via two different magnetic-resonance-based approaches: diffusion fMRI and dynamic T2 spectroscopy in the ex vivo perfused bullfrog sciatic nerves. Using this robust, classical model as a platform for testing, we demonstrate that noninvasive diffusion fMRI, based on standard diffusion tensor imaging (DTI), can clearly localize the sites of axonal conduction blockage as might be encountered in neurotrauma or other lesion types. It is also shown that the diffusion fMRI response is graded in proportion to the total number of electrical impulses carried through a given locus. Dynamic T2 spectroscopy of the perfused frog nerves point to an electrical-activity-induced redistribution of tissue water and myelin structural changes. Diffusion basis spectrum imaging (DBSI) reveals a reversible shift of tissue water into a restricted isotropic diffusion signal component. Submyelinic vacuoles are observed in electron-microscopy images of tissue fixed during electrical stimulation. A slowing of the compound action potential conduction velocity accompanies repetitive electrical activity. Correlations between electrophysiology and MRI parameters during and immediately after stimulation are presented. Potential mechanisms and interpretations of these results are discussed.

Neuroimaging in Psychiatric Disorders: A Bibliometric Analysis of the 100 Most Highly Cited Articles

BACKGROUND AND PURPOSE

Extensive research has been conducted to find neuroimaging biomarkers for psychiatric disorders. This study aimed at identifying trends of the 100 most highly cited articles on neuroimaging in primary psychiatric disorders.

METHODS

The most highly cited original research articles were identified and analyzed, following searches of MEDLINE and Web of Science All Databases.

RESULTS

The top 100 articles ranked by yearly citation (from 137.5 to 31.1) were published between 1989 and 2017. Depressive disorders (30 articles), schizophrenia spectrum and other psychotic disorders (27), autism spectrum disorder (17), substance-related and addictive disorders (7), and post-traumatic stress disorder (7) were among the most studied conditions. Functional magnetic resonance imaging (42), structural magnetic resonance imaging (30), and positron emission tomography (22) were the most utilized neuroimaging modalities. While 85 articles investigated the pathophysiology of psychiatric disorders (including 7 focusing on developmental changes and 1 on genetic susceptibility), 15 articles studied the impact of treatment, including antidepressants (6), deep brain stimulation (4), antipsychotics (3), behavior therapy (3), and exercise (1). The analysis also identified the most contributing authors, countries (the United States: 71 articles, the United Kingdom: 8, Canada: 5, and China: 5), and journals (JAMA Psychiatry: 20 articles and Biological Psychiatry: 17). Ninety-eight studies were prospective, and two were retrospective. The sample size ranged from 3 to 1,188 (median: 21).

CONCLUSIONS

Our study identified intellectual milestones in the utility of neuroimaging in investigating primary psychiatric disorders. The historic trends could help guide future research in this field.

Optimization of Acquisition and Analysis Methods for Clinical Dynamic Susceptibility Contrast MRI Using a Population-Based Digital Reference Object

BACKGROUND AND PURPOSE

The accuracy of DSC-MR imaging CBV maps in glioblastoma depends on acquisition and analysis protocols. Multisite protocol heterogeneity has challenged standardization initiatives due to the difficulties of in vivo validation. This study sought to compare the accuracy of routinely used protocols using a digital reference object.

MATERIALS AND METHODS

The digital reference object consisted of approximately 10,000 simulated voxels recapitulating typical signal heterogeneity encountered in vivo. The influence of acquisition and postprocessing methods on CBV reliability was evaluated across 6912 parameter combinations, including contrast agent dosing schemes, pulse sequence parameters, field strengths, and postprocessing methods. Accuracy and precision were assessed using the concordance correlation coefficient and coefficient of variation.

RESULTS

Across all parameter space, the optimal protocol included full-dose contrast agent preload and bolus, intermediate (60°) flip angle, 30-ms TE, and postprocessing with a leakage-correction algorithm (concordance correlation coefficient = 0.97, coefficient of variation = 6.6%). Protocols with no preload or fractional dose preload and bolus using these acquisition parameters were generally less robust. However, a protocol with no preload, full-dose bolus, and low (30°) flip angle performed very well (concordance correlation coefficient = 0.93, coefficient of variation = 8.7% at 1.5T and concordance correlation coefficient = 0.92, coefficient of variation = 8.2% at 3T).

CONCLUSIONS

Schemes with full-dose preload and bolus maximize CBV accuracy and reduce variability, which could enable smaller sample sizes and more reliable detection of CBV changes in clinical trials. When a lower total contrast agent dose is desired, use of a low flip angle, no preload, and full-dose bolus protocol may provide an attractive alternative.

COMPLEX-VALUED TIME SERIES MODELING FOR IMPROVED ACTIVATION DETECTION IN FMRI STUDIES

A complex-valued data-based model with pth order autoregressive errors and general real/imaginary error covariance structure is proposed as an alternative to the commonly-used magnitude-only data-based autoregressive model for fMRI time series. Likelihood-ratio-test-based activation statistics are derived for both models and compared for experimental and simulated data. For a dataset from a right-hand finger-tapping experiment, the activation map obtained using complex-valued modeling more clearly identifies the primary activation region (left functional central sulcus) than the magnitude-only model. Such improved accuracy in mapping the left functional central sulcus has important implications in neurosurgical planning for tumor and epilepsy patients. Additionally, we develop magnitude and phase detrending procedures for complex-valued time series and examine the effect of spatial smoothing. These methods improve the power of complex-valued data-based activation statistics. Our results advocate for the use of the complex-valued data and the modeling of its dependence structures as a more efficient and reliable tool in fMRI experiments over the current practice of using only magnitude-valued datasets.

System neuroscience: Past, present, and future

In this review, we discuss first the anatomical and lesion studies that allowed the localization of fundamental functions in the cerebral cortex of primates including humans. Subsequently, we argue that the years from the end of the Second World War until the end of the last century represented the "golden age" of system neuroscience. In this period, the mechanisms-not only the localization-underlying sensory, and in particular visual functions were described, followed by those underlying cognitive functions and housed in temporal, parietal, and premotor areas. At the end of the last century, brain imaging techniques were developed that allowed the assessment of the functions of different cortical areas in a more precise and sophisticated way. However, brain imaging tells little about the neural mechanisms underlying functions. Furthermore, the brain imaging suffers from 3 major problems: time is absent, the data are merely correlative and the testing is often not ecological. We conclude our review discussing the possibility that these pitfalls might be overcome by using intracortical recordings (eg stereo-EEG), which have millisecond time resolution, allow direct electrical stimulation of specific sites, and finally enable to study patients while freely moving.

Impulse response timing differences in BOLD and CBV weighted fMRI

Recent advances in BOLD fMRI scan techniques have substantially improved spatial and temporal resolution, currently reaching to sub-millimeter and sub-second levels respectively. Unfortunately, there remain physiological barriers that prevent achieving this resolution in practice. BOLD contrast relies on the hemodynamic response to neuronal activity, whose associated cerebral blood oxygenation (CBO) changes may spread over several millimeters and last several seconds. Recent reports have suggested that significant improvements may be possible with cerebral blood volume (CBV)-weighted fMRI, which highlights the CBV changes rather than the BOLD changes associated with the hemodynamic response. Nevertheless, quantitative comparisons between CBV and BOLD are sparse, in particular regarding their temporal characteristics in human brain. To address this, we studied a cohort of subjects that received injection of ferumoxytol, an intravascular iron-oxide based contrast agent that introduces strong CBV contrast. An event-related visual stimulus paradigm was used to compare the impulse response (IR) for CBV and BOLD contrast, obtained with and without ferumoxytol, respectively. Experiments performed at 7 T (n = 5) at 1.2-1.5 mm spatial and 1 s temporal resolution showed that the onset time and time-to-peak of the CBV IR averaged 0.8 and 3.5 s respectively, both 0.6 s shorter than the BOLD IR. While significant, these improvements are relatively small and not expected to lead to practical advantages for the extraction of temporal information about neural activity. Nonlinearities in the observed IR were also compared and found to be similar between the CBV and BOLD, indicating that these are likely not caused by a 'ceiling' effect in the CBO response, but rather support a previously proposed model of vascular compliance, in which changes in vascular tone elicited by a preceding stimulus affect the IR.

The impact of traditional neuroimaging methods on the spatial localization of cortical areas

Localizing human brain functions is a long-standing goal in systems neuroscience. Toward this goal, neuroimaging studies have traditionally used volume-based smoothing, registered data to volume-based standard spaces, and reported results relative to volume-based parcellations. A novel 360-area surface-based cortical parcellation was recently generated using multimodal data from the Human Connectome Project, and a volume-based version of this parcellation has frequently been requested for use with traditional volume-based analyses. However, given the major methodological differences between traditional volumetric and Human Connectome Project-style processing, the utility and interpretability of such an altered parcellation must first be established. By starting from automatically generated individual-subject parcellations and processing them with different methodological approaches, we show that traditional processing steps, especially volume-based smoothing and registration, substantially degrade cortical area localization compared with surface-based approaches. We also show that surface-based registration using features closely tied to cortical areas, rather than to folding patterns alone, improves the alignment of areas, and that the benefits of high-resolution acquisitions are largely unexploited by traditional volume-based methods. Quantitatively, we show that the most common version of the traditional approach has spatial localization that is only 35% as good as the best surface-based method as assessed using two objective measures (peak areal probabilities and "captured area fraction" for maximum probability maps). Finally, we demonstrate that substantial challenges exist when attempting to accurately represent volume-based group analysis results on the surface, which has important implications for the interpretability of studies, both past and future, that use these volume-based methods.

"Occipital Tunnel" Sign on FDG PET for Differentiating Dementias

PET using FDG is a critical tool for evaluation of dementias, with characteristic patterns of hypometabolism suggesting specific diagnoses. Hypometabolism in the occipital region is recognized as an important finding associated with dementia with Lewy bodies and posterior cortical atrophy. We describe here the novel "occipital tunnel" sign, which results from relative sparing of FDG uptake in the medial occipital (primary visual) cortex compared with more severe loss in the surrounding lateral occipital (visual association) cortex. This sign is useful for recognizing the occipital findings of dementia with Lewy bodies and posterior cortical atrophy, especially when viewing sagittal projections.

Functional MRI of brain physiology in aging and neurodegenerative diseases

Brain aging and associated neurodegeneration constitute a major societal challenge as well as one for the neuroimaging community. A full understanding of the physiological mechanisms underlying neurodegeneration still eludes medical researchers, fuelling the development of in vivo neuroimaging markers. Hence it is increasingly recognized that our understanding of neurodegenerative processes likely will depend upon the available information provided by imaging techniques. At the same time, the imaging techniques are often developed in response to the desire to observe certain physiological processes. In this context, functional MRI (fMRI), which has for decades provided information on neuronal activity, has evolved into a large family of techniques well suited for in vivo observations of brain physiology. Given the rapid technical advances in fMRI in recent years, this review aims to summarize the physiological basis of fMRI observations in healthy aging as well as in age-related neurodegeneration. This review focuses on in-vivo human brain imaging studies in this review and on disease features that can be imaged using fMRI methods. In addition to providing detailed literature summaries, this review also discusses future directions in the study of brain physiology using fMRI in the clinical setting.

Expertise-Level-Dependent Functionally Plastic Changes During Motor Imagery in Basketball Players

Motor imagery is the mental process of rehearsing or simulating a given action without overt movements. The aim of the present study is to examine plastic changes in relevant brain areas during motor imagery with increasing expertise level. Subjects (novices, intermediate and elite players) performed motor imagery of basketball throws under two experimental conditions (with-ball and without-ball). We found that all basketball players exhibited better temporal congruence (between motor imagery and motor execution) and higher vividness of motor imagery than novices. The vividness of motor imagery was higher for the with-ball than for the without-ball conditions in all three subject groups. The results from functional magnetic resonance imaging (fMRI) showed three different patterns of cortical activation. Activation in the left middle frontal gyrus increased and that in the left supplementary motor area decreased with increasing levels of motor expertise. Importantly, brain activation in the left postcentral gyrus was the highest in the intermediate players compared to both novices and elite players. For the elite group, these three areas showed higher activation in the without-ball condition than the with-ball condition, while the opposite trend was found in intermediate players. Our findings suggest that the level of motor expertise may be related to high-order brain functions that are linked to different activation patterns in different brain areas.

Ultra-Slow Single-Vessel BOLD and CBV-Based fMRI Spatiotemporal Dynamics and Their Correlation with Neuronal Intracellular Calcium Signals

Functional MRI has been used to map brain activity and functional connectivity based on the strength and temporal coherence of neurovascular-coupled hemodynamic signals. Here, single-vessel fMRI reveals vessel-specific correlation patterns in both rodents and humans. In anesthetized rats, fluctuations in the vessel-specific fMRI signal are correlated with the intracellular calcium signal measured in neighboring neurons. Further, the blood-oxygen-level-dependent (BOLD) signal from individual venules and the cerebral-blood-volume signal from individual arterioles show correlations at ultra-slow (<0.1 Hz), anesthetic-modulated rhythms. These data support a model that links neuronal activity to intrinsic oscillations in the cerebral vasculature, with a spatial correlation length of ∼2 mm for arterioles. In complementary data from awake human subjects, the BOLD signal is spatially correlated among sulcus veins and specified intracortical veins of the visual cortex at similar ultra-slow rhythms. These data support the use of fMRI to resolve functional connectivity at the level of single vessels.

EEG-Informed fMRI: A Review of Data Analysis Methods

The simultaneous acquisition of electroencephalography (EEG) with functional magnetic resonance imaging (fMRI) is a very promising non-invasive technique for the study of human brain function. Despite continuous improvements, it remains a challenging technique, and a standard methodology for data analysis is yet to be established. Here we review the methodologies that are currently available to address the challenges at each step of the data analysis pipeline. We start by surveying methods for pre-processing both EEG and fMRI data. On the EEG side, we focus on the correction for several MR-induced artifacts, particularly the gradient and pulse artifacts, as well as other sources of EEG artifacts. On the fMRI side, we consider image artifacts induced by the presence of EEG hardware inside the MR scanner, and the contamination of the fMRI signal by physiological noise of non-neuronal origin, including a review of several approaches to model and remove it. We then provide an overview of the approaches specifically employed for the integration of EEG and fMRI when using EEG to predict the blood oxygenation level dependent (BOLD) fMRI signal, the so-called EEG-informed fMRI integration strategy, the most commonly used strategy in EEG-fMRI research. Finally, we systematically review methods used for the extraction of EEG features reflecting neuronal phenomena of interest.

A life in academia: My career in brief

In this article I have summarized some of the main trends and topics of my research career, spanning a time period of 50 years, from its start as a master student at the Department of Psychology, University of Uppsala, Sweden to seeing the end of a long career, now at the University of Bergen, Norway. This journey has, apart from having been a journey across various disciplines and topics in experimental psychology, psychophysiology and neuropsychology, functional neuroimaging and cognitive neuroscience, also been a social class journey for me personally. I describe my academic career from my arrival as a young student at the University of Uppsala, Sweden in the late 1960s to my graduation as PhD in 1977 at the age of 29 years, brief postdoc period at the University of Pennsylvania, USA, and finally professor at the University of Bergen, Norway. The article focuses on my view of the research and research findings during these years, including studies of hemispheric asymmetry, dyslexia and language, dichotic listening, fMRI, and during the last years, studies of auditory hallucinations in schizophrenia. I have collaborated with numerous people, both nationally and internationally over the years, far too many to mention in a space-limited overview article. I apologize for this, and wish that I had time and space to mention all the fantastic colleagues and friends that I have met during my career. This article is what I recall of dates, places, encounters, etc., and any errors and misunderstandings are entirely due to my far from perfect memory, for which I also apologize.

What can we see with IVIM MRI?

Intravoxel Incoherent Motion (IVIM) refers to translational movements which within a given voxel and during the measurement time present a distribution of speeds in orientation and/or amplitude. The IVIM concept has been used to estimate perfusion in tissues as blood flow in randomly oriented capillaries mimics a pseudo-diffusion process. IVIM-based perfusion MRI, which does not require contrast agents, has gained momentum recently, especially in the field oncology. In this introductory review the basic concepts, models, technical requirements and limitations inherent to IVIM-based perfusion MRI are outlined, as well as new, non-perfusion applications of IVIM MRI, such as virtual MR Elastography.

Nutrients for neurocognition in health and disease: measures, methodologies and mechanisms

Effective pharmaceutical treatments for age-related cognitive decline have proved elusive. There is, however, compelling evidence that nutritional status and supplementation could play crucial roles in modifying the expression of cognitive change through the lifespan. Subjective memory impairment and mild cognitive impairment can be harbingers of dementia but this is by no means inevitable. Neurocognitive change is influenced by a variety of processes, many of which are involved in other aspects of systemic health, including cardiovascular function. Importantly, many of these processes are governed by mechanisms which may be modified by specific classes of bioactive nutrients. There is increasing, converging evidence from controlled trials that nutritional interventions can improve mood and cognitive function in both clinical and healthy populations. Specific examples include selected botanical extracts such as the flavonoids. Some nutritional supplements (e.g. broad-spectrum micronutrient supplementation) appear to support improved cognitive function, possibly through redressing insufficient nutrient status (i.e. suboptimal but above the threshold for frank deficiency). Recent mechanistic research has unveiled physiologically plausible, modifiable, cognition-relevant targets for nutrition and nutraceuticals. These include processes involved in both systemic and central vascular function, inflammation, metabolism, central activation, improved neural efficiency and angiogenesis. The advent and development of human neuroimaging methodology have greatly aided our understanding of the core central mechanisms of cognitive change. Different imaging modalities can provide insights into modifiable central mechanisms which may be targeted by bioactive nutrients. The latter may contribute to slowing age-related decline through supporting neurocognitive scaffolding mechanisms.

Task and resting-state fMRI studies in first-episode schizophrenia: A systematic review

In the last two decades there has been an increase on task and resting-state functional Magnetic Resonance Imaging (fMRI) studies that explore the brain's functional changes in schizophrenia. However, it remains unclear as to whether the brain's functional changes during the resting state are sensitive to the same brain regions during task fMRI. Therefore, we conducted a systematic literature search of task and resting-state fMRI studies that investigated brain pathological changes in first-episode schizophrenia (Fleischhacker et al.). Nineteen studies met the inclusion criteria; seven were resting state fMRI studies with 371 FES patients and 363 healthy controls and twelve were task fMRI studies with 235 FES patients and 291 healthy controls. We found overlapping task and resting-state fMRI abnormalities in the prefrontal regions, including the dorsal lateral prefrontal cortex, the orbital frontal cortex and the temporal lobe, especially in the left superior temporal gyrus (STG). The findings of this systematic review support the frontotemporal hypothesis of schizophrenia, and the disruption in prefrontal and STG might represent the pathophysiology of schizophrenia disorder at a relatively early stage.

Functional Characterization of 5-HT1B Receptor Drugs in Nonhuman Primates Using Simultaneous PET-MR

In the present study, we used a simultaneous PET-MR experimental design to investigate the effects of functionally different compounds (agonist, partial agonist, and antagonist) on 5-HT_1B receptor (5-HT_1BR) occupancy and the associated hemodynamic responses. In anesthetized male nonhuman primates (n = 3), we used positron emission tomography (PET) imaging with the radioligand [¹¹C]AZ10419369 administered as a bolus followed by constant infusion to measure changes in 5-HT_1BR occupancy. Simultaneously, we measured changes in cerebral blood volume (CBV) as a proxy of drug effects on neuronal activity. The 5-HT_1BR partial agonist AZ10419369 elicited a dose-dependent biphasic hemodynamic response that was related to the 5-HT_1BR occupancy. The magnitude of the response was spatially overlapping with high cerebral 5-HT_1BR densities. High doses of AZ10419369 exerted an extracranial tissue vasoconstriction that was comparable to the less blood-brain barrier-permeable 5-HT_1BR agonist sumatriptan. By contrast, injection of the antagonist GR127935 did not elicit significant hemodynamic responses, even at a 5-HT_1BR cerebral occupancy similar to the one obtained with a high dose of AZ10419369. Given the knowledge we have of the 5-HT_1BR and its function and distribution in the brain, the hemodynamic response informs us about the functionality of the given drug: changes in CBV are only produced when the receptor is stimulated by the partial agonist AZ10419369 and not by the antagonist GR127935, consistent with low basal occupancy by endogenous serotonin.SIGNIFICANCE STATEMENT We here show that combined simultaneous positron emission tomography and magnetic resonance imaging uniquely enables the assessment of CNS active compounds. We conducted a series of pharmacological interventions to interrogate 5-HT_1B receptor binding and function and determined blood-brain barrier passage of drugs and demonstrate target involvement. Importantly, we show how the spatial and temporal effects on brain hemodynamics provide information about pharmacologically driven downstream CNS drug effects; the brain hemodynamic response shows characteristic dose-related effects that differ depending on agonistic or antagonistic drug characteristics and on local 5-HT_1B receptor density. The technique lends itself to a comprehensive in vivo investigation and understanding of drugs' effects in the brain.

Emotions Are Rising: The Growing Field of Affect Neuropsychology

Thirty years ago, the neuropsychology of emotion started to emerge as a mainstream topic. Careful examination of individual patients showed that emotion, like memory, language, and so on, could be differentially affected by brain disorders, especially in the right hemisphere. Since then, there has been accelerating interest in uncovering the neural architecture of emotion, and the major steps in this process of discovery over the past 3 decades are detailed in this review. In the 1990s, magnetic resonance imaging (MRI) scans provided precise delineation of lesions in the amygdala, medial prefrontal cortex, insula and somatosensory cortex as underpinning emotion disorders. At the same time, functional MRI revealed activation that was bilateral and also lateralized according to task demands. In the 2000s, converging evidence suggested at least two routes to emotional responses: subcortical, automatic and autonomic responses and slower, cortical responses mediating cognitive processing. The discovery of mirror neurons in the 1990s reinvigorated older views that simulation was the means to recognize emotions and empathize with others. More recently, psychophysiological research, revisiting older Russian paradigms, has contributed new insights into how autonomic and other physiological indices contribute to decision making (the somatic marker theory), emotional simulation, and social cognition. Finally, this review considers the extent to which these seismic changes in understanding emotional processes in clinical disorders have been reflected in neuropsychological practice. (JINS, 2017, 23, 719-731).

Advances in neurocognitive rehabilitation research from 1992 to 2017: The ascension of neural plasticity

OBJECTIVE

The last 25 years have seen profound changes in neurocognitive rehabilitation that continue to motivate its evolution. Although the concept of nervous system plasticity was discussed by William James (1890), the foundation for experience-based plasticity had not reached the critical empirical mass to seriously impact rehabilitation research until after 1992. The objective of this review is to describe how the emergence of neural plasticity has changed neurocognitive rehabilitation research.

METHOD

The important developments included (a) introduction of a widely available tool that could measure brain plasticity (i.e., functional MRI); (b) development of new structural imaging techniques that could define limits of and opportunities for neural plasticity; (c) deployment of noninvasive brain stimulation to leverage neural plasticity for rehabilitation; (d) growth of a literature indicating that exercise has positively impacts neural plasticity, especially for older persons; and (e) enhancement of neural plasticity by creating interventions that generalize beyond the boundaries of treatment activities. Given the massive literature, each of these areas is developed by example.

RESULTS

The expanding influence of neural plasticity has provided new models and tools for neurocognitive rehabilitation in neural injuries and disorders, as well as methods for measuring neural plasticity and predicting its limits and opportunities. Early clinical trials have provided very encouraging results.

CONCLUSION

Now that neural plasticity has gained a firm foothold, it will continue to influence the evolution of neurocognitive rehabilitation research for the next 25 years and advance rehabilitation for neural injuries and disease. (PsycINFO Database Record

The Quest for the FFA and Where It Led

This article tells the story behind our first paper on the fusiform face area (FFA): how we chose the question, developed the methods, and followed the data to find the FFA and subsequently many other functionally specialized cortical regions. The paper's impact had less to do with the particular findings in the paper itself and more to do with the method that it promoted and the picture of the human mind and brain that it led to. The use of a functional localizer to define a candidate region in each subject individually enabled us not just to make pictures of brain activation, but also to ask principled, hypothesis-driven questions about a thing in nature. This method enabled stronger and more extensive tests of the function of each cortical region than had been possible before in humans and, as a result, has produced a large body of evidence that the human cortex contains numerous regions that are specifically engaged in particular mental processes. The growing inventory of cortical regions with distinctive and often very specific functions can be seen as an initial sketch of the basic components of the human mind. This sketch also serves as a roadmap into the vast and exciting new landscape of questions about the computations, structural connections, time course, development, plasticity, and evolution of each of these regions, as well as the hardest question of all: how do these regions work together to produce human intelligence?

Altered Functional Connectivity Following an Inflammatory White Matter Injury in the Newborn Rat: A High Spatial and Temporal Resolution Intrinsic Optical Imaging Study

Very preterm newborns have an increased risk of developing an inflammatory cerebral white matter injury that may lead to severe neuro-cognitive impairment. In this study we performed functional connectivity (fc) analysis using resting-state optical imaging of intrinsic signals (rs-OIS) to assess the impact of inflammation on resting-state networks (RSN) in a pre-clinical model of perinatal inflammatory brain injury. Lipopolysaccharide (LPS) or saline injections were administered in postnatal day (P3) rat pups and optical imaging of intrinsic signals were obtained 3 weeks later. (rs-OIS) fc seed-based analysis including spatial extent were performed. A support vector machine (SVM) was then used to classify rat pups in two categories using fc measures and an artificial neural network (ANN) was implemented to predict lesion size from those same fc measures. A significant decrease in the spatial extent of fc statistical maps was observed in the injured group, across contrasts and seeds (^*p = 0.0452 for HbO₂ and ^**p = 0.0036 for HbR). Both machine learning techniques were applied successfully, yielding 92% accuracy in group classification and a significant correlation r = 0.9431 in fractional lesion volume prediction (^**p = 0.0020). Our results suggest that fc is altered in the injured newborn brain, showing the long-standing effect of inflammation.

The dynamic programming high-order Dynamic Bayesian Networks learning for identifying effective connectivity in human brain from fMRI

BACKGROUND

Determination of effective connectivity (EC) among brain regions using fMRI is helpful in understanding the underlying neural mechanisms. Dynamic Bayesian Networks (DBNs) are an appropriate class of probabilistic graphical temporal-models that have been used in past to model EC from fMRI, specifically order-one.

NEW-METHOD

High-order DBNs (HO-DBNs) have still not been explored for fMRI data. A fundamental problem faced in the structure-learning of HO-DBN is high computational-burden and low accuracy by the existing heuristic search techniques used for EC detection from fMRI. In this paper, we propose using dynamic programming (DP) principle along with integration of properties of scoring-function in a way to reduce search space for structure-learning of HO-DBNs and finally, for identifying EC from fMRI which has not been done yet to the best of our knowledge. The proposed exact search-&-score learning approach HO-DBN-DP is an extension of the technique which was originally devised for learning a BN's structure from static data (Singh and Moore, 2005).

RESULTS

The effectiveness in structure-learning is shown on synthetic fMRI dataset. The algorithm reaches globally-optimal solution in appreciably reduced time-complexity than the static counterpart due to integration of properties. The proof of optimality is provided.

COMPARISON

The results demonstrate that HO-DBN-DP is comparably more accurate and faster than currently used structure-learning algorithms used for identifying EC from fMRI. The real data EC from HO-DBN-DP shows consistency with previous literature than the classical Granger Causality method.

CONCLUSION

Hence, the DP algorithm can be employed for reliable EC estimates from experimental fMRI data.

Mitochondrial calcium homeostasis: Implications for neurovascular and neurometabolic coupling

Mitochondrial function is critical to maintain high rates of oxidative metabolism supporting energy demands of both spontaneous and evoked neuronal activity in the brain. Mitochondria not only regulate energy metabolism, but also influence neuronal signaling. Regulation of "energy metabolism" and "neuronal signaling" (i.e. neurometabolic coupling), which are coupled rather than independent can be understood through mitochondria's integrative functions of calcium ion (Ca²⁺) uptake and cycling. While mitochondrial Ca²⁺ do not affect hemodynamics directly, neuronal activity changes are mechanistically linked to functional hyperemic responses (i.e. neurovascular coupling). Early in vitro studies lay the foundation of mitochondrial Ca²⁺ homeostasis and its functional roles within cells. However, recent in vivo approaches indicate mitochondrial Ca²⁺ homeostasis as maintained by the role of mitochondrial Ca²⁺ uniporter (mCU) influences system-level brain activity as measured by a variety of techniques. Based on earlier evidence of subcellular cytoplasmic Ca²⁺ microdomains and cellular bioenergetic states, a mechanistic model of Ca²⁺ mobilization is presented to understand systems-level neurovascular and neurometabolic coupling. This integrated view from molecular and cellular to the systems level, where mCU plays a major role in mitochondrial and cellular Ca²⁺ homeostasis, may explain the wide range of activation-induced coupling across neuronal activity, hemodynamic, and metabolic responses.

Comparison of Functional Connectivity Estimated from Concatenated Task-State Data from Block-Design Paradigm with That of Continuous Task

Functional connectivity (FC) analysis with data collected as continuous tasks and activation analysis using data from block-design paradigms are two main methods to investigate the task-induced brain activation. If the concatenated data of task blocks extracted from the block-design paradigm could provide equivalent FC information to that derived from continuous task data, it would shorten the data collection time and simplify experimental procedures, and the already collected data of block-design paradigms could be reanalyzed from the perspective of FC. Despite being used in many studies, such a hypothesis of equivalence has not yet been tested from multiple perspectives. In this study, we collected fMRI blood-oxygen-level-dependent signals from 24 healthy subjects during a continuous task session as well as in block-design task sessions. We compared concatenated task blocks and continuous task data in terms of region of interest- (ROI-) based FC, seed-based FC, and brain network topology during a short motor task. According to our results, the concatenated data was not significantly different from the continuous data in multiple aspects, indicating the potential of using concatenated data to estimate task-state FC in short motor tasks. However, even under appropriate experimental conditions, the interpretation of FC results based on concatenated data should be cautious and take the influence due to inherent information loss during concatenation into account.

The use of in vivo, ex vivo, in vitro, computational models and volunteer studies in vision research and therapy, and their contribution to the Three Rs

Much is known about mammalian vision, and considerable progress has been achieved in treating many vision disorders, especially those due to changes in the eye, by using various therapeutic methods, including stem cell and gene therapy. While cells and tissues from the main parts of the eye and the visual cortex (VC) can be maintained in culture, and many computer models exist, the current non-animal approaches are severely limiting in the study of visual perception and retinotopic imaging. Some of the early studies with cats and non-human primates (NHPs) are controversial for animal welfare reasons and are of questionable clinical relevance, particularly with respect to the treatment of amblyopia. More recently, the UK Home Office records have shown that attention is now more focused on rodents, especially the mouse. This is likely to be due to the perceived need for genetically-altered animals, rather than to knowledge of the similarities and differences of vision in cats, NHPs and rodents, and the fact that the same techniques can be used for all of the species. We discuss the advantages and limitations of animal and non-animal methods for vision research, and assess their relative contributions to basic knowledge and clinical practice, as well as outlining the opportunities they offer for implementing the principles of the Three Rs (Replacement, Reduction and Refinement).