Search

Intrathecal drug delivery is routinely used in the treatment and prophylaxis of varied central nervous system conditions, as doing so allows drugs to directly bypass the blood-brain barrier. However, the utility of this route of administration is limited by poor brain and spinal cord parenchymal drug uptake from the cerebrospinal fluid. We demonstrate that a simple noninvasive transcranial ultrasound protocol can significantly increase influx of cerebrospinal fluid into the perivascular spaces of the brain, to enhance the uptake of intrathecally administered drugs. Specifically, we administered small (~1 kDa) and large (~155 kDa) molecule agents into the cisterna magna of rats and then applied low, diagnostic-intensity focused ultrasound in a scanning protocol throughout the brain. Using real-time magnetic resonance imaging and ex vivo histologic analyses, we observed significantly increased uptake of small molecule agents into the brain parenchyma, and of both small and large molecule agents into the perivascular space from the cerebrospinal fluid. Notably, there was no evidence of brain parenchymal damage following this intervention. The low intensity and noninvasive approach of transcranial ultrasound in this protocol underscores the ready path to clinical translation of this technique. In this manner, this protocol can be used to directly bypass the blood-brain barrier for whole-brain delivery of a variety of agents. Additionally, this technique can potentially be used as a means to probe the causal role of the glymphatic system in the variety of disease and physiologic processes to which it has been correlated.

Functional ultrasound (fUS) is a rapidly emerging modality that enables whole-brain imaging of neural activity in awake and mobile rodents. To achieve sufficient blood flow sensitivity in the brain microvasculature, fUS relies on long ultrasound data acquisitions at high frame rates, posing high demands on the sampling and processing hardware. Here we develop an image reconstruction method based on deep learning that significantly reduces the amount of data necessary while retaining imaging performance. We trained convolutional neural networks to learn the power Doppler reconstruction function from sparse sequences of ultrasound data with compression factors of up to 95%. High-quality images from in vivo acquisitions in rats were used for training and performance evaluation. We demonstrate that time series of power Doppler images can be reconstructed with sufficient accuracy to detect the small changes in cerebral blood volume (~10%) characteristic of task-evoked cortical activation, even though the network was not formally trained to reconstruct such image series. The proposed platform may facilitate the development of this neuroimaging modality in any setting where dedicated hardware is not available or in clinical scanners.

Rationale: Localized blood-brain barrier (BBB) opening can be achieved with minimal to no tissue damage by applying pulsed focused ultrasound alongside a low microbubble (MB) dose. However, relatively little is known regarding how varying treatment parameters affect the degree of neuroinflammation following BBB opening. The goal of this study was to evaluate the activation of an inflammatory response following BBB opening as a function of applied acoustic pressure using two different microbubble doses. Methods: Mice were treated with 650 kHz ultrasound using varying acoustic peak negative pressures (PNPs) using two different MB doses, and activation of an inflammatory response, in terms of microglial and astrocyte activation, was assessed one hour following BBB opening using immunohistochemical staining. Harmonic and subharmonic acoustic emissions (AEs) were monitored for all treatments with a passive cavitation detector, and contrast-enhanced magnetic resonance imaging (CE-MRI) was performed following BBB opening to quantify the degree of opening. Hematoxylin and eosin-stained slides were assessed for the presence of microhemorrhage and edema. Results: For each MB dose, BBB opening was achieved with minimal activation of microglia and astrocytes using a PNP of 0.15 MPa. Higher PNPs were associated with increased activation, with greater increases associated with the use of the higher MB dose. Additionally, glial activation was still observed in the absence of histopathological findings. We found that CE-MRI was most strongly correlated with the degree of activation. While acoustic emissions were not predictive of microglial or astrocyte activation, subharmonic AEs were strongly associated with marked and severe histopathological findings. Conclusions: Our study demonstrated that there were mild histologic changes and activation of the acute inflammatory response using PNPs ranging from 0.15 MPa to 0.20 MPa, independent of MB dose. However, when higher PNPs of 0.25 MPa or above were applied, the same applied PNP resulted in more severe and widespread histological findings and activation of the acute inflammatory response when using the higher MB dose. The potential activation of the inflammatory response following ultrasound-mediated BBB opening should be considered when treating patients to maximize therapeutic benefit.

Functional ultrasound imaging is rapidly establishing itself as a state-of-the-art neuroimaging modality owing to its ability to image neural activation in awake and mobile small animals, its relatively low cost, and its unequaled portability. To achieve high blood flow sensitivity in the brain microvasculature, functional ultrasound relies on long sequences of ultrasound data acquired at high frame rates, which pose high demands on the hardware architecture and effectively limit the practical utility and clinical translation of this imaging modality. Here we propose Deep-fUS, a deep learning approach that aims to significantly reduce the amount of ultrasound data necessary, while retaining the imaging performance. We trained a neural network to learn the power Doppler reconstruction function from sparse sequences of compound ultrasound data, using ground truth images from high-quality in vivo acquisitions in rats, and with a custom loss function. The network produces highly accurate images with restored sensitivity in the smaller blood vessels even when using heavily under-sampled data. We tested the network performance in a task-evoked functional neuroimaging application, demonstrating that time series of power Doppler images can be reconstructed with adequate accuracy to compute functional activity maps. Notably, the network reduces the occurrence of motion artifacts in awake functional ultrasound imaging experiments. The proposed platform can facilitate the development of this neuroimaging modality in any setting where dedicated hardware is not available or even in clinical scanners, opening the way to new potential applications based on this technology. To our knowledge, this is the first attempt to implement a convolutional neural network approach for power Doppler reconstruction from sparse ultrasonic datasets.

The glymphatics system of the brain rapidly clears organic nanoparticles commonly used for brain drug delivery.

Purpose To evaluate the use of diffusion magnetic resonance imaging (MRI) tractography for neurosurgical guidance of transcranial MRI-guided focused ultrasound (tcMRgFUS) thalamotomy for essential tremor (ET). Materials and methods Eight patients with medication-refractory ET were treated with tcMRgFUS targeting the ventral intermediate nucleus (Vim) of the thalamus contralateral to their dominant hand. Diffusion and structural MRI data and clinical evaluations were acquired pre-treatment and post-treatment. To identify the optimal target location, tractography was performed on pre-treatment diffusion MRI data between the treated thalamus and the hand-knob region of the ipsilateral motor cortex, the entire ipsilateral motor cortex and the contralateral dentate nucleus. The tractography-identified locations were compared to the lesion location delineated on 1 year post-treatment T2-weighted MR image. Their overlap was correlated with the clinical outcomes measured by the percentage change of the Clinical Rating Scale for Tremor scores acquired pre-treatment, as well as 1 month, 3 months, 6 months and 1 year post-treatment. Results The probabilistic tractography was consistent from subject-to-subject and followed the expected anatomy of the thalamocortical radiation and the dentatothalamic tract. Higher overlap between the tractography-identified location and the tcMRgFUS treatment-induced lesion highly correlated with better treatment outcome (r = −0.929, −0.75, −0.643, p = 0.00675, 0.0663, 0.139 for the tractography between the treated thalamus and the hand-knob region of the ipsilateral motor cortex, the entire ipsilateral motor cortex and the contralateral dentate nucleus, respectively, at 1 year post-treatment). The correlation for the tractography between the treated thalamus and the hand-knob region of the ipsilateral motor cortex is the highest for all time points (r = −0.719, −0.976, −0.707, −0.929, p = 0.0519, 0.000397, 0.0595, 0.00675 at 1 month, 3 months, 6 months and 1 year post-treatment, respectively). Conclusion Our data support the use of diffusion tractography as a complementary approach to current targeting methods for tcMRgFUS thalamotomy., Highlights • Retrospectively used tractography to define a target for MRgFUS thalamotomy for ET. • Larger overlap between tractography and lesion correlates with better outcomes. • Strongest correlations for tract between the thalamus and motor hand-knob region • Diffusion tractography is a complementary approach to current targeting methods.

BACKGROUND AND PURPOSE: Resting-state fMRI readily identifies the dorsal but less consistently the ventral somatomotor network. Our aim was to assess the relative utility of resting-state fMRI in the identification of the ventral somatomotor network via comparison with task-based fMRI in patients with brain tumor. MATERIALS AND METHODS: We identified 26 surgically naive patients referred for presurgical fMRI brain mapping who had undergone both satisfactory ventral motor activation tasks and resting-state fMRI. Following standard preprocessing for task-based fMRI and resting-state fMRI, general linear model analysis of the ventral motor tasks and independent component analysis of resting-state fMRI were performed with the number of components set to 20, 30, 40, and 50. Visual overlap of task-based fMRI and resting-state fMRI at different component levels was assessed and categorized as full match, partial match, or no match. Rest-versus-task-fMRI concordance was calculated with Dice coefficients across varying fMRI thresholds before and after noise removal. Multithresholded Dice coefficient volume under the surface was calculated. RESULTS: The ventral somatomotor network was identified in 81% of patients. At the subject level, better matches between resting-state fMRI and task-based fMRI were seen with an increasing order of components (53% of cases for 20 components versus 73% for 50 components). Noise-removed group-mean volume under the surface improved as component numbers increased from 20 to 50, though ANOVA demonstrated no statistically significant difference among the 4 groups. CONCLUSIONS: In most patients, the ventral somatomotor network can be identified with an increase in the probability of a better match at a higher component number. There is variable concordance of the ventral somatomotor network at the single-subject level between resting-state and task-based fMRI.

Objective The aim of this study is to evaluate the correlation between resting state functional MRI (RS-fMRI) activity and motor and cognitive impairment in spinocerebellar ataxia type 6 (SCA6). Methods Twelve patients with genetically confirmed SCA6 and 14 age matched healthy controls were imaged with RS-fMRI. Whole brain gray matter was automatically parcellated into 1000 regions of interest (ROIs). For each ROI, the first eigenvariate of voxel time courses was extracted. For each patient, Pearson correlation coefficients between each pair of ROI time courses were calculated across the 1000 ROIs. The set of average control correlation coefficients were fed as an undirected weighted adjacency matrix into the Rubinov and Sporns (2010) modularity algorithm. The intranetwork global efficiency of the thresholded adjacency sub-matrix was calculated and correlated with ataxia scores and cognitive performance. Results SCA6 patients showed mild cognitive impairments in executive function and visual-motor processing compared to control subjects. These neuropsychological impairments were correlated with decreased RS functional connectivity (FC) in the attention network. Conclusions Mild cognitive executive functions and visual-motor coordination impairments seen in SCA6 patients correlate with decreased resting-state connectivity in the attention network, suggesting a possible metric for the study of cognitive dysfunction in cerebellar disease. Hum Brain Mapp 38:3001–3010, 2017. © 2017 Wiley Periodicals, Inc.

SummaryIntrathecal drug delivery is routinely used to bypass the blood-brain barrier in treating varied central nervous system conditions. However, the utility of intrathecal delivery is limited by poor parenchymal uptake of agents from the cerebrospinal fluid. We demonstrate that a simple noninvasive transcranial ultrasound protocol significantly increases the brain parenchymal uptake of intrathecally administered drugs and antibodies. Essentially, we show that our protocol of transcranial ultrasound can accelerate glymphatic fluid transport from the cisternal space into the parenchymal compartment. Specifically, we administered small (∼1kDa) and large (∼150 kDa) molecule agents into the cisterna magna of rats and then applied low, diagnostic-intensity focused ultrasound in a scanning protocol throughout the brain. Using both real-time magnetic resonance imaging and ex vivo histologic analyses, we observed significantly increased uptake of each agent into the brain parenchyma from the cisternal cerebrospinal fluid, notably with no brain parenchymal damage. The low intensity of the ultrasound and its noninvasiveness underscores the ready path to clinical translation of this technique for whole-brain delivery of a variety of agents. Furthermore, this technique can be used as a means to probe the causal role of the glymphatic system in the variety of disease and physiologic processes to which it has been correlated.eTOC SummaryA translation-ready ultrasound technique enhances the brain penetration of intrathecally delivered agents via upregulating the glymphatic pathway.

A long-standing goal of translational neuroscience is the ability to noninvasively deliver therapeutic agents to specific brain regions with high spatiotemporal resolution. Focused ultrasound (FUS) is an emerging technology that can noninvasively deliver energy up the order of 1 kW/cm2 with millimeter and millisecond resolution to any point in the human brain with Food and Drug Administration-approved hardware. Although FUS is clinically utilized primarily for focal ablation in conditions such as essential tremor, recent breakthroughs have enabled the use of FUS for drug delivery at lower intensities (i.e., tens of watts per square centimeter) without ablation of the tissue. In this review, we present strategies for image-guided FUS-mediated pharmacologic neurointerventions. First, we discuss blood–brain barrier opening to deliver therapeutic agents of a variety of sizes to the central nervous system. We then describe the use of ultrasound-sensitive nanoparticles to noninvasively deliver small molecules to millimeter-sized structures including superficial cortical regions and deep gray matter regions within the brain without the need for blood–brain barrier opening. We also consider the safety and potential complications of these techniques, with attention to temporal acuity. Finally, we close with a discussion of different methods for mapping the ultrasound field within the brain and describe future avenues of research in ultrasound-targeted drug therapies.

BACKGROUND: MRI performed with echo-planar imaging (EPI) sequences is sensitive to susceptibility artifacts in the presence of metallic objects, which presents a substantial barrier for performing functional MRI and diffusion tensor imaging (DTI) in patients with metallic orthodontic material and other head implants. PURPOSE: To evaluate the ability to reduce susceptibility artifacts in healthy human participants wearing metallic orthodontic braces for two alternative approaches: T2-prepared functional MRI and diffusion-prepared DTI with three-dimensional fast gradient-echo readout. MATERIALS AND METHODS: In this prospective study conducted from February to September 2018, T2-prepared functional MRI and diffusion-prepared DTI were performed in healthy human participants. Removable dental braces with bonding trays were used so that MRI could be performed with braces and without braces in the same participants. Results were evaluated in regions with strong (EPI dropout regions for functional MRI and the inferior fronto-occipital fasciculus for DTI) and minimal (motor cortex for functional MRI and the posterior limb of internal capsule for DTI) susceptibility artifacts. Signal-to-noise ratio (SNR), contrast-to-noise ratio for functional MRI, apparent diffusion coefficient and fractional anisotropy for DTI, and degree of distortion (quantified with the Jaccard index, which measures the similarity of geometric shapes) were compared in regions with strong or minimal susceptibility effects between the current standard EPI sequences and the proposed alternatives by using paired t test. RESULTS: Six participants were evaluated (mean age ± standard deviation, 40 years ± 6; three women). In brain regions with strong susceptibility effects from the metallic braces, T2-prepared functional MRI showed significantly higher SNR (37.8 ± 2.4 vs 15.5 ± 5.3; P < .001) and contrast-to-noise ratio (0.83 ± 0.16 vs 0.29 ± 0.10; P < .001), whereas diffusion-prepared DTI showed higher SNR (5.8 ± 1.5 vs 3.8 ± 0.7; P = .03) than did conventional EPI methods. Apparent diffusion coefficient and fractional anisotropy were consistent with the literature. Geometric distortion was substantially reduced throughout the brain with the proposed methods (significantly higher Jaccard index, 0.95 ± 0.12 vs 0.81 ± 0.61; P < .001). CONCLUSION: T2-prepared functional MRI and diffusion-prepared diffusion tensor imaging can acquire functional and diffusion MRI, respectively, in healthy human participants wearing metallic dental braces with less susceptibility artifacts and geometric distortion than with conventional echo-planar imaging. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Dietrich in this issue.

Background To develop liposomes loaded with iodinated agents as nanosized CT/MRI bimodal contrast agents for monitoring liposome-mediated drug delivery. Methods Rhodamine-labeled iodixanol (VisipaqueTM)-loaded liposomes (IX-lipo) were prepared and tested for their properties as a diamagnetic CEST contrast agent in vitro. Mice bearing subcutaneous CT26 colon tumors were injected i.v. with 1 g/kg (535 mg iodine/kg) IX-lipo, and in vivo CT and CEST MR images were acquired on day 3. CT and CEST MR images were also acquired for tumor-bearing mice co-injected with IX-lipo and tumor necrosis factor (TNF-α). Results In addition to CT contrast, IX-lipo exhibited a strong CEST contrast similar to its non-liposomal form, with a detectability of ~2 nM per liposome. Both CT imaging and CEST MRI showed that i.v. injection of IX-lipo resulted in a rim enhancement of CT26 tumors with a heterogeneous central distribution. In contrast, co-injection of TNF-α caused a significantly augmented CT/MRI contrast in the tumor center. The intratumoral biodistribution of IX-lipo correlated well to the rhodamine patterns observed with fluorescence microscopy. Conclusions We have developed a CT/MRI bimodal imaging approach for monitoring the delivery and biodistribution of liposomes by loading them with the clinically approved X-ray/CT contrast agent iodixanol. Our approach may be easily adapted for other-FDA approved iodinated agents and thus has great translational potential.

Targeted, noninvasive neuromodulation of the brain of an otherwise awake subject could revolutionize both basic and clinical neuroscience. Toward this goal, we have developed nanoparticles that allow noninvasive uncaging of a neuromodulatory drug, in this case the small molecule anesthetic propofol, upon the application of focused ultrasound. These nanoparticles are composed of biodegradable and biocompatible constituents and are activated using sonication parameters that are readily achievable by current clinical transcranial focused ultrasound systems. These particles are potent enough that their activation can silence seizures in an acute rat seizure model. Notably, there is no evidence of brain parenchymal damage or blood-brain barrier opening with their use. Further development of these particles promises noninvasive, focal, and image-guided clinical neuromodulation along a variety of pharmacological axes.

A wide variety of hydrophilic imaging and therapeutic agents are unable to gain access to the central nervous system (CNS) due to the blood-brain barrier (BBB). In particular, unless a particular transporter exists that may transport the agent across the BBB, most agents that are larger than 500 Da or that are hydrophilic will be excluded by the BBB. Glutamate carboxypeptidase II (GCPII), also known as the prostate-specific membrane antigen (PSMA) in the periphery, has been implicated in various neuropsychiatric conditions. As all agents that target GCPII are hydrophilic and thereby excluded from the CNS, we used GCPII as a platform for demonstrating our MR-guided focused ultrasound (MRgFUS) technique for delivery of GCPII/PSMA-specific imaging agents to the brain. Female rats underwent MRgFUS-mediated opening of the BBB. After opening of the BBB, either a radio- or fluorescently labeled ureido-based ligand for GCPII/PSMA was administered intravenously. Brain uptake was assessed for 2-(3-{1-carboxy-5-[(6-[18F]fluoro-pyridine-3-carbonyl)-amino]-pentyl}-ureido)-pentanedioic acid ([18F]DCFPyL) and YC-27, two compounds known to bind GCPII/PSMA with high affinity, using positron emission tomography (PET) and near-infrared fluorescence (NIRF) imaging, respectively. Specificity of ligand binding to GCPII/PSMA in the brain was determined with co-administration of a molar excess of ZJ-43, a compound of the same chemical class but different structure from either [18F]DCFPyL or YC-27, which competes for GCPII/PSMA binding. Dynamic PET imaging using [18F]DCFPyL demonstrated that target uptake reached a plateau by ∼1 h after radiotracer administration, with target/background ratios continuing to increase throughout the course of imaging, from a ratio of ∼4:1 at 45 min to ∼7:1 by 80 min. NIRF imaging likewise demonstrated delivery of YC-27 to the brain, with clear visualization of tracer in the brain at 24 h. Tissue uptake of both ligands was greatly diminished by ZJ-43 co-administration, establishing specificity of binding of each to GCPII/PSMA. On gross and histological examination, animals showed no evidence for hemorrhage or other deleterious consequences of MRgFUS. MRgFUS provided safe opening of the BBB to enable specific delivery of two hydrophilic agents to target tissues within the brain. This platform might facilitate imaging and therapy using a variety of agents that have heretofore been excluded from the CNS.

Much recent attention has been paid to quantifying anatomic and functional neuroimaging on the individual subject level. For optimal individual subject characterization, specific acquisition and analysis features need to be identified that maximize interindividual variability while concomitantly minimizing intra-subject variability. We delineate the effect of various acquisition parameters (length of acquisition, sampling frequency) and analysis methods (time course extraction, region of interest parcellation, and thresholding of connectivity-derived network graphs) on characterizing individual subject differentiation. We utilize a non-parametric statistical metric that quantifies the degree to which a parameter set allows this individual subject differentiation by both maximizing interindividual variance and minimizing intra-individual variance. We apply this metric to analysis of four publicly available test-retest resting-state fMRI (rs-fMRI) data sets. We find that for the question of maximizing individual differentiation, (i) for increasing sampling, there is a relative tradeoff between increased sampling frequency and increased acquisition time; (ii) for the sizes of the interrogated data sets, only 3-4 min of acquisition time was sufficient to maximally differentiate each subject with an algorithm that utilized no a priori information regarding subject identification; and (iii) brain regions that most contribute to this individual subject characterization lie in the default mode, attention, and executive control networks. These findings may guide optimal rs-fMRI experiment design and may elucidate the neural bases for subject-to-subject differences. Hum Brain Mapp 37:1986-1997, 2016. © 2016 Wiley Periodicals, Inc.

Catheter-based intra-arterial drug therapies have proven effective for a range of oncologic, neurologic, and cardiovascular applications. However, these procedures are limited by their invasiveness and relatively broad drug spatial distribution. The ideal technique for local pharmacotherapy would be noninvasive and would flexibly deliver a given drug to any region of the body with high spatial and temporal precision. Combining polymeric perfluorocarbon nanoemulsions with existent clinical focused ultrasound systems could in principle meet these needs, but it has not been clear whether these nanoparticles could provide the necessary drug loading, stability, and generalizability across a range of drugs, beyond a few niche applications. Here, we develop polymeric perfluorocarbon nanoemulsions into a generalized platform for ultrasound-targeted delivery of hydrophobic drugs with high potential for clinical translation. We demonstrate that a wide variety of drugs may be effectively uncaged with ultrasound using these nanoparticles, with drug loading increasing with hydrophobicity. We also set the stage for clinical translation by delineating production protocols that are scalable and yield sterile, stable, and optimized ultrasound-activated drug-loaded nanoemulsions. Finally, we exhibit a new potential application of these nanoemulsions for local control of vascular tone. This work establishes the power of polymeric perfluorocarbon nanoemulsions as a clinically-translatable platform for efficacious, noninvasive, and localized ultrasonic drug uncaging for myriad targets in the brain and body.

Being able to noninvasively modulate brain activity, where and when an experimenter desires, with an immediate path toward human translation is a long-standing goal for neuroscience. To enable robust perturbation of brain activity while leveraging the ability of focused ultrasound to deliver energy to any point of the brain noninvasively, we have developed biocompatible and clinically translatable nanoparticles that allow ultrasound-induced uncaging of neuromodulatory drugs. Utilizing the anesthetic propofol, together with electrophysiological and imaging assays, we show that the neuromodulatory effect of ultrasonic drug uncaging is limited spatially and temporally by the size of the ultrasound focus, the sonication timing, and the pharmacokinetics of the uncaged drug. Moreover, we see secondary effects in brain regions anatomically distinct from and functionally connected to the sonicated region, indicating that ultrasonic drug uncaging could noninvasively map the changes in functional network connectivity associated with pharmacologic action at a particular brain target.

Catheter-based intra-arterial drug therapies have proven effective for a range of oncologic, neurologic, and cardiovascular applications. However, these procedures are limited by their invasiveness, as well as the relatively broad drug spatial distribution that is achievable with selective arterial catheterization. The ideal technique for local pharmacotherapy would be noninvasive and would flexibly deliver a given drug to any region of the body. Combining polymeric perfluorocarbon nanoemulsions with existent clinical focused ultrasound systems could in principle enable noninvasive targeted drug delivery, but it has not been clear whether these nanoparticles could provide the necessary drug loading, stability, and generalizability across a range of drugs to meet these needs, beyond a few niche applications. Here, we directly address all of those challenges and fully develop polymeric perfluorocarbon nanoemulsions into a generalized platform for ultrasound-targeted drug delivery with high potential for clinical translation. We demonstrate that a wide variety of drugs may be effectively uncaged with ultrasound using these nanoparticles, with drug loading increasing with hydrophobicity. We also set the stage for clinical translation by delineating production protocols that hew to clinical standards and yield stable and optimized ultrasound-activated drug-loaded nanoemulsions. Finally, as a new potential clinical application for these nanoemulsions, we exhibit their in vivo efficacy and performance for cardiovascular applications, by achieving local vasodilation in the highest flow vessel of the body, the aorta. This work establishes the power of polymeric perfluorocarbon nanoemulsions as a clinically-translatable platform for effective noninvasive ultrasonic drug uncaging for myriad targets in the brain and body.

Data reproducibility is a critical issue in all scientific experiments. In this manuscript, we consider the problem of quantifying the reproducibility of graphical measurements. We generalize the concept of image intra-class correlation coefficient (I2C2) and propose the concept of the graphical intra-class correlation coefficient (GICC) for such purpose. The concept of GICC is based on multivariate probit-linear mixed effect models. We will present a Markov Chain EM (MCEM) algorithm for estimating the GICC. Simulations results with varied settings are demonstrated and our method is applied to the KIRBY21 test-retest dataset., Comment: 14 pages, 3 figures, 1 table

There are growing concerns about potential delayed, neuropsychiatric consequences (e.g, cognitive decline, mood or anxiety disorders) of sports-related traumatic brain injury (TBI). Autopsy studies of brains from a limited number of former athletes have described characteristic, pathologic changes of chronic traumatic encephalopathy (CTE) leading to questions about the relationship between these pathologic and the neuropsychiatric disturbances seen in former athletes. Research in this area will depend on in vivo methods that characterize molecular changes in the brain, linking CTE and other sports-related pathologies with delayed emergence of neuropsychiatric symptoms. In this pilot project we studied former National Football League (NFL) players using new neuroimaging techniques and clinical measures of cognitive functioning. We hypothesized that former NFL players would show molecular and structural changes in medial temporal and parietal lobe structures as well as specific cognitive deficits, namely those of verbal learning and memory. We observed a significant increase in binding of [(11)C]DPA-713 to the translocator protein (TSPO), a marker of brain injury and repair, in several brain regions, such as the supramarginal gyrus and right amygdala, in 9 former NFL players compared to 9 age-matched, healthy controls. We also observed significant atrophy of the right hippocampus. Finally, we report that these same former players had varied performance on a test of verbal learning and memory, suggesting that these molecular and pathologic changes may play a role in cognitive decline. These results suggest that localized brain injury and repair, indicated by increased [(11)C]DPA-713 binding to TSPO, may be linked to history of NFL play. [(11)C]DPA-713 PET is a promising new tool that can be used in future study design to examine further the relationship between TSPO expression in brain injury and repair, selective regional brain atrophy, and the potential link to deficits in verbal learning and memory after NFL play.

SummarySocial interaction is a complex behavior essential for many species and is impaired in major neuropsychiatric disorders. Pharmacological studies have implicated certain neurotransmitter systems in social behavior, but circuit-level understanding of endogenous neural activity during social interaction is lacking. We therefore developed and applied a new methodology, termed fiber photometry, to optically record natural neural activity in genetically and connectivity-defined projections to elucidate the real-time role of specified pathways in mammalian behavior. Fiber photometry revealed that activity dynamics of a ventral tegmental area (VTA)-to-nucleus accumbens (NAc) projection could encode and predict key features of social, but not novel object, interaction. Consistent with this observation, optogenetic control of cells specifically contributing to this projection was sufficient to modulate social behavior, which was mediated by type 1 dopamine receptor signaling downstream in the NAc. Direct observation of deep projection-specific activity in this way captures a fundamental and previously inaccessible dimension of mammalian circuit dynamics.

Advances in molecular biology in the early 1970s revolutionized research strategies for the study of complex biological processes, which, in turn, created a high demand for new means to visualize these dynamic biological changes noninvasively and in real time. In this respect, MRI was a perfect fit, because of the versatile possibility to alter the different contrast mechanisms. Genetic manipulations are now being translated to MRI through the development of reporters and sensors, as well as the imaging of transgenic and knockout mice. In the past few years, a new molecular biology toolset, namely optogenetics, has emerged, which allows for the manipulation of cellular behavior using light. This technology provides a few particularly attractive features for combination with newly developed MRI techniques for the probing of in vivo cellular and, in particular, neural processes, specifically the ability to control focal, genetically defined cellular populations with high temporal resolution using equipment that is magnetically inert and does not interact with radiofrequency pulses. Recent studies have demonstrated that the combination of optogenetics and functional MRI (fMRI) can provide an appropriate platform to investigate in vivo, at the cellular and molecular levels, the neuronal basis of fMRI signals. In addition, this novel combination of optogenetics with fMRI has the potential to resolve pre-synaptic versus post-synaptic changes in neuronal activity and changes in the activity of large neuronal networks in the context of plasticity associated with development, learning and pathophysiology.

OBJECTIVE: The aim of this study is to evaluate the correlation between resting state functional MRI (RS‐fMRI) activity and motor and cognitive impairment in spinocerebellar ataxia type 6 (SCA6). METHODS: Twelve patients with genetically confirmed SCA6 and 14 age matched healthy controls were imaged with RS‐fMRI. Whole brain gray matter was automatically parcellated into 1000 regions of interest (ROIs). For each ROI, the first eigenvariate of voxel time courses was extracted. For each patient, Pearson correlation coefficients between each pair of ROI time courses were calculated across the 1000 ROIs. The set of average control correlation coefficients were fed as an undirected weighted adjacency matrix into the Rubinov and Sporns (2010) modularity algorithm. The intranetwork global efficiency of the thresholded adjacency sub‐matrix was calculated and correlated with ataxia scores and cognitive performance. RESULTS: SCA6 patients showed mild cognitive impairments in executive function and visual‐motor processing compared to control subjects. These neuropsychological impairments were correlated with decreased RS functional connectivity (FC) in the attention network. CONCLUSIONS: Mild cognitive executive functions and visual‐motor coordination impairments seen in SCA6 patients correlate with decreased resting‐state connectivity in the attention network, suggesting a possible metric for the study of cognitive dysfunction in cerebellar disease. Hum Brain Mapp 38:3001–3010, 2017. © 2017 Wiley Periodicals, Inc.

To demonstrate in a small case series for the first time the phenomenon of brain tumor-related neurovascular uncoupling (NVU) in resting-state blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) at ultrahigh field (7T). Two de novo (i.e., untreated) brain tumor patients underwent both BOLD resting-state fMRI (rsfMRI) on a 7T MRI system and motor task-based BOLD fMRI at 3T. Ipsilesional (i.e., ipsilateral to tumor or IL) and contralesional (i.e., contralateral to tumor or CL) region of interest (ROI) analysis was performed on both 3T motor task-related general linear model-derived activation maps and on 7T rsfMRI independent component analysis (ICA)-derived sensorimotor network maps for each case. Asymmetry scores (ASs) were computed based on numbers of suprathreshold voxels in the IL and CL ROIs. In each patient, ASs derived from ROI analysis of suprathreshold voxels in IL and CL ROIs in task-related activation maps and rsfMRI ICA-derived sensorimotor component maps indicate greater number of suprathreshold voxels in contralesional than ipsilesional sensorimotor cortex in both maps. In patient 1, an AS of 0.2 was obtained from the suprathreshold Z-score spectrum (voxels with Z-scores >5.0) of the task-based activation map and AS of 1.0 was obtained from the suprathreshold Z-score spectrum (Z-scores >5.0) of the ICA-derived sensorimotor component map. Similarly, in patient 2, an AS of 1.0 was obtained from the suprathreshold Z-score spectrum (Z-scores >5.0) of the task-based activation map and an AS of 1.0 was obtained from the suprathreshold Z-score spectrum (Z-scores >5.0) of the ICA-derived sensorimotor component map. Overall, decreased BOLD signal was noted in IL compared with CL ROIs on both task-based activation maps and ultrahigh field resting-state maps, indicating the presence of NVU. We have demonstrated evidence of NVU on ultrahigh field 7T rsfMRI comparable with the findings on standard 3T motor task-based fMRI in both cases.

Purpose To compare language networks derived from resting-state fMRI (rs-fMRI) with task-fMRI in patients with brain tumors and investigate variables that affect rs-fMRI vs task-fMRI concordance. Materials and Methods Independent component analysis (ICA) of rs-fMRI was performed with 20, 30, 40, and 50 target components (ICA20 to ICA50) and language networks identified for patients presenting for presurgical fMRI mapping between 1/1/2009 and 7/1/2015. 49 patients were analyzed fulfilling criteria for presence of brain tumors, no prior brain surgery, and adequate task-fMRI performance. Rs-vs-task-fMRI concordance was measured using Dice coefficients across varying fMRI thresholds before and after noise removal. Multi-thresholded Dice coefficient volume under the surface (DiceVUS) and maximum Dice coefficient (MaxDice) were calculated. One-way Analysis of Variance (ANOVA) was performed to determine significance of DiceVUS and MaxDice between the four ICA order groups. Age, Sex, Handedness, Tumor Side, Tumor Size, WHO Grade, number of scrubbed volumes, image intensity root mean square (iRMS), and mean framewise displacement (FD) were used as predictors for VUS in a linear regression. Results Artificial elevation of rs-fMRI vs task-fMRI concordance is seen at low thresholds due to noise. Noise-removed group-mean DiceVUS and MaxDice improved as ICA order increased, however ANOVA demonstrated no statistically significant difference between the four groups. Linear regression demonstrated an association between iRMS and DiceVUS for ICA30-50, and iRMS and MaxDice for ICA50. Conclusion Overall there is moderate group level rs-vs-task fMRI language network concordance, however substantial subject-level variability exists; iRMS may be used to determine reliability of rs-fMRI derived language networks. Hum Brain Mapp, 2015. © 2015 Wiley Periodicals, Inc.

Much recent attention has been paid to quantifying anatomic and functional neuroimaging on the individual subject level. For optimal individual subject characterization, specific acquisition and analysis features need to be identified that maximize interindividual variability while concomitantly minimizing intra-subject variability. We delineate the effect of various acquisition parameters (length of acquisition, sampling frequency) and analysis methods (time course extraction, region of interest parcellation, and thresholding of connectivity-derived network graphs) on characterizing individual subject differentiation. We utilize a non-parametric statistical metric that quantifies the degree to which a parameter set allows this individual subject differentiation by both maximizing interindividual variance and minimizing intra-individual variance. We apply this metric to analysis of four publicly available test-retest resting-state fMRI (rs-fMRI) data sets. We find that for the question of maximizing individual differentiation, (i) for increasing sampling, there is a relative tradeoff between increased sampling frequency and increased acquisition time; (ii) for the sizes of the interrogated data sets, only 3-4 min of acquisition time was sufficient to maximally differentiate each subject with an algorithm that utilized no a priori information regarding subject identification; and (iii) brain regions that most contribute to this individual subject characterization lie in the default mode, attention, and executive control networks. These findings may guide optimal rs-fMRI experiment design and may elucidate the neural bases for subject-to-subject differences. Hum Brain Mapp 37:1986-1997, 2016. © 2016 Wiley Periodicals, Inc.

Current strategies for clinical neuromodulation are limited by either high invasiveness, low precision, or poor depth of penetration. Deep brain stimulation (DBS) and other electrical strategies for deep brain neuromodulation necessitate the use of invasive device placement. Similarly, optogenetic interventions generally require the placement of a fiber-optic cable into the tissue for light delivery and would necessitate gene therapy. Noninvasive techniques for electrical neuromodulation, such as transcranial magnetic stimulation (TMS) or transcranial direct current stimulation (tDCS), on the other hand, have an overly broad spatial extent and limited depth of penetration.

Alterations in mucin expression and glycosylation are associated with cancer development. Underglycosylated mucin-1 (uMUC1) is overexpressed in most malignant adenocarcinomas of epithelial origin (for example, colon, breast and ovarian cancer). Its counterpart MUC1 is a large polymer rich in glycans containing multiple exchangeable OH protons, which is readily detectable by chemical exchange saturation transfer (CEST) MRI. We show here that deglycosylation of MUC1 results in >75% reduction in CEST signal. Three uMUC1+ human malignant cancer cell lines overexpressing uMUC1 (BT20, HT29 and LS174T) show a significantly lower CEST signal compared with the benign human epithelial cell line MCF10A and the uMUC1− tumour cell line U87. Furthermore, we demonstrate that in vivo CEST MRI is able to make a distinction between LS174T and U87 tumour cells implanted in the mouse brain. These results suggest that the mucCEST MRI signal can be used as a label-free surrogate marker to non-invasively assess mucin glycosylation and tumour malignancy., Overexpression of underglycosylated MUC1 (uMUC1) is found in most malignant adenocarcinomas of epithelial origin. Here the authors use chemical exchange saturation transfer (CEST) MRI to detect uMUC1 and to distinguish between malignant and nonmalignant tumours.

The purpose of this paper is to extend the single-subject Eve atlas from Johns Hopkins University, which currently contains diffusion tensor and T1-weighted anatomical maps, by including contrast based on quantitative susceptibility mapping. The new atlas combines a "deep gray matter parcellation map" (DGMPM) derived from a single-subject quantitative susceptibility map with the previously established "white matter parcellation map" (WMPM) from the same subject's T1-weighted and diffusion tensor imaging data into an MNI coordinate map named the "Everything Parcellation Map in Eve Space," also known as the "EvePM." It allows automated segmentation of gray matter and white matter structures. Quantitative susceptibility maps from five healthy male volunteers (30 to 33 years of age) were coregistered to the Eve Atlas with AIR and Large Deformation Diffeomorphic Metric Mapping (LDDMM), and the transformation matrices were applied to the EvePM to produce automated parcellation in subject space. Parcellation accuracy was measured with a kappa analysis for the left and right structures of six deep gray matter regions. For multi-orientation QSM images, the Kappa statistic was 0.85 between automated and manual segmentation, with the inter-rater reproducibility Kappa being 0.89 for the human raters, suggesting "almost perfect" agreement between all segmentation methods. Segmentation seemed slightly more difficult for human raters on single-orientation QSM images, with the Kappa statistic being 0.88 between automated and manual segmentation, and 0.85 and 0.86 between human raters. Overall, this atlas provides a time-efficient tool for automated coregistration and segmentation of quantitative susceptibility data to analyze many regions of interest. These data were used to establish a baseline for normal magnetic susceptibility measurements for over 60 brain structures of 30- to 33-year-old males. Correlating the average susceptibility with age-based iron concentrations in gray matter structures measured by Hallgren and Sourander (1958) allowed interpolation of the average iron concentration of several deep gray matter regions delineated in the EvePM.

Advances in molecular biology in the early 1970s have revolutionized research strategies for studying complex biological processes, which in turn created a high demand for new means to visualize these dynamic biological changes non-invasively and in real-time. In that respect, magnetic resonance imaging (MRI) technology was a perfect fit, due the versatile possibility to alter the different contrast mechanisms. Genetic manipulations are now being translated to MRI trough the development of reporters and sensors, as well as imaging transgenic and knockout mice. In the past few years, a new molecular biology toolset, namely optogenetics, has emerged, which allows for the manipulation of cellular behavior using light. This technology provides a few particularly attractive features for combination with newly developed MRI techniques for probing in vivo cellular, and in particular neural, processes – specifically the ability to control focal, genetically-defined cellular populations with high temporal resolution using equipment that is magnetically inert and does not interact with radiofrequency pulses. Recent works demonstrate that the combination of optogenetics and functional MRI (fMRI) can provide an appropriate platform to investigate in vivo, at the cellular and molecular levels, the neuronal basis of fMRI signals. In addition, this novel combination of optogenetics with fMRI has the potential to resolve pre-synaptic vs. post-synaptic changes of neuronal activity and changes in the activity of large neuronal networks in the context of plasticity associated with development, learning and pathophysiology.

Elucidation of the neural substrates underlying complex animal behaviors depends on precise activity control tools, as well as compatible readout methods. Recent developments in optogenetics have addressed this need, opening up new possibilities for systems neuroscience. Interrogation of even deep neural circuits can be conducted by directly probing the necessity and sufficiency of defined circuit elements with millisecond-scale, cell type-specific optical perturbations, coupled with suitable readouts such as electrophysiology, optical circuit dynamics measures and freely moving behavior in mammals. Here we collect in detail our strategies for delivering microbial opsin genes to deep mammalian brain structures in vivo, along with protocols for integrating the resulting optical control with compatible readouts (electrophysiological, optical and behavioral). The procedures described here, from initial virus preparation to systems-level functional readout, can be completed within 4-5 weeks. Together, these methods may help in providing circuit-level insight into the dynamics underlying complex mammalian behaviors in health and disease.

In the study of complex mammalian behaviours, technological limitations have prevented spatiotemporally precise control over intracellular signalling processes. Here we report the development of a versatile family of genetically encoded optical tools ('optoXRs') that leverage common structure-function relationships among G-protein-coupled receptors (GPCRs) to recruit and control, with high spatiotemporal precision, receptor-initiated biochemical signalling pathways. In particular, we have developed and characterized two optoXRs that selectively recruit distinct, targeted signalling pathways in response to light. The two optoXRs exerted opposing effects on spike firing in nucleus accumbens in vivo, and precisely timed optoXR photostimulation in nucleus accumbens by itself sufficed to drive conditioned place preference in freely moving mice. The optoXR approach allows testing of hypotheses regarding the causal impact of biochemical signalling in behaving mammals, in a targetable and temporally precise manner.

For understanding normal and pathological circuit function, capitalizing on the full potential of recent advances in fast optical neural circuit control will depend crucially on fast, intact-circuit readout technology. First, millisecond-scale optical control will be best leveraged with simultaneous millisecond-scale optical imaging. Second, both fast circuit control and imaging should be adaptable to intact-circuit preparations from normal and diseased subjects. Here we illustrate integration of fast optical circuit control and fast circuit imaging, review recent work demonstrating utility of applying fast imaging to quantifying activity flow in disease models, and discuss integration of diverse optogenetic and chemical genetic tools that have been developed to precisely control the activity of genetically specified neural populations. Together these neuroengineering advances raise the exciting prospect of determining the role-specific cell types play in modulating neural activity flow in neuropsychiatric disease.

The hippocampus is one of several brain areas thought to play a central role in affective behaviors, but the underlying local network dynamics are not understood. We used quantitative voltage-sensitive dye imaging to probe hippocampal dynamics with millisecond resolution in brain slices after bidirectional modulation of affective state in rat models of depression. We found that a simple measure of real-time activity—stimulus-evoked percolation of activity through the dentate gyrus relative to the hippocampal output subfield—accounted for induced changes in animal behavior independent of the underlying mechanism of action of the treatments. Our results define a circuit-level neurophysiological endophenotype for affective behavior and suggest an approach to understanding circuit-level substrates underlying psychiatric disease symptoms.