Spatial and Spectral Components of the BOLD Global Signal in Rat Resting-State Functional MRI.

PURPOSE: In resting-state fMRI (rs-fMRI), the global signal average captures widespread fluctuations related to unwanted sources of variance such as motion and respiration, as well as widespread neural activity; however, relative contributions of neural and non-neural sources to the global signal remain poorly understood. This study sought to tackle this problem through the comparison of the BOLD global signal to an adjacent non-brain tissue signal, where neural activity was absent, from the same rs-fMRI scan obtained from anesthetized rats. In this dataset, motion was minimal and ventilation was phase-locked to image acquisition to minimize respiratory fluctuations. Data were acquired using three different anesthetics: isoflurane, dexmedetomidine, and a combination of dexmedetomidine and light isoflurane. METHODS: A power spectral density estimate, a voxel-wise spatial correlation via Pearson's correlation, and a co-activation pattern analysis were performed using the global signal and the non-brain tissue signal. Functional connectivity was calculated using Pearson's linear correlation on default mode network (DMN) regions. RESULTS: We report differences in the spectral composition of the two signals and show spatial selectivity within DMN structures that show an increased correlation to the global signal and decreased intra-network connectivity after global signal regression. All of the observed differences between the global signal and the non-brain tissue signal were maintained across anesthetics. CONCLUSION: These results show that the global signal is distinct from the noise contained in the tissue signal, as support for a neural contribution. This study provides a unique perspective to the contents of the global signal and their origins.

Spatiotemporal trajectories in resting-state FMRI revealed by convolutional variational autoencoder.

Recent resting-state fMRI studies have shown that brain activity exhibits temporal variations in functional connectivity by using various approaches including sliding window correlation, co-activation patterns, independent component analysis, quasi-periodic patterns, and hidden Markov models. These methods often model the brain activity as a discretized hopping among several brain states that are defined by the spatial configurations of network activity. However, the discretized states are merely a simplification of what is likely to be a continuous process, where each network evolves over time following its unique path. To model these characteristic spatiotemporal trajectories, we trained a variational autoencoder using rs-fMRI data and evaluated the spatiotemporal features of the latent variables obtained from the trained networks. Our results suggest that there are a relatively small number of approximately orthogonal whole-brain spatiotemporal patterns that capture the most prominent features of rs-fMRI data, which can serve as the building blocks to construct all possible spatiotemporal dynamics in resting state fMRI. These spatiotemporal patterns provide insight into how activity flows across the brain in concordance with known network structures and functional connectivity gradients.

Ketamine and pharmacological imaging: use of functional magnetic resonance imaging to evaluate mechanisms of action.

Ketamine has been used as a pharmacological model for schizophrenia as subanesthetic infusions have been shown to produce temporary schizophrenia-like symptoms in healthy humans. More recently, ketamine has emerged as a potential treatment for multiple psychiatric disorders, including treatment-resistant depression and suicidal ideation. However, the mechanisms underlying both the psychotomimetic and the therapeutic effects of ketamine remain poorly understood. This review provides an overview of what is known of the neural mechanisms underlying the effects of ketamine and details what functional MRI studies have yielded at a systems level focused on brain circuitry. Multiple analytic approaches show that ketamine exerts robust and consistent effects at the whole-brain level. These effects are highly conserved across human and nonhuman primates, validating the use of nonhuman primate models for further investigations with ketamine. Regional analysis of brain functional connectivity suggests that the therapeutic potential of ketamine may be derived from a strengthening of executive control circuitry, making it an intriguing candidate for the treatment of drug abuse. There are still important questions about the mechanism of action and the therapeutic potential of ketamine that can be addressed using appropriate functional neuroimaging techniques.

Associations between white matter microstructure and infants' working memory.

Working memory emerges in infancy and plays a privileged role in subsequent adaptive cognitive development. The neural networks important for the development of working memory during infancy remain unknown. We used diffusion tensor imaging (DTI) and deterministic fiber tracking to characterize the microstructure of white matter fiber bundles hypothesized to support working memory in 12-month-old infants (n=73). Here we show robust associations between infants' visuospatial working memory performance and microstructural characteristics of widespread white matter. Significant associations were found for white matter tracts that connect brain regions known to support working memory in older children and adults (genu, anterior and superior thalamic radiations, anterior cingulum, arcuate fasciculus, and the temporal-parietal segment). Better working memory scores were associated with higher FA and lower RD values in these selected white matter tracts. These tract-specific brain-behavior relationships accounted for a significant amount of individual variation above and beyond infants' gestational age and developmental level, as measured with the Mullen Scales of Early Learning. Working memory was not associated with global measures of brain volume, as expected, and few associations were found between working memory and control white matter tracts. To our knowledge, this study is among the first demonstrations of brain-behavior associations in infants using quantitative tractography. The ability to characterize subtle individual differences in infant brain development associated with complex cognitive functions holds promise for improving our understanding of normative development, biomarkers of risk, experience-dependent learning and neuro-cognitive periods of developmental plasticity.

Asymmetric bias in user guided segmentations of brain structures.

Brain morphometric studies often incorporate comparative hemispheric asymmetry analyses of segmented brain structures. In this work, we present evidence that common user guided structural segmentation techniques exhibit strong left-right asymmetric biases and thus fundamentally influence any left-right asymmetry analyses. In this study, MRI scans from ten pediatric subjects were employed for studying segmentations of amygdala, globus pallidus, putamen, caudate, and lateral ventricle. Additionally, two pediatric and three adult scans were used for studying hippocampus segmentation. Segmentations of the sub-cortical structures were performed by skilled raters using standard manual and semi-automated methods. The left-right mirrored versions of each image were included in the data and segmented in a random order to assess potential left-right asymmetric bias. Using shape analysis we further assessed whether the asymmetric bias is consistent across subjects and raters with the focus on the hippocampus. The user guided segmentation techniques on the sub-cortical structures exhibited left-right asymmetric volume bias with the hippocampus displaying the most significant asymmetry values (p<<0.01). The hippocampal shape analysis revealed the bias to be strongest on the lateral side of the body and medial side of the head and tail. The origin of this asymmetric bias is considered to be based in laterality of visual perception; therefore segmentations with any degree of user interaction contain an asymmetric bias. The aim of our study is to raise awareness in the neuroimaging community regarding the presence of the asymmetric bias and its influence on any left-right hemispheric analyses. We also recommend reexamining previous research results in the light of this new finding.

Comparison of Resting-State Functional MRI Methods for Characterizing Brain Dynamics.

Resting-state functional MRI (fMRI) exhibits time-varying patterns of functional connectivity. Several different analysis approaches have been developed for examining these resting-state dynamics including sliding window connectivity (SWC), phase synchrony (PS), co-activation pattern (CAP), and quasi-periodic patterns (QPP). Each of these approaches can be used to generate patterns of activity or inter-areal coordination which vary across time. The individual frames can then be clustered to produce temporal groupings commonly referred to as "brain states." Several recent publications have investigated brain state alterations in clinical populations, typically using a single method for quantifying frame-wise functional connectivity. This study directly compares the results of k-means clustering in conjunction with three of these resting-state dynamics methods (SWC, CAP, and PS) and quantifies the brain state dynamics across several metrics using high resolution data from the human connectome project. Additionally, these three dynamics methods are compared by examining how the brain state characterizations vary during the repeated sequences of brain states identified by a fourth dynamic analysis method, QPP. The results indicate that the SWC, PS, and CAP methods differ in the clusters and trajectories they produce. A clear illustration of these differences is given by how each one results in a very different clustering profile for the 24s sequences explicitly identified by the QPP algorithm. PS clustering is sensitive to QPPs with the mid-point of most QPP sequences grouped into the same single cluster. CAPs are also highly sensitive to QPPs, separating each phase of the QPP sequences into different sets of clusters. SWC (60s window) is less sensitive to QPPs. While the QPPs are slightly more likely to occur during specific SWC clusters, the SWC clustering does not vary during the 24s QPP sequences, the goal of this work is to improve both the practical and theoretical understanding of different resting-state dynamics methods, thereby enabling investigators to better conceptualize and implement these tools for characterizing functional brain networks.

Selective blockade of rat brain T-type calcium channels provides insights on neurophysiological basis of arousal dependent resting state functional magnetic resonance imaging signals.

A number of studies point to slow (0.1-2 Hz) brain rhythms as the basis for the resting-state functional magnetic resonance imaging (rsfMRI) signal. Slow waves exist in the absence of stimulation, propagate across the cortex, and are strongly modulated by vigilance similar to large portions of the rsfMRI signal. However, it is not clear if slow rhythms serve as the basis of all neural activity reflected in rsfMRI signals, or just the vigilance-dependent components. The rsfMRI data exhibit quasi-periodic patterns (QPPs) that appear to increase in strength with decreasing vigilance and propagate across the brain similar to slow rhythms. These QPPs can complicate the estimation of functional connectivity (FC) via rsfMRI, either by existing as unmodeled signal or by inducing additional wide-spread correlation between voxel-time courses of functionally connected brain regions. In this study, we examined the relationship between cortical slow rhythms and the rsfMRI signal, using a well-established pharmacological model of slow wave suppression. Suppression of cortical slow rhythms led to significant reduction in the amplitude of QPPs but increased rsfMRI measures of intrinsic FC in rats. The results suggest that cortical slow rhythms serve as the basis of only the vigilance-dependent components (e.g., QPPs) of rsfMRI signals. Further attenuation of these non-specific signals enhances delineation of brain functional networks.

Functional Connectivity of the Brain Across Rodents and Humans.

Resting-state functional magnetic resonance imaging (rs-fMRI), which measures the spontaneous fluctuations in the blood oxygen level-dependent (BOLD) signal, is increasingly utilized for the investigation of the brain's physiological and pathological functional activity. Rodents, as a typical animal model in neuroscience, play an important role in the studies that examine the neuronal processes that underpin the spontaneous fluctuations in the BOLD signal and the functional connectivity that results. Translating this knowledge from rodents to humans requires a basic knowledge of the similarities and differences across species in terms of both the BOLD signal fluctuations and the resulting functional connectivity. This review begins by examining similarities and differences in anatomical features, acquisition parameters, and preprocessing techniques, as factors that contribute to functional connectivity. Homologous functional networks are compared across species, and aspects of the BOLD fluctuations such as the topography of the global signal and the relationship between structural and functional connectivity are examined. Time-varying features of functional connectivity, obtained by sliding windowed approaches, quasi-periodic patterns, and coactivation patterns, are compared across species. Applications demonstrating the use of rs-fMRI as a translational tool for cross-species analysis are discussed, with an emphasis on neurological and psychiatric disorders. Finally, open questions are presented to encapsulate the future direction of the field.

DTI registration in atlas based fiber analysis of infantile Krabbe disease.

In recent years, diffusion tensor imaging (DTI) has become the modality of choice to investigate white matter pathology in the developing brain. To study neonate Krabbe disease with DTI, we evaluate the performance of linear and non-linear DTI registration algorithms for atlas based fiber tract analysis. The DTI scans of 10 age-matched neonates with infantile Krabbe disease are mapped into an atlas for the analysis of major fiber tracts - the genu and splenium of the corpus callosum, the internal capsules tracts and the uncinate fasciculi. The neonate atlas is based on 377 healthy control subjects, generated using an unbiased diffeomorphic atlas building method. To evaluate the performance of one linear and seven nonlinear commonly used registration algorithms for DTI we propose the use of two novel evaluation metrics: a regional matching quality criterion incorporating the local tensor orientation similarity, and a fiber property profile based metric using normative correlation. Our experimental results indicate that the whole tensor based registration method within the DTI-ToolKit (DTI-TK) shows the best performance for our application.

Examining fMRI time-series entropy as a marker for brain E/I balance with pharmacological neuromodulation in a non-human primate translational model.

Recently, there has been a lot of interest in the neuroimaging community in exploring fMRI time-series measures of local neuronal activity and excitation/inhibition (E/I) balance in the brain. In this preliminary study we probed the sensitivity of widely used sample entropy (SE) measure at multiple scales to controlled alteration of the brain's E/I balance in non-human primates (NHPs) with a well-characterized sub-anesthetic ketamine infusion fMRI model. We found that SE failed to detect the expected changes in E/I balance induced by ketamine. Subsequently, noticing that the complexity in the time series contributing SE could be dominated by non-neuronal noise in this experimental setting, we developed a new time-series measure called restricted sample entropy (RSE) by restricting SE estimations to regular portions of the fMRI time-series. RSE was able to adequately reflect the increased excitatory activity engendered by disinhibition of glutamergic neurons, through sub-anesthetic ketamine infusion. These results show that RSE is potentially a powerful tool for examining local neural activity, E/I balance, and alterations in brain state.

Relationship Between Basic Properties of BOLD Fluctuations and Calculated Metrics of Complexity in the Human Connectome Project.

Resting state functional MRI (rs-fMRI) creates a rich four-dimensional data set that can be analyzed in a variety of ways. As more researchers come to view the brain as a complex dynamical system, tools are increasingly being drawn from other fields to characterize the complexity of the brain's activity. However, given that the signal measured with rs-fMRI arises from the hemodynamic response to neural activity, the extent to which complexity metrics reflect neural complexity as compared to signal properties related to image quality remains unknown. To provide some insight into this question, correlation dimension, approximate entropy and Lyapunov exponent were calculated for different rs-fMRI scans from the same subject to examine their reliability. The metrics of complexity were then compared to several properties of the rs-fMRI signal from each brain area to determine if basic signal features could explain differences in the complexity metrics. Differences in complexity across brain areas were highly reliable and were closely linked to differences in the frequency profiles of the rs-fMRI signal. The spatial distributions of the complexity and frequency metrics suggest that they are both influenced by location-dependent signal properties that can obscure changes related to neural activity.

Effects of ketamine treatment on cocaine-induced reinstatement and disruption of functional connectivity in unanesthetized rhesus monkeys.

RATIONALE: Substance use disorders are characterized by a loss of executive control over reward-based decision-making, and disruption of fronto-striatal connectivity has been implicated in this process. Sub-anesthetic ketamine has recently been shown to bolster fronto-striatal connectivity in drug-naïve subjects. OBJECTIVES: The influence of ketamine treatment was examined on the disruptive effects of cocaine on functional connectivity (FC) and on cocaine-seeking behavior in female rhesus monkeys. METHODS: Three female rhesus were trained for unanesthetized MRI scanning. Each received three drug-naïve/abstinent pharmacological MRI scans with acute injections of saline, cocaine (0.3 mg/kg i.v.), and cocaine (0.3 mg/kg i.v.) 48-h after a ketamine treatment (low dose = 0.345 mg/kg bolus + 0.256 mg/kg/h for 1 h; i.v.), and a fourth scan with saline injection following 2 months of daily cocaine self-administration. A separate cohort of five rhesus (4 female), all with extensive histories of cocaine exposure, underwent reinstatement testing 48 h after ketamine (or vehicle) treatment. Two sub-anesthetic doses were tested: low dose and high dose = 0.69 mg/kg + 0.512 mg/kg/h for 1 h. RESULTS: Ketamine treatment attenuated the effects of cocaine on both global and fronto-striatal FC in drug-naïve/abstinent subjects. Two months of daily cocaine self-administration led to prolonged disruption of both global and fronto-striatal FC. Cocaine-seeking behavior during reinstatement was reduced following ketamine treatment at the low dose, but not high dose. CONCLUSION: These findings illustrate the disruptive effects of cocaine on functional connectivity and provide evidence for the potential efficacy of ketamine as a treatment for stimulant use disorder.

Effects of the serotonin 2C receptor agonist WAY163909 on the abuse-related effects and mesolimbic dopamine neurochemistry induced by abused stimulants in rhesus monkeys.

RATIONALE: Accumulating evidence shows that the serotonergic system plays a major role in psychostimulant abuse through its interactions with the dopaminergic system. Studies indicate that serotonin 5-HT2C receptors are one of the main classes of receptors involved in mediating the influence of serotonin in drug abuse. OBJECTIVE: The aim of the present study was to evaluate the effects of the selective serotonin 5-HT2C receptor agonist WAY163909 on the behavioral neuropharmacology of cocaine and methamphetamine in adult rhesus macaques. METHODS: Cocaine or methamphetamine self-administration and reinstatement were evaluated under second-order and fixed-ratio schedules of reinforcement, respectively. Cocaine- and methamphetamine-induced increases in dopamine were assessed through in vivo microdialysis targeting the nucleus accumbens. RESULTS: Pretreatment with WAY163909 dose-dependently attenuated cocaine and methamphetamine self-administration and drug-induced reinstatement of extinguished behavior previously maintained by cocaine or methamphetamine delivery. In an additional experiment, WAY163909 induced a dose-dependent attenuation of cocaine- or methamphetamine-induced dopamine overflow in the nucleus accumbens. CONCLUSIONS: Our data indicate that selective 5-HT2C receptor activation decreases drug intake and drug-seeking behavior in nonhuman primate models of psychostimulant abuse through neurochemical mechanisms involved in the modulation of mesolimbic dopamine.

Ketamine-induced brain activation in awake female nonhuman primates: a translational functional imaging model.

RATIONALE: There is significant interest in the NMDA receptor antagonist ketamine due to its efficacy in treating depressive disorders and its induction of psychotic-like symptoms that make it a useful tool for modeling psychosis. OBJECTIVE: The present study extends the successful development of an apparatus and methodology to conduct pharmacological MRI studies in awake rhesus monkeys in order to evaluate the CNS effects of ketamine. METHODS: Functional MRI scans were conducted in four awake adult female rhesus monkeys during sub-anesthetic intravenous (i.v.) infusions of ketamine (0.345 mg/kg bolus followed by 0.256 mg/kg/h constant infusion) with and without risperidone pretreatment (0.06 mg/kg). Statistical parametric maps of ketamine-induced blood oxygenation level-dependent (BOLD) activation were obtained with appropriate general linear regression models (GLMs) incorporating motion and hemodynamics of ketamine infusion. RESULTS: Ketamine infusion induced and sustained robust BOLD activation in a number of cortical and subcortical regions, including the thalamus, cingulate gyrus, and supplementary motor area. Pretreatment with the antipsychotic drug risperidone markedly blunted ketamine-induced activation in many brain areas. CONCLUSIONS: The results are remarkably similar to human imaging studies showing ketamine-induced BOLD activation in many of the same brain areas, and pretreatment with risperidone or another antipsychotic blunting the ketamine response to a similar extent. The strong concordance of the functional imaging data in humans with these results from nonhuman primates highlights the translational value of the model and provides an excellent avenue for future research examining the CNS effects of ketamine. This model may also be a useful tool for evaluating the efficacy of novel antipsychotic drugs.

Ketamine-induced changes in connectivity of functional brain networks in awake female nonhuman primates: a translational functional imaging model.

RATIONALE: There is a significant interest in the NMDA-receptor antagonist ketamine due to its efficacy in treating depressive disorders and its induction of psychotic-like symptoms that make it a useful tool for modeling psychosis. Pharmacological MRI in awake nonhuman primates provides a highly translational model for studying the brain network dynamics involved in producing these drug effects. OBJECTIVE: The present study evaluated ketamine-induced changes in functional connectivity (FC) in awake rhesus monkeys. The effects of ketamine after pretreatment with the antipsychotic drug risperidone were also examined. METHODS: Functional MRI scans were conducted in four awake adult female rhesus monkeys during sub-anesthetic i.v. infusions of ketamine (0.345 mg/kg bolus followed by 0.256 mg kg-1 h-1 constant infusion) with and without risperidone pretreatment (0.06 mg/kg). A 10-min window of stable BOLD signal was used to compare FC between baseline and drug conditions. FC was assessed in specific regions of interest using seed-based cross-correlation analysis. RESULTS: Ketamine infusion induced extensive changes in FC. In particular, FC to the dorsolateral prefrontal cortex (dlPFC) was increased in several cortical and subcortical regions. Pretreatment with risperidone largely attenuated ketamine-induced changes in FC. CONCLUSIONS: The results are highly consistent with similar human imaging studies showing ketamine-induced changes in FC, as well as a significant attenuation of these changes when ketamine infusion is preceded by pretreatment with risperidone. The extensive increases shown in FC to the dlPFC are consistent with the idea that disinhibition of the dlPFC may be a key driver of the antidepressant and psychotomimetic effects of ketamine.

Localized differences in caudate and hippocampal shape are associated with schizophrenia but not antipsychotic type.

UNLABELLED: Caudate and hippocampal volume differences in patients with schizophrenia are associated with disease and antipsychotic treatment, but local shape alterations have not been thoroughly examined. Schizophrenia patients randomly assigned to haloperidol and olanzapine treatment underwent magnetic resonance imaging (MRI) at 3, 6, and 12 months. The caudate and hippocampus were represented as medial representations (M-reps); mesh structures derived from automatic segmentations of high resolution MRIs. Two quantitative shape measures were examined: local width and local deformation. A novel nonparametric statistical method, adjusted exponentially tilted (ET) likelihood, was used to compare the shape measures across the three groups while controlling for covariates. Longitudinal shape change was not observed in the hippocampus or caudate when the treatment groups and controls were examined in a global analysis, nor when the three groups were examined individually. Both baseline and repeated measures analysis showed differences in local caudate and hippocampal size between patients and controls, while no consistent differences were shown between treatment groups. Regionally specific differences in local hippocampal and caudate shape are present in schizophrenic patients. Treatment-related related longitudinal shape change was not observed within the studied timeframe. Our results provide additional evidence for disrupted cortico-basal ganglia-thalamo-cortical circuits in schizophrenia. CLINICAL TRIAL INFORMATION: This longitudinal study was conducted from March 1, 1997 to July 31, 2001 at 14 academic medical centers (11 in the United States, one in Canada, one in the Netherlands, and one in England). This study was performed prior to the establishment of centralized registries of federally and privately supported clinical trials.

Comparison of magnetic resonance imaging in live vs. post mortem rat brains.

Magnetic Resonance Imaging (MRI) is an increasingly popular technique for examining neurobiology in rodents because it is both noninvasive and nondestructive. MRI scans can be acquired from either live or post mortem specimens. In vivo scans have a key advantage in that subjects can be scanned at multiple time-points in longitudinal studies. However, repeated exposure to anesthesia and stress may confound studies. In contrast, post mortem scans offer improved image quality and increased signal-to-noise ratio (SNR) due to several key advantages: First, the images are not disrupted by motion and pulsation artifacts. Second, they allow the brain tissue to be perfused with contrast agents, enhancing tissue contrast. Third, they allow longer image acquisition times, yielding higher resolution and/or improved SNR. Fourth, they allow assessment of groups of animals at the same age without scheduling complications. Despite these advantages, researchers are often skeptical of post mortem MRI scans because of uncertainty about whether the fixation process alters the MRI measurements. To address these concerns, we present a thorough comparative study of in vivo and post mortem MRI scans in healthy male Wistar rats at three age points throughout adolescence (postnatal days 28 through 80). For each subject, an in vivo scan was acquired, followed by perfusion and two post mortem scans at two different MRI facilities. The goal was to assess robustness of measurements, to detect any changes in volumetric measurements after fixation, and to investigate any differential bias that may exist between image acquisition techniques. We present this volumetric analysis for comparison of 22 anatomical structures between in vivo and post mortem scans. No significant changes in volumetric measurements were detected; however, as hypothesized, the image quality is dramatically improved in post mortem scans. These findings illustrate the validity and utility of using post mortem scans in volumetric neurobiological studies.

Software-based Diffusion MR Human Brain Phantom for Evaluating Fiber-tracking Algorithms.

Fiber tracking provides insights into the brain white matter network and has become more and more popular in diffusion MR imaging. Hardware or software phantom provides an essential platform to investigate, validate and compare various tractography algorithms towards a "gold standard". Software phantoms excel due to their flexibility in varying imaging parameters, such as tissue composition, SNR, as well as potential to model various anatomies and pathologies. This paper describes a novel method in generating diffusion MR images with various imaging parameters from realistically appearing, individually varying brain anatomy based on predefined fiber tracts within a high-resolution human brain atlas. Specifically, joint, high resolution DWI and structural MRI brain atlases were constructed with images acquired from 6 healthy subjects (age 22-26) for the DWI data and 56 healthy subject (age 18-59) for the structural MRI data. Full brain fiber tracking was performed with filtered, two-tensor tractography in atlas space. A deformation field based principal component model from the structural MRI as well as unbiased atlas building was then employed to generate synthetic structural brain MR images that are individually varying. Atlas fiber tracts were accordingly warped into each synthetic brain anatomy. Diffusion MR images were finally computed from these warped tracts via a composite hindered and restricted model of diffusion with various imaging parameters for gradient directions, image resolution and SNR. Furthermore, an open-source program was developed to evaluate the fiber tracking results both qualitatively and quantitatively based on various similarity measures.