Fiber tracking of brain white matter based on graph theory.

PubMed

Lu, Meng

2015-01-01

Brain white matter tractography is reconstructed via diffusion-weighted magnetic resonance images. Due to the complex structure of brain white matter fiber bundles, fiber crossing and fiber branching are abundant in human brain. And regular methods with diffusion tensor imaging (DTI) can't accurately handle this problem. the biggest problems of the brain tractography. Therefore, this paper presented a novel brain white matter tractography method based on graph theory, so the fiber tracking between two voxels is transformed into locating the shortest path in a graph. Besides, the presented method uses Q-ball imaging (QBI) as the source data instead of DTI, because QBI can provide accurate information about multiple fiber crossing and branching in one voxel using orientation distribution function (ODF). Experiments showed that the presented method can accurately handle the problem of brain white matter fiber crossing and branching, and reconstruct brain tractograhpy both in phantom data and real brain data.

Brain white matter fiber estimation and tractography using Q-ball imaging and Bayesian MODEL.

PubMed

Lu, Meng

2015-01-01

Diffusion tensor imaging allows for the non-invasive in vivo mapping of the brain tractography. However, fiber bundles have complex structures such as fiber crossings, fiber branchings and fibers with large curvatures that tensor imaging (DTI) cannot accurately handle. This study presents a novel brain white matter tractography method using Q-ball imaging as the data source instead of DTI, because QBI can provide accurate information about multiple fiber crossings and branchings in a single voxel using an orientation distribution function (ODF). The presented method also uses graph theory to construct the Bayesian model-based graph, so that the fiber tracking between two voxels can be represented as the shortest path in a graph. Our experiment showed that our new method can accurately handle brain white matter fiber crossings and branchings, and reconstruct brain tractograhpy both in phantom data and real brain data.

A fast atlas-guided high density diffuse optical tomography system for brain imaging

NASA Astrophysics Data System (ADS)

Dai, Xianjin; Zhang, Tao; Yang, Hao; Jiang, Huabei

2017-02-01

Near infrared spectroscopy (NIRS) is an emerging functional brain imaging tool capable of assessing cerebral concentrations of oxygenated hemoglobin (HbO) and deoxygenated hemoglobin (HbR) during brain activation noninvasively. As an extension of NIRS, diffuse optical tomography (DOT) not only shares the merits of providing continuous readings of cerebral oxygenation, but also has the ability to provide spatial resolution in the millimeter scale. Based on the scattering and absorption properties of nonionizing near-infrared light in biological tissue, DOT has been successfully applied in the imaging of breast tumors, osteoarthritis and cortex activations. Here, we present a state-of-art fast high density DOT system suitable for brain imaging. It can achieve up to a 21 Hz sampling rate for a full set of two-wavelength data for 3-D DOT brain image reconstruction. The system was validated using tissue-mimicking brain-model phantom. Then, experiments on healthy subjects were conducted to demonstrate the capability of the system.

Approaching the biology of human parental attachment: brain imaging, oxytocin and coordinated assessments of mothers and fathers.

PubMed

Swain, J E; Kim, P; Spicer, J; Ho, S S; Dayton, C J; Elmadih, A; Abel, K M

2014-09-11

Brain networks that govern parental response to infant signals have been studied with imaging techniques over the last 15 years. The complex interaction of thoughts and behaviors required for sensitive parenting enables the formation of each individual's first social bonds and critically shapes development. This review concentrates on magnetic resonance imaging experiments which directly examine the brain systems involved in parental responses to infant cues. First, we introduce themes in the literature on parental brain circuits studied to date. Next, we present a thorough chronological review of state-of-the-art fMRI studies that probe the parental brain with a range of baby audio and visual stimuli. We also highlight the putative role of oxytocin and effects of psychopathology, as well as the most recent work on the paternal brain. Taken together, a new model emerges in which we propose that cortico-limbic networks interact to support parental brain responses to infants. These include circuitry for arousal/salience/motivation/reward, reflexive/instrumental caring, emotion response/regulation and integrative/complex cognitive processing. Maternal sensitivity and the quality of caregiving behavior are likely determined by the responsiveness of these circuits during early parent-infant experiences. The function of these circuits is modifiable by current and early-life experiences, hormonal and other factors. Severe deviation from the range of normal function in these systems is particularly associated with (maternal) mental illnesses - commonly, depression and anxiety, but also schizophrenia and bipolar disorder. Finally, we discuss the limits and extent to which brain imaging may broaden our understanding of the parental brain given our current model. Developments in the understanding of the parental brain may have profound implications for long-term outcomes in families across risk, resilience and possible interventions. This article is part of a Special Issue entitled Oxytocin and Social Behav. Copyright © 2014 Elsevier B.V. All rights reserved.

“Optical communication with brain cells by means of an implanted duplex micro-device with optogenetics and Ca2+ fluoroimaging”

PubMed Central

Kobayashi, Takuma; Haruta, Makito; Sasagawa, Kiyotaka; Matsumata, Miho; Eizumi, Kawori; Kitsumoto, Chikara; Motoyama, Mayumi; Maezawa, Yasuyo; Ohta, Yasumi; Noda, Toshihiko; Tokuda, Takashi; Ishikawa, Yasuyuki; Ohta, Jun

2016-01-01

To better understand the brain function based on neural activity, a minimally invasive analysis technology in a freely moving animal is necessary. Such technology would provide new knowledge in neuroscience and contribute to regenerative medical techniques and prosthetics care. An application that combines optogenetics for voluntarily stimulating nerves, imaging to visualize neural activity, and a wearable micro-instrument for implantation into the brain could meet the abovementioned demand. To this end, a micro-device that can be applied to the brain less invasively and a system for controlling the device has been newly developed in this study. Since the novel implantable device has dual LEDs and a CMOS image sensor, photostimulation and fluorescence imaging can be performed simultaneously. The device enables bidirectional communication with the brain by means of light. In the present study, the device was evaluated in an in vitro experiment using a new on-chip 3D neuroculture with an extracellular matrix gel and an in vivo experiment involving regenerative medical transplantation and gene delivery to the brain by using both photosensitive channel and fluorescent Ca2+ indicator. The device succeeded in activating cells locally by selective photostimulation, and the physiological Ca2+ dynamics of neural cells were visualized simultaneously by fluorescence imaging. PMID:26878910

“Optical communication with brain cells by means of an implanted duplex micro-device with optogenetics and Ca2+ fluoroimaging”

NASA Astrophysics Data System (ADS)

Kobayashi, Takuma; Haruta, Makito; Sasagawa, Kiyotaka; Matsumata, Miho; Eizumi, Kawori; Kitsumoto, Chikara; Motoyama, Mayumi; Maezawa, Yasuyo; Ohta, Yasumi; Noda, Toshihiko; Tokuda, Takashi; Ishikawa, Yasuyuki; Ohta, Jun

2016-02-01

To better understand the brain function based on neural activity, a minimally invasive analysis technology in a freely moving animal is necessary. Such technology would provide new knowledge in neuroscience and contribute to regenerative medical techniques and prosthetics care. An application that combines optogenetics for voluntarily stimulating nerves, imaging to visualize neural activity, and a wearable micro-instrument for implantation into the brain could meet the abovementioned demand. To this end, a micro-device that can be applied to the brain less invasively and a system for controlling the device has been newly developed in this study. Since the novel implantable device has dual LEDs and a CMOS image sensor, photostimulation and fluorescence imaging can be performed simultaneously. The device enables bidirectional communication with the brain by means of light. In the present study, the device was evaluated in an in vitro experiment using a new on-chip 3D neuroculture with an extracellular matrix gel and an in vivo experiment involving regenerative medical transplantation and gene delivery to the brain by using both photosensitive channel and fluorescent Ca2+ indicator. The device succeeded in activating cells locally by selective photostimulation, and the physiological Ca2+ dynamics of neural cells were visualized simultaneously by fluorescence imaging.

Pulsed laser diode photoacoustic tomography (PLD-PAT) system for fast in vivo imaging of small animal brain

NASA Astrophysics Data System (ADS)

Upputuri, Paul Kumar; Kalva, Sandeep Kumar; Moothanchery, Mohesh; Pramanik, Manojit

2017-03-01

In recent years, high-repetition rate pulsed laser diode (PLD) was used as an alternative to the Nd:YAG lasers for photoacoustic tomography (PAT). The use of PLD makes the overall PAT system, a low-cost, portable, and high frame rate imaging tool for preclinical applications. In this work, we will present a portable in vivo pulsed laser diode based photoacoustic tomography (PLD-PAT) system. The PLD is integrated inside a circular scanning geometry. The PLD can provide near-infrared ( 803 nm) pulses with pulse duration 136 ns, and pulse energy 1.4 mJ / pulse at 7 kHz repetition rate. The system will be demonstrated for in vivo fast imaging of small animal brain. To enhance the contrast of brain imaging, experiments will be carried out using contrast agents which have strong absorption around laser excitation wavelength. This low-cost, portable small animal brain imaging system could be very useful for brain tumor imaging and therapy.

Neuronal Tracing with Magnetic Labels: NMR Imaging Methods, Preliminary Results, and New Optimized Coils.

NASA Astrophysics Data System (ADS)

Ghosh, Pratik

1992-01-01

The investigations focussed on in vivo NMR imaging studies of magnetic particles with and within neural cells. NMR imaging methods, both Fourier transform and projection reconstruction, were implemented and new protocols were developed to perform "Neuronal Tracing with Magnetic Labels" on small animal brains. Having performed the preliminary experiments with neuronal tracing, new optimized coils and experimental set-up were devised. A novel gradient coil technology along with new rf-coils were implemented, and optimized for future use with small animals in them. A new magnetic labelling procedure was developed that allowed labelling of billions of cells with ultra -small magnetite particles in a short time. The relationships among the viability of such cells, the amount of label and the contrast in the images were studied as quantitatively as possible. Intracerebral grafting of magnetite labelled fetal rat brain cells made it possible for the first time to attempt monitoring in vivo the survival, differentiation, and possible migration of both host and grafted cells in the host rat brain. This constituted the early steps toward future experiments that may lead to the monitoring of human brain grafts of fetal brain cells. Preliminary experiments with direct injection of horse radish peroxidase-conjugated magnetite particles into neurons, followed by NMR imaging, revealed a possible non-invasive alternative, allowing serial study of the dynamic transport pattern of tracers in single living animals. New gradient coils were built by using parallel solid-conductor ribbon cables that could be wrapped easily and quickly. Rapid rise times provided by these coils allowed implementation of fast imaging methods. Optimized rf-coil circuit development made it possible to understand better the sample-coil properties and the associated trade -offs in cases of small but conducting samples.

Stereo Navi 2.0: software for stereotaxic surgery of the common marmoset (Callithrix jacchus).

PubMed

Tokuno, Hironobu; Tanaka, Ikuko; Umitsu, Yoshitomo; Nakamura, Yasuhisa

2009-11-01

Recently, we reported our web-accessible digital brain atlas of the common marmoset (Callithrix jacchus) at http://marmoset-brain.org:2008. Using digital images obtained during construction of this website, we developed stand-alone software for navigation of electrodes or injection needles for stereotaxic electrophysiological or anatomical experiments in vivo. This software enables us to draw lines on exchangeable section images, measure the length and angle of lines, superimpose a stereotaxic reference grid on the image, and send the image to the system clipboard. The software, Stereo Navi 2.0, is freely available at our brain atlas website.

Photoacoustic Imaging of Epilepsy

DTIC Science & Technology

2014-04-01

with the skin and skull intact. MCA, middle cerebral artery; RH, right hemispheres; LH, left hemispheres; LOB, left olfactory bulbs; ROB, Right...moving rat brain with skin and skull intact. (D) Open-skull photograph of the rat cortex surface after the PAT experiments The PAT detecting...22D shows a typical non-invasive PAT image obtained with the miniature PAT imaging system of a freely moving rat brain with skin and skull intact. Fig

Decoding brain responses to pixelized images in the primary visual cortex: implications for visual cortical prostheses

PubMed Central

Guo, Bing-bing; Zheng, Xiao-lin; Lu, Zhen-gang; Wang, Xing; Yin, Zheng-qin; Hou, Wen-sheng; Meng, Ming

2015-01-01

Visual cortical prostheses have the potential to restore partial vision. Still limited by the low-resolution visual percepts provided by visual cortical prostheses, implant wearers can currently only “see” pixelized images, and how to obtain the specific brain responses to different pixelized images in the primary visual cortex (the implant area) is still unknown. We conducted a functional magnetic resonance imaging experiment on normal human participants to investigate the brain activation patterns in response to 18 different pixelized images. There were 100 voxels in the brain activation pattern that were selected from the primary visual cortex, and voxel size was 4 mm × 4 mm × 4 mm. Multi-voxel pattern analysis was used to test if these 18 different brain activation patterns were specific. We chose a Linear Support Vector Machine (LSVM) as the classifier in this study. The results showed that the classification accuracies of different brain activation patterns were significantly above chance level, which suggests that the classifier can successfully distinguish the brain activation patterns. Our results suggest that the specific brain activation patterns to different pixelized images can be obtained in the primary visual cortex using a 4 mm × 4 mm × 4 mm voxel size and a 100-voxel pattern. PMID:26692860

Using Copula Distributions to Support More Accurate Imaging-Based Diagnostic Classifiers for Neuropsychiatric Disorders

PubMed Central

Bansal, Ravi; Hao, Xuejun; Liu, Jun; Peterson, Bradley S.

2014-01-01

Many investigators have tried to apply machine learning techniques to magnetic resonance images (MRIs) of the brain in order to diagnose neuropsychiatric disorders. Usually the number of brain imaging measures (such as measures of cortical thickness and measures of local surface morphology) derived from the MRIs (i.e., their dimensionality) has been large (e.g. >10) relative to the number of participants who provide the MRI data (<100). Sparse data in a high dimensional space increases the variability of the classification rules that machine learning algorithms generate, thereby limiting the validity, reproducibility, and generalizability of those classifiers. The accuracy and stability of the classifiers can improve significantly if the multivariate distributions of the imaging measures can be estimated accurately. To accurately estimate the multivariate distributions using sparse data, we propose to estimate first the univariate distributions of imaging data and then combine them using a Copula to generate more accurate estimates of their multivariate distributions. We then sample the estimated Copula distributions to generate dense sets of imaging measures and use those measures to train classifiers. We hypothesize that the dense sets of brain imaging measures will generate classifiers that are stable to variations in brain imaging measures, thereby improving the reproducibility, validity, and generalizability of diagnostic classification algorithms in imaging datasets from clinical populations. In our experiments, we used both computer-generated and real-world brain imaging datasets to assess the accuracy of multivariate Copula distributions in estimating the corresponding multivariate distributions of real-world imaging data. Our experiments showed that diagnostic classifiers generated using imaging measures sampled from the Copula were significantly more accurate and more reproducible than were the classifiers generated using either the real-world imaging measures or their multivariate Gaussian distributions. Thus, our findings demonstrate that estimated multivariate Copula distributions can generate dense sets of brain imaging measures that can in turn be used to train classifiers, and those classifiers are significantly more accurate and more reproducible than are those generated using real-world imaging measures alone. PMID:25093634

Fully automated rodent brain MR image processing pipeline on a Midas server: from acquired images to region-based statistics.

PubMed

Budin, Francois; Hoogstoel, Marion; Reynolds, Patrick; Grauer, Michael; O'Leary-Moore, Shonagh K; Oguz, Ipek

2013-01-01

Magnetic resonance imaging (MRI) of rodent brains enables study of the development and the integrity of the brain under certain conditions (alcohol, drugs etc.). However, these images are difficult to analyze for biomedical researchers with limited image processing experience. In this paper we present an image processing pipeline running on a Midas server, a web-based data storage system. It is composed of the following steps: rigid registration, skull-stripping, average computation, average parcellation, parcellation propagation to individual subjects, and computation of region-based statistics on each image. The pipeline is easy to configure and requires very little image processing knowledge. We present results obtained by processing a data set using this pipeline and demonstrate how this pipeline can be used to find differences between populations.

The experience of beauty derived from sorrow.

PubMed

Ishizu, Tomohiro; Zeki, Semir

2017-08-01

We studied the neural mechanisms that are engaged during the experience of beauty derived from sorrow and from joy, two experiences that share a common denominator (beauty) but are linked to opposite emotional valences. Twenty subjects viewed and rerated, in a functional magnetic resonance imaging scanner, 120 images which each had classified into the following four categories: beautiful and sad; beautiful and joyful; neutral; ugly. The medial orbito-frontal cortex (mOFC) was active during the experience of both types of beauty. Otherwise, the two experiences engaged different parts of the brain: joyful beauty engaged areas linked to positive emotions while sorrowful beauty engaged areas linked to negative experiences. Separate regions of the cerebellum were engaged during experience of the two conditions. A functional connectivity analysis indicated that the activity within the mOFC was modulated by the supplementary motor area/middle cingulate cortex, known to be engaged during empathetic experiences provoked by other peoples' sadness. Hum Brain Mapp 38:4185-4200, 2017. © 2017 Wiley Periodicals, Inc. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Perception of Suffering and Compassion Experience: Brain Gender Disparities

ERIC Educational Resources Information Center

Mercadillo, Roberto E.; Diaz, Jose Luis; Pasaye, Erick H.; Barrios, Fernando A.

2011-01-01

Compassion is considered a moral emotion related to the perception of suffering in others, and resulting in a motivation to alleviate the afflicted party. We compared brain correlates of compassion-evoking images in women and men. BOLD functional images of 24 healthy volunteers (twelve women and twelve men; age=27 [plus or minus] 2.5 y.o.) were…

From nociception to pain perception: imaging the spinal and supraspinal pathways

PubMed Central

Brooks, Jonathan; Tracey, Irene

2005-01-01

Functional imaging techniques have allowed researchers to look within the brain, and revealed the cortical representation of pain. Initial experiments, performed in the early 1990s, revolutionized pain research, as they demonstrated that pain was not processed in a single cortical area, but in several distributed brain regions. Over the last decade, the roles of these pain centres have been investigated and a clearer picture has emerged of the medial and lateral pain system. In this brief article, we review the imaging literature to date that has allowed these advances to be made, and examine the new frontiers for pain imaging research: imaging the brainstem and other structures involved in the descending control of pain; functional and anatomical connectivity studies of pain processing brain regions; imaging models of neuropathic pain-like states; and going beyond the brain to image spinal function. The ultimate goal of such research is to take these new techniques into the clinic, to investigate and provide new remedies for chronic pain sufferers. PMID:16011543

Fluorescence laminar optical tomography for brain imaging: system implementation and performance evaluation.

PubMed

Azimipour, Mehdi; Sheikhzadeh, Mahya; Baumgartner, Ryan; Cullen, Patrick K; Helmstetter, Fred J; Chang, Woo-Jin; Pashaie, Ramin

2017-01-01

We present our effort in implementing a fluorescence laminar optical tomography scanner which is specifically designed for noninvasive three-dimensional imaging of fluorescence proteins in the brains of small rodents. A laser beam, after passing through a cylindrical lens, scans the brain tissue from the surface while the emission signal is captured by the epi-fluorescence optics and is recorded using an electron multiplication CCD sensor. Image reconstruction algorithms are developed based on Monte Carlo simulation to model light–tissue interaction and generate the sensitivity matrices. To solve the inverse problem, we used the iterative simultaneous algebraic reconstruction technique. The performance of the developed system was evaluated by imaging microfabricated silicon microchannels embedded inside a substrate with optical properties close to the brain as a tissue phantom and ultimately by scanning brain tissue in vivo. Details of the hardware design and reconstruction algorithms are discussed and several experimental results are presented. The developed system can specifically facilitate neuroscience experiments where fluorescence imaging and molecular genetic methods are used to study the dynamics of the brain circuitries.

Histogram-based normalization technique on human brain magnetic resonance images from different acquisitions.

PubMed

Sun, Xiaofei; Shi, Lin; Luo, Yishan; Yang, Wei; Li, Hongpeng; Liang, Peipeng; Li, Kuncheng; Mok, Vincent C T; Chu, Winnie C W; Wang, Defeng

2015-07-28

Intensity normalization is an important preprocessing step in brain magnetic resonance image (MRI) analysis. During MR image acquisition, different scanners or parameters would be used for scanning different subjects or the same subject at a different time, which may result in large intensity variations. This intensity variation will greatly undermine the performance of subsequent MRI processing and population analysis, such as image registration, segmentation, and tissue volume measurement. In this work, we proposed a new histogram normalization method to reduce the intensity variation between MRIs obtained from different acquisitions. In our experiment, we scanned each subject twice on two different scanners using different imaging parameters. With noise estimation, the image with lower noise level was determined and treated as the high-quality reference image. Then the histogram of the low-quality image was normalized to the histogram of the high-quality image. The normalization algorithm includes two main steps: (1) intensity scaling (IS), where, for the high-quality reference image, the intensities of the image are first rescaled to a range between the low intensity region (LIR) value and the high intensity region (HIR) value; and (2) histogram normalization (HN),where the histogram of low-quality image as input image is stretched to match the histogram of the reference image, so that the intensity range in the normalized image will also lie between LIR and HIR. We performed three sets of experiments to evaluate the proposed method, i.e., image registration, segmentation, and tissue volume measurement, and compared this with the existing intensity normalization method. It is then possible to validate that our histogram normalization framework can achieve better results in all the experiments. It is also demonstrated that the brain template with normalization preprocessing is of higher quality than the template with no normalization processing. We have proposed a histogram-based MRI intensity normalization method. The method can normalize scans which were acquired on different MRI units. We have validated that the method can greatly improve the image analysis performance. Furthermore, it is demonstrated that with the help of our normalization method, we can create a higher quality Chinese brain template.

Intuitive operability evaluation of surgical robot using brain activity measurement to determine immersive reality.

PubMed

Miura, Satoshi; Kobayashi, Yo; Kawamura, Kazuya; Seki, Masatoshi; Nakashima, Yasutaka; Noguchi, Takehiko; Kasuya, Masahiro; Yokoo, Yuki; Fujie, Masakatsu G

2012-01-01

Surgical robots have improved considerably in recent years, but intuitive operability, which represents user inter-operability, has not been quantitatively evaluated. Therefore, for design of a robot with intuitive operability, we propose a method to measure brain activity to determine intuitive operability. The objective of this paper is to determine the master configuration against the monitor that allows users to perceive the manipulator as part of their own body. We assume that the master configuration produces an immersive reality experience for the user of putting his own arm into the monitor. In our experiments, as subjects controlled the hand controller to position the tip of the virtual slave manipulator on a target in a surgical simulator, we measured brain activity through brain-imaging devices. We performed our experiments for a variety of master manipulator configurations with the monitor position fixed. For all test subjects, we found that brain activity was stimulated significantly when the master manipulator was located behind the monitor. We conclude that this master configuration produces immersive reality through the body image, which is related to visual and somatic sense feedback.

Functional connectivity in the mouse brain imaged by B-mode photoacoustic microscopy

NASA Astrophysics Data System (ADS)

Nasiriavanaki, Mohammadreza; Xing, Wenxin; Xia, Jun; Wang, Lihong V.

2014-03-01

The increasing use of mouse models for human brain disease studies, coupled with the fact that existing functional imaging modalities cannot be easily applied to mice, presents an emerging need for a new functional imaging modality. Utilizing acoustic-resolution photoacoustic microscopy (AR-PAM), we imaged spontaneous cerebral hemodynamic fluctuations and their associated functional connections in the mouse brain. The images were acquired noninvasively in B-scan mode with a fast frame rate, a large field of view, and a high spatial resolution. At a location relative to the bregma 0, correlations were investigated inter-hemispherically between bilaterally homologous regions, as well as intra-hemispherically within the same functional regions. The functional connectivity in different functional regions was studied. The locations of these regions agreed well with the Paxinos mouse brain atlas. The functional connectivity map obtained in this study can then be used in the investigation of brain disorders such as stroke, Alzheimer's, schizophrenia, multiple sclerosis, autism, and epilepsy. Our experiments show that photoacoustic microscopy is capable to detect connectivities between different functional regions in B-scan mode, promising a powerful functional imaging modality for future brain research.

Level set method with automatic selective local statistics for brain tumor segmentation in MR images.

PubMed

Thapaliya, Kiran; Pyun, Jae-Young; Park, Chun-Su; Kwon, Goo-Rak

2013-01-01

The level set approach is a powerful tool for segmenting images. This paper proposes a method for segmenting brain tumor images from MR images. A new signed pressure function (SPF) that can efficiently stop the contours at weak or blurred edges is introduced. The local statistics of the different objects present in the MR images were calculated. Using local statistics, the tumor objects were identified among different objects. In this level set method, the calculation of the parameters is a challenging task. The calculations of different parameters for different types of images were automatic. The basic thresholding value was updated and adjusted automatically for different MR images. This thresholding value was used to calculate the different parameters in the proposed algorithm. The proposed algorithm was tested on the magnetic resonance images of the brain for tumor segmentation and its performance was evaluated visually and quantitatively. Numerical experiments on some brain tumor images highlighted the efficiency and robustness of this method. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

A combined solenoid-surface RF coil for high-resolution whole-brain rat imaging on a 3.0 Tesla clinical MR scanner.

PubMed

Underhill, Hunter R; Yuan, Chun; Hayes, Cecil E

2010-09-01

Rat brain models effectively simulate a multitude of human neurological disorders. Improvements in coil design have facilitated the wider utilization of rat brain models by enabling the utilization of clinical MR scanners for image acquisition. In this study, a novel coil design, subsequently referred to as the rat brain coil, is described that exploits and combines the strengths of both solenoids and surface coils into a simple, multichannel, receive-only coil dedicated to whole-brain rat imaging on a 3.0 T clinical MR scanner. Compared with a multiturn solenoid mouse body coil, a 3-cm surface coil, a modified Helmholtz coil, and a phased-array surface coil, the rat brain coil improved signal-to-noise ratio by approximately 72, 61, 78, and 242%, respectively. Effects of the rat brain coil on amplitudes of static field and radiofrequency field uniformity were similar to each of the other coils. In vivo, whole-brain images of an adult male rat were acquired with a T(2)-weighted spin-echo sequence using an isotropic acquisition resolution of 0.25 x 0.25 x 0.25 mm(3) in 60.6 min. Multiplanar images of the in vivo rat brain with identification of anatomic structures are presented. Improvement in signal-to-noise ratio afforded by the rat brain coil may broaden experiments that utilize clinical MR scanners for in vivo image acquisition. 2010 Wiley-Liss, Inc.

A framework for correcting brain retraction based on an eXtended Finite Element Method using a laser range scanner.

PubMed

Li, Ping; Wang, Weiwei; Song, Zhijian; An, Yong; Zhang, Chenxi

2014-07-01

Brain retraction causes great distortion that limits the accuracy of an image-guided neurosurgery system that uses preoperative images. Therefore, brain retraction correction is an important intraoperative clinical application. We used a linear elastic biomechanical model, which deforms based on the eXtended Finite Element Method (XFEM) within a framework for brain retraction correction. In particular, a laser range scanner was introduced to obtain a surface point cloud of the exposed surgical field including retractors inserted into the brain. A brain retraction surface tracking algorithm converted these point clouds into boundary conditions applied to XFEM modeling that drive brain deformation. To test the framework, we performed a brain phantom experiment involving the retraction of tissue. Pairs of the modified Hausdorff distance between Canny edges extracted from model-updated images, pre-retraction, and post-retraction CT images were compared to evaluate the morphological alignment of our framework. Furthermore, the measured displacements of beads embedded in the brain phantom and the predicted ones were compared to evaluate numerical performance. The modified Hausdorff distance of 19 pairs of images decreased from 1.10 to 0.76 mm. The forecast error of 23 stainless steel beads in the phantom was between 0 and 1.73 mm (mean 1.19 mm). The correction accuracy varied between 52.8 and 100 % (mean 81.4 %). The results demonstrate that the brain retraction compensation can be incorporated intraoperatively into the model-updating process in image-guided neurosurgery systems.

Examination of Cognitive Fatigue in Multiple Sclerosis using Functional Magnetic Resonance Imaging and Diffusion Tensor Imaging

PubMed Central

Genova, Helen M.; Rajagopalan, Venkateswaran; DeLuca, John; Das, Abhijit; Binder, Allison; Arjunan, Aparna; Chiaravalloti, Nancy; Wylie, Glenn

2013-01-01

The present study investigated the neural correlates of cognitive fatigue in Multiple Sclerosis (MS), looking specifically at the relationship between self-reported fatigue and objective measures of cognitive fatigue. In Experiment 1, functional magnetic resonance imaging (fMRI) was used to examine where in the brain BOLD activity covaried with “state” fatigue, assessed during performance of a task designed to induce cognitive fatigue while in the scanner. In Experiment 2, diffusion tensor imaging (DTI) was used to examine where in the brain white matter damage correlated with increased “trait” fatigue in individuals with MS, assessed by the Fatigue Severity Scale (FSS) completed outside the scanning session. During the cognitively fatiguing task, the MS group had increased brain activity associated with fatigue in the caudate as compared with HCs. DTI findings revealed that reduced fractional anisotropy in the anterior internal capsule was associated with increased self-reported fatigue on the FSS. Results are discussed in terms of identifying a “fatigue-network” in MS. PMID:24223850

Examination of cognitive fatigue in multiple sclerosis using functional magnetic resonance imaging and diffusion tensor imaging.

PubMed

Genova, Helen M; Rajagopalan, Venkateswaran; Deluca, John; Das, Abhijit; Binder, Allison; Arjunan, Aparna; Chiaravalloti, Nancy; Wylie, Glenn

2013-01-01

The present study investigated the neural correlates of cognitive fatigue in Multiple Sclerosis (MS), looking specifically at the relationship between self-reported fatigue and objective measures of cognitive fatigue. In Experiment 1, functional magnetic resonance imaging (fMRI) was used to examine where in the brain BOLD activity covaried with "state" fatigue, assessed during performance of a task designed to induce cognitive fatigue while in the scanner. In Experiment 2, diffusion tensor imaging (DTI) was used to examine where in the brain white matter damage correlated with increased "trait" fatigue in individuals with MS, assessed by the Fatigue Severity Scale (FSS) completed outside the scanning session. During the cognitively fatiguing task, the MS group had increased brain activity associated with fatigue in the caudate as compared with HCs. DTI findings revealed that reduced fractional anisotropy in the anterior internal capsule was associated with increased self-reported fatigue on the FSS. Results are discussed in terms of identifying a "fatigue-network" in MS.

Application of an enhanced fuzzy algorithm for MR brain tumor image segmentation

NASA Astrophysics Data System (ADS)

Hemanth, D. Jude; Vijila, C. Kezi Selva; Anitha, J.

2010-02-01

Image segmentation is one of the significant digital image processing techniques commonly used in the medical field. One of the specific applications is tumor detection in abnormal Magnetic Resonance (MR) brain images. Fuzzy approaches are widely preferred for tumor segmentation which generally yields superior results in terms of accuracy. But most of the fuzzy algorithms suffer from the drawback of slow convergence rate which makes the system practically non-feasible. In this work, the application of modified Fuzzy C-means (FCM) algorithm to tackle the convergence problem is explored in the context of brain image segmentation. This modified FCM algorithm employs the concept of quantization to improve the convergence rate besides yielding excellent segmentation efficiency. This algorithm is experimented on real time abnormal MR brain images collected from the radiologists. A comprehensive feature vector is extracted from these images and used for the segmentation technique. An extensive feature selection process is performed which reduces the convergence time period and improve the segmentation efficiency. After segmentation, the tumor portion is extracted from the segmented image. Comparative analysis in terms of segmentation efficiency and convergence rate is performed between the conventional FCM and the modified FCM. Experimental results show superior results for the modified FCM algorithm in terms of the performance measures. Thus, this work highlights the application of the modified algorithm for brain tumor detection in abnormal MR brain images.

Semiautomatic Segmentation of Glioma on Mobile Devices.

PubMed

Wu, Ya-Ping; Lin, Yu-Song; Wu, Wei-Guo; Yang, Cong; Gu, Jian-Qin; Bai, Yan; Wang, Mei-Yun

2017-01-01

Brain tumor segmentation is the first and the most critical step in clinical applications of radiomics. However, segmenting brain images by radiologists is labor intense and prone to inter- and intraobserver variability. Stable and reproducible brain image segmentation algorithms are thus important for successful tumor detection in radiomics. In this paper, we propose a supervised brain image segmentation method, especially for magnetic resonance (MR) brain images with glioma. This paper uses hard edge multiplicative intrinsic component optimization to preprocess glioma medical image on the server side, and then, the doctors could supervise the segmentation process on mobile devices in their convenient time. Since the preprocessed images have the same brightness for the same tissue voxels, they have small data size (typically 1/10 of the original image size) and simple structure of 4 types of intensity value. This observation thus allows follow-up steps to be processed on mobile devices with low bandwidth and limited computing performance. Experiments conducted on 1935 brain slices from 129 patients show that more than 30% of the sample can reach 90% similarity; over 60% of the samples can reach 85% similarity, and more than 80% of the sample could reach 75% similarity. The comparisons with other segmentation methods also demonstrate both efficiency and stability of the proposed approach.

Neurobiology of Dyslexia

PubMed Central

Norton, Elizabeth S.; Beach, Sara D.; Gabrieli, John D. E.

2014-01-01

Dyslexia is one of the most common learning disabilities, yet its brain basis and core causes are not yet fully understood. Neuroimaging methods, including structural and functional magnetic resonance imaging, diffusion tensor imaging, and electrophysiology, have significantly contributed to knowledge about the neurobiology of dyslexia. Recent studies have discovered brain differences prior to formal instruction that likely encourage or discourage learning to read effectively, distinguished between brain differences that likely reflect the etiology of dyslexia versus brain differences that are the consequences of variation in reading experience, and identified distinct neural networks associated with specific psychological factors that are associated with dyslexia. PMID:25290881

Adolescents' behavioral and neural responses to e-cigarette advertising.

PubMed

Chen, Yvonnes; Fowler, Carina H; Papa, Vlad B; Lepping, Rebecca J; Brucks, Morgan G; Fox, Andrew T; Martin, Laura E

2018-03-01

Although adolescents are a group heavily targeted by the e-cigarette industry, research in cue-reactivity has not previously examined adolescents' behavioral and neural responses to e-cigarette advertising. This study addressed this gap through two experiments. In Experiment One, adult traditional cigarette smokers (n = 41) and non-smokers (n = 41) answered questions about e-cigarette and neutral advertising images. The 40 e-cigarette advertising images that most increased desire to use the product were matched to 40 neutral advertising images with similar content. In Experiment Two, the 80 advertising images selected in Experiment One were presented to adolescents (n = 30) during an functional magnetic resonance imaging brain scan. There was a range of traditional cigarette smoking across the sample with some adolescents engaging in daily smoking and others who had never smoked. Adolescents self-reported that viewing the e-cigarette advertising images increased their desire to smoke. Additionally, all participants regardless of smoking statuses showed significantly greater brain activation to e-cigarette advertisements in areas associated with cognitive control (left middle frontal gyrus), reward (right medial frontal gyrus), visual processing/attention (left lingual gyrus/fusiform gyrus, right inferior parietal lobule, left posterior cingulate, left angular gyrus) and memory (right parahippocampus, left insula). Further, an exploratory analysis showed that compared with age-matched non-smokers (n = 7), adolescent smokers (n = 7) displayed significantly greater neural activation to e-cigarette advertising images in the left inferior temporal gyrus/fusiform gyrus, compared with their responses to neutral advertising images. Overall, participants' brain responses to e-cigarette advertisements suggest a need to further investigate the long-run impact of e-cigarette advertising on adolescents. © 2017 Society for the Study of Addiction.

Physical experience enhances science learning.

PubMed

Kontra, Carly; Lyons, Daniel J; Fischer, Susan M; Beilock, Sian L

2015-06-01

Three laboratory experiments involving students' behavior and brain imaging and one randomized field experiment in a college physics class explored the importance of physical experience in science learning. We reasoned that students' understanding of science concepts such as torque and angular momentum is aided by activation of sensorimotor brain systems that add kinetic detail and meaning to students' thinking. We tested whether physical experience with angular momentum increases involvement of sensorimotor brain systems during students' subsequent reasoning and whether this involvement aids their understanding. The physical experience, a brief exposure to forces associated with angular momentum, significantly improved quiz scores. Moreover, improved performance was explained by activation of sensorimotor brain regions when students later reasoned about angular momentum. This finding specifies a mechanism underlying the value of physical experience in science education and leads the way for classroom practices in which experience with the physical world is an integral part of learning. © The Author(s) 2015.

Cortical Enhanced Tissue Segmentation of Neonatal Brain MR Images Acquired by a Dedicated Phased Array Coil

PubMed Central

Shi, Feng; Yap, Pew-Thian; Fan, Yong; Cheng, Jie-Zhi; Wald, Lawrence L.; Gerig, Guido; Lin, Weili; Shen, Dinggang

2010-01-01

The acquisition of high quality MR images of neonatal brains is largely hampered by their characteristically small head size and low tissue contrast. As a result, subsequent image processing and analysis, especially for brain tissue segmentation, are often hindered. To overcome this problem, a dedicated phased array neonatal head coil is utilized to improve MR image quality by effectively combing images obtained from 8 coil elements without lengthening data acquisition time. In addition, a subject-specific atlas based tissue segmentation algorithm is specifically developed for the delineation of fine structures in the acquired neonatal brain MR images. The proposed tissue segmentation method first enhances the sheet-like cortical gray matter (GM) structures in neonatal images with a Hessian filter for generation of cortical GM prior. Then, the prior is combined with our neonatal population atlas to form a cortical enhanced hybrid atlas, which we refer to as the subject-specific atlas. Various experiments are conducted to compare the proposed method with manual segmentation results, as well as with additional two population atlas based segmentation methods. Results show that the proposed method is capable of segmenting the neonatal brain with the highest accuracy, compared to other two methods. PMID:20862268

Robust generative asymmetric GMM for brain MR image segmentation.

PubMed

Ji, Zexuan; Xia, Yong; Zheng, Yuhui

2017-11-01

Accurate segmentation of brain tissues from magnetic resonance (MR) images based on the unsupervised statistical models such as Gaussian mixture model (GMM) has been widely studied during last decades. However, most GMM based segmentation methods suffer from limited accuracy due to the influences of noise and intensity inhomogeneity in brain MR images. To further improve the accuracy for brain MR image segmentation, this paper presents a Robust Generative Asymmetric GMM (RGAGMM) for simultaneous brain MR image segmentation and intensity inhomogeneity correction. First, we develop an asymmetric distribution to fit the data shapes, and thus construct a spatial constrained asymmetric model. Then, we incorporate two pseudo-likelihood quantities and bias field estimation into the model's log-likelihood, aiming to exploit the neighboring priors of within-cluster and between-cluster and to alleviate the impact of intensity inhomogeneity, respectively. Finally, an expectation maximization algorithm is derived to iteratively maximize the approximation of the data log-likelihood function to overcome the intensity inhomogeneity in the image and segment the brain MR images simultaneously. To demonstrate the performances of the proposed algorithm, we first applied the proposed algorithm to a synthetic brain MR image to show the intermediate illustrations and the estimated distribution of the proposed algorithm. The next group of experiments is carried out in clinical 3T-weighted brain MR images which contain quite serious intensity inhomogeneity and noise. Then we quantitatively compare our algorithm to state-of-the-art segmentation approaches by using Dice coefficient (DC) on benchmark images obtained from IBSR and BrainWeb with different level of noise and intensity inhomogeneity. The comparison results on various brain MR images demonstrate the superior performances of the proposed algorithm in dealing with the noise and intensity inhomogeneity. In this paper, the RGAGMM algorithm is proposed which can simply and efficiently incorporate spatial constraints into an EM framework to simultaneously segment brain MR images and estimate the intensity inhomogeneity. The proposed algorithm is flexible to fit the data shapes, and can simultaneously overcome the influence of noise and intensity inhomogeneity, and hence is capable of improving over 5% segmentation accuracy comparing with several state-of-the-art algorithms. Copyright © 2017 Elsevier B.V. All rights reserved.

Susceptibility-based functional brain mapping by 3D deconvolution of an MR-phase activation map.

PubMed

Chen, Zikuan; Liu, Jingyu; Calhoun, Vince D

2013-05-30

The underlying source of T2*-weighted magnetic resonance imaging (T2*MRI) for brain imaging is magnetic susceptibility (denoted by χ). T2*MRI outputs a complex-valued MR image consisting of magnitude and phase information. Recent research has shown that both the magnitude and the phase images are morphologically different from the source χ, primarily due to 3D convolution, and that the source χ can be reconstructed from complex MR images by computed inverse MRI (CIMRI). Thus, we can obtain a 4D χ dataset from a complex 4D MR dataset acquired from a brain functional MRI study by repeating CIMRI to reconstruct 3D χ volumes at each timepoint. Because the reconstructed χ is a more direct representation of neuronal activity than the MR image, we propose a method for χ-based functional brain mapping, which is numerically characterised by a temporal correlation map of χ responses to a stimulant task. Under the linear imaging conditions used for T2*MRI, we show that the χ activation map can be calculated from the MR phase map by CIMRI. We validate our approach using numerical simulations and Gd-phantom experiments. We also analyse real data from a finger-tapping visuomotor experiment and show that the χ-based functional mapping provides additional activation details (in the form of positive and negative correlation patterns) beyond those generated by conventional MR-magnitude-based mapping. Copyright © 2013 Elsevier B.V. All rights reserved.

Brain Atlas Fusion from High-Thickness Diagnostic Magnetic Resonance Images by Learning-Based Super-Resolution

PubMed Central

Zhang, Jinpeng; Zhang, Lichi; Xiang, Lei; Shao, Yeqin; Wu, Guorong; Zhou, Xiaodong; Shen, Dinggang; Wang, Qian

2017-01-01

It is fundamentally important to fuse the brain atlas from magnetic resonance (MR) images for many imaging-based studies. Most existing works focus on fusing the atlases from high-quality MR images. However, for low-quality diagnostic images (i.e., with high inter-slice thickness), the problem of atlas fusion has not been addressed yet. In this paper, we intend to fuse the brain atlas from the high-thickness diagnostic MR images that are prevalent for clinical routines. The main idea of our works is to extend the conventional groupwise registration by incorporating a novel super-resolution strategy. The contribution of the proposed super-resolution framework is two-fold. First, each high-thickness subject image is reconstructed to be isotropic by the patch-based sparsity learning. Then, the reconstructed isotropic image is enhanced for better quality through the random-forest-based regression model. In this way, the images obtained by the super-resolution strategy can be fused together by applying the groupwise registration method to construct the required atlas. Our experiments have shown that the proposed framework can effectively solve the problem of atlas fusion from the low-quality brain MR images. PMID:29062159

Brain Atlas Fusion from High-Thickness Diagnostic Magnetic Resonance Images by Learning-Based Super-Resolution.

PubMed

Zhang, Jinpeng; Zhang, Lichi; Xiang, Lei; Shao, Yeqin; Wu, Guorong; Zhou, Xiaodong; Shen, Dinggang; Wang, Qian

2017-03-01

It is fundamentally important to fuse the brain atlas from magnetic resonance (MR) images for many imaging-based studies. Most existing works focus on fusing the atlases from high-quality MR images. However, for low-quality diagnostic images (i.e., with high inter-slice thickness), the problem of atlas fusion has not been addressed yet. In this paper, we intend to fuse the brain atlas from the high-thickness diagnostic MR images that are prevalent for clinical routines. The main idea of our works is to extend the conventional groupwise registration by incorporating a novel super-resolution strategy. The contribution of the proposed super-resolution framework is two-fold. First, each high-thickness subject image is reconstructed to be isotropic by the patch-based sparsity learning. Then, the reconstructed isotropic image is enhanced for better quality through the random-forest-based regression model. In this way, the images obtained by the super-resolution strategy can be fused together by applying the groupwise registration method to construct the required atlas. Our experiments have shown that the proposed framework can effectively solve the problem of atlas fusion from the low-quality brain MR images.

Adaptive Intuitionistic Fuzzy Enhancement of Brain Tumor MR Images

NASA Astrophysics Data System (ADS)

Deng, He; Deng, Wankai; Sun, Xianping; Ye, Chaohui; Zhou, Xin

2016-10-01

Image enhancement techniques are able to improve the contrast and visual quality of magnetic resonance (MR) images. However, conventional methods cannot make up some deficiencies encountered by respective brain tumor MR imaging modes. In this paper, we propose an adaptive intuitionistic fuzzy sets-based scheme, called as AIFE, which takes information provided from different MR acquisitions and tries to enhance the normal and abnormal structural regions of the brain while displaying the enhanced results as a single image. The AIFE scheme firstly separates an input image into several sub images, then divides each sub image into object and background areas. After that, different novel fuzzification, hyperbolization and defuzzification operations are implemented on each object/background area, and finally an enhanced result is achieved via nonlinear fusion operators. The fuzzy implementations can be processed in parallel. Real data experiments demonstrate that the AIFE scheme is not only effectively useful to have information from images acquired with different MR sequences fused in a single image, but also has better enhancement performance when compared to conventional baseline algorithms. This indicates that the proposed AIFE scheme has potential for improving the detection and diagnosis of brain tumors.

Locally adaptive MR intensity models and MRF-based segmentation of multiple sclerosis lesions

NASA Astrophysics Data System (ADS)

Galimzianova, Alfiia; Lesjak, Žiga; Likar, Boštjan; Pernuš, Franjo; Špiclin, Žiga

2015-03-01

Neuroimaging biomarkers are an important paraclinical tool used to characterize a number of neurological diseases, however, their extraction requires accurate and reliable segmentation of normal and pathological brain structures. For MR images of healthy brains the intensity models of normal-appearing brain tissue (NABT) in combination with Markov random field (MRF) models are known to give reliable and smooth NABT segmentation. However, the presence of pathology, MR intensity bias and natural tissue-dependent intensity variability altogether represent difficult challenges for a reliable estimation of NABT intensity model based on MR images. In this paper, we propose a novel method for segmentation of normal and pathological structures in brain MR images of multiple sclerosis (MS) patients that is based on locally-adaptive NABT model, a robust method for the estimation of model parameters and a MRF-based segmentation framework. Experiments on multi-sequence brain MR images of 27 MS patients show that, compared to whole-brain model and compared to the widely used Expectation-Maximization Segmentation (EMS) method, the locally-adaptive NABT model increases the accuracy of MS lesion segmentation.

Hyperpolarized 13C pyruvate mouse brain metabolism with absorptive-mode EPSI at 1 T

NASA Astrophysics Data System (ADS)

Miloushev, Vesselin Z.; Di Gialleonardo, Valentina; Salamanca-Cardona, Lucia; Correa, Fabian; Granlund, Kristin L.; Keshari, Kayvan R.

2017-02-01

The expected signal in echo-planar spectroscopic imaging experiments was explicitly modeled jointly in spatial and spectral dimensions. Using this as a basis, absorptive-mode type detection can be achieved by appropriate choice of spectral delays and post-processing techniques. We discuss the effects of gradient imperfections and demonstrate the implementation of this sequence at low field (1.05 T), with application to hyperpolarized [1-13C] pyruvate imaging of the mouse brain. The sequence achieves sufficient signal-to-noise to monitor the conversion of hyperpolarized [1-13C] pyruvate to lactate in the mouse brain. Hyperpolarized pyruvate imaging of mouse brain metabolism using an absorptive-mode EPSI sequence can be applied to more sophisticated murine disease and treatment models. The simple modifications presented in this work, which permit absorptive-mode detection, are directly translatable to human clinical imaging and generate improved absorptive-mode spectra without the need for refocusing pulses.

Resting-state functional connectivity imaging of the mouse brain using photoacoustic tomography

NASA Astrophysics Data System (ADS)

Nasiriavanaki, Mohammadreza; Xia, Jun; Wan, Hanlin; Bauer, Adam Q.; Culver, Joseph P.; Wang, Lihong V.

2014-03-01

Resting-state functional connectivity (RSFC) imaging is an emerging neuroimaging approach that aims to identify spontaneous cerebral hemodynamic fluctuations and their associated functional connections. Clinical studies have demonstrated that RSFC is altered in brain disorders such as stroke, Alzheimer's, autism, and epilepsy. However, conventional neuroimaging modalities cannot easily be applied to mice, the most widely used model species for human brain disease studies. For instance, functional magnetic resonance imaging (fMRI) of mice requires a very high magnetic field to obtain a sufficient signal-to-noise ratio and spatial resolution. Functional connectivity mapping with optical intrinsic signal imaging (fcOIS) is an alternative method. Due to the diffusion of light in tissue, the spatial resolution of fcOIS is limited, and experiments have been performed using an exposed skull preparation. In this study, we show for the first time, the use of photoacoustic computed tomography (PACT) to noninvasively image resting-state functional connectivity in the mouse brain, with a large field of view and a high spatial resolution. Bilateral correlations were observed in eight regions, as well as several subregions. These findings agreed well with the Paxinos mouse brain atlas. This study showed that PACT is a promising, non-invasive modality for small-animal functional brain imaging.

Brain connectivity study of joint attention using frequency-domain optical imaging technique

NASA Astrophysics Data System (ADS)

Chaudhary, Ujwal; Zhu, Banghe; Godavarty, Anuradha

2010-02-01

Autism is a socio-communication brain development disorder. It is marked by degeneration in the ability to respond to joint attention skill task, from as early as 12 to 18 months of age. This trait is used to distinguish autistic from nonautistic populations. In this study, diffuse optical imaging is being used to study brain connectivity for the first time in response to joint attention experience in normal adults. The prefrontal region of the brain was non-invasively imaged using a frequency-domain based optical imager. The imaging studies were performed on 11 normal right-handed adults and optical measurements were acquired in response to joint-attention based video clips. While the intensity-based optical data provides information about the hemodynamic response of the underlying neural process, the time-dependent phase-based optical data has the potential to explicate the directional information on the activation of the brain. Thus brain connectivity studies are performed by computing covariance/correlations between spatial units using this frequency-domain based optical measurements. The preliminary results indicate that the extent of synchrony and directional variation in the pattern of activation varies in the left and right frontal cortex. The results have significant implication for research in neural pathways associated with autism that can be mapped using diffuse optical imaging tools in the future.

Automatic MRI 2D brain segmentation using graph searching technique.

PubMed

Pedoia, Valentina; Binaghi, Elisabetta

2013-09-01

Accurate and efficient segmentation of the whole brain in magnetic resonance (MR) images is a key task in many neuroscience and medical studies either because the whole brain is the final anatomical structure of interest or because the automatic extraction facilitates further analysis. The problem of segmenting brain MRI images has been extensively addressed by many researchers. Despite the relevant achievements obtained, automated segmentation of brain MRI imagery is still a challenging problem whose solution has to cope with critical aspects such as anatomical variability and pathological deformation. In the present paper, we describe and experimentally evaluate a method for segmenting brain from MRI images basing on two-dimensional graph searching principles for border detection. The segmentation of the whole brain over the entire volume is accomplished slice by slice, automatically detecting frames including eyes. The method is fully automatic and easily reproducible by computing the internal main parameters directly from the image data. The segmentation procedure is conceived as a tool of general applicability, although design requirements are especially commensurate with the accuracy required in clinical tasks such as surgical planning and post-surgical assessment. Several experiments were performed to assess the performance of the algorithm on a varied set of MRI images obtaining good results in terms of accuracy and stability. Copyright © 2012 John Wiley & Sons, Ltd.

Identifying Degenerative Brain Disease Using Rough Set Classifier Based on Wavelet Packet Method.

PubMed

Cheng, Ching-Hsue; Liu, Wei-Xiang

2018-05-28

Population aging has become a worldwide phenomenon, which causes many serious problems. The medical issues related to degenerative brain disease have gradually become a concern. Magnetic Resonance Imaging is one of the most advanced methods for medical imaging and is especially suitable for brain scans. From the literature, although the automatic segmentation method is less laborious and time-consuming, it is restricted in several specific types of images. In addition, hybrid techniques segmentation improves the shortcomings of the single segmentation method. Therefore, this study proposed a hybrid segmentation combined with rough set classifier and wavelet packet method to identify degenerative brain disease. The proposed method is a three-stage image process method to enhance accuracy of brain disease classification. In the first stage, this study used the proposed hybrid segmentation algorithms to segment the brain ROI (region of interest). In the second stage, wavelet packet was used to conduct the image decomposition and calculate the feature values. In the final stage, the rough set classifier was utilized to identify the degenerative brain disease. In verification and comparison, two experiments were employed to verify the effectiveness of the proposed method and compare with the TV-seg (total variation segmentation) algorithm, Discrete Cosine Transform, and the listing classifiers. Overall, the results indicated that the proposed method outperforms the listing methods.

Quantitative Machine Learning Analysis of Brain MRI Morphology throughout Aging.

PubMed

Shamir, Lior; Long, Joe

2016-01-01

While cognition is clearly affected by aging, it is unclear whether the process of brain aging is driven solely by accumulation of environmental damage, or involves biological pathways. We applied quantitative image analysis to profile the alteration of brain tissues during aging. A dataset of 463 brain MRI images taken from a cohort of 416 subjects was analyzed using a large set of low-level numerical image content descriptors computed from the entire brain MRI images. The correlation between the numerical image content descriptors and the age was computed, and the alterations of the brain tissues during aging were quantified and profiled using machine learning. The comprehensive set of global image content descriptors provides high Pearson correlation of ~0.9822 with the chronological age, indicating that the machine learning analysis of global features is sensitive to the age of the subjects. Profiling of the predicted age shows several periods of mild changes, separated by shorter periods of more rapid alterations. The periods with the most rapid changes were around the age of 55, and around the age of 65. The results show that the process of brain aging of is not linear, and exhibit short periods of rapid aging separated by periods of milder change. These results are in agreement with patterns observed in cognitive decline, mental health status, and general human aging, suggesting that brain aging might not be driven solely by accumulation of environmental damage. Code and data used in the experiments are publicly available.

Scatter Correction with Combined Single-Scatter Simulation and Monte Carlo Simulation Scaling Improved the Visual Artifacts and Quantification in 3-Dimensional Brain PET/CT Imaging with 15O-Gas Inhalation.

PubMed

Magota, Keiichi; Shiga, Tohru; Asano, Yukari; Shinyama, Daiki; Ye, Jinghan; Perkins, Amy E; Maniawski, Piotr J; Toyonaga, Takuya; Kobayashi, Kentaro; Hirata, Kenji; Katoh, Chietsugu; Hattori, Naoya; Tamaki, Nagara

2017-12-01

In 3-dimensional PET/CT imaging of the brain with 15 O-gas inhalation, high radioactivity in the face mask creates cold artifacts and affects the quantitative accuracy when scatter is corrected by conventional methods (e.g., single-scatter simulation [SSS] with tail-fitting scaling [TFS-SSS]). Here we examined the validity of a newly developed scatter-correction method that combines SSS with a scaling factor calculated by Monte Carlo simulation (MCS-SSS). Methods: We performed phantom experiments and patient studies. In the phantom experiments, a plastic bottle simulating a face mask was attached to a cylindric phantom simulating the brain. The cylindric phantom was filled with 18 F-FDG solution (3.8-7.0 kBq/mL). The bottle was filled with nonradioactive air or various levels of 18 F-FDG (0-170 kBq/mL). Images were corrected either by TFS-SSS or MCS-SSS using the CT data of the bottle filled with nonradioactive air. We compared the image activity concentration in the cylindric phantom with the true activity concentration. We also performed 15 O-gas brain PET based on the steady-state method on patients with cerebrovascular disease to obtain quantitative images of cerebral blood flow and oxygen metabolism. Results: In the phantom experiments, a cold artifact was observed immediately next to the bottle on TFS-SSS images, where the image activity concentrations in the cylindric phantom were underestimated by 18%, 36%, and 70% at the bottle radioactivity levels of 2.4, 5.1, and 9.7 kBq/mL, respectively. At higher bottle radioactivity, the image activity concentrations in the cylindric phantom were greater than 98% underestimated. For the MCS-SSS, in contrast, the error was within 5% at each bottle radioactivity level, although the image generated slight high-activity artifacts around the bottle when the bottle contained significantly high radioactivity. In the patient imaging with 15 O 2 and C 15 O 2 inhalation, cold artifacts were observed on TFS-SSS images, whereas no artifacts were observed on any of the MCS-SSS images. Conclusion: MCS-SSS accurately corrected the scatters in 15 O-gas brain PET when the 3-dimensional acquisition mode was used, preventing the generation of cold artifacts, which were observed immediately next to a face mask on TFS-SSS images. The MCS-SSS method will contribute to accurate quantitative assessments. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

Multi circular-cavity surface coil for magnetic resonance imaging of monkey's brain at 4 Tesla

NASA Astrophysics Data System (ADS)

Osorio, A. I.; Solis-Najera, S. E.; Vázquez, F.; Wang, R. L.; Tomasi, D.; Rodriguez, A. O.

2014-11-01

Animal models in medical research has been used to study humans diseases for several decades. The use of different imaging techniques together with different animal models offers a great advantage due to the possibility to study some human pathologies without the necessity of chirurgical intervention. The employ of magnetic resonance imaging for the acquisition of anatomical and functional images is an excellent tool because its noninvasive nature. Dedicated coils to perform magnetic resonance imaging experiments are obligatory due to the improvement on the signal-to-noise ratio and reduced specific absorption ratio. A specifically designed surface coil for magnetic resonance imaging of monkey's brain is proposed based on the multi circular-slot coil. Numerical simulations of the magnetic and electric fields were also performed using the Finite Integration Method to solve Maxwell's equations for this particular coil design and, to study the behavior of various vector magnetic field configurations and specific absorption ratio. Monkey's brain images were then acquired with a research-dedicated magnetic resonance imaging system at 4T, to evaluate the anatomical images with conventional imaging sequences. This coil showed good quality images of a monkey's brain and full compatibility with standard pulse sequences implemented in research-dedicated imager.

Decreased Peripheral and Central Responses to Acupuncture Stimulation following Modification of Body Ownership

PubMed Central

Chae, Younbyoung; Lee, In-Seon; Jung, Won-Mo; Chang, Dong-Seon; Napadow, Vitaly; Lee, Hyejung; Park, Hi-Joon; Wallraven, Christian

2014-01-01

Acupuncture stimulation increases local blood flow around the site of stimulation and induces signal changes in brain regions related to the body matrix. The rubber hand illusion (RHI) is an experimental paradigm that manipulates important aspects of bodily self-awareness. The present study aimed to investigate how modifications of body ownership using the RHI affect local blood flow and cerebral responses during acupuncture needle stimulation. During the RHI, acupuncture needle stimulation was applied to the real left hand while measuring blood microcirculation with a LASER Doppler imager (Experiment 1, N = 28) and concurrent brain signal changes using functional magnetic resonance imaging (fMRI; Experiment 2, N = 17). When the body ownership of participants was altered by the RHI, acupuncture stimulation resulted in a significantly lower increase in local blood flow (Experiment 1), and significantly less brain activation was detected in the right insula (Experiment 2). This study found changes in both local blood flow and brain responses during acupuncture needle stimulation following modification of body ownership. These findings suggest that physiological responses during acupuncture stimulation can be influenced by the modification of body ownership. PMID:25285620

Reduction in radiation dose with reconstruction technique in the brain perfusion CT

NASA Astrophysics Data System (ADS)

Kim, H. J.; Lee, H. K.; Song, H.; Ju, M. S.; Dong, K. R.; Chung, W. K.; Cho, M. S.; Cho, J. H.

2011-12-01

The principal objective of this study was to verify the utility of the reconstruction imaging technique in the brain perfusion computed tomography (PCT) scan by assessing reductions in the radiation dose and analyzing the generated images. The setting used for image acquisition had a detector coverage of 40 mm, a helical thickness of 0.625 mm, a helical shuttle mode scan type and a rotation time of 0.5 s as the image parameters used for the brain PCT scan. Additionally, a phantom experiment and an animal experiment were carried out. In the phantom and animal experiments, noise was measured in the scanning with the tube voltage fixed at 80 kVp (kilovolt peak) and the level of the adaptive statistical iterative reconstruction (ASIR) was changed from 0% to 100% at 10% intervals. The standard deviation of the CT coefficient was measured three times to calculate the mean value. In the phantom and animal experiments, the absorbed dose was measured 10 times under the same conditions as the ones for noise measurement before the mean value was calculated. In the animal experiment, pencil-type and CT-dedicated ionization chambers were inserted into the central portion of pig heads for measurement. In the phantom study, as the level of the ASIR changed from 0% to 100% under identical scanning conditions, the noise value and dose were proportionally reduced. In our animal experiment, the noise value was lowest when the ASIR level was 50%, unlike in the phantom study. The dose was reduced as in the phantom study.

Image guided constitutive modeling of the silicone brain phantom

NASA Astrophysics Data System (ADS)

Puzrin, Alexander; Skrinjar, Oskar; Ozan, Cem; Kim, Sihyun; Mukundan, Srinivasan

2005-04-01

The goal of this work is to develop reliable constitutive models of the mechanical behavior of the in-vivo human brain tissue for applications in neurosurgery. We propose to define the mechanical properties of the brain tissue in-vivo, by taking the global MR or CT images of a brain response to ventriculostomy - the relief of the elevated intracranial pressure. 3D image analysis translates these images into displacement fields, which by using inverse analysis allow for the constitutive models of the brain tissue to be developed. We term this approach Image Guided Constitutive Modeling (IGCM). The presented paper demonstrates performance of the IGCM in the controlled environment: on the silicone brain phantoms closely simulating the in-vivo brain geometry, mechanical properties and boundary conditions. The phantom of the left hemisphere of human brain was cast using silicon gel. An inflatable rubber membrane was placed inside the phantom to model the lateral ventricle. The experiments were carried out in a specially designed setup in a CT scanner with submillimeter isotropic voxels. The non-communicative hydrocephalus and ventriculostomy were simulated by consequently inflating and deflating the internal rubber membrane. The obtained images were analyzed to derive displacement fields, meshed, and incorporated into ABAQUS. The subsequent Inverse Finite Element Analysis (based on Levenberg-Marquardt algorithm) allowed for optimization of the parameters of the Mooney-Rivlin non-linear elastic model for the phantom material. The calculated mechanical properties were consistent with those obtained from the element tests, providing justification for the future application of the IGCM to in-vivo brain tissue.

Early parental care is important for hippocampal maturation: evidence from brain morphology in humans.

PubMed

Rao, Hengyi; Betancourt, Laura; Giannetta, Joan M; Brodsky, Nancy L; Korczykowski, Marc; Avants, Brian B; Gee, James C; Wang, Jiongjiong; Hurt, Hallam; Detre, John A; Farah, Martha J

2010-01-01

The effects of early life experience on later brain structure and function have been studied extensively in animals, yet the relationship between childhood experience and normal brain development in humans remains largely unknown. Using a unique longitudinal data set including ecologically valid in-home measures of early experience during childhood (at age 4 and 8 years) and high-resolution structural brain imaging during adolescence (mean age 14 years), we examined the effects on later brain morphology of two dimensions of early experience: parental nurturance and environmental stimulation. Parental nurturance at age 4 predicts the volume of the left hippocampus in adolescence, with better nurturance associated with smaller hippocampal volume. In contrast, environmental stimulation did not correlate with hippocampal volume. Moreover, the association between hippocampal volume and parental nurturance disappears at age 8, supporting the existence of a sensitive developmental period for brain maturation. These findings indicate that variation in normal childhood experience is associated with differences in brain morphology, and hippocampal volume is specifically associated with early parental nurturance. Our results provide neuroimaging evidence supporting the important role of warm parental care during early childhood for brain maturation.

Blood-brain barrier dysfunction in brain diseases: clinical experience.

PubMed

Schoknecht, Karl; Shalev, Hadar

2012-11-01

The blood-brain barrier, a unique feature of the cerebral vasculature, is gaining attention as a feature in common neurologic disorders including stroke, traumatic brain injury, epilepsy, and schizophrenia. Although acute blood-brain barrier dysfunction can induce cerebral edema, seizures, or neuropsychiatric symptoms, epileptogenesis and cognitive decline are among the chronic effects. The mechanisms underlying blood-brain barrier dysfunction are diverse and may range from physical endothelial damage in traumatic brain injury to degradation of extracellular matrix proteins via matrix metalloproteinases as part of an inflammatory response. Clinically, blood-brain barrier dysfunction is often detected using contrast-enhanced imaging. However, these techniques do not give any insights into the underlying mechanism. Elucidating the specific pathways of blood-brain barrier dysfunction at different time points and in different brain diseases using novel imaging techniques promises a more accurate blood-brain barrier terminology as well as new treatment options and personalized treatment. Wiley Periodicals, Inc. © 2012 International League Against Epilepsy.

Hierarchical Neural Representation of Dreamed Objects Revealed by Brain Decoding with Deep Neural Network Features.

PubMed

Horikawa, Tomoyasu; Kamitani, Yukiyasu

2017-01-01

Dreaming is generally thought to be generated by spontaneous brain activity during sleep with patterns common to waking experience. This view is supported by a recent study demonstrating that dreamed objects can be predicted from brain activity during sleep using statistical decoders trained with stimulus-induced brain activity. However, it remains unclear whether and how visual image features associated with dreamed objects are represented in the brain. In this study, we used a deep neural network (DNN) model for object recognition as a proxy for hierarchical visual feature representation, and DNN features for dreamed objects were analyzed with brain decoding of fMRI data collected during dreaming. The decoders were first trained with stimulus-induced brain activity labeled with the feature values of the stimulus image from multiple DNN layers. The decoders were then used to decode DNN features from the dream fMRI data, and the decoded features were compared with the averaged features of each object category calculated from a large-scale image database. We found that the feature values decoded from the dream fMRI data positively correlated with those associated with dreamed object categories at mid- to high-level DNN layers. Using the decoded features, the dreamed object category could be identified at above-chance levels by matching them to the averaged features for candidate categories. The results suggest that dreaming recruits hierarchical visual feature representations associated with objects, which may support phenomenal aspects of dream experience.

Transferring cognitive tasks between brain imaging modalities: implications for task design and results interpretation in FMRI studies.

PubMed

Warbrick, Tracy; Reske, Martina; Shah, N Jon

2014-09-22

As cognitive neuroscience methods develop, established experimental tasks are used with emerging brain imaging modalities. Here transferring a paradigm (the visual oddball task) with a long history of behavioral and electroencephalography (EEG) experiments to a functional magnetic resonance imaging (fMRI) experiment is considered. The aims of this paper are to briefly describe fMRI and when its use is appropriate in cognitive neuroscience; illustrate how task design can influence the results of an fMRI experiment, particularly when that task is borrowed from another imaging modality; explain the practical aspects of performing an fMRI experiment. It is demonstrated that manipulating the task demands in the visual oddball task results in different patterns of blood oxygen level dependent (BOLD) activation. The nature of the fMRI BOLD measure means that many brain regions are found to be active in a particular task. Determining the functions of these areas of activation is very much dependent on task design and analysis. The complex nature of many fMRI tasks means that the details of the task and its requirements need careful consideration when interpreting data. The data show that this is particularly important in those tasks relying on a motor response as well as cognitive elements and that covert and overt responses should be considered where possible. Furthermore, the data show that transferring an EEG paradigm to an fMRI experiment needs careful consideration and it cannot be assumed that the same paradigm will work equally well across imaging modalities. It is therefore recommended that the design of an fMRI study is pilot tested behaviorally to establish the effects of interest and then pilot tested in the fMRI environment to ensure appropriate design, implementation and analysis for the effects of interest.

Real time in vivo imaging and measurement of serine protease activity in the mouse hippocampus using a dedicated complementary metal-oxide semiconductor imaging device.

PubMed

Ng, David C; Tamura, Hideki; Tokuda, Takashi; Yamamoto, Akio; Matsuo, Masamichi; Nunoshita, Masahiro; Ishikawa, Yasuyuki; Shiosaka, Sadao; Ohta, Jun

2006-09-30

The aim of the present study is to demonstrate the application of complementary metal-oxide semiconductor (CMOS) imaging technology for studying the mouse brain. By using a dedicated CMOS image sensor, we have successfully imaged and measured brain serine protease activity in vivo, in real-time, and for an extended period of time. We have developed a biofluorescence imaging device by packaging the CMOS image sensor which enabled on-chip imaging configuration. In this configuration, no optics are required whereby an excitation filter is applied onto the sensor to replace the filter cube block found in conventional fluorescence microscopes. The fully packaged device measures 350 microm thick x 2.7 mm wide, consists of an array of 176 x 144 pixels, and is small enough for measurement inside a single hemisphere of the mouse brain, while still providing sufficient imaging resolution. In the experiment, intraperitoneally injected kainic acid induced upregulation of serine protease activity in the brain. These events were captured in real time by imaging and measuring the fluorescence from a fluorogenic substrate that detected this activity. The entire device, which weighs less than 1% of the body weight of the mouse, holds promise for studying freely moving animals.

Dreaming and the brain: from phenomenology to neurophysiology

PubMed Central

Nir, Yuval; Tononi, Giulio

2009-01-01

Dreams are a most remarkable experiment in psychology and neuroscience, conducted every night in every sleeping person. They show that our brain, disconnected from the environment, can generate by itself an entire world of conscious experiences. Content analysis and developmental studies have furthered our understanding of dream phenomenology. In parallel, brain lesion studies, functional imaging, and neurophysiology have advanced our knowledge of the neural basis of dreaming. It is now possible to start integrating these two strands of research in order to address some fundamental questions that dreams pose for cognitive neuroscience: how conscious experiences in sleep relate to underlying brain activity; why the dreamer is largely disconnected from the environment; and whether dreaming is more closely related to mental imagery or to perception. PMID:20079677

Dreaming and the brain: from phenomenology to neurophysiology.

PubMed

Nir, Yuval; Tononi, Giulio

2010-02-01

Dreams are a remarkable experiment in psychology and neuroscience, conducted every night in every sleeping person. They show that the human brain, disconnected from the environment, can generate an entire world of conscious experiences by itself. Content analysis and developmental studies have promoted understanding of dream phenomenology. In parallel, brain lesion studies, functional imaging and neurophysiology have advanced current knowledge of the neural basis of dreaming. It is now possible to start integrating these two strands of research to address fundamental questions that dreams pose for cognitive neuroscience: how conscious experiences in sleep relate to underlying brain activity; why the dreamer is largely disconnected from the environment; and whether dreaming is more closely related to mental imagery or to perception. Published by Elsevier Ltd.

Towards real-time diffuse optical tomography for imaging brain functions cooperated with Kalman estimator

NASA Astrophysics Data System (ADS)

Wang, Bingyuan; Zhang, Yao; Liu, Dongyuan; Ding, Xuemei; Dan, Mai; Pan, Tiantian; Wang, Yihan; Li, Jiao; Zhou, Zhongxing; Zhang, Limin; Zhao, Huijuan; Gao, Feng

2018-02-01

Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging method to monitor the cerebral hemodynamic through the optical changes measured at the scalp surface. It has played a more and more important role in psychology and medical imaging communities. Real-time imaging of brain function using NIRS makes it possible to explore some sophisticated human brain functions unexplored before. Kalman estimator has been frequently used in combination with modified Beer-Lamber Law (MBLL) based optical topology (OT), for real-time brain function imaging. However, the spatial resolution of the OT is low, hampering the application of OT in exploring some complicated brain functions. In this paper, we develop a real-time imaging method combining diffuse optical tomography (DOT) and Kalman estimator, much improving the spatial resolution. Instead of only presenting one spatially distributed image indicating the changes of the absorption coefficients at each time point during the recording process, one real-time updated image using the Kalman estimator is provided. Its each voxel represents the amplitude of the hemodynamic response function (HRF) associated with this voxel. We evaluate this method using some simulation experiments, demonstrating that this method can obtain more reliable spatial resolution images. Furthermore, a statistical analysis is also conducted to help to decide whether a voxel in the field of view is activated or not.

Functional brain imaging and bioacoustics in the Bottlenose dolphins, Tursiops truncatus

NASA Astrophysics Data System (ADS)

Ridgway, Sam; Finneran, James; Carder, Donald; van Bonn, William; Smith, Cynthia; Houser, Dorian; Mattrey, Robert; Hoh, Carl

2003-10-01

The dolphin brain is the central processing computer for a complex and effective underwater echolocation and communication system. Until now, it has not been possible to study or diagnose disorders of the dolphin brain employing modern functional imaging methods like those used in human medicine. Our most recent studies employ established methods such as behavioral tasks, physiological observations, and computed tomography (CT) and, for the first time, single photon emission computed tomography (SPECT), and positron emission tomography (PET). Trained dolphins slide out of their enclosure on to a mat and are transported by trainers and veterinarians to the laboratory for injection of a ligand. Following ligand injection, brief experiments include trained vocal responses to acoustic, visual, or tactile stimuli. We have used the ligand technetium (Tc-99m) biscisate (Neurolite) to image circulatory flow by SPECT. Fluro-deoxy-d-glucose (18-F-FDG) has been employed to image brain metabolism with PET. Veterinarians carefully monitored dolphins during and after the procedure. Through these methods, we have demonstrated that functional imaging can be employed safely and productively with dolphins to obtain valuable information on brain structure and function for medical and research purposes. Hemispheric differences and variations in flow and metabolism in different brain areas will be shown.

Brain MRI Tumor Detection using Active Contour Model and Local Image Fitting Energy

NASA Astrophysics Data System (ADS)

Nabizadeh, Nooshin; John, Nigel

2014-03-01

Automatic abnormality detection in Magnetic Resonance Imaging (MRI) is an important issue in many diagnostic and therapeutic applications. Here an automatic brain tumor detection method is introduced that uses T1-weighted images and K. Zhang et. al.'s active contour model driven by local image fitting (LIF) energy. Local image fitting energy obtains the local image information, which enables the algorithm to segment images with intensity inhomogeneities. Advantage of this method is that the LIF energy functional has less computational complexity than the local binary fitting (LBF) energy functional; moreover, it maintains the sub-pixel accuracy and boundary regularization properties. In Zhang's algorithm, a new level set method based on Gaussian filtering is used to implement the variational formulation, which is not only vigorous to prevent the energy functional from being trapped into local minimum, but also effective in keeping the level set function regular. Experiments show that the proposed method achieves high accuracy brain tumor segmentation results.

The experience of beauty derived from sorrow

PubMed Central

2017-01-01

Abstract We studied the neural mechanisms that are engaged during the experience of beauty derived from sorrow and from joy, two experiences that share a common denominator (beauty) but are linked to opposite emotional valences. Twenty subjects viewed and rerated, in a functional magnetic resonance imaging scanner, 120 images which each had classified into the following four categories: beautiful and sad; beautiful and joyful; neutral; ugly. The medial orbito‐frontal cortex (mOFC) was active during the experience of both types of beauty. Otherwise, the two experiences engaged different parts of the brain: joyful beauty engaged areas linked to positive emotions while sorrowful beauty engaged areas linked to negative experiences. Separate regions of the cerebellum were engaged during experience of the two conditions. A functional connectivity analysis indicated that the activity within the mOFC was modulated by the supplementary motor area/middle cingulate cortex, known to be engaged during empathetic experiences provoked by other peoples' sadness. Hum Brain Mapp 38:4185–4200, 2017. © 2017 Wiley Periodicals, Inc. PMID:28544456

Imaging Nicotine in Rat Brain Tissue by Use of Nanospray Desorption Electrospray Ionization Mass Spectrometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lanekoff, Ingela T.; Thomas, Mathew; Carson, James P.

Imaging mass spectrometry offers simultaneous detection of drugs, drug metabolites and endogenous substances in a single experiment. This is important when evaluating effects of a drug on a complex organ system such as the brain, where there is a need to understand how regional drug distribution impacts function. Nicotine is an addictive drug and its action in the brain is of high interest. Here we use nanospray desorption electrospray ionization, nano-DESI, imaging to discover the localization of nicotine in rat brain tissue after in vivo administration of nicotine. Nano-DESI is a new ambient technique that enables spatially-resolved analysis of tissuemore » samples without special sample pretreatment. We demonstrate high sensitivity of nano-DESI imaging that enables detection of only 0.7 fmole nicotine per pixel in the complex brain matrix. Furthermore, by adding deuterated nicotine to the solvent, we examined how matrix effects, ion suppression, and normalization affect the observed nicotine distribution. Finally, we provide preliminary results suggesting that nicotine localizes to the hippocampal substructure called dentate gyrus.« less

In vivo imaging of scattering and absorption properties of exposed brain using a digital red-green-blue camera

NASA Astrophysics Data System (ADS)

Nishidate, Izumi; Yoshida, Keiichiro; Kawauchi, Satoko; Sato, Shunichi; Sato, Manabu

2014-03-01

We investigate a method to estimate the spectral images of reduced scattering coefficients and the absorption coefficients of in vivo exposed brain tissues in the range from visible to near-infrared wavelength (500-760 nm) based on diffuse reflectance spectroscopy using a digital RGB camera. In the proposed method, the multi-spectral reflectance images of in vivo exposed brain are reconstructed from the digital red, green blue images using the Wiener estimation algorithm. The Monte Carlo simulation-based multiple regression analysis for the absorbance spectra is then used to specify the absorption and scattering parameters of brain tissue. In this analysis, the concentration of oxygenated hemoglobin and that of deoxygenated hemoglobin are estimated as the absorption parameters whereas the scattering amplitude a and the scattering power b in the expression of μs'=aλ-b as the scattering parameters, respectively. The spectra of absorption and reduced scattering coefficients are reconstructed from the absorption and scattering parameters, and finally, the spectral images of absorption and reduced scattering coefficients are estimated. The estimated images of absorption coefficients were dominated by the spectral characteristics of hemoglobin. The estimated spectral images of reduced scattering coefficients showed a broad scattering spectrum, exhibiting larger magnitude at shorter wavelengths, corresponding to the typical spectrum of brain tissue published in the literature. In vivo experiments with exposed brain of rats during CSD confirmed the possibility of the method to evaluate both hemodynamics and changes in tissue morphology due to electrical depolarization.

A critical review of the neuroimaging literature on synesthesia

PubMed Central

Hupé, Jean-Michel; Dojat, Michel

2015-01-01

Synesthesia refers to additional sensations experienced by some people for specific stimulations, such as the systematic arbitrary association of colors to letters for the most studied type. Here, we review all the studies (based mostly on functional and structural magnetic resonance imaging) that have searched for the neural correlates of this subjective experience, as well as structural differences related to synesthesia. Most differences claimed for synesthetes are unsupported, due mainly to low statistical power, statistical errors, and methodological limitations. Our critical review therefore casts some doubts on whether any neural correlate of the synesthetic experience has been established yet. Rather than being a neurological condition (i.e., a structural or functional brain anomaly), synesthesia could be reconsidered as a special kind of childhood memory, whose signature in the brain may be out of reach with present brain imaging techniques. PMID:25873873

A novel approach to segmentation and measurement of medical image using level set methods.

PubMed

Chen, Yao-Tien

2017-06-01

The study proposes a novel approach for segmentation and visualization plus value-added surface area and volume measurements for brain medical image analysis. The proposed method contains edge detection and Bayesian based level set segmentation, surface and volume rendering, and surface area and volume measurements for 3D objects of interest (i.e., brain tumor, brain tissue, or whole brain). Two extensions based on edge detection and Bayesian level set are first used to segment 3D objects. Ray casting and a modified marching cubes algorithm are then adopted to facilitate volume and surface visualization of medical-image dataset. To provide physicians with more useful information for diagnosis, the surface area and volume of an examined 3D object are calculated by the techniques of linear algebra and surface integration. Experiment results are finally reported in terms of 3D object extraction, surface and volume rendering, and surface area and volume measurements for medical image analysis. Copyright © 2017 Elsevier Inc. All rights reserved.

A highly accurate symmetric optical flow based high-dimensional nonlinear spatial normalization of brain images.

PubMed

Wen, Ying; Hou, Lili; He, Lianghua; Peterson, Bradley S; Xu, Dongrong

2015-05-01

Spatial normalization plays a key role in voxel-based analyses of brain images. We propose a highly accurate algorithm for high-dimensional spatial normalization of brain images based on the technique of symmetric optical flow. We first construct a three dimension optical model with the consistency assumption of intensity and consistency of the gradient of intensity under a constraint of discontinuity-preserving spatio-temporal smoothness. Then, an efficient inverse consistency optical flow is proposed with aims of higher registration accuracy, where the flow is naturally symmetric. By employing a hierarchical strategy ranging from coarse to fine scales of resolution and a method of Euler-Lagrange numerical analysis, our algorithm is capable of registering brain images data. Experiments using both simulated and real datasets demonstrated that the accuracy of our algorithm is not only better than that of those traditional optical flow algorithms, but also comparable to other registration methods used extensively in the medical imaging community. Moreover, our registration algorithm is fully automated, requiring a very limited number of parameters and no manual intervention. Copyright © 2015 Elsevier Inc. All rights reserved.

Automated brain tumor segmentation using spatial accuracy-weighted hidden Markov Random Field.

PubMed

Nie, Jingxin; Xue, Zhong; Liu, Tianming; Young, Geoffrey S; Setayesh, Kian; Guo, Lei; Wong, Stephen T C

2009-09-01

A variety of algorithms have been proposed for brain tumor segmentation from multi-channel sequences, however, most of them require isotropic or pseudo-isotropic resolution of the MR images. Although co-registration and interpolation of low-resolution sequences, such as T2-weighted images, onto the space of the high-resolution image, such as T1-weighted image, can be performed prior to the segmentation, the results are usually limited by partial volume effects due to interpolation of low-resolution images. To improve the quality of tumor segmentation in clinical applications where low-resolution sequences are commonly used together with high-resolution images, we propose the algorithm based on Spatial accuracy-weighted Hidden Markov random field and Expectation maximization (SHE) approach for both automated tumor and enhanced-tumor segmentation. SHE incorporates the spatial interpolation accuracy of low-resolution images into the optimization procedure of the Hidden Markov Random Field (HMRF) to segment tumor using multi-channel MR images with different resolutions, e.g., high-resolution T1-weighted and low-resolution T2-weighted images. In experiments, we evaluated this algorithm using a set of simulated multi-channel brain MR images with known ground-truth tissue segmentation and also applied it to a dataset of MR images obtained during clinical trials of brain tumor chemotherapy. The results show that more accurate tumor segmentation results can be obtained by comparing with conventional multi-channel segmentation algorithms.

Reading skill and structural brain development

PubMed Central

Houston, S.M.; Lebel, C.; Katzir, T.; Manis, F.R.; Kan, E.; Rodriguez, G.R.; Sowell, E.R.

2014-01-01

Reading is a learned skill that is likely influenced by both brain maturation and experience. Functional imaging studies have identified brain regions important for skilled reading, but the structural brain changes that co-occur with reading acquisition remain largely unknown. We investigated maturational volume changes in brain reading regions and their association with performance on reading measures. Sixteen typically developing children (5-15 years old, 8 male, mean age of sample=10.06 ±3.29) received two magnetic resonance imaging (MRI) scans, (mean inter-scan interval =2.19 years), and were administered a battery of cognitive measures. Volume changes between time points in five bilateral cortical regions of interest were measured, and assessed for relationships to three measures of reading. Better baseline performances on measures of word reading, fluency and rapid naming, independent of age and total cortical gray matter volume change, were associated with volume decrease in the left inferior parietal cortex. Better baseline performance on a rapid naming measure was associated with volume decrease in the left inferior frontal region. These results suggest that children who are better readers, and who perhaps read more than less skilled readers, exhibit different development trajectories in brain reading regions. Understanding relationships between reading performance, reading experience and brain maturation trajectories may help with the development and evaluation of targeted interventions. PMID:24407200

In vitro and in vivo studies on the transport of PEGylated silica nanoparticles across the blood-brain barrier.

PubMed

Liu, Dan; Lin, Bingqian; Shao, Wei; Zhu, Zhi; Ji, Tianhai; Yang, Chaoyong

2014-02-12

Transport of PEGylated silica nanoparticles (PSiNPs) with diameters of 100, 50, and 25 nm across the blood-brain barrier (BBB) was evaluated using an in vitro BBB model based on mouse cerebral endothelial cells (bEnd.3) cultured on transwell inserts within a chamber. In vivo animal experiments were further performed by noninvasive in vivo imaging and ex vivo optical imaging after injection via carotid artery. Confocal fluorescence studies were carried out to evaluate the uptake of PSiNPs by brain endothelial cells. The results showed that PSiNPs can traverse the BBB in vitro and in vivo. The transport efficiency of PSiNPs across BBB was found to be size-dependent, with increased particle size resulting in decreased efficiency. This work points to the potential application of small sized silica nanoparticles in brain imaging or drug delivery.

Balanced steady state free precession for arterial spin labeling MRI: Initial experience for blood flow mapping in human brain, retina, and kidney.

PubMed

Park, Sung-Hong; Wang, Danny J J; Duong, Timothy Q

2013-09-01

We implemented pseudo-continuous ASL (pCASL) with 2D and 3D balanced steady state free precession (bSSFP) readout for mapping blood flow in the human brain, retina, and kidney, free of distortion and signal dropout, which are typically observed in the most commonly used echo-planar imaging acquisition. High resolution functional brain imaging in the human visual cortex was feasible with 3D bSSFP pCASL. Blood flow of the human retina could be imaged with pCASL and bSSFP in conjunction with a phase cycling approach to suppress the banding artifacts associated with bSSFP. Furthermore, bSSFP based pCASL enabled us to map renal blood flow within a single breath hold. Control and test-retest experiments suggested that the measured blood flow values in retina and kidney were reliable. Because there is no specific imaging tool for mapping human retina blood flow and the standard contrast agent technique for mapping renal blood flow can cause problems for patients with kidney dysfunction, bSSFP based pCASL may provide a useful tool for the diagnosis of retinal and renal diseases and can complement existing imaging techniques. Copyright © 2013 Elsevier Inc. All rights reserved.

Capturing intraoperative deformations: research experience at Brigham and Women's Hospital.

PubMed

Warfield, Simon K; Haker, Steven J; Talos, Ion-Florin; Kemper, Corey A; Weisenfeld, Neil; Mewes, Andrea U J; Goldberg-Zimring, Daniel; Zou, Kelly H; Westin, Carl-Fredrik; Wells, William M; Tempany, Clare M C; Golby, Alexandra; Black, Peter M; Jolesz, Ferenc A; Kikinis, Ron

2005-04-01

During neurosurgical procedures the objective of the neurosurgeon is to achieve the resection of as much diseased tissue as possible while achieving the preservation of healthy brain tissue. The restricted capacity of the conventional operating room to enable the surgeon to visualize critical healthy brain structures and tumor margin has lead, over the past decade, to the development of sophisticated intraoperative imaging techniques to enhance visualization. However, both rigid motion due to patient placement and nonrigid deformations occurring as a consequence of the surgical intervention disrupt the correspondence between preoperative data used to plan surgery and the intraoperative configuration of the patient's brain. Similar challenges are faced in other interventional therapies, such as in cryoablation of the liver, or biopsy of the prostate. We have developed algorithms to model the motion of key anatomical structures and system implementations that enable us to estimate the deformation of the critical anatomy from sequences of volumetric images and to prepare updated fused visualizations of preoperative and intraoperative images at a rate compatible with surgical decision making. This paper reviews the experience at Brigham and Women's Hospital through the process of developing and applying novel algorithms for capturing intraoperative deformations in support of image guided therapy.

Dual-slit confocal light sheet microscopy for in vivo whole-brain imaging of zebrafish

PubMed Central

Yang, Zhe; Mei, Li; Xia, Fei; Luo, Qingming; Fu, Ling; Gong, Hui

2015-01-01

In vivo functional imaging at single-neuron resolution is an important approach to visualize biological processes in neuroscience. Light sheet microscopy (LSM) is a cutting edge in vivo imaging technique that provides micron-scale spatial resolution at high frame rate. Due to the scattering and absorption of tissue, however, conventional LSM is inadequate to resolve cells because of the attenuated signal to noise ratio (SNR). Using dual-beam illumination and confocal dual-slit detection, here a dual-slit confocal LSM is demonstrated to obtain the SNR enhanced images with frame rate twice as high as line confocal LSM method. Through theoretical calculations and experiments, the correlation between the slit’s width and SNR was determined to optimize the image quality. In vivo whole brain structural imaging stacks and the functional imaging sequences of single slice were obtained for analysis of calcium activities at single-cell resolution. A two-fold increase in imaging speed of conventional confocal LSM makes it possible to capture the sequence of the neurons’ activities and help reveal the potential functional connections in the whole zebrafish’s brain. PMID:26137381

The smartphone brain scanner: a portable real-time neuroimaging system.

PubMed

Stopczynski, Arkadiusz; Stahlhut, Carsten; Larsen, Jakob Eg; Petersen, Michael Kai; Hansen, Lars Kai

2014-01-01

Combining low-cost wireless EEG sensors with smartphones offers novel opportunities for mobile brain imaging in an everyday context. Here we present the technical details and validation of a framework for building multi-platform, portable EEG applications with real-time 3D source reconstruction. The system--Smartphone Brain Scanner--combines an off-the-shelf neuroheadset or EEG cap with a smartphone or tablet, and as such represents the first fully portable system for real-time 3D EEG imaging. We discuss the benefits and challenges, including technical limitations as well as details of real-time reconstruction of 3D images of brain activity. We present examples of brain activity captured in a simple experiment involving imagined finger tapping, which shows that the acquired signal in a relevant brain region is similar to that obtained with standard EEG lab equipment. Although the quality of the signal in a mobile solution using an off-the-shelf consumer neuroheadset is lower than the signal obtained using high-density standard EEG equipment, we propose mobile application development may offset the disadvantages and provide completely new opportunities for neuroimaging in natural settings.

High slew-rate head-only gradient for improving distortion in echo planar imaging: Preliminary experience.

PubMed

Tan, Ek T; Lee, Seung-Kyun; Weavers, Paul T; Graziani, Dominic; Piel, Joseph E; Shu, Yunhong; Huston, John; Bernstein, Matt A; Foo, Thomas K F

2016-09-01

To investigate the effects on echo planar imaging (EPI) distortion of using high gradient slew rates (SR) of up to 700 T/m/s for in vivo human brain imaging, with a dedicated, head-only gradient coil. Simulation studies were first performed to determine the expected echo spacing and distortion reduction in EPI. A head gradient of 42-cm inner diameter and with asymmetric transverse coils was then installed in a whole-body, conventional 3T magnetic resonance imaging (MRI) system. Human subject imaging was performed on five subjects to determine the effects of EPI on echo spacing and signal dropout at various gradient slew rates. The feasibility of whole-brain imaging at 1.5 mm-isotropic spatial resolution was demonstrated with gradient-echo and spin-echo diffusion-weighted EPI. As compared to a whole-body gradient coil, the EPI echo spacing in the head-only gradient coil was reduced by 48%. Simulation and in vivo results, respectively, showed up to 25-26% and 19% improvement in signal dropout. Whole-brain imaging with EPI at 1.5 mm spatial resolution provided good whole-brain coverage, spatial linearity, and low spatial distortion effects. Our results of human brain imaging with EPI using the compact head gradient coil at slew rates higher than in conventional whole-body MR systems demonstrate substantially improved image distortion, and point to a potential for benefits to non-EPI pulse sequences. J. Magn. Reson. Imaging 2016;44:653-664. © 2016 International Society for Magnetic Resonance in Medicine.

Diffusion-tensor imaging of white matter tracts in patients with cerebral neoplasm.

PubMed

Witwer, Brian P; Moftakhar, Roham; Hasan, Khader M; Deshmukh, Praveen; Haughton, Victor; Field, Aaron; Arfanakis, Konstantinos; Noyes, Jane; Moritz, Chad H; Meyerand, M Elizabeth; Rowley, Howard A; Alexander, Andrew L; Badie, Behnam

2002-09-01

Preserving vital cerebral function while maximizing tumor resection is a principal goal in surgical neurooncology. Although functional magnetic resonance imaging has been useful in the localization of eloquent cerebral cortex, this method does not provide information about the white matter tracts that may be involved in invasive, intrinsic brain tumors. Recently, diffusion-tensor (DT) imaging techniques have been used to map white matter tracts in the normal brain. The aim of this study was to demonstrate the role of DT imaging in preoperative mapping of white matter tracts in relation to cerebral neoplasms. Nine patients with brain malignancies (one pilocytic astrocytoma, five oligodendrogliomas, one low-grade oligoastrocytoma, one Grade 4 astrocytoma, and one metastatic adenocarcinoma) underwent DT imaging examinations prior to tumor excision. Anatomical information about white matter tract location, orientation, and projections was obtained in every patient. Depending on the tumor type and location, evidence of white matter tract edema (two patients), infiltration (two patients), displacement (five patients), and disruption (two patients) could be assessed with the aid of DT imaging in each case. Diffusion-tensor imaging allowed for visualization of white matter tracts and was found to be beneficial in the surgical planning for patients with intrinsic brain tumors. The authors' experience with DT imaging indicates that anatomically intact fibers may be present in abnormal-appearing areas of the brain. Whether resection of these involved fibers results in subtle postoperative neurological deficits requires further systematic study.

High Slew-Rate Head-Only Gradient for Improving Distortion in Echo Planar Imaging: Preliminary Experience

PubMed Central

Tan, Ek T.; Lee, Seung-Kyun; Weavers, Paul T.; Graziani, Dominic; Piel, Joseph E.; Shu, Yunhong; Huston, John; Bernstein, Matt A.; Foo, Thomas K.F.

2016-01-01

Purpose To investigate the effects on echo planar imaging (EPI) distortion of using high gradient slew rates (SR) of up to 700 T/m/s for in-vivo human brain imaging, with a dedicated, head-only gradient coil. Materials and Methods Simulation studies were first performed to determine the expected echo spacing and distortion reduction in EPI. A head gradient of 42-cm inner diameter and with asymmetric transverse coils was then installed in a whole-body, conventional 3T MRI system. Human subject imaging was performed on five subjects to determine the effects of EPI on echo spacing and signal dropout at various gradient slew rates. The feasibility of whole-brain imaging at 1.5 mm-isotropic spatial resolution was demonstrated with gradient-echo and spin-echo diffusion-weighted EPI. Results As compared to a whole-body gradient coil, the EPI echo spacing in the head-only gradient coil was reduced by 48%. Simulation and in vivo results, respectively, showed up to 25-26% and 19% improvement in signal dropout. Whole-brain imaging with EPI at 1.5 mm spatial resolution provided good whole-brain coverage, spatial linearity, and low spatial distortion effects. Conclusion Our results of human brain imaging with EPI using the compact head gradient coil at slew rates higher than in conventional whole-body MR systems demonstrate substantially improved image distortion, and point to a potential for benefits to non-EPI pulse sequences. PMID:26921117

Diffusion tensor imaging using multiple coils for mouse brain connectomics.

PubMed

Nouls, John C; Badea, Alexandra; Anderson, Robert B J; Cofer, Gary P; Allan Johnson, G

2018-06-01

The correlation between brain connectivity and psychiatric or neurological diseases has intensified efforts to develop brain connectivity mapping techniques on mouse models of human disease. The neural architecture of mouse brain specimens can be shown non-destructively and three-dimensionally by diffusion tensor imaging, which enables tractography, the establishment of a connectivity matrix and connectomics. However, experiments on cohorts of animals can be prohibitively long. To improve throughput in a 7-T preclinical scanner, we present a novel two-coil system in which each coil is shielded, placed off-isocenter along the axis of the magnet and connected to a receiver circuit of the scanner. Preservation of the quality factor of each coil is essential to signal-to-noise ratio (SNR) performance and throughput, because mouse brain specimen imaging at 7 T takes place in the coil-dominated noise regime. In that regime, we show a shielding configuration causing no SNR degradation in the two-coil system. To acquire data from several coils simultaneously, the coils are placed in the magnet bore, around the isocenter, in which gradient field distortions can bias diffusion tensor imaging metrics, affect tractography and contaminate measurements of the connectivity matrix. We quantified the experimental alterations in fractional anisotropy and eigenvector direction occurring in each coil. We showed that, when the coils were placed 12 mm away from the isocenter, measurements of the brain connectivity matrix appeared to be minimally altered by gradient field distortions. Simultaneous measurements on two mouse brain specimens demonstrated a full doubling of the diffusion tensor imaging throughput in practice. Each coil produced images devoid of shading or artifact. To further improve the throughput of mouse brain connectomics, we suggested a future expansion of the system to four coils. To better understand acceptable trade-offs between imaging throughput and connectivity matrix integrity, studies may seek to clarify how measurement variability, post-processing techniques and biological variability impact mouse brain connectomics. Copyright © 2018 John Wiley & Sons, Ltd.

Visual perception and stereoscopic imaging: an artist's perspective

NASA Astrophysics Data System (ADS)

Mason, Steve

2015-03-01

This paper continues my 2014 February IS and T/SPIE Convention exploration into the relationship of stereoscopic vision and consciousness (90141F-1). It was proposed then that by using stereoscopic imaging people may consciously experience, or see, what they are viewing and thereby help make them more aware of the way their brains manage and interpret visual information. Environmental imaging was suggested as a way to accomplish this. This paper is the result of further investigation, research, and follow-up imaging. A show of images, that is a result of this research, allows viewers to experience for themselves the effects of stereoscopy on consciousness. Creating dye-infused aluminum prints while employing ChromaDepth® 3D glasses, I hope to not only raise awareness of visual processing but also explore the differences and similarities between the artist and scientist―art increases right brain spatial consciousness, not only empirical thinking, while furthering the viewer's cognizance of the process of seeing. The artist must abandon preconceptions and expectations, despite what the evidence and experience may indicate in order to see what is happening in his work and to allow it to develop in ways he/she could never anticipate. This process is then revealed to the viewer in a show of work. It is in the experiencing, not just from the thinking, where insight is achieved. Directing the viewer's awareness during the experience using stereoscopic imaging allows for further understanding of the brain's function in the visual process. A cognitive transformation occurs, the preverbal "left/right brain shift," in order for viewers to "see" the space. Using what we know from recent brain research, these images will draw from certain parts of the brain when viewed in two dimensions and different ones when viewed stereoscopically, a shift, if one is looking for it, which is quite noticeable. People who have experienced these images in the context of examining their own visual process have been startled by the effect they have on how they perceive the world around them. For instance, when viewing the mountains on a trip to Montana, one woman exclaimed, "I could no longer see just mountains, but also so many amazing colors and shapes"―she could see beyond her preconceptions of mountains to realize more of the beauty that was really there, not just the objects she "thought" to be there. The awareness gained from experiencing the artist's perspective will help with creative thinking in particular and overall research in general. Perceiving the space in these works, completely removing the picture-plane by use of the 3D glasses, making a conscious connection between the feeling and visual content, and thus gaining a deeper appreciation of the visual process will all contribute to understanding how our thinking, our left-brain domination, gets in the way of our seeing what is right in front of us. We fool ourselves with concept and memory―experiencing these prints may help some come a little closer to reality.

Intermittent behavior in the brain neuronal network in the perception of ambiguous images

NASA Astrophysics Data System (ADS)

Hramov, Alexander E.; Kurovskaya, Maria K.; Runnova, Anastasiya E.; Zhuravlev, Maxim O.; Grubov, Vadim V.; Koronovskii, Alexey A.; Pavlov, Alexey N.; Pisarchik, Alexander N.

2017-03-01

Characteristics of intermittency during the perception of ambiguous images have been studied in the case the Necker cube image has been used as a bistable object for demonstration in the experiments, with EEG being simultaneously measured. Distributions of time interval lengths corresponding to the left-oriented and right-oriented Necker cube perception have been obtain. EEG data have been analyzed using continuous wavelet transform which was shown that the destruction of alpha rhythm with accompanying generation of high frequency oscillations can serve as a electroencephalographical marker of Necker cube recognition process in human brain.

[Tumor segmentation of brain MRI with adaptive bandwidth mean shift].

PubMed

Hou, Xiaowen; Liu, Qi

2014-10-01

In order to get the adaptive bandwidth of mean shift to make the tumor segmentation of brain magnetic resonance imaging (MRI) to be more accurate, we in this paper present an advanced mean shift method. Firstly, we made use of the space characteristics of brain image to eliminate the impact on segmentation of skull; and then, based on the characteristics of spatial agglomeration of different tissues of brain (includes tumor), we applied edge points to get the optimal initial mean value and the respectively adaptive bandwidth, in order to improve the accuracy of tumor segmentation. The results of experiment showed that, contrast to the fixed bandwidth mean shift method, the method in this paper could segment the tumor more accurately.

Non-invasive neuroimaging using near-infrared light

NASA Technical Reports Server (NTRS)

Strangman, Gary; Boas, David A.; Sutton, Jeffrey P.

2002-01-01

This article reviews diffuse optical brain imaging, a technique that employs near-infrared light to non-invasively probe the brain for changes in parameters relating to brain function. We describe the general methodology, including types of measurements and instrumentation (including the tradeoffs inherent in the various instrument components), and the basic theory required to interpret the recorded data. A brief review of diffuse optical applications is included, with an emphasis on research that has been done with psychiatric populations. Finally, we discuss some practical issues and limitations that are relevant when conducting diffuse optical experiments. We find that, while diffuse optics can provide substantial advantages to the psychiatric researcher relative to the alternative brain imaging methods, the method remains substantially underutilized in this field.

Two-photon probes for in vivo multicolor microscopy of the structure and signals of brain cells.

PubMed

Ricard, Clément; Arroyo, Erica D; He, Cynthia X; Portera-Cailliau, Carlos; Lepousez, Gabriel; Canepari, Marco; Fiole, Daniel

2018-05-11

Imaging the brain of living laboratory animals at a microscopic scale can be achieved by two-photon microscopy thanks to the high penetrability and low phototoxicity of the excitation wavelengths used. However, knowledge of the two-photon spectral properties of the myriad fluorescent probes is generally scarce and, for many, non-existent. In addition, the use of different measurement units in published reports further hinders the design of a comprehensive imaging experiment. In this review, we compile and homogenize the two-photon spectral properties of 280 fluorescent probes. We provide practical data, including the wavelengths for optimal two-photon excitation, the peak values of two-photon action cross section or molecular brightness, and the emission ranges. Beyond the spectroscopic description of these fluorophores, we discuss their binding to biological targets. This specificity allows in vivo imaging of cells, their processes, and even organelles and other subcellular structures in the brain. In addition to probes that monitor endogenous cell metabolism, studies of healthy and diseased brain benefit from the specific binding of certain probes to pathology-specific features, ranging from amyloid-β plaques to the autofluorescence of certain antibiotics. A special focus is placed on functional in vivo imaging using two-photon probes that sense specific ions or membrane potential, and that may be combined with optogenetic actuators. Being closely linked to their use, we examine the different routes of intravital delivery of these fluorescent probes according to the target. Finally, we discuss different approaches, strategies, and prerequisites for two-photon multicolor experiments in the brains of living laboratory animals.

Temporal and spatial localization of prediction-error signals in the visual brain.

PubMed

Johnston, Patrick; Robinson, Jonathan; Kokkinakis, Athanasios; Ridgeway, Samuel; Simpson, Michael; Johnson, Sam; Kaufman, Jordy; Young, Andrew W

2017-04-01

It has been suggested that the brain pre-empts changes in the environment through generating predictions, although real-time electrophysiological evidence of prediction violations in the domain of visual perception remain elusive. In a series of experiments we showed participants sequences of images that followed a predictable implied sequence or whose final image violated the implied sequence. Through careful design we were able to use the same final image transitions across predictable and unpredictable conditions, ensuring that any differences in neural responses were due only to preceding context and not to the images themselves. EEG and MEG recordings showed that early (N170) and mid-latency (N300) visual evoked potentials were robustly modulated by images that violated the implied sequence across a range of types of image change (expression deformations, rigid-rotations and visual field location). This modulation occurred irrespective of stimulus object category. Although the stimuli were static images, MEG source reconstruction of the early latency signal (N/M170) localized expectancy violation signals to brain areas associated with motion perception. Our findings suggest that the N/M170 can index mismatches between predicted and actual visual inputs in a system that predicts trajectories based on ongoing context. More generally we suggest that the N/M170 may reflect a "family" of brain signals generated across widespread regions of the visual brain indexing the resolution of top-down influences and incoming sensory data. This has important implications for understanding the N/M170 and investigating how the brain represents context to generate perceptual predictions. Copyright © 2017 Elsevier B.V. All rights reserved.

Multispectral imaging of absorption and scattering properties of in vivo exposed rat brain using a digital red-green-blue camera.

PubMed

Yoshida, Keiichiro; Nishidate, Izumi; Ishizuka, Tomohiro; Kawauchi, Satoko; Sato, Shunichi; Sato, Manabu

2015-05-01

In order to estimate multispectral images of the absorption and scattering properties in the cerebral cortex of in vivo rat brain, we investigated spectral reflectance images estimated by the Wiener estimation method using a digital RGB camera. A Monte Carlo simulation-based multiple regression analysis for the corresponding spectral absorbance images at nine wavelengths (500, 520, 540, 560, 570, 580, 600, 730, and 760 nm) was then used to specify the absorption and scattering parameters of brain tissue. In this analysis, the concentrations of oxygenated hemoglobin and that of deoxygenated hemoglobin were estimated as the absorption parameters, whereas the coefficient a and the exponent b of the reduced scattering coefficient spectrum approximated by a power law function were estimated as the scattering parameters. The spectra of absorption and reduced scattering coefficients were reconstructed from the absorption and scattering parameters, and the spectral images of absorption and reduced scattering coefficients were then estimated. In order to confirm the feasibility of this method, we performed in vivo experiments on exposed rat brain. The estimated images of the absorption coefficients were dominated by the spectral characteristics of hemoglobin. The estimated spectral images of the reduced scattering coefficients had a broad scattering spectrum, exhibiting a larger magnitude at shorter wavelengths, corresponding to the typical spectrum of brain tissue published in the literature. The changes in the estimated absorption and scattering parameters during normoxia, hyperoxia, and anoxia indicate the potential applicability of the method by which to evaluate the pathophysiological conditions of in vivo brain due to the loss of tissue viability.

Towards High-Resolution Tissue Imaging Using Nanospray Desorption Electrospray Ionization Mass Spectrometry Coupled to Shear Force Microscopy

NASA Astrophysics Data System (ADS)

Nguyen, Son N.; Sontag, Ryan L.; Carson, James P.; Corley, Richard A.; Ansong, Charles; Laskin, Julia

2018-02-01

Constant mode ambient mass spectrometry imaging (MSI) of tissue sections with high lateral resolution of better than 10 μm was performed by combining shear force microscopy with nanospray desorption electrospray ionization (nano-DESI). Shear force microscopy enabled precise control of the distance between the sample and nano-DESI probe during MSI experiments and provided information on sample topography. Proof-of-concept experiments were performed using lung and brain tissue sections representing spongy and dense tissues, respectively. Topography images obtained using shear force microscopy were comparable to the results obtained using contact profilometry over the same region of the tissue section. Variations in tissue height were found to be dependent on the tissue type and were in the range of 0-5 μm for lung tissue and 0-3 μm for brain tissue sections. Ion images of phospholipids obtained in this study are in good agreement with literature data. Normalization of nano-DESI MSI images to the signal of the internal standard added to the extraction solvent allowed us to construct high-resolution ion images free of matrix effects.

Endoscopic Full-Field Swept-Source Optical Coherence Tomography Neuroimaging System

NASA Astrophysics Data System (ADS)

Felts Almog, Ilan

Optical Coherence Tomography (OCT) has the capability to differentiate brain elements with intrinsic contrast and at a resolution an order-of-magnitude higher than other imaging modalities. This thesis investigates the feasibility of OCT for neuroimaging applied to neurosurgical guidance. We present, to our knowledge, the first Full-Field Swept-Source OCT system operating near a wavelength of 1310 nm, achieving a transverse imaging resolution of 6.5 mum, an axial resolution of 14 mum in tissue and a field of view of 270 mum x 180 mum x 400 mum. Imaging experiments were performed on rat brain tissues ex vivo, human cortical tissue ex vivo, and rats in vivo. A multi-level threshold metric applied on the intensity of the images led to a plausible correlation between the observed density and location in the brain. The proof-of-concept OCT system can be improved and miniaturized for clinical use.

Patterns of Brain Activation when Mothers View Their Own Child and Dog: An fMRI Study

PubMed Central

Gollub, Randy L.; Niemi, Steven M.; Evins, Anne Eden

2014-01-01

Neural substrates underlying the human-pet relationship are largely unknown. We examined fMRI brain activation patterns as mothers viewed images of their own child and dog and an unfamiliar child and dog. There was a common network of brain regions involved in emotion, reward, affiliation, visual processing and social cognition when mothers viewed images of both their child and dog. Viewing images of their child resulted in brain activity in the midbrain (ventral tegmental area/substantia nigra involved in reward/affiliation), while a more posterior cortical brain activation pattern involving fusiform gyrus (visual processing of faces and social cognition) characterized a mother's response to her dog. Mothers also rated images of their child and dog as eliciting similar levels of excitement (arousal) and pleasantness (valence), although the difference in the own vs. unfamiliar child comparison was larger than the own vs. unfamiliar dog comparison for arousal. Valence ratings of their dog were also positively correlated with ratings of the attachment to their dog. Although there are similarities in the perceived emotional experience and brain function associated with the mother-child and mother-dog bond, there are also key differences that may reflect variance in the evolutionary course and function of these relationships. PMID:25279788

Patterns of brain activation when mothers view their own child and dog: an fMRI study.

PubMed

Stoeckel, Luke E; Palley, Lori S; Gollub, Randy L; Niemi, Steven M; Evins, Anne Eden

2014-01-01

Neural substrates underlying the human-pet relationship are largely unknown. We examined fMRI brain activation patterns as mothers viewed images of their own child and dog and an unfamiliar child and dog. There was a common network of brain regions involved in emotion, reward, affiliation, visual processing and social cognition when mothers viewed images of both their child and dog. Viewing images of their child resulted in brain activity in the midbrain (ventral tegmental area/substantia nigra involved in reward/affiliation), while a more posterior cortical brain activation pattern involving fusiform gyrus (visual processing of faces and social cognition) characterized a mother's response to her dog. Mothers also rated images of their child and dog as eliciting similar levels of excitement (arousal) and pleasantness (valence), although the difference in the own vs. unfamiliar child comparison was larger than the own vs. unfamiliar dog comparison for arousal. Valence ratings of their dog were also positively correlated with ratings of the attachment to their dog. Although there are similarities in the perceived emotional experience and brain function associated with the mother-child and mother-dog bond, there are also key differences that may reflect variance in the evolutionary course and function of these relationships.

Recent Developments in Molecular Brain Imaging of Neuropsychiatric Disorders.

PubMed

Slifstein, Mark; Abi-Dargham, Anissa

2017-01-01

Molecular imaging with PET or SPECT has been an important research tool in psychiatry for as long as these modalities have been available. Here, we discuss two areas of neuroimaging relevant to current psychiatry research. The first is the use of imaging to study neurotransmission. We discuss the use of pharmacologic probes to induce changes in levels of neurotransmitters that can be inferred through their effects on outcome measures of imaging experiments, from their historical origins focusing on dopamine transmission through recent developments involving serotonin, GABA, and glutamate. Next, we examine imaging of neuroinflammation in the context of psychiatry. Imaging markers of neuroinflammation have been studied extensively in other areas of brain research, but they have more recently attracted interest in psychiatry research, based on accumulating evidence that there may be an inflammatory component to some psychiatric conditions. Furthermore, new probes are under development that would allow unprecedented insights into cellular processes. In summary, molecular imaging would continue to offer great potential as a unique tool to further our understanding of brain function in health and disease. Copyright © 2017 Elsevier Inc. All rights reserved.

Impact of the Glymphatic System on the Kinetic and Distribution of Gadodiamide in the Rat Brain: Observations by Dynamic MRI and Effect of Circadian Rhythm on Tissue Gadolinium Concentrations.

PubMed

Taoka, Toshiaki; Jost, Gregor; Frenzel, Thomas; Naganawa, Shinji; Pietsch, Hubertus

2018-04-12

The glymphatic system is a recently hypothesized waste clearance system of the brain in which perivascular space constitutes a pathway similar to the lymphatic system in other body regions. Sleep and anesthesia are reported to influence the activity of the glymphatic system. Because rats are nocturnal animals, the glymphatic system is expected to be more active during the day. We attempted to elucidate the influence of the glymphatic system for intravenously injected gadodiamide in the rat brain by 2 experiments. One was a magnetic resonance imaging (MRI) experiment to evaluate the short-term dynamics of signal intensity changes after gadodiamide administration. The other was a quantification experiment to evaluate the concentration of retained gadolinium within the rat brain after repeated intravenous administration of gadodiamide at different times of day and levels of anesthesia. The imaging experiment was performed on 6 rats that received an intravenous injection of gadodiamide (1 mmol/kg) and dynamic MRI for 3 hours at 2.4-minute intervals. The time course of the signal intensity changes was evaluated for different brain structures. The tissue quantification experiment was performed on 24 rats divided into 4 groups by injection time (morning, late afternoon) and anesthesia (none, short, long) during administration. All animals received gadodiamide (1.8 mmol/kg, 8 times over 2 weeks). Gadolinium concentration of dissected brain tissues was quantified 5 weeks after the last administration by inductively coupled plasma mass spectrometry. In the imaging experiment, muscle and the fourth ventricle showed an instantaneous signal intensity increase immediately after gadodiamide injection. The signal curve of the cerebral cortex and deep cerebellar nuclei reached the peak signal intensity later than the fourth ventricle but earlier than that of the prepontine cistern. In the gadolinium quantification experiment, the concentration in the group with the morning injection showed a significantly lower concentration than the late afternoon injection group. The lowest tissue gadolinium concentrations were found in the groups injected in the morning during long anesthesia. Instantaneous transition of gadodiamide from blood to cerebrospinal fluid was indicated by dynamic MRI. The gadodiamide distribution to the cerebral cortex and deep cerebellar nuclei seemed to depend on both blood flow and cerebrospinal fluid. This confirms previous studies indicating that the cerebrospinal fluid is one potential pathway of gadolinium-based contrast agent entry into the brain. For the distribution and clearance of the gadodiamide from brain tissue, involvement of the glymphatic system seemed to be indicated in terms of the influence of sleep and anesthesia.

Feasibility study of hidden flow imaging based on laser speckle technique using multiperspectives contrast images

NASA Astrophysics Data System (ADS)

Abookasis, David; Moshe, Tomer

2014-11-01

This paper demonstrates the insertion of lens array in the front of a CCD camera in a laser speckle imaging (LSI) like-technique to acquire multiple speckle reflectance projections for imaging blood flow in an intact biological tissue. In some of LSI applications, flow imaging is obtained by thinning or removing of the upper tissue layers to access blood vessels. In contrast, with the proposed approach flow imaging can be achieved while the tissue is intact. In the system, each lens from an hexagonal lens array observed the sample from slightly different perspectives and captured with a CCD camera. In the computer, these multiview raw images are converted to speckled contrast maps. Then, a self-deconvolution shift-and-add algorithm is employed for processing yields high contrast flow information. The method is experimentally validated first with a plastic tube filled with scattering liquid running at different controlled flow rates hidden in a biological tissue and then extensively tested for imaging of cerebral blood flow in an intact rodent head experience different conditions. A total of fifteen mice were used in the experiments divided randomly into three groups as follows: Group 1 (n=5) consisted of injured mice experience hypoxic ischemic brain injury monitored for ~40 min. Group 2 (n=5) injured mice experience anoxic brain injury monitored up to 20 min. Group 3 (n=5) experience functional activation monitored up to ~35 min. To increase tissue transparency and the penetration depth of photons through head tissue layers, an optical clearing method was employed. To our knowledge, this work presents for the first time the use of lens array in LSI scheme.

Acute Brain Imaging in Children: Can MRI Replace CT as a Screening Tool?

PubMed

Wagner, Matthias W; Kontzialis, Marinos; Seeburg, Daniel; Stern, Steven E; Oshmyansky, Alexander; Poretti, Andrea; Huisman, Thierry A G M

2016-01-01

To determine if axial T2-weighted imaging can serve as screening tool for pediatric brain imaging. We retrospectively evaluated consecutive brain magnetic resonance imaging (MRI) data of 161 children (74 girls) with a mean age of 7.44 ± 5.71 years. Standard of reference was the final report of neuroradiology attendings. Three readers with different levels of experience were blinded for clinical diagnoses and study indications. First, readers studied only the axial T2-weighted screening sequence. Second, they studied all available anatomical and functional MRI sequences as performed per standard protocol for each clinical indication. The readings were classified as normal or abnormal. Sensitivity and specificity were measured. Axial T2 screening yielded a sensitivity of 77-88% and a specificity of 92%. The full studies/data sets had a sensitivity of 89-95% and a specificity of 86-93%. Nineteen of 167 studies were acquired for acute and 148 of 167 studies for nonacute clinical indication. Twenty-five false-negative diagnoses paneled in three groups were made by all readers together. Readers misread four of 19 studies with acute and 21 of 148 studies with nonacute clinical indication. Four of 21 misread studies with nonacute indications harbored unexpected findings needing management. Axial T2 screening can detect pediatric brain abnormalities with high sensitivity and specificity and can possibly replace CT as screening tool if the reading physician is aware of possible limitations/pitfalls. The level of experience influences sensitivity and specificity. Adding diffusion-weighted imaging and susceptibility-weighted imaging to a 3-dimensional T2-weighted sequence would most likely further increase sensitivity and specificity. Copyright © 2015 by the American Society of Neuroimaging.

Quantitative MRI in refractory temporal lobe epilepsy: relationship with surgical outcomes

PubMed Central

Bonilha, Leonardo

2015-01-01

Medically intractable temporal lobe epilepsy (TLE) remains a serious health problem. Across treatment centers, up to 40% of patients with TLE will continue to experience persistent postoperative seizures at 2-year follow-up. It is unknown why such a large number of patients continue to experience seizures despite being suitable candidates for resective surgery. Preoperative quantitative MRI techniques may provide useful information on why some patients continue to experience disabling seizures, and may have the potential to develop prognostic markers of surgical outcome. In this article, we provide an overview of how quantitative MRI morphometric and diffusion tensor imaging (DTI) data have improved the understanding of brain structural alterations in patients with refractory TLE. We subsequently review the studies that have applied quantitative structural imaging techniques to identify the neuroanatomical factors that are most strongly related to a poor postoperative prognosis. In summary, quantitative imaging studies strongly suggest that TLE is a disorder affecting a network of neurobiological systems, characterized by multiple and inter-related limbic and extra-limbic network abnormalities. The relationship between brain alterations and postoperative outcome are less consistent, but there is emerging evidence suggesting that seizures are less likely to remit with surgery when presurgical abnormalities are observed in the connectivity supporting brain regions serving as network nodes located outside the resected temporal lobe. Future work, possibly harnessing the potential from multimodal imaging approaches, may further elucidate the etiology of persistent postoperative seizures in patients with refractory TLE. Furthermore, quantitative imaging techniques may be explored to provide individualized measures of postoperative seizure freedom outcome. PMID:25853080

Problem of intraoperative anatomical shift in image-guided surgery

NASA Astrophysics Data System (ADS)

Nauta, Haring J.; Bonnen, J. G.

1998-06-01

Experience with image guided, frameless stereotactic neurosurgery shows that intraoperative brain position shifts can be large enough to be problematic, and can occur in different directions at different directions at different stages of an operation. An understanding of the behavior of shifts will allow the surgeon to make the most appropriate use of the image guidance by first minimizing the shift itself, and then anticipating and compensating for any influence the remaining shift will have on the accuracy of the guidance. Three types of shift are described. Type I shift is a local outward bulging that occurs after the skull and dura are opened but before a mass lesion is resected. Type II shift is a local collapse of the brain tissue into the space previously occupied by the tumor. Type III shift is related to loss of cerebrospinal fluid or brain dehydration and is a generalized, more symmetric loss of brain volume. Strategies to minimize these types of shift include appropriate use of medical measures to reduce brain swelling early in the procedure without producing so much brain dehydration that Type II shift is accentuated later in the procedure. Other strategies include mechanical stabilization of brain position with retractors. Anticipating shift, the neurosurgeon should use the guidance as far as possible to map key boundaries early in the procedure before shift becomes more pronounced. Ultimately, however, the correction for the problem of intraoperative brain shift will require the ability to update the imaging data during the surgery.

Functional cliques in the amygdala and related brain networks driven by fear assessment acquired during movie viewing.

PubMed

Kinreich, Sivan; Intrator, Nathan; Hendler, Talma

2011-01-01

One of the greatest challenges involved in studying the brain mechanisms of fear is capturing the individual's unique instantaneous experience. Brain imaging studies to date commonly sacrifice valuable information regarding the individual real-time conscious experience, especially when focusing on elucidating the amygdala's activity. Here, we assumed that by using a minimally intrusive cue along with applying a robust clustering approach to probe the amygdala, it would be possible to rate fear in real time and to derive the related network of activation. During functional magnetic resonance imaging scanning, healthy volunteers viewed two excerpts from horror movies and were periodically auditory cued to rate their instantaneous experience of "I'm scared." Using graph theory and community mathematical concepts, data-driven clustering of the fear-related functional cliques in the amygdala was performed guided by the individually marked periods of heightened fear. Individually tailored functions derived from these amygdala activation cliques were subsequently applied as general linear model predictors to a whole-brain analysis to reveal the correlated networks. Our results suggest that by using a localized robust clustering approach, it is possible to probe activation in the right dorsal amygdala that is directly related to individual real-time emotional experience. Moreover, this fear-evoked amygdala revealed two opposing networks of co-activation and co-deactivation, which correspond to vigilance and rest-related circuits, respectively.

Imaging brain microstructure with diffusion MRI: practicality and applications.

PubMed

Alexander, Daniel C; Dyrby, Tim B; Nilsson, Markus; Zhang, Hui

2017-11-29

This article gives an overview of microstructure imaging of the brain with diffusion MRI and reviews the state of the art. The microstructure-imaging paradigm aims to estimate and map microscopic properties of tissue using a model that links these properties to the voxel scale MR signal. Imaging techniques of this type are just starting to make the transition from the technical research domain to wide application in biomedical studies. We focus here on the practicalities of both implementing such techniques and using them in applications. Specifically, the article summarizes the relevant aspects of brain microanatomy and the range of diffusion-weighted MR measurements that provide sensitivity to them. It then reviews the evolution of mathematical and computational models that relate the diffusion MR signal to brain tissue microstructure, as well as the expanding areas of application. Next we focus on practicalities of designing a working microstructure imaging technique: model selection, experiment design, parameter estimation, validation, and the pipeline of development of this class of technique. The article concludes with some future perspectives on opportunities in this topic and expectations on how the field will evolve in the short-to-medium term. Copyright © 2017 John Wiley & Sons, Ltd.

Seeing mathematics: perceptual experience and brain activity in acquired synesthesia.

PubMed

Brogaard, Berit; Vanni, Simo; Silvanto, Juha

2013-01-01

We studied the patient JP who has exceptional abilities to draw complex geometrical images by hand and a form of acquired synesthesia for mathematical formulas and objects, which he perceives as geometrical figures. JP sees all smooth curvatures as discrete lines, similarly regardless of scale. We carried out two preliminary investigations to establish the perceptual nature of synesthetic experience and to investigate the neural basis of this phenomenon. In a functional magnetic resonance imaging (fMRI) study, image-inducing formulas produced larger fMRI responses than non-image inducing formulas in the left temporal, parietal and frontal lobes. Thus our main finding is that the activation associated with his experience of complex geometrical images emerging from mathematical formulas is restricted to the left hemisphere.

Segmentation, feature extraction, and multiclass brain tumor classification.

PubMed

Sachdeva, Jainy; Kumar, Vinod; Gupta, Indra; Khandelwal, Niranjan; Ahuja, Chirag Kamal

2013-12-01

Multiclass brain tumor classification is performed by using a diversified dataset of 428 post-contrast T1-weighted MR images from 55 patients. These images are of primary brain tumors namely astrocytoma (AS), glioblastoma multiforme (GBM), childhood tumor-medulloblastoma (MED), meningioma (MEN), secondary tumor-metastatic (MET), and normal regions (NR). Eight hundred fifty-six regions of interest (SROIs) are extracted by a content-based active contour model. Two hundred eighteen intensity and texture features are extracted from these SROIs. In this study, principal component analysis (PCA) is used for reduction of dimensionality of the feature space. These six classes are then classified by artificial neural network (ANN). Hence, this approach is named as PCA-ANN approach. Three sets of experiments have been performed. In the first experiment, classification accuracy by ANN approach is performed. In the second experiment, PCA-ANN approach with random sub-sampling has been used in which the SROIs from the same patient may get repeated during testing. It is observed that the classification accuracy has increased from 77 to 91 %. PCA-ANN has delivered high accuracy for each class: AS-90.74 %, GBM-88.46 %, MED-85 %, MEN-90.70 %, MET-96.67 %, and NR-93.78 %. In the third experiment, to remove bias and to test the robustness of the proposed system, data is partitioned in a manner such that the SROIs from the same patient are not common for training and testing sets. In this case also, the proposed system has performed well by delivering an overall accuracy of 85.23 %. The individual class accuracy for each class is: AS-86.15 %, GBM-65.1 %, MED-63.36 %, MEN-91.5 %, MET-65.21 %, and NR-93.3 %. A computer-aided diagnostic system comprising of developed methods for segmentation, feature extraction, and classification of brain tumors can be beneficial to radiologists for precise localization, diagnosis, and interpretation of brain tumors on MR images.

The Brain Adapts to Orthography with Experience: Evidence from English and Chinese

ERIC Educational Resources Information Center

Cao, Fan; Brennan, Christine; Booth, James R.

2015-01-01

Using functional magnetic resonance imaging (fMRI), we examined the process of language specialization in the brain by comparing developmental changes in two contrastive orthographies: Chinese and English. In a visual word rhyming judgment task, we found a significant interaction between age and language in left inferior parietal lobule and left…

Cannabis Use and Memory Brain Function in Adolescent Boys: A Cross-Sectional Multicenter Functional Magnetic Resonance Imaging Study

ERIC Educational Resources Information Center

Jager, Gerry; Block, Robert I.; Luijten, Maartje; Ramsey, Nick F.

2010-01-01

Objective: Early-onset cannabis use has been associated with later use/abuse, mental health problems (psychosis, depression), and abnormal development of cognition and brain function. During adolescence, ongoing neurodevelopmental maturation and experience shape the neural circuitry underlying complex cognitive functions such as memory and…

Middle School Students' Lived Experiences of Teacher Relationship Impact

ERIC Educational Resources Information Center

Kauffman, Theresa Rose

2013-01-01

Researchers have found that positive relationships in schools can impact student achievement, and researchers in brain imaging have connected emotion centers in the brain to the learning process. However, current practice in schools reflects a lack of understanding of the impact of relationships in the classroom on learning from a student…

Correlation between 99Tcm-HMPAO-SPECT brain image and a history of decompression illness or extent of diving experience in commercial divers.

PubMed Central

Shields, T G; Duff, P M; Evans, S A; Gemmell, H G; Sharp, P F; Smith, F W; Staff, R T; Wilcock, S E

1997-01-01

OBJECTIVES: To explore the use of 99technetiumm-hexamethyl propylene amine oxime single photon computed tomography (HMPAO-SPECT) of the brain as a means of detecting nervous tissue damage in divers and to determine if there is any correlation between brain image and a diver's history of diving or decompression illness (DCI). METHODS: 28 commercial divers with a history of DCI, 26 divers with no history of DCI, and 19 non-diving controls were examined with brain HMPAO-SPECT. Results were classified by observer assessment as normal (I) or as a pattern variants (II-V). The brain images of a subgroup of these divers (n = 44) and the controls (n = 17) were further analysed with a first order texture analysis technique based on a grey level histogram. RESULTS: 15 of 54 commercial divers (28%) were visually assessed as having HMPAO-SPECT images outside normal limits compared with 15.8% in appropriately identified non-diver control subjects. 18% of divers with a history of DCI were classified as having a pattern different from the normal image compared with 38% with no history of DCI. No association was established between the presence of a pattern variant from the normal image and history of DCI, diving, or other previous possible neurological insult. On texture analysis of the brain images, divers had a significantly lower mean grey level (MGL) than non-divers. Divers with a history of DCI (n = 22) had a significantly lower MGL when compared with divers with no history of DCI (n = 22). Divers with > 14 years professional diving or > 100 decompression days a year had a significantly lower MGL value. CONCLUSIONS: Observer assessment of HMPAO-SPECT brain images can lead to disparity in results. Texture analysis of the brain images supplies both an objective and consistent method of measurement. A significant correlation was found between a low measure of MGL and a history of DCI. There was also an indication that diving itself had an effect on texture measurement, implying that it had caused subclinical nervous tissue damage. PMID:9166130

A priori collaboration in population imaging: The Uniform Neuro-Imaging of Virchow-Robin Spaces Enlargement consortium.

PubMed

Adams, Hieab H H; Hilal, Saima; Schwingenschuh, Petra; Wittfeld, Katharina; van der Lee, Sven J; DeCarli, Charles; Vernooij, Meike W; Katschnig-Winter, Petra; Habes, Mohamad; Chen, Christopher; Seshadri, Sudha; van Duijn, Cornelia M; Ikram, M Kamran; Grabe, Hans J; Schmidt, Reinhold; Ikram, M Arfan

2015-12-01

Virchow-Robin spaces (VRS), or perivascular spaces, are compartments of interstitial fluid enclosing cerebral blood vessels and are potential imaging markers of various underlying brain pathologies. Despite a growing interest in the study of enlarged VRS, the heterogeneity in rating and quantification methods combined with small sample sizes have so far hampered advancement in the field. The Uniform Neuro-Imaging of Virchow-Robin Spaces Enlargement (UNIVRSE) consortium was established with primary aims to harmonize rating and analysis (www.uconsortium.org). The UNIVRSE consortium brings together 13 (sub)cohorts from five countries, totaling 16,000 subjects and over 25,000 scans. Eight different magnetic resonance imaging protocols were used in the consortium. VRS rating was harmonized using a validated protocol that was developed by the two founding members, with high reliability independent of scanner type, rater experience, or concomitant brain pathology. Initial analyses revealed risk factors for enlarged VRS including increased age, sex, high blood pressure, brain infarcts, and white matter lesions, but this varied by brain region. Early collaborative efforts between cohort studies with respect to data harmonization and joint analyses can advance the field of population (neuro)imaging. The UNIVRSE consortium will focus efforts on other potential correlates of enlarged VRS, including genetics, cognition, stroke, and dementia.

Simple platform for chronic imaging of hippocampal activity during spontaneous behaviour in an awake mouse

PubMed Central

Villette, Vincent; Levesque, Mathieu; Miled, Amine; Gosselin, Benoit; Topolnik, Lisa

2017-01-01

Chronic electrophysiological recordings of neuronal activity combined with two-photon Ca2+ imaging give access to high resolution and cellular specificity. In addition, awake drug-free experimentation is required for investigating the physiological mechanisms that operate in the brain. Here, we developed a simple head fixation platform, which allows simultaneous chronic imaging and electrophysiological recordings to be obtained from the hippocampus of awake mice. We performed quantitative analyses of spontaneous animal behaviour, the associated network states and the cellular activities in the dorsal hippocampus as well as estimated the brain stability limits to image dendritic processes and individual axonal boutons. Ca2+ imaging recordings revealed a relatively stereotyped hippocampal activity despite a high inter-animal and inter-day variability in the mouse behavior. In addition to quiet state and locomotion behavioural patterns, the platform allowed the reliable detection of walking steps and fine speed variations. The brain motion during locomotion was limited to ~1.8 μm, thus allowing for imaging of small sub-cellular structures to be performed in parallel with recordings of network and behavioural states. This simple device extends the drug-free experimentation in vivo, enabling high-stability optophysiological experiments with single-bouton resolution in the mouse awake brain. PMID:28240275

Neural signatures of experimentally induced flow experiences identified in a typical fMRI block design with BOLD imaging

PubMed Central

Keller, Johannes; Grön, Georg

2016-01-01

Previously, experimentally induced flow experiences have been demonstrated with perfusion imaging during activation blocks of 3 min length to accommodate with the putatively slowly evolving “mood” characteristics of flow. Here, we used functional magnetic resonance imaging (fMRI) in a sample of 23 healthy, male participants to investigate flow in the context of a typical fMRI block design with block lengths as short as 30 s. To induce flow, demands of arithmetic tasks were automatically and continuously adjusted to the individual skill level. Compared against conditions of boredom and overload, experience of flow was evident from individuals’ reported subjective experiences and changes in electrodermal activity. Neural activation was relatively increased during flow, particularly in the anterior insula, inferior frontal gyri, basal ganglia and midbrain. Relative activation decreases during flow were observed in medial prefrontal and posterior cingulate cortex, and in the medial temporal lobe including the amygdala. Present findings suggest that even in the context of comparably short activation blocks flow can be reliably experienced and is associated with changes in neural activation of brain regions previously described. Possible mechanisms of interacting brain regions are outlined, awaiting further investigation which should now be possible given the greater temporal resolution compared with previous perfusion imaging. PMID:26508774

3-Substituted 1,5-Diaryl-1 H-1,2,4-triazoles as Prospective PET Radioligands for Imaging Brain COX-1 in Monkey. Part 2: Selection and Evaluation of [11C]PS13 for Quantitative Imaging.

PubMed

Shrestha, Stal; Singh, Prachi; Cortes-Salva, Michelle Y; Jenko, Kimberly J; Ikawa, Masamichi; Kim, Min-Jeong; Kobayashi, Masato; Morse, Cheryl L; Gladding, Robert L; Liow, Jeih-San; Zoghbi, Sami S; Fujita, Masahiro; Innis, Robert B; Pike, Victor W

2018-06-13

In our preceding paper (Part 1), we identified three 1,5-bis-diaryl-1,2,4-triazole-based compounds that merited evaluation as potential positron emission tomography (PET) radioligands for selectively imaging cyclooxygenase-1 (COX-1) in monkey and human brain, namely, 1,5-bis(4-methoxyphenyl)-3-(alkoxy)-1 H-1,2,4-triazoles bearing a 3-methoxy (PS1), a 3-(2,2,2-trifluoroethoxy) (PS13), or a 3-fluoromethoxy substituent (PS2). PS1 and PS13 were labeled from phenol precursors by O- 11 C-methylation with [ 11 C]iodomethane and PS2 by O- 18 F-fluoroalkylation with [ 2 H 2 , 18 F]fluorobromomethane. Here, we evaluated these PET radioligands in monkey. All three radioligands gave moderately high uptake in brain, although [ 2 H 2 , 18 F]PS2 also showed undesirable radioactivity uptake in skull. [ 11 C]PS13 was selected for further evaluation, mainly based on more favorable brain kinetics than [ 11 C]PS1. Pharmacological preblock experiments showed that about 55% of the radioactivity uptake in brain was specifically bound to COX-1. An index of enzyme density, V T , was well identified from serial brain scans and from the concentrations of parent radioligand in arterial plasma. In addition, V T values were stable within 80 min, suggesting that brain uptake was not contaminated by radiometabolites. [ 11 C]PS13 successfully images and quantifies COX-1 in monkey brain, and merits further investigation for imaging COX-1 in monkey models of neuroinflammation and in healthy human subjects.

The Smartphone Brain Scanner: A Portable Real-Time Neuroimaging System

PubMed Central

Stopczynski, Arkadiusz; Stahlhut, Carsten; Larsen, Jakob Eg; Petersen, Michael Kai; Hansen, Lars Kai

2014-01-01

Combining low-cost wireless EEG sensors with smartphones offers novel opportunities for mobile brain imaging in an everyday context. Here we present the technical details and validation of a framework for building multi-platform, portable EEG applications with real-time 3D source reconstruction. The system – Smartphone Brain Scanner – combines an off-the-shelf neuroheadset or EEG cap with a smartphone or tablet, and as such represents the first fully portable system for real-time 3D EEG imaging. We discuss the benefits and challenges, including technical limitations as well as details of real-time reconstruction of 3D images of brain activity. We present examples of brain activity captured in a simple experiment involving imagined finger tapping, which shows that the acquired signal in a relevant brain region is similar to that obtained with standard EEG lab equipment. Although the quality of the signal in a mobile solution using an off-the-shelf consumer neuroheadset is lower than the signal obtained using high-density standard EEG equipment, we propose mobile application development may offset the disadvantages and provide completely new opportunities for neuroimaging in natural settings. PMID:24505263

[11C]PF-3274167 as a PET radiotracer of oxytocin receptors: Radiosynthesis and evaluation in rat brain.

PubMed

Vidal, Benjamin; Karpenko, Iuliia A; Liger, François; Fieux, Sylvain; Bouillot, Caroline; Billard, Thierry; Hibert, Marcel; Zimmer, Luc

2017-12-01

Oxytocin plays a major role in the regulation of social interactions in mammals by interacting with the oxytocin receptor (OTR) expressed in the brain. Furthermore, the oxytocin system appears as a possible therapeutic target in autism spectrum disorders and other psychiatric troubles, justifying current pharmacological researches. Since no specific PET radioligand is currently available to image OTR in the brain, the aim of this study was to radiolabel the specific OTR antagonist PF-3274167 and to evaluate [ 11 C]PF-3274167 as a potential PET tracer for OTR in rat brains. [ 11 C]PF-3274167 was prepared via the O-methylation of its desmethyl precursor with [ 11 C]methyl iodide. The lipophilicity of the radioactive compound was evaluated by measuring the n-octanol-buffer partition coefficient (logD). Autoradiography experiments were performed on rat brain tissue to evaluate the in vitro distribution of the [ 11 C]PF-3274167. MicroPET experiments were conducted with and without pre-injection of ciclosporin in order to evaluate the influence of the P-glycoprotein (P-gp) on the brain uptake. [ 11 C]PF-3274167 was synthesized with high radiochemical and chemical purities (>95%) and good specific activity. The measured logD was 1.93. In vitro, [ 11 C]PF-3274167 did not show any evidence of specific binding to OTR. PET imaging showed that [ 11 C]PF-3274167 uptake in rat brain was very low in basal conditions but increased significantly after the administration of ciclosporin, suggesting that it is a substrate of the P-gp. In the ciclosporin-pre-injected rat, however, [ 11 C]PF-3274167 distribution did not match with the known distribution of OTR in rats. [ 11 C]PF-3274167 is not a suitable tracer for imaging of OTR in rat brain, probably because of a too low affinity for this receptor in addition to a poor brain penetration. Copyright © 2017 Elsevier Inc. All rights reserved.

[Research on K-means clustering segmentation method for MRI brain image based on selecting multi-peaks in gray histogram].

PubMed

Chen, Zhaoxue; Yu, Haizhong; Chen, Hao

2013-12-01

To solve the problem of traditional K-means clustering in which initial clustering centers are selected randomly, we proposed a new K-means segmentation algorithm based on robustly selecting 'peaks' standing for White Matter, Gray Matter and Cerebrospinal Fluid in multi-peaks gray histogram of MRI brain image. The new algorithm takes gray value of selected histogram 'peaks' as the initial K-means clustering center and can segment the MRI brain image into three parts of tissue more effectively, accurately, steadily and successfully. Massive experiments have proved that the proposed algorithm can overcome many shortcomings caused by traditional K-means clustering method such as low efficiency, veracity, robustness and time consuming. The histogram 'peak' selecting idea of the proposed segmentootion method is of more universal availability.

Simultaneous imaging of cerebral partial pressure of oxygen and blood flow during functional activation and cortical spreading depression

PubMed Central

Sakadžić, Sava; Yuan, Shuai; Dilekoz, Ergin; Ruvinskaya, Svetlana; Vinogradov, Sergei A.; Ayata, Cenk; Boas, David A.

2009-01-01

We developed a novel imaging technique that provides real-time two-dimensional maps of the absolute partial pressure of oxygen and relative cerebral blood flow in rats by combining phosphorescence lifetime imaging with laser speckle contrast imaging. Direct measurement of blood oxygenation based on phosphorescence lifetime is not significantly affected by changes in the optical parameters of the tissue during the experiment. The potential of the system as a novel tool for quantitative analysis of the dynamic delivery of oxygen to support brain metabolism was demonstrated in rats by imaging cortical responses to forepaw stimulation and the propagation of cortical spreading depression waves. This new instrument will enable further study of neurovascular coupling in normal and diseased brain. PMID:19340106

Imaging learning and memory: classical conditioning.

PubMed

Schreurs, B G; Alkon, D L

2001-12-15

The search for the biological basis of learning and memory has, until recently, been constrained by the limits of technology to classic anatomic and electrophysiologic studies. With the advent of functional imaging, we have begun to delve into what, for many, was a "black box." We review several different types of imaging experiments, including steady state animal experiments that image the functional labeling of fixed tissues, and dynamic human studies based on functional imaging of the intact brain during learning. The data suggest that learning and memory involve a surprising conservation of mechanisms and the integrated networking of a number of structures and processes. Copyright 2001 Wiley-Liss, Inc.

Brain MRI analysis for Alzheimer's disease diagnosis using an ensemble system of deep convolutional neural networks.

PubMed

Islam, Jyoti; Zhang, Yanqing

2018-05-31

Alzheimer's disease is an incurable, progressive neurological brain disorder. Earlier detection of Alzheimer's disease can help with proper treatment and prevent brain tissue damage. Several statistical and machine learning models have been exploited by researchers for Alzheimer's disease diagnosis. Analyzing magnetic resonance imaging (MRI) is a common practice for Alzheimer's disease diagnosis in clinical research. Detection of Alzheimer's disease is exacting due to the similarity in Alzheimer's disease MRI data and standard healthy MRI data of older people. Recently, advanced deep learning techniques have successfully demonstrated human-level performance in numerous fields including medical image analysis. We propose a deep convolutional neural network for Alzheimer's disease diagnosis using brain MRI data analysis. While most of the existing approaches perform binary classification, our model can identify different stages of Alzheimer's disease and obtains superior performance for early-stage diagnosis. We conducted ample experiments to demonstrate that our proposed model outperformed comparative baselines on the Open Access Series of Imaging Studies dataset.

Active Dentate Granule Cells Encode Experience to Promote the Addition of Adult-Born Hippocampal Neurons

PubMed Central

Kirschen, Gregory W.; Shen, Jia; Wang, Jia; Man, Guoming; Wu, Song

2017-01-01

The continuous addition of new dentate granule cells (DGCs), which is regulated exquisitely by brain activity, renders the hippocampus plastic. However, how neural circuits encode experiences to affect the addition of adult-born neurons remains unknown. Here, we used endoscopic Ca2+ imaging to track the real-time activity of individual DGCs in freely behaving mice. For the first time, we found that active DGCs responded to a novel experience by increasing their Ca2+ event frequency preferentially. This elevated activity, which we found to be associated with object exploration, returned to baseline by 1 h in the same environment, but could be dishabituated via introduction to a novel environment. To transition seamlessly between environments, we next established a freely controllable virtual reality system for unrestrained mice. We again observed increased firing of active neurons in a virtual enriched environment. Interestingly, multiple novel virtual experiences increased the number of newborn neurons accumulatively compared with a single experience. Finally, optogenetic silencing of existing DGCs during novel environmental exploration perturbed experience-induced neuronal addition. Our study shows that the adult brain conveys novel, enriched experiences to increase the addition of adult-born hippocampal neurons by increasing the firing of active DGCs. SIGNIFICANCE STATEMENT Adult brains are constantly reshaping themselves from synapses to circuits as we encounter novel experiences from moment to moment. Importantly, this reshaping includes the addition of newborn hippocampal neurons. However, it remains largely unknown how our circuits encode experience-induced brain activity to govern the addition of new hippocampal neurons. By coupling in vivo Ca2+ imaging of dentate granule neurons with a novel, unrestrained virtual reality system for rodents, we discovered that a new experience increased firing of active dentate granule neurons rapidly and robustly. Exploration in multiple novel virtual environments, compared with a single environment, promoted dentate activation and enhanced the addition of new hippocampal neurons accumulatively. Finally, silencing this activation optogenetically during novel experiences perturbed experience-induced neuronal addition. PMID:28373391

Spread spectrum time-resolved diffuse optical measurement system for enhanced sensitivity in detecting human brain activity

NASA Astrophysics Data System (ADS)

Mehta, Kalpesh; Hasnain, Ali; Zhou, Xiaowei; Luo, Jianwen; Penney, Trevor B.; Chen, Nanguang

2017-04-01

Diffuse optical spectroscopy (DOS) and imaging methods have been widely applied to noninvasive detection of brain activity. We have designed and implemented a low cost, portable, real-time one-channel time-resolved DOS system for neuroscience studies. Phantom experiments were carried out to test the performance of the system. We further conducted preliminary human experiments and demonstrated that enhanced sensitivity in detecting neural activity in the cortex could be achieved by the use of late arriving photons.

Learning Computational Models of Video Memorability from fMRI Brain Imaging.

PubMed

Han, Junwei; Chen, Changyuan; Shao, Ling; Hu, Xintao; Han, Jungong; Liu, Tianming

2015-08-01

Generally, various visual media are unequally memorable by the human brain. This paper looks into a new direction of modeling the memorability of video clips and automatically predicting how memorable they are by learning from brain functional magnetic resonance imaging (fMRI). We propose a novel computational framework by integrating the power of low-level audiovisual features and brain activity decoding via fMRI. Initially, a user study experiment is performed to create a ground truth database for measuring video memorability and a set of effective low-level audiovisual features is examined in this database. Then, human subjects' brain fMRI data are obtained when they are watching the video clips. The fMRI-derived features that convey the brain activity of memorizing videos are extracted using a universal brain reference system. Finally, due to the fact that fMRI scanning is expensive and time-consuming, a computational model is learned on our benchmark dataset with the objective of maximizing the correlation between the low-level audiovisual features and the fMRI-derived features using joint subspace learning. The learned model can then automatically predict the memorability of videos without fMRI scans. Evaluations on publically available image and video databases demonstrate the effectiveness of the proposed framework.

MR images of mouse brain using clinical 3T MR scanner and 4CH-Mouse coil

NASA Astrophysics Data System (ADS)

Lim, Soo Mee; Park, Eun Mi; Lyoo, In Kyoon; Lee, Junghyun; Han, Bo Mi; Lee, Jeong Kyong; Lee, Su Bin

2015-07-01

Objectives: Although small-bore high-field magnets are useful for research in small rodent models,this technology, however, has not been easily accessible to most researchers. This current study, thus,tried to evaluate the usability of 4CH-Mouse coil (Philips Healthcare, Best, the Netherlands) forpreclinical investigations in clinical 3T MR scan environment. We evaluated the effects of ischemicpreconditioning (IP) in the mouse stroke model with clinical 3T MR scanner and 4CH-Mouse coil. Materials and Methods: Experiments were performed on male C57BL/6 mice that either received the IP or sham operation (control). Three different MR sequences including diffusion weighted images (DWI), T2-weighted images (T2WI), and fluid attenuated inversion recovery (FLAIR) were performed on the mouse brains following 24, 72 hours of middle cerebral artery occlusion (MCAO) and analyzed for infarct lesions. Results: The images showed that the IP-treated mouse brains had significantly smaller infarct volumes compared to the control group. Of the MR sequences employed, the T2WI showed the highest level of correlations with postmortem infarct volume measurements. Conclusions: The clinical 3T MR scanner turned out to have a solid potential as a practical tool for imaging small animal brains. MR sequences including DWI, T2WI, FLAIR were obtained with acceptable resolution and in a reasonable time constraint in evaluating a mouse stroke model brain.

Tissue microstructure features derived from anomalous diffusion measurements in magnetic resonance imaging.

PubMed

Yu, Qiang; Reutens, David; O'Brien, Kieran; Vegh, Viktor

2017-02-01

Tissue microstructure features, namely axon radius and volume fraction, provide important information on the function of white matter pathways. These parameters vary on the scale much smaller than imaging voxels (microscale) yet influence the magnetic resonance imaging diffusion signal at the image voxel scale (macroscale) in an anomalous manner. Researchers have already mapped anomalous diffusion parameters from magnetic resonance imaging data, but macroscopic variations have not been related to microscale influences. With the aid of a tissue model, we aimed to connect anomalous diffusion parameters to axon radius and volume fraction using diffusion-weighted magnetic resonance imaging measurements. An ex vivo human brain experiment was performed to directly validate axon radius and volume fraction measurements in the human brain. These findings were validated using electron microscopy. Additionally, we performed an in vivo study on nine healthy participants to map axon radius and volume fraction along different regions of the corpus callosum projecting into various cortical areas identified using tractography. We found a clear relationship between anomalous diffusion parameters and axon radius and volume fraction. We were also able to map accurately the trend in axon radius along the corpus callosum, and in vivo findings resembled the low-high-low-high behaviour in axon radius demonstrated previously. Axon radius and volume fraction measurements can potentially be used in brain connectivity studies and to understand the implications of white matter structure in brain diseases and disorders. Hum Brain Mapp 38:1068-1081, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Statistical model of laminar structure for atlas-based segmentation of the fetal brain from in utero MR images

NASA Astrophysics Data System (ADS)

Habas, Piotr A.; Kim, Kio; Chandramohan, Dharshan; Rousseau, Francois; Glenn, Orit A.; Studholme, Colin

2009-02-01

Recent advances in MR and image analysis allow for reconstruction of high-resolution 3D images from clinical in utero scans of the human fetal brain. Automated segmentation of tissue types from MR images (MRI) is a key step in the quantitative analysis of brain development. Conventional atlas-based methods for adult brain segmentation are limited in their ability to accurately delineate complex structures of developing tissues from fetal MRI. In this paper, we formulate a novel geometric representation of the fetal brain aimed at capturing the laminar structure of developing anatomy. The proposed model uses a depth-based encoding of tissue occurrence within the fetal brain and provides an additional anatomical constraint in a form of a laminar prior that can be incorporated into conventional atlas-based EM segmentation. Validation experiments are performed using clinical in utero scans of 5 fetal subjects at gestational ages ranging from 20.5 to 22.5 weeks. Experimental results are evaluated against reference manual segmentations and quantified in terms of Dice similarity coefficient (DSC). The study demonstrates that the use of laminar depth-encoded tissue priors improves both the overall accuracy and precision of fetal brain segmentation. Particular refinement is observed in regions of the parietal and occipital lobes where the DSC index is improved from 0.81 to 0.82 for cortical grey matter, from 0.71 to 0.73 for the germinal matrix, and from 0.81 to 0.87 for white matter.

Anatomical analysis of an aye-aye brain (Daubentonia madagascariensis, primates: Prosimii) combining histology, structural magnetic resonance imaging, and diffusion-tensor imaging.

PubMed

Kaufman, Jason A; Ahrens, Eric T; Laidlaw, David H; Zhang, Song; Allman, John M

2005-11-01

This report presents initial results of a multimodal analysis of tissue volume and microstructure in the brain of an aye-aye (Daubentonia madagascariensis). The left hemisphere of an aye-aye brain was scanned using T2-weighted structural magnetic resonance imaging (MRI) and diffusion-tensor imaging (DTI) prior to histological processing and staining for Nissl substance and myelinated fibers. The objectives of the experiment were to estimate the volume of gross brain regions for comparison with published data on other prosimians and to validate DTI data on fiber anisotropy with histological measurements of fiber spread. Measurements of brain structure volumes in the specimen are consistent with those reported in the literature: the aye-aye has a very large brain for its body size, a reduced volume of visual structures (V1 and LGN), and an increased volume of the olfactory lobe. This trade-off between visual and olfactory reliance is likely a reflection of the nocturnal extractive foraging behavior practiced by Daubentonia. Additionally, frontal cortex volume is large in the aye-aye, a feature that may also be related to its complex foraging behavior and sensorimotor demands. Analysis of DTI data in the anterior cingulum bundle demonstrates a strong correlation between fiber spread as measured from histological sections and fiber spread as measured from DTI. These results represent the first quantitative comparison of DTI data and fiber-stained histology in the brain. (c) 2005 Wiley-Liss, Inc.

Traumatic brain injury and delayed sequelae: a review--traumatic brain injury and mild traumatic brain injury (concussion) are precursors to later-onset brain disorders, including early-onset dementia.

PubMed

Kiraly, Michael; Kiraly, Stephen J

2007-11-12

Brain injuries are too common. Most people are unaware of the incidence of and horrendous consequences of traumatic brain injury (TBI) and mild traumatic brain injury (MTBI). Research and the advent of sophisticated imaging have led to progression in the understanding of brain pathophysiology following TBI. Seminal evidence from animal and human experiments demonstrate links between TBI and the subsequent onset of premature, psychiatric syndromes and neurodegenerative diseases, including Alzheimer's disease (AD) and Parkinson's disease (PD). Objectives of this summary are, therefore, to instill appreciation regarding the importance of brain injury prevention, diagnosis, and treatment, and to increase awareness regarding the long-term delayed consequences following TBI.

Towards High-Resolution Tissue Imaging Using Nanospray Desorption Electrospray Ionization Mass Spectrometry Coupled to Shear Force Microscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nguyen, Son N.; Sontag, Ryan L.; Carson, James P.

Constant mode ambient mass spectrometry imaging (MSI) of tissue sections with high lateral resolution of better than 10 µm was performed by combining shear force microscopy with nanospray desorption electrospray ionization (nano-DESI). Shear force microscopy enabled precise control of the distance between the sample and nano-DESI probe during MSI experiments and provided information on sample topography. Proof-of-concept experiments were performed using lung and brain tissue sections representing spongy and dense tissues, respectively. Topography images obtained using shear force microscopy were comparable to the results obtained using contact profilometry over the same region of the tissue section. Variations in tissue heightmore » were found to be dependent on the tissue type and were in the range of 0-5 µm for lung tissue and 0-3 µm for brain tissue sections. Ion images of phospholipids obtained in this study are in good agreement with literature data. Normalization of nano-DESI MSI images to the signal of the internal standard added to the extraction solvent allowed us to construct high-resolution ion images free of matrix effects.« less

Methods for Dichoptic Stimulus Presentation in Functional Magnetic Resonance Imaging - A Review

PubMed Central

Choubey, Bhaskar; Jurcoane, Alina; Muckli, Lars; Sireteanu, Ruxandra

2009-01-01

Dichoptic stimuli (different stimuli displayed to each eye) are increasingly being used in functional brain imaging experiments using visual stimulation. These studies include investigation into binocular rivalry, interocular information transfer, three-dimensional depth perception as well as impairments of the visual system like amblyopia and stereodeficiency. In this paper, we review various approaches of displaying dichoptic stimulus used in functional magnetic resonance imaging experiments. These include traditional approaches of using filters (red-green, red-blue, polarizing) with optical assemblies as well as newer approaches of using bi-screen goggles. PMID:19526076

Brain basis of self: self-organization and lessons from dreaming

PubMed Central

Kahn, David

2013-01-01

Through dreaming, a different facet of the self is created as a result of a self-organizing process in the brain. Self-organization in biological systems often happens as an answer to an environmental change for which the existing system cannot cope; self-organization creates a system that can cope in the newly changed environment. In dreaming, self-organization serves the function of organizing disparate memories into a dream since the dreamer herself is not able to control how individual memories become weaved into a dream. The self-organized dream provides, thereby, a wide repertoire of experiences; this expanded repertoire of experience results in an expansion of the self beyond that obtainable when awake. Since expression of the self is associated with activity in specific areas of the brain, the article also discusses the brain basis of the self by reviewing studies of brain injured patients, discussing brain imaging studies in normal brain functioning when focused, when daydreaming and when asleep and dreaming. PMID:23882232

Bridging the gap between system and cell: The role of ultra-high field MRI in human neuroscience.

PubMed

Turner, Robert; De Haan, Daniel

2017-01-01

The volume of published research at the levels of systems and cellular neuroscience continues to increase at an accelerating rate. At the same time, progress in psychiatric medicine has stagnated and scientific confidence in cognitive psychology research is under threat due to careless analysis methods and underpowered experiments. With the advent of ultra-high field MRI, with submillimeter image voxels, imaging neuroscience holds the potential to bridge the cellular and systems levels. Use of these accurate and precisely localized quantitative measures of brain activity may go far in providing more secure foundations for psychology, and hence for more appropriate treatment and management of psychiatric illness. However, fundamental issues regarding the construction of testable mechanistic models using imaging data require careful consideration. This chapter summarizes the characteristics of acceptable models of brain function and provides concise descriptions of the relevant types of neuroimaging data that have recently become available. Approaches to data-driven experiments and analyses are described that may lead to more realistic conceptions of the competences of neural assemblages, as they vary across the brain's complex neuroanatomy. © 2017 Elsevier B.V. All rights reserved.

Simultaneous two-photon imaging of cerebral oxygenation and capillary blood flow in atherosclerotic mice

NASA Astrophysics Data System (ADS)

Lu, Xuecong; Li, Baoqiang; Moeini, Mohammad; Lesage, Frédéric

2017-02-01

Gradual changes in brain microvasculature and cerebral capillary blood flow occurring with atherosclerosis may significantly contribute to cognition decline due to their role in brain tissue oxygenation. However, previous stud- ies of the relationship between cerebral capillary blood flow and brain tissue oxygenation are limited. This study aimed to investigate vascular and concomitant changes in brain tissue pO2 with atherosclerosis. Experiments in young healthy C57B1/6 mice (n=6 , WT), young atherosclerotic mice (n=6 , ATX Y) and old atherosclerotic mice (n=6 , ATX O) were performed imaging on the left sensory-motor cortex at resting state under urethane (1.5 g/kg) anesthesia using two-photon fluorescence microscopy. The results showed that pO2 around capillaries, correlated with red blood cell (RBC) flux, increased with atherosclerosis.

Neurophenomenology of an Altered State of Consciousness: An fMRI Case Study.

PubMed

Modestino, Edward J

2016-01-01

A research participant came to our lab with self-proclaimed, ecstatic, Kundalini meditative experiences. Using neurophenomenology and functional magnetic resonance imaging (fMRI), we were able to identify brain activation in the left prefrontal cortex [primarily in left Brodmann׳s areas (BAs) 46 and 10, but also extending into BAs 11, 47, and 45] associated with this experience. The Phenomenology of Consciousness Inventory provided evidence that this was a perceived altered state of consciousness. Additionally, the Physio-Kundalini Syndrome Index strongly suggested that what he was experiencing was indeed Kundalini. The feelings of joy, happiness and the left prefrontal brain region found in this study are consistent with many published neuroimaging and electrophysiological studies of meditation. This case study suggests that using first-person subjective experience within a phenomenological reduction process can be combined with neuroimaging to divulge objective brain regions associated with such experiences. Furthermore, this provides evidence that at least in this participant, the Kundalini experience is associated with brain activation in the left prefrontal cortex. Future research is needed to confirm these results in a large group study, perhaps contrasting brain activation of those who experience spontaneously emerging Kundalini with trained Kundalini practitioners. Copyright © 2016 Elsevier Inc. All rights reserved.

Neuroimaging in repetitive brain trauma

PubMed Central

2014-01-01

Sports-related concussions are one of the major causes of mild traumatic brain injury. Although most patients recover completely within days to weeks, those who experience repetitive brain trauma (RBT) may be at risk for developing a condition known as chronic traumatic encephalopathy (CTE). While this condition is most commonly observed in athletes who experience repetitive concussive and/or subconcussive blows to the head, such as boxers, football players, or hockey players, CTE may also affect soldiers on active duty. Currently, the only means by which to diagnose CTE is by the presence of phosphorylated tau aggregations post-mortem. Non-invasive neuroimaging, however, may allow early diagnosis as well as improve our understanding of the underlying pathophysiology of RBT. The purpose of this article is to review advanced neuroimaging methods used to investigate RBT, including diffusion tensor imaging, magnetic resonance spectroscopy, functional magnetic resonance imaging, susceptibility weighted imaging, and positron emission tomography. While there is a considerable literature using these methods in brain injury in general, the focus of this review is on RBT and those subject populations currently known to be susceptible to RBT, namely athletes and soldiers. Further, while direct detection of CTE in vivo has not yet been achieved, all of the methods described in this review provide insight into RBT and will likely lead to a better characterization (diagnosis), in vivo, of CTE than measures of self-report. PMID:25031630

An Automated Platform for High-Resolution Tissue Imaging Using Nanospray Desorption Electrospray Ionization Mass Spectrometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lanekoff, Ingela T.; Heath, Brandi S.; Liyu, Andrey V.

2012-10-02

An automated platform has been developed for acquisition and visualization of mass spectrometry imaging (MSI) data using nanospray desorption electrospray ionization (nano-DESI). The new system enables robust operation of the nano-DESI imaging source over many hours. This is achieved by controlling the distance between the sample and the probe by mounting the sample holder onto an automated XYZ stage and defining the tilt of the sample plane. This approach is useful for imaging of relatively flat samples such as thin tissue sections. Custom software called MSI QuickView was developed for visualization of large data sets generated in imaging experiments. MSImore » QuickView enables fast visualization of the imaging data during data acquisition and detailed processing after the entire image is acquired. The performance of the system is demonstrated by imaging rat brain tissue sections. High resolution mass analysis combined with MS/MS experiments enabled identification of lipids and metabolites in the tissue section. In addition, high dynamic range and sensitivity of the technique allowed us to generate ion images of low-abundance isobaric lipids. High-spatial resolution image acquired over a small region of the tissue section revealed the spatial distribution of an abundant brain metabolite, creatine, in the white and gray matter that is consistent with the literature data obtained using magnetic resonance spectroscopy.« less

Natural image classification driven by human brain activity

NASA Astrophysics Data System (ADS)

Zhang, Dai; Peng, Hanyang; Wang, Jinqiao; Tang, Ming; Xue, Rong; Zuo, Zhentao

2016-03-01

Natural image classification has been a hot topic in computer vision and pattern recognition research field. Since the performance of an image classification system can be improved by feature selection, many image feature selection methods have been developed. However, the existing supervised feature selection methods are typically driven by the class label information that are identical for different samples from the same class, ignoring with-in class image variability and therefore degrading the feature selection performance. In this study, we propose a novel feature selection method, driven by human brain activity signals collected using fMRI technique when human subjects were viewing natural images of different categories. The fMRI signals associated with subjects viewing different images encode the human perception of natural images, and therefore may capture image variability within- and cross- categories. We then select image features with the guidance of fMRI signals from brain regions with active response to image viewing. Particularly, bag of words features based on GIST descriptor are extracted from natural images for classification, and a sparse regression base feature selection method is adapted to select image features that can best predict fMRI signals. Finally, a classification model is built on the select image features to classify images without fMRI signals. The validation experiments for classifying images from 4 categories of two subjects have demonstrated that our method could achieve much better classification performance than the classifiers built on image feature selected by traditional feature selection methods.

Comparison of two freely available software packages for mass spectrometry imaging data analysis using brains from morphine addicted rats.

PubMed

Bodzon-Kulakowska, Anna; Marszalek-Grabska, Marta; Antolak, Anna; Drabik, Anna; Kotlinska, Jolanta H; Suder, Piotr

Data analysis from mass spectrometry imaging (MSI) imaging experiments is a very complex task. Most of the software packages devoted to this purpose are designed by the mass spectrometer manufacturers and, thus, are not freely available. Laboratories developing their own MS-imaging sources usually do not have access to the commercial software, and they must rely on the freely available programs. The most recognized ones are BioMap, developed by Novartis under Interactive Data Language (IDL), and Datacube, developed by the Dutch Foundation for Fundamental Research of Matter (FOM-Amolf). These two systems were used here for the analysis of images received from rat brain tissues subjected to morphine influence and their capabilities were compared in terms of ease of use and the quality of obtained results.

Synaesthetic colour in the brain: beyond colour areas. A functional magnetic resonance imaging study of synaesthetes and matched controls.

PubMed

van Leeuwen, Tessa M; Petersson, Karl Magnus; Hagoort, Peter

2010-08-10

In synaesthesia, sensations in a particular modality cause additional experiences in a second, unstimulated modality (e.g., letters elicit colour). Understanding how synaesthesia is mediated in the brain can help to understand normal processes of perceptual awareness and multisensory integration. In several neuroimaging studies, enhanced brain activity for grapheme-colour synaesthesia has been found in ventral-occipital areas that are also involved in real colour processing. Our question was whether the neural correlates of synaesthetically induced colour and real colour experience are truly shared. First, in a free viewing functional magnetic resonance imaging (fMRI) experiment, we located main effects of synaesthesia in left superior parietal lobule and in colour related areas. In the left superior parietal lobe, individual differences between synaesthetes (projector-associator distinction) also influenced brain activity, confirming the importance of the left superior parietal lobe for synaesthesia. Next, we applied a repetition suppression paradigm in fMRI, in which a decrease in the BOLD (blood-oxygenated-level-dependent) response is generally observed for repeated stimuli. We hypothesized that synaesthetically induced colours would lead to a reduction in BOLD response for subsequently presented real colours, if the neural correlates were overlapping. We did find BOLD suppression effects induced by synaesthesia, but not within the colour areas. Because synaesthetically induced colours were not able to suppress BOLD effects for real colour, we conclude that the neural correlates of synaesthetic colour experience and real colour experience are not fully shared. We propose that synaesthetic colour experiences are mediated by higher-order visual pathways that lie beyond the scope of classical, ventral-occipital visual areas. Feedback from these areas, in which the left parietal cortex is likely to play an important role, may induce V4 activation and the percept of synaesthetic colour.

Different early rearing experiences have long term effects on cortical organization in captive chimpanzees (Pan troglodytes)

PubMed Central

Bogart, Stephanie L.; Bennett, Allyson J.; Schapiro, Steven J.; Reamer, Lisa A.; Hopkins, William D.

2014-01-01

Consequences of rearing history in chimpanzees (Pan troglodytes) have been explored in relation to behavioral abnormalities and cognition, however, little is known about the effects of rearing conditions on anatomical brain development. Human studies have revealed that experiences of maltreatment and neglect during infancy and childhood can have detrimental effects on brain development and cognition. In this study, we evaluated the effects of early rearing experience on brain morphology in 92 captive chimpanzees (ages 11-43) who were either reared by their mothers (n = 46) or in a nursery (n = 46) with age-group peers. Magnetic resonance brain images were analyzed with a processing program (BrainVISA) that extracts cortical sulci. We obtained various measurements from 11 sulci located throughout the brain, as well as whole brain gyrification and white and grey matter volumes. We found that mother-reared chimpanzees have greater global white-to-grey matter volume, more cortical folding and thinner grey matter within the cortical folds than nursery-reared animals. The findings reported here are the first to demonstrate that differences in early rearing conditions have significant consequences on brain morphology in chimpanzees and suggests potential differences in the development of white matter expansion and myelination. PMID:24206013

Different early rearing experiences have long-term effects on cortical organization in captive chimpanzees (Pan troglodytes).

PubMed

Bogart, Stephanie L; Bennett, Allyson J; Schapiro, Steven J; Reamer, Lisa A; Hopkins, William D

2014-03-01

Consequences of rearing history in chimpanzees (Pan troglodytes) have been explored in relation to behavioral abnormalities and cognition; however, little is known about the effects of rearing conditions on anatomical brain development. Human studies have revealed that experiences of maltreatment and neglect during infancy and childhood can have detrimental effects on brain development and cognition. In this study, we evaluated the effects of early rearing experience on brain morphology in 92 captive chimpanzees (ages 11-43) who were either reared by their mothers (n = 46) or in a nursery (n = 46) with age-group peers. Magnetic resonance brain images were analyzed with a processing program (BrainVISA) that extracts cortical sulci. We obtained various measurements from 11 sulci located throughout the brain, as well as whole brain gyrification and white and grey matter volumes. We found that mother-reared chimpanzees have greater global white-to-grey matter volume, more cortical folding and thinner grey matter within the cortical folds than nursery-reared animals. The findings reported here are the first to demonstrate that differences in early rearing conditions have significant consequences on brain morphology in chimpanzees and suggests potential differences in the development of white matter expansion and myelination. © 2013 John Wiley & Sons Ltd.

The Road to FUNCTIONAL IMAGING and ULTRAHIGH FIELDS

PubMed Central

Uğurbil, Kâmil

2012-01-01

The Center for Magnetic Resonance (CMRR) at the University of Minnesota was one of laboratories where the work that simultaneously and independently introduced functional magnetic resonance imaging (fMRI) of human brain activity was carried out. However, unlike other laboratories pursuing fMRI at the time, our work was performed at 4 Tesla magnetic field and coincided with the effort to push human magnetic resonance imaging to field strength significantly beyond 1.5 Tesla which was the high-end standard of the time. The human fMRI experiments performed in CMRR were planned between two colleagues who had known each other and had worked together previously in Bell Laboratories, namely Seiji Ogawa and myself, immediately after the Blood Oxygenation Level Dependent (BOLD) contrast was developed by Seiji. We were waiting for our first human system, a 4 Tesla system, to arrive in order to attempt at imaging brain activity in the human brain and these were the first experiments we performed on the 4 Tesla instrument in CMRR when it became marginally operational. This was a prelude to a subsequent systematic push we initiated for exploiting higher magnetic fields to improve the accuracy and sensitivity of fMRI maps, first going to 9.4 Tesla for animal model studies and subsequently developing a 7 Tesla human system for the first time. Steady improvements in high field instrumentation and ever expanding armamentarium of image acquisition and engineering solutions to challenges posed by ultrahigh fields has brought fMRI to submillimeter resolution in the whole brain at 7 Tesla, the scale necessary to reach cortical columns and laminar differentiation in the whole brain. The solutions that emerged in response to technological challenges posed by 7 Tesla also propagated and continues to propagate to lower field clinical systems, a major advantage of the ultrahigh fields effort that is underappreciated. Further improvements at 7T are inevitable. Further translation of these improvements to lower field clinical systems to achieve new capabilities and to magnetic fields significantly higher than 7 Tesla to enable human imaging is inescapable. PMID:22333670

Neuroimaging of the Injured Pediatric Brain: Methods and New Lessons.

PubMed

Dennis, Emily L; Babikian, Talin; Giza, Christopher C; Thompson, Paul M; Asarnow, Robert F

2018-02-01

Traumatic brain injury (TBI) is a significant public health problem in the United States, especially for children and adolescents. Current epidemiological data estimate over 600,000 patients younger than 20 years are treated for TBI in emergency rooms annually. While many patients experience a full recovery, for others there can be long-lasting cognitive, neurological, psychological, and behavioral disruptions. TBI in youth can disrupt ongoing brain development and create added family stress during a formative period. The neuroimaging methods used to assess brain injury improve each year, providing researchers a more detailed characterization of the injury and recovery process. In this review, we cover current imaging methods used to quantify brain disruption post-injury, including structural magnetic resonance imaging (MRI), diffusion MRI, functional MRI, resting state fMRI, and magnetic resonance spectroscopy (MRS), with brief coverage of other methods, including electroencephalography (EEG), single-photon emission computed tomography (SPECT), and positron emission tomography (PET). We include studies focusing on pediatric moderate-severe TBI from 2 months post-injury and beyond. While the morbidity of pediatric TBI is considerable, continuing advances in imaging methods have the potential to identify new treatment targets that can lead to significant improvements in outcome.

Paramagnetic perfluorocarbon-filled albumin-(Gd-DTPA) microbubbles for the induction of focused-ultrasound-induced blood-brain barrier opening and concurrent MR and ultrasound imaging

NASA Astrophysics Data System (ADS)

Liao, Ai-Ho; Liu, Hao-Li; Su, Chia-Hao; Hua, Mu-Yi; Yang, Hung-Wei; Weng, Yu-Ting; Hsu, Po-Hung; Huang, Sheng-Min; Wu, Shih-Yen; Wang, Hsin-Ell; Yen, Tzu-Chen; Li, Pai-Chi

2012-05-01

This paper presents new albumin-shelled Gd-DTPA microbubbles (MBs) that can concurrently serve as a dual-modality contrast agent for ultrasound (US) imaging and magnetic resonance (MR) imaging to assist blood-brain barrier (BBB) opening and detect intracerebral hemorrhage (ICH) during focused ultrasound brain drug delivery. Perfluorocarbon-filled albumin-(Gd-DTPA) MBs were prepared with a mean diameter of 2320 nm and concentration of 2.903×109 MBs ml-1 using albumin-(Gd-DTPA) and by sonication with perfluorocarbon (C3F8) gas. The albumin-(Gd-DTPA) MBs were then centrifuged and the procedure was repeated until the free Gd3+ ions were eliminated (which were detected by the xylenol orange sodium salt solution). The albumin-(Gd-DTPA) MBs were also characterized and evaluated both in vitro and in vivo by US and MR imaging. Focused US was used with the albumin-(Gd-DTPA) MBs to induce disruption of the BBB in 18 rats. BBB disruption was confirmed with contrast-enhanced T1-weighted turbo-spin-echo sequence MR imaging. Heavy T2*-weighted 3D fast low-angle shot sequence MR imaging was used to detect ICH. In vitro US imaging experiments showed that albumin-(Gd-DTPA) MBs can significantly enhance the US contrast in T1-, T2- and T2*-weighted MR images. The r1 and r2 relaxivities for Gd-DTPA were 7.69 and 21.35 s-1mM-1, respectively, indicating that the MBs represent a positive contrast agent in T1-weighted images. In vivo MR imaging experiments on 18 rats showed that focused US combined with albumin-(Gd-DTPA) MBs can be used to both induce disruption of the BBB and detect ICH. To compare the signal intensity change between pure BBB opening and BBB opening accompanying ICH, albumin-(Gd-DTPA) MB imaging can provide a ratio of 5.14 with significant difference (p = 0.026), whereas Gd-DTPA imaging only provides a ratio of 2.13 and without significant difference (p = 0.108). The results indicate that albumin-(Gd-DTPA) MBs have potential as a US/MR dual-modality contrast agent for BBB opening and differentiating focused-US-induced BBB opening from ICH, and can monitor the focused ultrasound brain drug delivery process.

Paramagnetic perfluorocarbon-filled albumin-(Gd-DTPA) microbubbles for the induction of focused-ultrasound-induced blood-brain barrier opening and concurrent MR and ultrasound imaging.

PubMed

Liao, Ai-Ho; Liu, Hao-Li; Su, Chia-Hao; Hua, Mu-Yi; Yang, Hung-Wei; Weng, Yu-Ting; Hsu, Po-Hung; Huang, Sheng-Min; Wu, Shih-Yen; Wang, Hsin-Ell; Yen, Tzu-Chen; Li, Pai-Chi

2012-05-07

This paper presents new albumin-shelled Gd-DTPA microbubbles (MBs) that can concurrently serve as a dual-modality contrast agent for ultrasound (US) imaging and magnetic resonance (MR) imaging to assist blood-brain barrier (BBB) opening and detect intracerebral hemorrhage (ICH) during focused ultrasound brain drug delivery. Perfluorocarbon-filled albumin-(Gd-DTPA) MBs were prepared with a mean diameter of 2320 nm and concentration of 2.903×10(9) MBs ml(-1) using albumin-(Gd-DTPA) and by sonication with perfluorocarbon (C(3)F(8)) gas. The albumin-(Gd-DTPA) MBs were then centrifuged and the procedure was repeated until the free Gd(3+) ions were eliminated (which were detected by the xylenol orange sodium salt solution). The albumin-(Gd-DTPA) MBs were also characterized and evaluated both in vitro and in vivo by US and MR imaging. Focused US was used with the albumin-(Gd-DTPA) MBs to induce disruption of the BBB in 18 rats. BBB disruption was confirmed with contrast-enhanced T(1)-weighted turbo-spin-echo sequence MR imaging. Heavy T(2)*-weighted 3D fast low-angle shot sequence MR imaging was used to detect ICH. In vitro US imaging experiments showed that albumin-(Gd-DTPA) MBs can significantly enhance the US contrast in T(1)-, T(2)- and T(2)*-weighted MR images. The r(1) and r(2) relaxivities for Gd-DTPA were 7.69 and 21.35 s(-1)mM(-1), respectively, indicating that the MBs represent a positive contrast agent in T(1)-weighted images. In vivo MR imaging experiments on 18 rats showed that focused US combined with albumin-(Gd-DTPA) MBs can be used to both induce disruption of the BBB and detect ICH. To compare the signal intensity change between pure BBB opening and BBB opening accompanying ICH, albumin-(Gd-DTPA) MB imaging can provide a ratio of 5.14 with significant difference (p = 0.026), whereas Gd-DTPA imaging only provides a ratio of 2.13 and without significant difference (p = 0.108). The results indicate that albumin-(Gd-DTPA) MBs have potential as a US/MR dual-modality contrast agent for BBB opening and differentiating focused-US-induced BBB opening from ICH, and can monitor the focused ultrasound brain drug delivery process.

Planar implantable sensor for in vivo measurement of cellular oxygen metabolism in brain tissue.

PubMed

Tsytsarev, Vassiliy; Akkentli, Fatih; Pumbo, Elena; Tang, Qinggong; Chen, Yu; Erzurumlu, Reha S; Papkovsky, Dmitri B

2017-04-01

Brain imaging methods are continually improving. Imaging of the cerebral cortex is widely used in both animal experiments and charting human brain function in health and disease. Among the animal models, the rodent cerebral cortex has been widely used because of patterned neural representation of the whiskers on the snout and relative ease of activating cortical tissue with whisker stimulation. We tested a new planar solid-state oxygen sensor comprising a polymeric film with a phosphorescent oxygen-sensitive coating on the working side, to monitor dynamics of oxygen metabolism in the cerebral cortex following sensory stimulation. Sensory stimulation led to changes in oxygenation and deoxygenation processes of activated areas in the barrel cortex. We demonstrate the possibility of dynamic mapping of relative changes in oxygenation in live mouse brain tissue with such a sensor. Oxygenation-based functional magnetic resonance imaging (fMRI) is very effective method for functional brain mapping but have high costs and limited spatial resolution. Optical imaging of intrinsic signal (IOS) does not provide the required sensitivity, and voltage-sensitive dye optical imaging (VSDi) has limited applicability due to significant toxicity of the voltage-sensitive dye. Our planar solid-state oxygen sensor imaging approach circumvents these limitations, providing a simple optical contrast agent with low toxicity and rapid application. The planar solid-state oxygen sensor described here can be used as a tool in visualization and real-time analysis of sensory-evoked neural activity in vivo. Further, this approach allows visualization of local neural activity with high temporal and spatial resolution. Copyright © 2017 Elsevier B.V. All rights reserved.

Shear Shock Waves Observed in the Brain

NASA Astrophysics Data System (ADS)

Espíndola, David; Lee, Stephen; Pinton, Gianmarco

2017-10-01

The internal deformation of the brain is far more complex than the rigid motion of the skull. An ultrasound imaging technique that we have developed has a combination of penetration, frame-rate, and motion-detection accuracy required to directly observe the formation and evolution of shear shock waves in the brain. Experiments at low impacts on the traumatic-brain-injury scale demonstrate that they are spontaneously generated and propagate within the porcine brain. Compared to the initially smooth impact, the acceleration at the shock front is amplified up to a factor of 8.5. This highly localized increase in acceleration suggests that shear shock waves are a previously unappreciated mechanism that could play a significant role in traumatic brain injury.

Intraoperative brain hemodynamic response assessment with real-time hyperspectral optical imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Laurence, Audrey; Pichette, Julien; Angulo-Rodríguez, Leticia M.; Saint Pierre, Catherine; Lesage, Frédéric; Bouthillier, Alain; Nguyen, Dang Khoa; Leblond, Frédéric

2016-03-01

Following normal neuronal activity, there is an increase in cerebral blood flow and cerebral blood volume to provide oxygenated hemoglobin to active neurons. For abnormal activity such as epileptiform discharges, this hemodynamic response may be inadequate to meet the high metabolic demands. To verify this hypothesis, we developed a novel hyperspectral imaging system able to monitor real-time cortical hemodynamic changes during brain surgery. The imaging system is directly integrated into a surgical microscope, using the white-light source for illumination. A snapshot hyperspectral camera is used for detection (4x4 mosaic filter array detecting 16 wavelengths simultaneously). We present calibration experiments where phantoms made of intralipid and food dyes were imaged. Relative concentrations of three dyes were recovered at a video rate of 30 frames per second. We also present hyperspectral recordings during brain surgery of epileptic patients with concurrent electrocorticography recordings. Relative concentration maps of oxygenated and deoxygenated hemoglobin were extracted from the data, allowing real-time studies of hemodynamic changes with a good spatial resolution. Finally, we present preliminary results on phantoms obtained with an integrated spatial frequency domain imaging system to recover tissue optical properties. This additional module, used together with the hyperspectral imaging system, will allow quantification of hemoglobin concentrations maps. Our hyperspectral imaging system offers a new tool to analyze hemodynamic changes, especially in the case of epileptiform discharges. It also offers an opportunity to study brain connectivity by analyzing correlations between hemodynamic responses of different tissue regions.

VoxResNet: Deep voxelwise residual networks for brain segmentation from 3D MR images.

PubMed

Chen, Hao; Dou, Qi; Yu, Lequan; Qin, Jing; Heng, Pheng-Ann

2018-04-15

Segmentation of key brain tissues from 3D medical images is of great significance for brain disease diagnosis, progression assessment and monitoring of neurologic conditions. While manual segmentation is time-consuming, laborious, and subjective, automated segmentation is quite challenging due to the complicated anatomical environment of brain and the large variations of brain tissues. We propose a novel voxelwise residual network (VoxResNet) with a set of effective training schemes to cope with this challenging problem. The main merit of residual learning is that it can alleviate the degradation problem when training a deep network so that the performance gains achieved by increasing the network depth can be fully leveraged. With this technique, our VoxResNet is built with 25 layers, and hence can generate more representative features to deal with the large variations of brain tissues than its rivals using hand-crafted features or shallower networks. In order to effectively train such a deep network with limited training data for brain segmentation, we seamlessly integrate multi-modality and multi-level contextual information into our network, so that the complementary information of different modalities can be harnessed and features of different scales can be exploited. Furthermore, an auto-context version of the VoxResNet is proposed by combining the low-level image appearance features, implicit shape information, and high-level context together for further improving the segmentation performance. Extensive experiments on the well-known benchmark (i.e., MRBrainS) of brain segmentation from 3D magnetic resonance (MR) images corroborated the efficacy of the proposed VoxResNet. Our method achieved the first place in the challenge out of 37 competitors including several state-of-the-art brain segmentation methods. Our method is inherently general and can be readily applied as a powerful tool to many brain-related studies, where accurate segmentation of brain structures is critical. Copyright © 2017 Elsevier Inc. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Pei-Hsin; Chung, Hsiao-Wen; Tsai, Ping-Huei

Purpose: One of the technical advantages of functional magnetic resonance imaging (fMRI) is its precise localization of changes from neuronal activities. While current practice of fMRI acquisition at voxel size around 3 × 3 × 3 mm{sup 3} achieves satisfactory results in studies of basic brain functions, higher spatial resolution is required in order to resolve finer cortical structures. This study investigated spatial resolution effects on brain fMRI experiments using balanced steady-state free precession (bSSFP) imaging with 0.37 mm{sup 3} voxel volume at 3.0 T. Methods: In fMRI experiments, full and unilateral visual field 5 Hz flashing checkerboard stimulations weremore » given to healthy subjects. The bSSFP imaging experiments were performed at three different frequency offsets to widen the coverage, with functional activations in the primary visual cortex analyzed using the general linear model. Variations of the spatial resolution were achieved by removing outerk-space data components. Results: Results show that a reduction in voxel volume from 3.44 × 3.44 × 2 mm{sup 3} to 0.43 × 0.43 × 2 mm{sup 3} has resulted in an increase of the functional activation signals from (7.7 ± 1.7)% to (20.9 ± 2.0)% at 3.0 T, despite of the threefold SNR decreases in the original images, leading to nearly invariant functional contrast-to-noise ratios (fCNR) even at high spatial resolution. Activation signals aligning nicely with gray matter sulci at high spatial resolution would, on the other hand, have possibly been mistaken as noise at low spatial resolution. Conclusions: It is concluded that the bSSFP sequence is a plausible technique for fMRI investigations at submillimeter voxel widths without compromising fCNR. The reduction of partial volume averaging with nonactivated brain tissues to retain fCNR is uniquely suitable for high spatial resolution applications such as the resolving of columnar organization in the brain.« less

Reading visually embodied meaning from the brain: Visually grounded computational models decode visual-object mental imagery induced by written text.

PubMed

Anderson, Andrew James; Bruni, Elia; Lopopolo, Alessandro; Poesio, Massimo; Baroni, Marco

2015-10-15

Embodiment theory predicts that mental imagery of object words recruits neural circuits involved in object perception. The degree of visual imagery present in routine thought and how it is encoded in the brain is largely unknown. We test whether fMRI activity patterns elicited by participants reading objects' names include embodied visual-object representations, and whether we can decode the representations using novel computational image-based semantic models. We first apply the image models in conjunction with text-based semantic models to test predictions of visual-specificity of semantic representations in different brain regions. Representational similarity analysis confirms that fMRI structure within ventral-temporal and lateral-occipital regions correlates most strongly with the image models and conversely text models correlate better with posterior-parietal/lateral-temporal/inferior-frontal regions. We use an unsupervised decoding algorithm that exploits commonalities in representational similarity structure found within both image model and brain data sets to classify embodied visual representations with high accuracy (8/10) and then extend it to exploit model combinations to robustly decode different brain regions in parallel. By capturing latent visual-semantic structure our models provide a route into analyzing neural representations derived from past perceptual experience rather than stimulus-driven brain activity. Our results also verify the benefit of combining multimodal data to model human-like semantic representations. Copyright © 2015 Elsevier Inc. All rights reserved.

Monitoring of injury induced brain regeneration of the adult zebrafish by using optical coherence tomography

NASA Astrophysics Data System (ADS)

Yuan, Zhen; Zhang, Jian

2018-02-01

The adult zebrafish has pronounced regenerative capacity of the brain, which makes it an ideal model organism of vertebrate biology for the investigation of recovery of central nervous system injuries. The aim of this study was to employ spectral-domain optical coherence tomography (SD-OCT) system for long-term in vivo monitoring of tissue regeneration using an adult zebrafish model of brain injury. Based on a 1325 nm light source and two high-speed galvo mirrors, the SD-OCT system can offer a large field of view of the three-dimensional (3D) brain structures with high imaging resolution (12 μm axial and 13 μm lateral) at video rate. In vivo experiments based on this system were conducted to monitor the regeneration process of zebrafish brain after injury during a period of 43 days. To monitor and detect the process of tissue regeneration, we performed 3D in vivo imaging in a zebrafish model of adult brain injury during a period of 43 days. The coronal and sagittal views of the injured zebrafish brain at each time point (0 days, 10 days, 20 days and 43 days postlesion) were presented to show the changes of the brain lesion in detail. In addition, the 3D SD-OCT images for an injured zebrafish brain were also reconstructed at days 0 and days 43 post-lesion. We found that SD-OCT is able to effectively and noninvasively monitor the regeneration of the adult zebrafish brain after injury in real time with high 3D spatial resolution and good penetration depth. Our findings also suggested that the adult zebrafish has the extraordinary capability of brain regeneration and is able to repair itself after brain injury.

Markerless rat head motion tracking using structured light for brain PET imaging of unrestrained awake small animals

NASA Astrophysics Data System (ADS)

Miranda, Alan; Staelens, Steven; Stroobants, Sigrid; Verhaeghe, Jeroen

2017-03-01

Preclinical positron emission tomography (PET) imaging in small animals is generally performed under anesthesia to immobilize the animal during scanning. More recently, for rat brain PET studies, methods to perform scans of unrestrained awake rats are being developed in order to avoid the unwanted effects of anesthesia on the brain response. Here, we investigate the use of a projected structure stereo camera to track the motion of the rat head during the PET scan. The motion information is then used to correct the PET data. The stereo camera calculates a 3D point cloud representation of the scene and the tracking is performed by point cloud matching using the iterative closest point algorithm. The main advantage of the proposed motion tracking is that no intervention, e.g. for marker attachment, is needed. A manually moved microDerenzo phantom experiment and 3 awake rat [18F]FDG experiments were performed to evaluate the proposed tracking method. The tracking accuracy was 0.33 mm rms. After motion correction image reconstruction, the microDerenzo phantom was recovered albeit with some loss of resolution. The reconstructed FWHM of the 2.5 and 3 mm rods increased with 0.94 and 0.51 mm respectively in comparison with the motion-free case. In the rat experiments, the average tracking success rate was 64.7%. The correlation of relative brain regional [18F]FDG uptake between the anesthesia and awake scan reconstructions was increased from on average 0.291 (not significant) before correction to 0.909 (p  <  0.0001) after motion correction. Markerless motion tracking using structured light can be successfully used for tracking of the rat head for motion correction in awake rat PET scans.

Real-time strategy video game experience and structural connectivity - A diffusion tensor imaging study.

PubMed

Kowalczyk, Natalia; Shi, Feng; Magnuski, Mikolaj; Skorko, Maciek; Dobrowolski, Pawel; Kossowski, Bartosz; Marchewka, Artur; Bielecki, Maksymilian; Kossut, Malgorzata; Brzezicka, Aneta

2018-06-20

Experienced video game players exhibit superior performance in visuospatial cognition when compared to non-players. However, very little is known about the relation between video game experience and structural brain plasticity. To address this issue, a direct comparison of the white matter brain structure in RTS (real time strategy) video game players (VGPs) and non-players (NVGPs) was performed. We hypothesized that RTS experience can enhance connectivity within and between occipital and parietal regions, as these regions are likely to be involved in the spatial and visual abilities that are trained while playing RTS games. The possible influence of long-term RTS game play experience on brain structural connections was investigated using diffusion tensor imaging (DTI) and a region of interest (ROI) approach in order to describe the experience-related plasticity of white matter. Our results revealed significantly more total white matter connections between occipital and parietal areas and within occipital areas in RTS players compared to NVGPs. Additionally, the RTS group had an altered topological organization of their structural network, expressed in local efficiency within the occipito-parietal subnetwork. Furthermore, the positive association between network metrics and time spent playing RTS games suggests a close relationship between extensive, long-term RTS game play and neuroplastic changes. These results indicate that long-term and extensive RTS game experience induces alterations along axons that link structures of the occipito-parietal loop involved in spatial and visual processing. © 2018 Wiley Periodicals, Inc.

Toward A Brain-Based Theory of Beauty

PubMed Central

Ishizu, Tomohiro; Zeki, Semir

2011-01-01

We wanted to learn whether activity in the same area(s) of the brain correlate with the experience of beauty derived from different sources. 21 subjects took part in a brain-scanning experiment using functional magnetic resonance imaging. Prior to the experiment, they viewed pictures of paintings and listened to musical excerpts, both of which they rated on a scale of 1–9, with 9 being the most beautiful. This allowed us to select three sets of stimuli–beautiful, indifferent and ugly–which subjects viewed and heard in the scanner, and rated at the end of each presentation. The results of a conjunction analysis of brain activity showed that, of the several areas that were active with each type of stimulus, only one cortical area, located in the medial orbito-frontal cortex (mOFC), was active during the experience of musical and visual beauty, with the activity produced by the experience of beauty derived from either source overlapping almost completely within it. The strength of activation in this part of the mOFC was proportional to the strength of the declared intensity of the experience of beauty. We conclude that, as far as activity in the brain is concerned, there is a faculty of beauty that is not dependent on the modality through which it is conveyed but which can be activated by at least two sources–musical and visual–and probably by other sources as well. This has led us to formulate a brain-based theory of beauty. PMID:21755004

Toward a brain-based theory of beauty.

PubMed

Ishizu, Tomohiro; Zeki, Semir

2011-01-01

We wanted to learn whether activity in the same area(s) of the brain correlate with the experience of beauty derived from different sources. 21 subjects took part in a brain-scanning experiment using functional magnetic resonance imaging. Prior to the experiment, they viewed pictures of paintings and listened to musical excerpts, both of which they rated on a scale of 1-9, with 9 being the most beautiful. This allowed us to select three sets of stimuli--beautiful, indifferent and ugly--which subjects viewed and heard in the scanner, and rated at the end of each presentation. The results of a conjunction analysis of brain activity showed that, of the several areas that were active with each type of stimulus, only one cortical area, located in the medial orbito-frontal cortex (mOFC), was active during the experience of musical and visual beauty, with the activity produced by the experience of beauty derived from either source overlapping almost completely within it. The strength of activation in this part of the mOFC was proportional to the strength of the declared intensity of the experience of beauty. We conclude that, as far as activity in the brain is concerned, there is a faculty of beauty that is not dependent on the modality through which it is conveyed but which can be activated by at least two sources--musical and visual--and probably by other sources as well. This has led us to formulate a brain-based theory of beauty.

Dorsomedial prefontal cortex supports spontaneous thinking per se.

PubMed

Raij, T T; Riekki, T J J

2017-06-01

Spontaneous thinking, an action to produce, consider, integrate, and reason through mental representations, is central to our daily experience and has been suggested to serve crucial adaptive purposes. Such thinking occurs among other experiences during mind wandering that is associated with activation of the default mode network among other brain circuitries. Whether and how such brain activation is linked to the experience of spontaneous thinking per se remains poorly known. We studied 51 healthy subjects using a comprehensive experience-sampling paradigm during 3T functional magnetic resonance imaging. In comparison with fixation, the experiences of spontaneous thinking and spontaneous perception were related to activation of wide-spread brain circuitries, including the cortical midline structures, the anterior cingulate cortex and the visual cortex. In direct comparison of the spontaneous thinking versus spontaneous perception, activation was observed in the anterior dorsomedial prefrontal cortex. Modality congruence of spontaneous-experience-related brain activation was suggested by several findings, including association of the lingual gyrus with visual in comparison with non-verbal-non-visual thinking. In the context of current literature, these findings suggest that the cortical midline structures are involved in the integrative core substrate of spontaneous thinking that is coupled with other brain systems depending on the characteristics of thinking. Furthermore, involvement of the anterior dorsomedial prefrontal cortex suggests the control of high-order abstract functions to characterize spontaneous thinking per se. Hum Brain Mapp 38:3277-3288, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

A mathematical theory of shape and neuro-fuzzy methodology-based diagnostic analysis: a comparative study on early detection and treatment planning of brain cancer.

PubMed

Kar, Subrata; Majumder, D Dutta

2017-08-01

Investigation of brain cancer can detect the abnormal growth of tissue in the brain using computed tomography (CT) scans and magnetic resonance (MR) images of patients. The proposed method classifies brain cancer on shape-based feature extraction as either benign or malignant. The authors used input variables such as shape distance (SD) and shape similarity measure (SSM) in fuzzy tools, and used fuzzy rules to evaluate the risk status as an output variable. We presented a classifier neural network system (NNS), namely Levenberg-Marquardt (LM), which is a feed-forward back-propagation learning algorithm used to train the NN for the status of brain cancer, if any, and which achieved satisfactory performance with 100% accuracy. The proposed methodology is divided into three phases. First, we find the region of interest (ROI) in the brain to detect the tumors using CT and MR images. Second, we extract the shape-based features, like SD and SSM, and grade the brain tumors as benign or malignant with the concept of SD function and SSM as shape-based parameters. Third, we classify the brain cancers using neuro-fuzzy tools. In this experiment, we used a 16-sample database with SSM (μ) values and classified the benignancy or malignancy of the brain tumor lesions using the neuro-fuzzy system (NFS). We have developed a fuzzy expert system (FES) and NFS for early detection of brain cancer from CT and MR images. In this experiment, shape-based features, such as SD and SSM, were extracted from the ROI of brain tumor lesions. These shape-based features were considered as input variables and, using fuzzy rules, we were able to evaluate brain cancer risk values for each case. We used an NNS with LM, a feed-forward back-propagation learning algorithm, as a classifier for the diagnosis of brain cancer and achieved satisfactory performance with 100% accuracy. The proposed network was trained with MR image datasets of 16 cases. The 16 cases were fed to the ANN with 2 input neurons, one hidden layer of 10 neurons and 2 output neurons. Of the 16-sample database, 10 datasets for training, 3 datasets for validation, and 3 datasets for testing were used in the ANN classification system. From the SSM (µ) confusion matrix, the number of output datasets of true positive, false positive, true negative and false negative was 6, 0, 10, and 0, respectively. The sensitivity, specificity and accuracy were each equal to 100%. The method of diagnosing brain cancer presented in this study is a successful model to assist doctors in the screening and treatment of brain cancer patients. The presented FES successfully identified the presence of brain cancer in CT and MR images using the extracted shape-based features and the use of NFS for the identification of brain cancer in the early stages. From the analysis and diagnosis of the disease, the doctors can decide the stage of cancer and take the necessary steps for more accurate treatment. Here, we have presented an investigation and comparison study of the shape-based feature extraction method with the use of NFS for classifying brain tumors as showing normal or abnormal patterns. The results have proved that the shape-based features with the use of NFS can achieve a satisfactory performance with 100% accuracy. We intend to extend this methodology for the early detection of cancer in other regions such as the prostate region and human cervix.

Denoising Sparse Images from GRAPPA using the Nullspace Method (DESIGN)

PubMed Central

Weller, Daniel S.; Polimeni, Jonathan R.; Grady, Leo; Wald, Lawrence L.; Adalsteinsson, Elfar; Goyal, Vivek K

2011-01-01

To accelerate magnetic resonance imaging using uniformly undersampled (nonrandom) parallel imaging beyond what is achievable with GRAPPA alone, the Denoising of Sparse Images from GRAPPA using the Nullspace method (DESIGN) is developed. The trade-off between denoising and smoothing the GRAPPA solution is studied for different levels of acceleration. Several brain images reconstructed from uniformly undersampled k-space data using DESIGN are compared against reconstructions using existing methods in terms of difference images (a qualitative measure), PSNR, and noise amplification (g-factors) as measured using the pseudo-multiple replica method. Effects of smoothing, including contrast loss, are studied in synthetic phantom data. In the experiments presented, the contrast loss and spatial resolution are competitive with existing methods. Results for several brain images demonstrate significant improvements over GRAPPA at high acceleration factors in denoising performance with limited blurring or smoothing artifacts. In addition, the measured g-factors suggest that DESIGN mitigates noise amplification better than both GRAPPA and L1 SPIR-iT (the latter limited here by uniform undersampling). PMID:22213069

Optical imaging characterizing brain response to thermal insult in injured rodent

NASA Astrophysics Data System (ADS)

Abookasis, David; Shaul, Oren; Meitav, Omri; Pinhasi, Gadi A.

2018-02-01

We used spatially modulated optical imaging system to assess the effect of temperature elevation on intact brain tissue in a mouse heatstress model. Heatstress or heatstroke is a medical emergency defined by abnormally elevated body temperature that causes biochemical, physiological and hematological changes. During experiments, brain temperature was measured concurrently with a thermal camera while core body temperature was monitored with rectal thermocouple probe. Changes in a battery of macroscopic brain physiological parameters, such as hemoglobin oxygen saturation level, cerebral water content, as well as intrinsic tissue optical properties were monitored during temperature elevation. These concurrent changes reflect the pathophysiology of the brain during heatstress and demonstrate successful monitoring of thermoregulation mechanisms. In addition, the variation of tissue refractive index was calculated showing a monotonous decrease with increasing wavelength. We found increased temperature to greatly affect both the scattering properties and refractive index which represent cellular and subcellular swelling indicative of neuronal damage. The overall trends detected in brain tissue parameters were consistent with previous observations using conventional medical devices and optical modalities.

Brain CT image similarity retrieval method based on uncertain location graph.

PubMed

Pan, Haiwei; Li, Pengyuan; Li, Qing; Han, Qilong; Feng, Xiaoning; Gao, Linlin

2014-03-01

A number of brain computed tomography (CT) images stored in hospitals that contain valuable information should be shared to support computer-aided diagnosis systems. Finding the similar brain CT images from the brain CT image database can effectively help doctors diagnose based on the earlier cases. However, the similarity retrieval for brain CT images requires much higher accuracy than the general images. In this paper, a new model of uncertain location graph (ULG) is presented for brain CT image modeling and similarity retrieval. According to the characteristics of brain CT image, we propose a novel method to model brain CT image to ULG based on brain CT image texture. Then, a scheme for ULG similarity retrieval is introduced. Furthermore, an effective index structure is applied to reduce the searching time. Experimental results reveal that our method functions well on brain CT images similarity retrieval with higher accuracy and efficiency.

Brain imaging and behavioral outcome in traumatic brain injury.

PubMed

Bigler, E D

1996-09-01

Brain imaging studies have become an essential diagnostic assessment procedure in evaluating the effects of traumatic brain injury (TBI). Such imaging studies provide a wealth of information about structural and functional deficits following TBI. But how pathologic changes identified by brain imaging methods relate to neurobehavioral outcome is not as well known. Thus, the focus of this article is on brain imaging findings and outcome following TBI. The article starts with an overview of current research dealing with the cellular pathology associated with TBI. Understanding the cellular elements of pathology permits extrapolation to what is observed with brain imaging. Next, this article reviews the relationship of brain imaging findings to underlying pathology and how that pathology relates to neurobehavioral outcome. The brain imaging techniques of magnetic resonance imaging, computerized tomography, and single photon emission computed tomography are reviewed. Various image analysis procedures, and how such findings relate to neuropsychological testing, are discussed. The importance of brain imaging in evaluating neurobehavioral deficits following brain injury is stressed.

Photoacoustic micro-imaging of focused ultrasound induced blood-brain-barrier opening in a rat model

NASA Astrophysics Data System (ADS)

Wang, Po-Hsun; Hsu, Po-Hung; Liu, Hao-Li; Wang, Churng-Ren Chris; Li, Meng-Lin

2010-02-01

Blood brain barrier (BBB) prevents most of the drug from transmitting into the brain tissue and decreases the treatment performance for brain disease. One of the methods to overcome the difficulty of drug delivery is to locally increase the permeability of BBB with high-intensity focused ultrasound. In this study, we have investigated the feasibility of photoacoustic microscopy of focused-ultrasound induced BBB opening in a rat model in vivo with gold nanorods (AuNRs) as a contrast agent. This study takes advantage of the strong near-infrared absorption of AuNRs and their extravasation tendency from BBB opening foci due to their nano-scale size. Before the experiments, craniotomy was performed on rats to provide a path for focused ultrasound beam. Localized BBB opening at the depth of about 3 mm from left cortex of rat brains was achieved by delivering 1.5 MHz focused ultrasound energy into brain tissue in the presence of microbubbles. PEGylated AuNRs with a peak optical absorption at ~800 nm were then intravenously administered. Pre-scan prior to BBB disruption and AuNR injection was taken to mark the signal background. After injection, the distribution of AuNRs in rat brains was monitored up to 2 hours. Experimental results show that imaging AuNRs reveals BBB disruption area in left brains while there are no changes observed in the right brains. From our results, photoacoustic imaging plus AuNRs shows the promise as a novel monitoring strategy in identifying the location and variation of focused-ultrasound BBB-opening in a rat model.

Patch Based Synthesis of Whole Head MR Images: Application to EPI Distortion Correction.

PubMed

Roy, Snehashis; Chou, Yi-Yu; Jog, Amod; Butman, John A; Pham, Dzung L

2016-10-01

Different magnetic resonance imaging pulse sequences are used to generate image contrasts based on physical properties of tissues, which provide different and often complementary information about them. Therefore multiple image contrasts are useful for multimodal analysis of medical images. Often, medical image processing algorithms are optimized for particular image contrasts. If a desirable contrast is unavailable, contrast synthesis (or modality synthesis) methods try to "synthesize" the unavailable constrasts from the available ones. Most of the recent image synthesis methods generate synthetic brain images, while whole head magnetic resonance (MR) images can also be useful for many applications. We propose an atlas based patch matching algorithm to synthesize T 2 -w whole head (including brain, skull, eyes etc) images from T 1 -w images for the purpose of distortion correction of diffusion weighted MR images. The geometric distortion in diffusion MR images due to in-homogeneous B 0 magnetic field are often corrected by non-linearly registering the corresponding b = 0 image with zero diffusion gradient to an undistorted T 2 -w image. We show that our synthetic T 2 -w images can be used as a template in absence of a real T 2 -w image. Our patch based method requires multiple atlases with T 1 and T 2 to be registeLowRes to a given target T 1 . Then for every patch on the target, multiple similar looking matching patches are found on the atlas T 1 images and corresponding patches on the atlas T 2 images are combined to generate a synthetic T 2 of the target. We experimented on image data obtained from 44 patients with traumatic brain injury (TBI), and showed that our synthesized T 2 images produce more accurate distortion correction than a state-of-the-art registration based image synthesis method.

Brain medical image diagnosis based on corners with importance-values.

PubMed

Gao, Linlin; Pan, Haiwei; Li, Qing; Xie, Xiaoqin; Zhang, Zhiqiang; Han, Jinming; Zhai, Xiao

2017-11-21

Brain disorders are one of the top causes of human death. Generally, neurologists analyze brain medical images for diagnosis. In the image analysis field, corners are one of the most important features, which makes corner detection and matching studies essential. However, existing corner detection studies do not consider the domain information of brain. This leads to many useless corners and the loss of significant information. Regarding corner matching, the uncertainty and structure of brain are not employed in existing methods. Moreover, most corner matching studies are used for 3D image registration. They are inapplicable for 2D brain image diagnosis because of the different mechanisms. To address these problems, we propose a novel corner-based brain medical image classification method. Specifically, we automatically extract multilayer texture images (MTIs) which embody diagnostic information from neurologists. Moreover, we present a corner matching method utilizing the uncertainty and structure of brain medical images and a bipartite graph model. Finally, we propose a similarity calculation method for diagnosis. Brain CT and MRI image sets are utilized to evaluate the proposed method. First, classifiers are trained in N-fold cross-validation analysis to produce the best θ and K. Then independent brain image sets are tested to evaluate the classifiers. Moreover, the classifiers are also compared with advanced brain image classification studies. For the brain CT image set, the proposed classifier outperforms the comparison methods by at least 8% on accuracy and 2.4% on F1-score. Regarding the brain MRI image set, the proposed classifier is superior to the comparison methods by more than 7.3% on accuracy and 4.9% on F1-score. Results also demonstrate that the proposed method is robust to different intensity ranges of brain medical image. In this study, we develop a robust corner-based brain medical image classifier. Specifically, we propose a corner detection method utilizing the diagnostic information from neurologists and a corner matching method based on the uncertainty and structure of brain medical images. Additionally, we present a similarity calculation method for brain image classification. Experimental results on two brain image sets show the proposed corner-based brain medical image classifier outperforms the state-of-the-art studies.

[Three-dimensional reconstruction of functional brain images].

PubMed

Inoue, M; Shoji, K; Kojima, H; Hirano, S; Naito, Y; Honjo, I

1999-08-01

We consider PET (positron emission tomography) measurement with SPM (Statistical Parametric Mapping) analysis to be one of the most useful methods to identify activated areas of the brain involved in language processing. SPM is an effective analytical method that detects markedly activated areas over the whole brain. However, with the conventional presentations of these functional brain images, such as horizontal slices, three directional projection, or brain surface coloring, makes understanding and interpreting the positional relationships among various brain areas difficult. Therefore, we developed three-dimensionally reconstructed images from these functional brain images to improve the interpretation. The subjects were 12 normal volunteers. The following three types of images were constructed: 1) routine images by SPM, 2) three-dimensional static images, and 3) three-dimensional dynamic images, after PET images were analyzed by SPM during daily dialog listening. The creation of images of both the three-dimensional static and dynamic types employed the volume rendering method by VTK (The Visualization Toolkit). Since the functional brain images did not include original brain images, we synthesized SPM and MRI brain images by self-made C++ programs. The three-dimensional dynamic images were made by sequencing static images with available software. Images of both the three-dimensional static and dynamic types were processed by a personal computer system. Our newly created images showed clearer positional relationships among activated brain areas compared to the conventional method. To date, functional brain images have been employed in fields such as neurology or neurosurgery, however, these images may be useful even in the field of otorhinolaryngology, to assess hearing and speech. Exact three-dimensional images based on functional brain images are important for exact and intuitive interpretation, and may lead to new developments in brain science. Currently, the surface model is the most common method of three-dimensional display. However, the volume rendering method may be more effective for imaging regions such as the brain.

Image-driven Population Analysis through Mixture Modeling

PubMed Central

Sabuncu, Mert R.; Balci, Serdar K.; Shenton, Martha E.; Golland, Polina

2009-01-01

We present iCluster, a fast and efficient algorithm that clusters a set of images while co-registering them using a parameterized, nonlinear transformation model. The output of the algorithm is a small number of template images that represent different modes in a population. This is in contrast with traditional, hypothesis-driven computational anatomy approaches that assume a single template to construct an atlas. We derive the algorithm based on a generative model of an image population as a mixture of deformable template images. We validate and explore our method in four experiments. In the first experiment, we use synthetic data to explore the behavior of the algorithm and inform a design choice on parameter settings. In the second experiment, we demonstrate the utility of having multiple atlases for the application of localizing temporal lobe brain structures in a pool of subjects that contains healthy controls and schizophrenia patients. Next, we employ iCluster to partition a data set of 415 whole brain MR volumes of subjects aged 18 through 96 years into three anatomical subgroups. Our analysis suggests that these subgroups mainly correspond to age groups. The templates reveal significant structural differences across these age groups that confirm previous findings in aging research. In the final experiment, we run iCluster on a group of 15 patients with dementia and 15 age-matched healthy controls. The algorithm produces two modes, one of which contains dementia patients only. These results suggest that the algorithm can be used to discover sub-populations that correspond to interesting structural or functional “modes.” PMID:19336293

Visualization of children's mathematics solving process using near infrared spectroscopic approach

NASA Astrophysics Data System (ADS)

Kuroda, Yasufumi; Okamoto, Naoko; Chance, Britton; Nioka, Shoko; Eda, Hideo; Maesako, Takanori

2009-02-01

Over the past decade, the application of results from brain science research to education research has been a controversial topic. A NIRS imaging system shows images of Hb parameters in the brain. Measurements using NIRS are safe, easy and the equipment is portable, allowing subjects to tolerate longer research periods. The purpose of this research is to examine the characteristics of Hb using NIRS at the moment of understanding. We measured Hb in the prefrontal cortex of children while they were solving mathematical problems (tangram puzzles). As a result of the experiment, we were able to classify the children into three groups based on their solution methods. Hb continually increased in a group which could not develop a problem solving strategy for the tangram puzzles. Hb declined steadily for a group which was able to develop a strategy for the tangram puzzles. Hb was steady for a certain group that had already developed a strategy before solving the problems. Our experiments showed that the brain data from NIRS enables the visualization of children's mathematical solution processes.

Intraoperative intrinsic optical imaging of human somatosensory cortex during neurosurgical operations.

PubMed

Sato, Katsushige; Nariai, Tadashi; Momose-Sato, Yoko; Kamino, Kohtaro

2017-07-01

Intrinsic optical imaging as developed by Grinvald et al. is a powerful technique for monitoring neural function in the in vivo central nervous system. The advent of this dye-free imaging has also enabled us to monitor human brain function during neurosurgical operations. We briefly describe our own experience in functional mapping of the human somatosensory cortex, carried out using intraoperative optical imaging. The maps obtained demonstrate new additional evidence of a hierarchy for sensory response patterns in the human primary somatosensory cortex.

Computational and mathematical methods in brain atlasing.

PubMed

Nowinski, Wieslaw L

2017-12-01

Brain atlases have a wide range of use from education to research to clinical applications. Mathematical methods as well as computational methods and tools play a major role in the process of brain atlas building and developing atlas-based applications. Computational methods and tools cover three areas: dedicated editors for brain model creation, brain navigators supporting multiple platforms, and atlas-assisted specific applications. Mathematical methods in atlas building and developing atlas-aided applications deal with problems in image segmentation, geometric body modelling, physical modelling, atlas-to-scan registration, visualisation, interaction and virtual reality. Here I overview computational and mathematical methods in atlas building and developing atlas-assisted applications, and share my contribution to and experience in this field.

Enhancing the Teaching of Digital Processing of Remote Sensing Image Course through Geospatial Web Processing Services

NASA Astrophysics Data System (ADS)

di, L.; Deng, M.

2010-12-01

Remote sensing (RS) is an essential method to collect data for Earth science research. Huge amount of remote sensing data, most of them in the image form, have been acquired. Almost all geography departments in the world offer courses in digital processing of remote sensing images. Such courses place emphasis on how to digitally process large amount of multi-source images for solving real world problems. However, due to the diversity and complexity of RS images and the shortcomings of current data and processing infrastructure, obstacles for effectively teaching such courses still remain. The major obstacles include 1) difficulties in finding, accessing, integrating and using massive RS images by students and educators, and 2) inadequate processing functions and computing facilities for students to freely explore the massive data. Recent development in geospatial Web processing service systems, which make massive data, computing powers, and processing capabilities to average Internet users anywhere in the world, promises the removal of the obstacles. The GeoBrain system developed by CSISS is an example of such systems. All functions available in GRASS Open Source GIS have been implemented as Web services in GeoBrain. Petabytes of remote sensing images in NASA data centers, the USGS Landsat data archive, and NOAA CLASS are accessible transparently and processable through GeoBrain. The GeoBrain system is operated on a high performance cluster server with large disk storage and fast Internet connection. All GeoBrain capabilities can be accessed by any Internet-connected Web browser. Dozens of universities have used GeoBrain as an ideal platform to support data-intensive remote sensing education. This presentation gives a specific example of using GeoBrain geoprocessing services to enhance the teaching of GGS 588, Digital Remote Sensing taught at the Department of Geography and Geoinformation Science, George Mason University. The course uses the textbook "Introductory Digital Image Processing, A Remote Sensing Perspective" authored by John Jensen. The textbook is widely adopted in the geography departments around the world for training students on digital processing of remote sensing images. In the traditional teaching setting for the course, the instructor prepares a set of sample remote sensing images to be used for the course. Commercial desktop remote sensing software, such as ERDAS, is used for students to do the lab exercises. The students have to do the excurses in the lab and can only use the simple images. For this specific course at GMU, we developed GeoBrain-based lab excurses for the course. With GeoBrain, students now can explore petabytes of remote sensing images in the NASA, NOAA, and USGS data archives instead of dealing only with sample images. Students have a much more powerful computing facility available for their lab excurses. They can explore the data and do the excurses any time at any place they want as long as they can access the Internet through the Web Browser. The feedbacks from students are all very positive about the learning experience on the digital image processing with the help of GeoBrain web processing services. The teaching/lab materials and GeoBrain services are freely available to anyone at http://www.laits.gmu.edu.

Structural Brain Imaging of Long-Term Anabolic-Androgenic Steroid Users and Nonusing Weightlifters.

PubMed

Bjørnebekk, Astrid; Walhovd, Kristine B; Jørstad, Marie L; Due-Tønnessen, Paulina; Hullstein, Ingunn R; Fjell, Anders M

2017-08-15

Prolonged high-dose anabolic-androgenic steroid (AAS) use has been associated with psychiatric symptoms and cognitive deficits, yet we have almost no knowledge of the long-term consequences of AAS use on the brain. The purpose of this study is to investigate the association between long-term AAS exposure and brain morphometry, including subcortical neuroanatomical volumes and regional cortical thickness. Male AAS users and weightlifters with no experience with AASs or any other equivalent doping substances underwent structural magnetic resonance imaging scans of the brain. The current paper is based upon high-resolution structural T1-weighted images from 82 current or past AAS users exceeding 1 year of cumulative AAS use and 68 non-AAS-using weightlifters. Images were processed with the FreeSurfer software to compare neuroanatomical volumes and cerebral cortical thickness between the groups. Compared to non-AAS-using weightlifters, the AAS group had thinner cortex in widespread regions and significantly smaller neuroanatomical volumes, including total gray matter, cerebral cortex, and putamen. Both volumetric and thickness effects remained relatively stable across different AAS subsamples comprising various degrees of exposure to AASs and also when excluding participants with previous and current non-AAS drug abuse. The effects could not be explained by differences in verbal IQ, intracranial volume, anxiety/depression, or attention or behavioral problems. This large-scale systematic investigation of AAS use on brain structure shows negative correlations between AAS use and brain volume and cortical thickness. Although the findings are correlational, they may serve to raise concern about the long-term consequences of AAS use on structural features of the brain. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Dynamic time warping-based averaging framework for functional near-infrared spectroscopy brain imaging studies

NASA Astrophysics Data System (ADS)

Zhu, Li; Najafizadeh, Laleh

2017-06-01

We investigate the problem related to the averaging procedure in functional near-infrared spectroscopy (fNIRS) brain imaging studies. Typically, to reduce noise and to empower the signal strength associated with task-induced activities, recorded signals (e.g., in response to repeated stimuli or from a group of individuals) are averaged through a point-by-point conventional averaging technique. However, due to the existence of variable latencies in recorded activities, the use of the conventional averaging technique can lead to inaccuracies and loss of information in the averaged signal, which may result in inaccurate conclusions about the functionality of the brain. To improve the averaging accuracy in the presence of variable latencies, we present an averaging framework that employs dynamic time warping (DTW) to account for the temporal variation in the alignment of fNIRS signals to be averaged. As a proof of concept, we focus on the problem of localizing task-induced active brain regions. The framework is extensively tested on experimental data (obtained from both block design and event-related design experiments) as well as on simulated data. In all cases, it is shown that the DTW-based averaging technique outperforms the conventional-based averaging technique in estimating the location of task-induced active regions in the brain, suggesting that such advanced averaging methods should be employed in fNIRS brain imaging studies.

Image-guided microbeam irradiation to brain tumour bearing mice using a carbon nanotube x-ray source array

NASA Astrophysics Data System (ADS)

Zhang, Lei; Yuan, Hong; Burk, Laurel M.; Inscoe, Christy R.; Hadsell, Michael J.; Chtcheprov, Pavel; Lee, Yueh Z.; Lu, Jianping; Chang, Sha; Zhou, Otto

2014-03-01

Microbeam radiation therapy (MRT) is a promising experimental and preclinical radiotherapy method for cancer treatment. Synchrotron based MRT experiments have shown that spatially fractionated microbeam radiation has the unique capability of preferentially eradicating tumour cells while sparing normal tissue in brain tumour bearing animal models. We recently demonstrated the feasibility of generating orthovoltage microbeam radiation with an adjustable microbeam width using a carbon nanotube based x-ray source array. Here we report the preliminary results from our efforts in developing an image guidance procedure for the targeted delivery of the narrow microbeams to the small tumour region in the mouse brain. Magnetic resonance imaging was used for tumour identification, and on-board x-ray radiography was used for imaging of landmarks without contrast agents. The two images were aligned using 2D rigid body image registration to determine the relative position of the tumour with respect to a landmark. The targeting accuracy and consistency were evaluated by first irradiating a group of mice inoculated with U87 human glioma brain tumours using the present protocol and then determining the locations of the microbeam radiation tracks using γ-H2AX immunofluorescence staining. The histology results showed that among 14 mice irradiated, 11 received the prescribed number of microbeams on the targeted tumour, with an average localization accuracy of 454 µm measured directly from the histology (537 µm if measured from the registered histological images). Two mice received one of the three prescribed microbeams on the tumour site. One mouse was excluded from the analysis due to tissue staining errors.

Multi-scale spectrally resolved quantitative fluorescence imaging system: towards neurosurgical guidance in glioma resection

NASA Astrophysics Data System (ADS)

Xie, Yijing; Thom, Maria; Miserocchi, Anna; McEvoy, Andrew W.; Desjardins, Adrien; Ourselin, Sebastien; Vercauteren, Tom

2017-02-01

In glioma resection surgery, the detection of tumour is often guided by using intraoperative fluorescence imaging notably with 5-ALA-PpIX, providing fluorescent contrast between normal brain tissue and the gliomas tissue to achieve improved tumour delineation and prolonged patient survival compared with the conventional white-light guided resection. However, the commercially available fluorescence imaging system relies on surgeon's eyes to visualise and distinguish the fluorescence signals, which unfortunately makes the resection subjective. In this study, we developed a novel multi-scale spectrally-resolved fluorescence imaging system and a computational model for quantification of PpIX concentration. The system consisted of a wide-field spectrally-resolved quantitative imaging device and a fluorescence endomicroscopic imaging system enabling optical biopsy. Ex vivo animal tissue experiments as well as human tumour sample studies demonstrated that the system was capable of specifically detecting the PpIX fluorescent signal and estimate the true concentration of PpIX in brain specimen.

Effects of the murine skull in optoacoustic brain microscopy.

PubMed

Kneipp, Moritz; Turner, Jake; Estrada, Héctor; Rebling, Johannes; Shoham, Shy; Razansky, Daniel

2016-01-01

Despite the great promise behind the recent introduction of optoacoustic technology into the arsenal of small-animal neuroimaging methods, a variety of acoustic and light-related effects introduced by adult murine skull severely compromise the performance of optoacoustics in transcranial imaging. As a result, high-resolution noninvasive optoacoustic microscopy studies are still limited to a thin layer of pial microvasculature, which can be effectively resolved by tight focusing of the excitation light. We examined a range of distortions introduced by an adult murine skull in transcranial optoacoustic imaging under both acoustically- and optically-determined resolution scenarios. It is shown that strong low-pass filtering characteristics of the skull may significantly deteriorate the achievable spatial resolution in deep brain imaging where no light focusing is possible. While only brain vasculature with a diameter larger than 60 µm was effectively resolved via transcranial measurements with acoustic resolution, significant improvements are seen through cranial windows and thinned skull experiments. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Photoacoustic Imaging of Animals with an Annular Transducer Array

NASA Astrophysics Data System (ADS)

Yang, Di-Wu; Zhou, Zhi-Bin; Zeng, Lv-Ming; Zhou, Xin; Chen, Xing-Hui

2014-07-01

A photoacoustic system with an annular transducer array is presented for rapid, high-resolution photoacoustic tomography of animals. An eight-channel data acquisition system is applied to capture the photoacoustic signals by using multiplexing and the total time of data acquisition and transferring is within 3 s. A limited-view filtered back projection algorithm is used to reconstruct the photoacoustic images. Experiments are performed on a mouse head and a rabbit head and clear photoacoustic images are obtained. The experimental results demonstrate that this imaging system holds the potential for imaging the human brain.

Prediction of standard-dose brain PET image by using MRI and low-dose brain [18F]FDG PET images.

PubMed

Kang, Jiayin; Gao, Yaozong; Shi, Feng; Lalush, David S; Lin, Weili; Shen, Dinggang

2015-09-01

Positron emission tomography (PET) is a nuclear medical imaging technology that produces 3D images reflecting tissue metabolic activity in human body. PET has been widely used in various clinical applications, such as in diagnosis of brain disorders. High-quality PET images play an essential role in diagnosing brain diseases/disorders. In practice, in order to obtain high-quality PET images, a standard-dose radionuclide (tracer) needs to be used and injected into a living body. As a result, it will inevitably increase the patient's exposure to radiation. One solution to solve this problem is predicting standard-dose PET images using low-dose PET images. As yet, no previous studies with this approach have been reported. Accordingly, in this paper, the authors propose a regression forest based framework for predicting a standard-dose brain [(18)F]FDG PET image by using a low-dose brain [(18)F]FDG PET image and its corresponding magnetic resonance imaging (MRI) image. The authors employ a regression forest for predicting the standard-dose brain [(18)F]FDG PET image by low-dose brain [(18)F]FDG PET and MRI images. Specifically, the proposed method consists of two main steps. First, based on the segmented brain tissues (i.e., cerebrospinal fluid, gray matter, and white matter) in the MRI image, the authors extract features for each patch in the brain image from both low-dose PET and MRI images to build tissue-specific models that can be used to initially predict standard-dose brain [(18)F]FDG PET images. Second, an iterative refinement strategy, via estimating the predicted image difference, is used to further improve the prediction accuracy. The authors evaluated their algorithm on a brain dataset, consisting of 11 subjects with MRI, low-dose PET, and standard-dose PET images, using leave-one-out cross-validations. The proposed algorithm gives promising results with well-estimated standard-dose brain [(18)F]FDG PET image and substantially enhanced image quality of low-dose brain [(18)F]FDG PET image. In this paper, the authors propose a framework to generate standard-dose brain [(18)F]FDG PET image using low-dose brain [(18)F]FDG PET and MRI images. Both the visual and quantitative results indicate that the standard-dose brain [(18)F]FDG PET can be well-predicted using MRI and low-dose brain [(18)F]FDG PET.

Prediction of standard-dose brain PET image by using MRI and low-dose brain [18F]FDG PET images

PubMed Central

Kang, Jiayin; Gao, Yaozong; Shi, Feng; Lalush, David S.; Lin, Weili; Shen, Dinggang

2015-01-01

Purpose: Positron emission tomography (PET) is a nuclear medical imaging technology that produces 3D images reflecting tissue metabolic activity in human body. PET has been widely used in various clinical applications, such as in diagnosis of brain disorders. High-quality PET images play an essential role in diagnosing brain diseases/disorders. In practice, in order to obtain high-quality PET images, a standard-dose radionuclide (tracer) needs to be used and injected into a living body. As a result, it will inevitably increase the patient’s exposure to radiation. One solution to solve this problem is predicting standard-dose PET images using low-dose PET images. As yet, no previous studies with this approach have been reported. Accordingly, in this paper, the authors propose a regression forest based framework for predicting a standard-dose brain [18F]FDG PET image by using a low-dose brain [18F]FDG PET image and its corresponding magnetic resonance imaging (MRI) image. Methods: The authors employ a regression forest for predicting the standard-dose brain [18F]FDG PET image by low-dose brain [18F]FDG PET and MRI images. Specifically, the proposed method consists of two main steps. First, based on the segmented brain tissues (i.e., cerebrospinal fluid, gray matter, and white matter) in the MRI image, the authors extract features for each patch in the brain image from both low-dose PET and MRI images to build tissue-specific models that can be used to initially predict standard-dose brain [18F]FDG PET images. Second, an iterative refinement strategy, via estimating the predicted image difference, is used to further improve the prediction accuracy. Results: The authors evaluated their algorithm on a brain dataset, consisting of 11 subjects with MRI, low-dose PET, and standard-dose PET images, using leave-one-out cross-validations. The proposed algorithm gives promising results with well-estimated standard-dose brain [18F]FDG PET image and substantially enhanced image quality of low-dose brain [18F]FDG PET image. Conclusions: In this paper, the authors propose a framework to generate standard-dose brain [18F]FDG PET image using low-dose brain [18F]FDG PET and MRI images. Both the visual and quantitative results indicate that the standard-dose brain [18F]FDG PET can be well-predicted using MRI and low-dose brain [18F]FDG PET. PMID:26328979

Prediction of standard-dose brain PET image by using MRI and low-dose brain [{sup 18}F]FDG PET images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kang, Jiayin; Gao, Yaozong; Shi, Feng

Purpose: Positron emission tomography (PET) is a nuclear medical imaging technology that produces 3D images reflecting tissue metabolic activity in human body. PET has been widely used in various clinical applications, such as in diagnosis of brain disorders. High-quality PET images play an essential role in diagnosing brain diseases/disorders. In practice, in order to obtain high-quality PET images, a standard-dose radionuclide (tracer) needs to be used and injected into a living body. As a result, it will inevitably increase the patient’s exposure to radiation. One solution to solve this problem is predicting standard-dose PET images using low-dose PET images. Asmore » yet, no previous studies with this approach have been reported. Accordingly, in this paper, the authors propose a regression forest based framework for predicting a standard-dose brain [{sup 18}F]FDG PET image by using a low-dose brain [{sup 18}F]FDG PET image and its corresponding magnetic resonance imaging (MRI) image. Methods: The authors employ a regression forest for predicting the standard-dose brain [{sup 18}F]FDG PET image by low-dose brain [{sup 18}F]FDG PET and MRI images. Specifically, the proposed method consists of two main steps. First, based on the segmented brain tissues (i.e., cerebrospinal fluid, gray matter, and white matter) in the MRI image, the authors extract features for each patch in the brain image from both low-dose PET and MRI images to build tissue-specific models that can be used to initially predict standard-dose brain [{sup 18}F]FDG PET images. Second, an iterative refinement strategy, via estimating the predicted image difference, is used to further improve the prediction accuracy. Results: The authors evaluated their algorithm on a brain dataset, consisting of 11 subjects with MRI, low-dose PET, and standard-dose PET images, using leave-one-out cross-validations. The proposed algorithm gives promising results with well-estimated standard-dose brain [{sup 18}F]FDG PET image and substantially enhanced image quality of low-dose brain [{sup 18}F]FDG PET image. Conclusions: In this paper, the authors propose a framework to generate standard-dose brain [{sup 18}F]FDG PET image using low-dose brain [{sup 18}F]FDG PET and MRI images. Both the visual and quantitative results indicate that the standard-dose brain [{sup 18}F]FDG PET can be well-predicted using MRI and low-dose brain [{sup 18}F]FDG PET.« less

Transcranial MRI-guided FUS-induced BBB opening in the rat brain

NASA Astrophysics Data System (ADS)

Treat, Lisa H.; McDannold, Nathan J.; Hynynen, Kullervo

2004-05-01

The blood-brain barrier (BBB) has been a major limitation in treating diseases of the brain because therapeutic agents are either unable to penetrate or have dose-limiting side effects in diffuse opening of the BBB. A previous study demonstrated that focused ultrasound (FUS) can locally open the BBB in a rabbit model when a piece of skull is removed and that magnetic resonance imaging (MRI) can be used to guide and monitor the procedure. This study examined whether the same desired effect of local BBB disruption can be achieved by applying FUS through an intact skull in a rat model. Twenty-eight Sprague-Dawley rats were anesthetized, shaved, and sonicated at four focal locations in the brain, using a 1.5-MHz focused transducer. Contrast-enhanced MR images were obtained before and after sonication. The images indicated contrast agent penetration at the focal coordinates following Optison-enhanced sonication. This study demonstrated that the distortion of the ultrasound beam by the rat skull was not significant enough to inhibit focal BBB opening. Subsequent experiments using MRI-guided FUS to aid in targeted drug delivery to brain tumors in a rodent model could thus be performed more efficiently without cranial surgery. [Research funded by NIH Grant No. CA76550.

Automatic selection of localized region-based active contour models using image content analysis applied to brain tumor segmentation.

PubMed

Ilunga-Mbuyamba, Elisee; Avina-Cervantes, Juan Gabriel; Cepeda-Negrete, Jonathan; Ibarra-Manzano, Mario Alberto; Chalopin, Claire

2017-12-01

Brain tumor segmentation is a routine process in a clinical setting and provides useful information for diagnosis and treatment planning. Manual segmentation, performed by physicians or radiologists, is a time-consuming task due to the large quantity of medical data generated presently. Hence, automatic segmentation methods are needed, and several approaches have been introduced in recent years including the Localized Region-based Active Contour Model (LRACM). There are many popular LRACM, but each of them presents strong and weak points. In this paper, the automatic selection of LRACM based on image content and its application on brain tumor segmentation is presented. Thereby, a framework to select one of three LRACM, i.e., Local Gaussian Distribution Fitting (LGDF), localized Chan-Vese (C-V) and Localized Active Contour Model with Background Intensity Compensation (LACM-BIC), is proposed. Twelve visual features are extracted to properly select the method that may process a given input image. The system is based on a supervised approach. Applied specifically to Magnetic Resonance Imaging (MRI) images, the experiments showed that the proposed system is able to correctly select the suitable LRACM to handle a specific image. Consequently, the selection framework achieves better accuracy performance than the three LRACM separately. Copyright © 2017 Elsevier Ltd. All rights reserved.

Attentional Modulation of Brain Responses to Primary Appetitive and Aversive Stimuli

PubMed Central

Field, Brent A.; Buck, Cara L.; McClure, Samuel M.; Nystrom, Leigh E.; Kahneman, Daniel; Cohen, Jonathan D.

2015-01-01

Studies of subjective well-being have conventionally relied upon self-report, which directs subjects’ attention to their emotional experiences. This method presumes that attention itself does not influence emotional processes, which could bias sampling. We tested whether attention influences experienced utility (the moment-by-moment experience of pleasure) by using functional magnetic resonance imaging (fMRI) to measure the activity of brain systems thought to represent hedonic value while manipulating attentional load. Subjects received appetitive or aversive solutions orally while alternatively executing a low or high attentional load task. Brain regions associated with hedonic processing, including the ventral striatum, showed a response to both juice and quinine. This response decreased during the high-load task relative to the low-load task. Thus, attentional allocation may influence experienced utility by modulating (either directly or indirectly) the activity of brain mechanisms thought to represent hedonic value. PMID:26158468

Sequential variation in brain functional magnetic resonance imaging after peripheral nerve injury: A rat study.

PubMed

Onishi, Okihiro; Ikoma, Kazuya; Oda, Ryo; Yamazaki, Tetsuro; Fujiwara, Hiroyoshi; Yamada, Shunji; Tanaka, Masaki; Kubo, Toshikazu

2018-04-23

Although treatment protocols are available, patients experience both acute neuropathic pain and chronic neuropathic pain, hyperalgesia, and allodynia after peripheral nerve injury. The purpose of this study was to identify the brain regions activated after peripheral nerve injury using functional magnetic resonance imaging (fMRI) sequentially and assess the relevance of the imaging results using histological findings. To model peripheral nerve injury in male Sprague-Dawley rats, the right sciatic nerve was crushed using an aneurysm clip, under general anesthesia. We used a 7.04T MRI system. T 2 * weighted image, coronal slice, repetition time, 7 ms; echo time, 3.3 ms; field of view, 30 mm × 30 mm; pixel matrix, 64 × 64 by zero-filling; slice thickness, 2 mm; numbers of slices, 9; numbers of average, 2; and flip angle, 8°. fMR images were acquired during electrical stimulation to the rat's foot sole; after 90 min, c-Fos immunohistochemical staining of the brain was performed in rats with induced peripheral nerve injury for 3, 6, and 9 weeks. Data were pre-processed by realignment in the Statistical Parametric Mapping 8 software. A General Linear Model first level analysis was used to obtain T-values. One week after the injury, significant changes were detected in the cingulate cortex, insular cortex, amygdala, and basal ganglia; at 6 weeks, the brain regions with significant changes in signal density were contracted; at 9 weeks, the amygdala and hippocampus showed activation. Histological findings of the rat brain supported the fMRI findings. We detected sequential activation in the rat brain using fMRI after sciatic nerve injury. Many brain regions were activated during the acute stage of peripheral nerve injury. Conversely, during the chronic stage, activation of the amygdala and hippocampus may be related to chronic-stage hyperalgesia, allodynia, and chronic neuropathic pain. Copyright © 2018 Elsevier B.V. All rights reserved.

Brain responses to sexual images in 46,XY women with complete androgen insensitivity syndrome are female-typical.

PubMed

Hamann, Stephan; Stevens, Jennifer; Vick, Janice Hassett; Bryk, Kristina; Quigley, Charmian A; Berenbaum, Sheri A; Wallen, Kim

2014-11-01

Androgens, estrogens, and sex chromosomes are the major influences guiding sex differences in brain development, yet their relative roles and importance remain unclear. Individuals with complete androgen insensitivity syndrome (CAIS) offer a unique opportunity to address these issues. Although women with CAIS have a Y chromosome, testes, and produce male-typical levels of androgens, they lack functional androgen receptors preventing responding to their androgens. Thus, they develop a female physical phenotype, are reared as girls, and develop into women. Because sexually differentiated brain development in primates is determined primarily by androgens, but may be affected by sex chromosome complement, it is currently unknown whether brain structure and function in women with CAIS is more like that of women or men. In the first functional neuroimaging study of (46,XY) women with CAIS, typical (46,XX) women, and typical (46, XY) men, we found that men showed greater amygdala activation to sexual images than did either typical women or women with CAIS. Typical women and women with CAIS had highly similar patterns of brain activation, indicating that a Y chromosome is insufficient for male-typical human brain responses. Because women with CAIS produce male-typical or elevated levels of testosterone which is aromatized to estradiol these results rule out aromatization of testosterone to estradiol as a determinate of sex differences in patterns of brain activation to sexual images. We cannot, however, rule out an effect of social experience on the brain responses of women with CAIS as all were raised as girls. Copyright © 2014 Elsevier Inc. All rights reserved.

Two-photon voltage imaging using a genetically encoded voltage indicator

PubMed Central

Akemann, Walther; Sasaki, Mari; Mutoh, Hiroki; Imamura, Takeshi; Honkura, Naoki; Knöpfel, Thomas

2013-01-01

Voltage-sensitive fluorescent proteins (VSFPs) are a family of genetically-encoded voltage indicators (GEVIs) reporting membrane voltage fluctuation from genetically-targeted cells in cell cultures to whole brains in awake mice as demonstrated earlier using 1-photon (1P) fluorescence excitation imaging. However, in-vivo 1P imaging captures optical signals only from superficial layers and does not optically resolve single neurons. Two-photon excitation (2P) imaging, on the other hand, has not yet been convincingly applied to GEVI experiments. Here we show that 2P imaging of VSFP Butterfly 1.2 expresssing pyramidal neurons in layer 2/3 reports optical membrane voltage in brain slices consistent with 1P imaging but with a 2–3 larger ΔR/R value. 2P imaging of mouse cortex in-vivo achieved cellular resolution throughout layer 2/3. In somatosensory cortex we recorded sensory responses to single whisker deflections in anesthetized mice at full frame video rate. Our results demonstrate the feasibility of GEVI-based functional 2P imaging in mouse cortex. PMID:23868559

Studying Axon-Astrocyte Functional Interactions by 3D Two-Photon Ca2+ Imaging: A Practical Guide to Experiments and "Big Data" Analysis.

PubMed

Savtchouk, Iaroslav; Carriero, Giovanni; Volterra, Andrea

2018-01-01

Recent advances in fast volumetric imaging have enabled rapid generation of large amounts of multi-dimensional functional data. While many computer frameworks exist for data storage and analysis of the multi-gigabyte Ca 2+ imaging experiments in neurons, they are less useful for analyzing Ca 2+ dynamics in astrocytes, where transients do not follow a predictable spatio-temporal distribution pattern. In this manuscript, we provide a detailed protocol and commentary for recording and analyzing three-dimensional (3D) Ca 2+ transients through time in GCaMP6f-expressing astrocytes of adult brain slices in response to axonal stimulation, using our recently developed tools to perform interactive exploration, filtering, and time-correlation analysis of the transients. In addition to the protocol, we release our in-house software tools and discuss parameters pertinent to conducting axonal stimulation/response experiments across various brain regions and conditions. Our software tools are available from the Volterra Lab webpage at https://wwwfbm.unil.ch/dnf/group/glia-an-active-synaptic-partner/member/volterra-andrea-volterra in the form of software plugins for Image J (NIH)-a de facto standard in scientific image analysis. Three programs are available: MultiROI_TZ_profiler for interactive graphing of several movable ROIs simultaneously, Gaussian_Filter5D for Gaussian filtering in several dimensions, and Correlation_Calculator for computing various cross-correlation parameters on voxel collections through time.

Development of integrated semiconductor optical sensors for functional brain imaging

NASA Astrophysics Data System (ADS)

Lee, Thomas T.

Optical imaging of neural activity is a widely accepted technique for imaging brain function in the field of neuroscience research, and has been used to study the cerebral cortex in vivo for over two decades. Maps of brain activity are obtained by monitoring intensity changes in back-scattered light, called Intrinsic Optical Signals (IOS), that correspond to fluctuations in blood oxygenation and volume associated with neural activity. Current imaging systems typically employ bench-top equipment including lamps and CCD cameras to study animals using visible light. Such systems require the use of anesthetized or immobilized subjects with craniotomies, which imposes limitations on the behavioral range and duration of studies. The ultimate goal of this work is to overcome these limitations by developing a single-chip semiconductor sensor using arrays of sources and detectors operating at near-infrared (NIR) wavelengths. A single-chip implementation, combined with wireless telemetry, will eliminate the need for immobilization or anesthesia of subjects and allow in vivo studies of free behavior. NIR light offers additional advantages because it experiences less absorption in animal tissue than visible light, which allows for imaging through superficial tissues. This, in turn, reduces or eliminates the need for traumatic surgery and enables long-term brain-mapping studies in freely-behaving animals. This dissertation concentrates on key engineering challenges of implementing the sensor. This work shows the feasibility of using a GaAs-based array of vertical-cavity surface emitting lasers (VCSELs) and PIN photodiodes for IOS imaging. I begin with in-vivo studies of IOS imaging through the skull in mice, and use these results along with computer simulations to establish minimum performance requirements for light sources and detectors. I also evaluate the performance of a current commercial VCSEL for IOS imaging, and conclude with a proposed prototype sensor.

Speech processing asymmetry revealed by dichotic listening and functional brain imaging.

PubMed

Hugdahl, Kenneth; Westerhausen, René

2016-12-01

In this article, we review research in our laboratory from the last 25 to 30 years on the neuronal basis for laterality of speech perception focusing on the upper, posterior parts of the temporal lobes, and its functional and structural connections to other brain regions. We review both behavioral and brain imaging data, with a focus on dichotic listening experiments, and using a variety of imaging modalities. The data have come in most parts from healthy individuals and from studies on normally functioning brain, although we also review a few selected clinical examples. We first review and discuss the structural model for the explanation of the right-ear advantage (REA) and left hemisphere asymmetry for auditory language processing. A common theme across many studies have been our interest in the interaction between bottom-up, stimulus-driven, and top-down, instruction-driven, aspects of hemispheric asymmetry, and how perceptual factors interact with cognitive factors to shape asymmetry of auditory language information processing. In summary, our research have shown laterality for the initial processing of consonant-vowel syllables, first observed as a behavioral REA when subjects are required to report which syllable of a dichotic syllable-pair they perceive. In subsequent work we have corroborated the REA with brain imaging, and have shown that the REA is modulated through both bottom-up manipulations of stimulus properties, like sound intensity, and top-down manipulations of cognitive properties, like attention focus. Copyright © 2015 Elsevier Ltd. All rights reserved.

A high-definition fiber tracking report for patients with traumatic brain injury and their doctors.

PubMed

Chmura, Jon; Presson, Nora; Benso, Steven; Puccio, Ava M; Fissel, Katherine; Hachey, Rebecca; Braun, Emily; Okonkwo, David O; Schneider, Walter

2015-03-01

We have developed a tablet-based application, the High-Definition Fiber Tracking Report App, to enable clinicians and patients in research studies to see and understand damage from Traumatic Brain Injury (TBI) by viewing 2-dimensional and 3-dimensional images of their brain, with a focus on white matter tracts with quantitative metrics. The goal is to visualize white matter fiber tract injury like bone fractures; that is, to make the "invisible wounds of TBI" understandable for patients. Using mobile computing technology (iPad), imaging data for individual patients can be downloaded remotely within hours of a magnetic resonance imaging brain scan. Clinicians and patients can view the data in the form of images of each tract, rotating animations of the tracts, 3-dimensional models, and graphics. A growing number of tracts can be examined for asymmetry, gaps in streamline coverage, reduced arborization (branching), streamline volume, and standard quantitative metrics (e.g., Fractional Anisotropy (FA)). Novice users can learn to effectively navigate and interact with the application (explain the figures and graphs representing normal and injured brain tracts) within 15 minutes of simple orientation with high accuracy (96%). The architecture supports extensive graphics, configurable reports, provides an easy-to-use, attractive interface with a smooth user experience, and allows for securely serving cases from a database. Patients and clinicians have described the application as providing dramatic benefits in understanding their TBI and improving their lives. Reprint & Copyright © 2015 Association of Military Surgeons of the U.S.

Behavioral, Brain Imaging and Genomic Measures to Predict Functional Outcomes Post-Bed Rest and Space Flight

NASA Technical Reports Server (NTRS)

Mulavara, A. P.; Peters, B.; De Dios, Y. E.; Gadd, N. E.; Caldwell, E. E.; Batson, C. D.; Goel, R.; Oddsson, L.; Kreutzberg, G.; Zanello, S.;

Brain Imaging and Behavioral Outcome in Traumatic Brain Injury.

ERIC Educational Resources Information Center

Bigler, Erin D.

1996-01-01

This review explores the cellular pathology associated with traumatic brain injury (TBI) and its relation to neurobehavioral outcomes, the relationship of brain imaging findings to underlying pathology, brain imaging techniques, various image analysis procedures and how they relate to neuropsychological testing, and the importance of brain imaging…

Cross contrast multi-channel image registration using image synthesis for MR brain images.

PubMed

Chen, Min; Carass, Aaron; Jog, Amod; Lee, Junghoon; Roy, Snehashis; Prince, Jerry L

2017-02-01

Multi-modal deformable registration is important for many medical image analysis tasks such as atlas alignment, image fusion, and distortion correction. Whereas a conventional method would register images with different modalities using modality independent features or information theoretic metrics such as mutual information, this paper presents a new framework that addresses the problem using a two-channel registration algorithm capable of using mono-modal similarity measures such as sum of squared differences or cross-correlation. To make it possible to use these same-modality measures, image synthesis is used to create proxy images for the opposite modality as well as intensity-normalized images from each of the two available images. The new deformable registration framework was evaluated by performing intra-subject deformation recovery, intra-subject boundary alignment, and inter-subject label transfer experiments using multi-contrast magnetic resonance brain imaging data. Three different multi-channel registration algorithms were evaluated, revealing that the framework is robust to the multi-channel deformable registration algorithm that is used. With a single exception, all results demonstrated improvements when compared against single channel registrations using the same algorithm with mutual information. Copyright © 2016 Elsevier B.V. All rights reserved.

In vivo functional photoacoustic tomography of traumatic brain injury in rats

NASA Astrophysics Data System (ADS)

Oh, Jung-Taek; Song, Kwang-Hyung; Li, Meng-Lin; Stoica, George; Wang, Lihong V.

2006-02-01

In this study, we demonstrate the potential of photoacoustic tomography for the study of traumatic brain injury (TBI) in rats in vivo. Based on spectroscopic photoacoustic tomography that can detect the absorption rates of oxy- and deoxy-hemoglobins, the blood oxygen saturation and total blood volume in TBI rat brains were visualized. Reproducible cerebral trauma was induced using a fluid percussion TBI device. The time courses of the hemodynamic response following the trauma initiation were imaged with multi-wavelength photoacoustic tomography with bandwidth-limited spatial resolution through the intact skin and skull. In the pilot set of experiments, trauma induced hematomas and blood oxygen saturation level changes were detected, a finding consistent with the known physiological responses to TBI. This new imaging method will be useful for future studies on TBI-related metabolic activities and the effects of therapeutic agents.

Clinical image and pathology of hypertrophic cranial pachymeningitis.

PubMed

Shi, C H; Niu, S T; Zhang, Z Q

2014-12-12

The objective of this study was to examine the clinical findings, magnetic resonance imaging (MRI), pathological features, and treatment experiments of patients with hypertrophic cranial pachymeningitis (HCP). The clinical findings, MRI, and pathological appearances of 9 patients with HCP were analyzed retrospectively. The thickened dura mater was markedly enhanced after contrast media injection. The lesion near the brain hemisphere presented long regions of T1- and T2-weighted abnormal signal intensities. The abnormal signal intensities of the brain tissue were decreased significantly. Pathological examination demonstrated chronic inflammation changes, with cerebral dura mater fibrous tissue showing obvious hyperplasia, and the periphery of the blood vessel showing a great quantity of infiltrating phlegmonosis cells. HCP mainly presents headache and paralysis of multiple cranial nerves. The distinctive signs on brain MRIs involve strengthening the signal in the cerebral dura.

Triple-Quantum Filtered NMR Imaging of Sodium -23 in the Human Brain

NASA Astrophysics Data System (ADS)

Keltner, John Robinson

In the past multiple-quantum filtered imaging of biexponential relaxation sodium-23 nuclei in the human brain has been limited by low signal to noise ratios; this thesis demonstrates that such imaging is feasible when using a modified gradient-selected triple-quantum filter at a repetition time which maximizes the signal to noise ratio. Nuclear magnetic resonance imaging of biexponential relaxation sodium-23 (^{23}Na) nuclei in the human brain may be useful for detecting ischemia, cancer, and pathophysiology related to manic-depression. Multiple -quantum filters may be used to selectively image biexponential relaxation ^{23}Na signals since these filters suppress single-exponential relaxation ^{23}Na signals. In this thesis, the typical repetition times (200 -300 ms) used for in vivo multiple-quantum filtered ^{23}Na experiments are shown to be approximately 5 times greater than the optimal repetition time which maximizes multiple-quantum filtered SNR. Calculations and experimental verification show that the gradient-selected triple-quantum (GS3Q) filtered SNR for ^ {23}Na in a 4% agarose gel increases by a factor of two as the repetition time decreases from 300 ms to 55 ms. It is observed that a simple reduction of repetition time also increases spurious single-quantum signals from GS3Q filtered experiments. Irreducible superoperator calculations have been used to design a modified GS3Q filter which more effectively suppresses the spurious single-quantum signals. The modified GS3Q filter includes a preparatory crusher gradient and two-step-phase cycling. Using the modified GS3Q filter and a repetition time of 70 ms, a three dimensional triple-quantum filtered image of a phantom modelling ^{23} Na in the brain was obtained. The phantom consisted of two 4 cm diameter spheres inside of a 8.5 cm x 7 cm ellipsoid. The two spheres contained 0.012 and 0.024 M ^{23}Na in 4% agarose gel. Surrounding the spheres and inside the ellipsoid was 0.03 M aqueous ^{23}Na. The image dimensions were 16 x 16 x 16 voxels with the dimension of a voxel being 1.5 x 1.5 x 1.5 cm^3. The signal to noise ratio for the GS3Q filtered ^ {23}Na signal from the 0.012 and 0.024 M ^{23}Na spheres was 17 and 30 for a 54 minute experiment at 2.35 T. (Abstract shortened by UMI.).

Image-guided intracranial cannula placement for awake in vivo microdialysis in nonhuman primates

NASA Astrophysics Data System (ADS)

Chen, Antong; Bone, Ashleigh; Hines, Catherine D. G.; Dogdas, Belma; Montgomery, Tamara O.; Michener, Maria; Winkelmann, Christopher T.; Ghafurian, Soheil; Lubbers, Laura S.; Renger, John; Bagchi, Ansuman; Uslaner, Jason M.; Johnson, Colena; Zariwala, Hatim A.

2016-03-01

Intracranial microdialysis is used for sampling neurochemicals and large peptides along with their metabolites from the interstitial fluid (ISF) of the brain. The ability to perform this in nonhuman primates (NHP) e.g., rhesus could improve the prediction of pharmacokinetic (PK) and pharmacodynamics (PD) action of drugs in human. However, microdialysis in rhesus brains is not as routinely performed as in rodents. One challenge is that the precise intracranial probe placement in NHP brains is difficult due to the richness of the anatomical structure and the variability of the size and shape of brains across animals. Also, a repeatable and reproducible ISF sampling from the same animal is highly desirable when combined with cognitive behaviors or other longitudinal study end points. Toward that end, we have developed a semi-automatic flexible neurosurgical method employing MR and CT imaging to (a) derive coordinates for permanent guide cannula placement in mid-brain structures and (b) fabricate a customized recording chamber to implant above the skull for enclosing and safeguarding access to the cannula for repeated experiments. In order to place the intracranial guide cannula in each subject, the entry points in the skull and the depth in the brain were derived using co-registered images acquired from MR and CT scans. The anterior/posterior (A/P) and medial-lateral (M/L) rotation in the pose of the animal was corrected in the 3D image to appropriately represent the pose used in the stereotactic frame. An array of implanted fiducial markers was used to transform stereotactic coordinates to the images. The recording chamber was custom fabricated using computer-aided design (CAD), such that it would fit the contours of the individual skull with minimum error. The chamber also helped in guiding the cannula through the entry points down a trajectory into the depth of the brain. We have validated our method in four animals and our results indicate average placement error of cannula to be 1.20 +/- 0.68 mm of the targeted positions. The approach employed here for derivation of the coordinates, surgical implantation and post implant validation is built using traditional access to surgical and imaging methods without the necessity of intra-operative imaging. The validation of our method lends support to its wider application in most nonhuman primate laboratories with onsite MR and CT imaging capabilities.

The ultrasound brain helmet: early human feasibility study of multiple simultaneous 3D scans of cerebral vasculature

NASA Astrophysics Data System (ADS)

Lindsey, Brooks D.; Ivancevich, Nikolas M.; Whitman, John; Light, Edward; Fronheiser, Matthew; Nicoletto, Heather A.; Laskowitz, Daniel T.; Smith, Stephen W.

2009-02-01

We describe early stage experiments to test the feasibility of an ultrasound brain helmet to produce multiple simultaneous real-time 3D scans of the cerebral vasculature from temporal and suboccipital acoustic windows of the skull. The transducer hardware and software of the Volumetrics Medical Imaging real-time 3D scanner were modified to support dual 2.5 MHz matrix arrays of 256 transmit elements and 128 receive elements which produce two simultaneous 64° pyramidal scans. The real-time display format consists of two coronal B-mode images merged into a 128° sector, two simultaneous parasagittal images merged into a 128° × 64° C-mode plane, and a simultaneous 64° axial image. Real-time 3D color Doppler images acquired in initial clinical studies after contrast injection demonstrate flow in several representative blood vessels. An offline Doppler rendering of data from two transducers simultaneously scanning via the temporal windows provides an early visualization of the flow in vessels on both sides of the brain. The long-term goal is to produce real-time 3D ultrasound images of the cerebral vasculature from a portable unit capable of internet transmission, thus enabling interactive 3D imaging, remote diagnosis and earlier therapeutic intervention. We are motivated by the urgency for rapid diagnosis of stroke due to the short time window of effective therapeutic intervention.

Cryo-imaging of fluorescently labeled single cells in a mouse

NASA Astrophysics Data System (ADS)

Steyer, Grant J.; Roy, Debashish; Salvado, Olivier; Stone, Meredith E.; Wilson, David L.

2009-02-01

We developed a cryo-imaging system to provide single-cell detection of fluorescently labeled cells in mouse, with particular applicability to stem cells and metastatic cancer. The Case cryoimaging system consists of a fluorescence microscope, robotic imaging positioner, customized cryostat, PC-based control system, and visualization/analysis software. The system alternates between sectioning (10-40 μm) and imaging, collecting color brightfield and fluorescent blockface image volumes >60GB. In mouse experiments, we imaged quantum-dot labeled stem cells, GFP-labeled cancer and stem cells, and cell-size fluorescent microspheres. To remove subsurface fluorescence, we used a simplified model of light-tissue interaction whereby the next image was scaled, blurred, and subtracted from the current image. We estimated scaling and blurring parameters by minimizing entropy of subtracted images. Tissue specific attenuation parameters were found [uT : heart (267 +/- 47.6 μm), liver (218 +/- 27.1 μm), brain (161 +/- 27.4 μm)] to be within the range of estimates in the literature. "Next image" processing removed subsurface fluorescence equally well across multiple tissues (brain, kidney, liver, adipose tissue, etc.), and analysis of 200 microsphere images in the brain gave 97+/-2% reduction of subsurface fluorescence. Fluorescent signals were determined to arise from single cells based upon geometric and integrated intensity measurements. Next image processing greatly improved axial resolution, enabled high quality 3D volume renderings, and improved enumeration of single cells with connected component analysis by up to 24%. Analysis of image volumes identified metastatic cancer sites, found homing of stem cells to injury sites, and showed microsphere distribution correlated with blood flow patterns. We developed and evaluated cryo-imaging to provide single-cell detection of fluorescently labeled cells in mouse. Our cryo-imaging system provides extreme (>60GB), micron-scale, fluorescence, and bright field image data. Here we describe our image preprocessing, analysis, and visualization techniques. Processing improves axial resolution, reduces subsurface fluorescence by 97%, and enables single cell detection and counting. High quality 3D volume renderings enable us to evaluate cell distribution patterns. Applications include the myriad of biomedical experiments using fluorescent reporter gene and exogenous fluorophore labeling of cells in applications such as stem cell regenerative medicine, cancer, tissue engineering, etc.

Assessing Relevance of External Cognitive Measures.

PubMed

Cairó, Osvaldo

2017-01-01

The arrival of modern brain imaging technologies has provided new opportunities for examining the biological essence of human intelligence as well as the relationship between brain size and cognition. Thanks to these advances, we can now state that the relationship between brain size and intelligence has never been well understood. This view is supported by findings showing that cognition is correlated more with brain tissues than sheer brain size. The complexity of cellular and molecular organization of neural connections actually determines the computational capacity of the brain. In this review article, we determine that while genotypes are responsible for defining the theoretical limits of intelligence, what is primarily responsible for determining whether those limits are reached or exceeded is experience (environmental influence). Therefore, we contend that the gene-environment interplay defines the intelligent quotient of an individual.

Using brain stimulation to disentangle neural correlates of conscious vision

PubMed Central

de Graaf, Tom A.; Sack, Alexander T.

2014-01-01

Research into the neural correlates of consciousness (NCCs) has blossomed, due to the advent of new and increasingly sophisticated brain research tools. Neuroimaging has uncovered a variety of brain processes that relate to conscious perception, obtained in a range of experimental paradigms. But methods such as functional magnetic resonance imaging or electroencephalography do not always afford inference on the functional role these brain processes play in conscious vision. Such empirical NCCs could reflect neural prerequisites, neural consequences, or neural substrates of a conscious experience. Here, we take a closer look at the use of non-invasive brain stimulation (NIBS) techniques in this context. We discuss and review how NIBS methodology can enlighten our understanding of brain mechanisms underlying conscious vision by disentangling the empirical NCCs. PMID:25295015

Revised and updated recommendations for the establishment of primary stroke centers: a summary statement from the brain attack coalition.

PubMed

Alberts, Mark J; Latchaw, Richard E; Jagoda, Andy; Wechsler, Lawrence R; Crocco, Todd; George, Mary G; Connolly, E S; Mancini, Barbara; Prudhomme, Stephen; Gress, Daryl; Jensen, Mary E; Bass, Robert; Ruff, Robert; Foell, Kathy; Armonda, Rocco A; Emr, Marian; Warren, Margo; Baranski, Jim; Walker, Michael D

2011-09-01

The formation and certification of Primary Stroke Centers has progressed rapidly since the Brain Attack Coalition's original recommendations in 2000. The purpose of this article is to revise and update our recommendations for Primary Stroke Centers to reflect the latest data and experience. We conducted a literature review using MEDLINE and PubMed from March 2000 to January 2011. The review focused on studies that were relevant for acute stroke diagnosis, treatment, and care. Original references as well as meta-analyses and other care guidelines were also reviewed and included if found to be valid and relevant. Levels of evidence were added to reflect current guideline development practices. Based on the literature review and experience at Primary Stroke Centers, the importance of some elements has been further strengthened, and several new areas have been added. These include (1) the importance of acute stroke teams; (2) the importance of Stroke Units with telemetry monitoring; (3) performance of brain imaging with MRI and diffusion-weighted sequences; (4) assessment of cerebral vasculature with MR angiography or CT angiography; (5) cardiac imaging; (6) early initiation of rehabilitation therapies; and (7) certification by an independent body, including a site visit and disease performance measures. Based on the evidence, several elements of Primary Stroke Centers are particularly important for improving the care of patients with an acute stroke. Additional elements focus on imaging of the brain, the cerebral vasculature, and the heart. These new elements may improve the care and outcomes for patients with stroke cared for at a Primary Stroke Center.

Assessment of variability in cerebral vasculature for neuro-anatomical surgery planning in rodent brain

NASA Astrophysics Data System (ADS)

Rangarajan, J. R.; Van Kuyck, K.; Himmelreich, U.; Nuttin, B.; Maes, F.; Suetens, P.

2011-03-01

Clinical and pre-clinical studies show that deep brain stimulation (DBS) of targeted brain regions by neurosurgical techniques ameliorate psychiatric disorder such as anorexia nervosa. Neurosurgical interventions in preclinical rodent brain are mostly accomplished manually with a 2D atlas. Considering both the large number of animals subjected to stereotactic surgical experiments and the associated imaging cost, feasibility of sophisticated pre-operative imaging based surgical path planning and/or robotic guidance is limited. Here, we spatially normalize vasculature information and assess the intra-strain variability in cerebral vasculature for a neurosurgery planning. By co-registering and subsequently building a probabilistic vasculature template in a standard space, we evaluate the risk of a user defined electrode trajectory damaging a blood vessel on its path. The use of such a method may not only be confined to DBS therapy in small animals, but also could be readily applicable to a wide range of stereotactic small animal surgeries like targeted injection of contrast agents and cell labeling applications.

Current approaches to the treatment of metastatic brain tumours

PubMed Central

Owonikoko, Taofeek K.; Arbiser, Jack; Zelnak, Amelia; Shu, Hui-Kuo G.; Shim, Hyunsuk; Robin, Adam M.; Kalkanis, Steven N.; Whitsett, Timothy G.; Salhia, Bodour; Tran, Nhan L.; Ryken, Timothy; Moore, Michael K.; Egan, Kathleen M.; Olson, Jeffrey J.

2014-01-01

Metastatic tumours involving the brain overshadow primary brain neoplasms in frequency and are an important complication in the overall management of many cancers. Importantly, advances are being made in understanding the molecular biology underlying the initial development and eventual proliferation of brain metastases. Surgery and radiation remain the cornerstones of the therapy for symptomatic lesions; however, image-based guidance is improving surgical technique to maximize the preservation of normal tissue, while more sophisticated approaches to radiation therapy are being used to minimize the long-standing concerns over the toxicity of whole-brain radiation protocols used in the past. Furthermore, the burgeoning knowledge of tumour biology has facilitated the entry of systemically administered therapies into the clinic. Responses to these targeted interventions have ranged from substantial toxicity with no control of disease to periods of useful tumour control with no decrement in performance status of the treated individual. This experience enables recognition of the limits of targeted therapy, but has also informed methods to optimize this approach. This Review focuses on the clinically relevant molecular biology of brain metastases, and summarizes the current applications of these data to imaging, surgery, radiation therapy, cytotoxic chemotherapy and targeted therapy. PMID:24569448

3D brain oxygenation measurements in awake hypertensive mice using two photon phosphorescence lifetime imaging

NASA Astrophysics Data System (ADS)

Lu, Xuecong; Moeini, Mohammad; Li, Baoqiang; Zhang, Cong; Sakadžić, Sava; Lesage, Frédéric

2018-02-01

Cardiovascular risk factors, such as hypertension, have been associated with cognitive decline, potentially due to their impact on brain tissue oxygenation. In this study, high spatial resolution imaging in three dimensions was used to understand changes in brain oxygenation with hypertension. Experiments were performed on Young (WT_Y, 3-4 months, n=8), Old (WT_O, 6-7 months, n=8), and Old with hypertension (HP_O, 6-7 months, n=8) C57bL/6 awake mice. Two photon phosphorescence lifetime microscopy using an O2-sensitive phosphorescent dye PtPC343 was employed to measure two dimensional grids of PO2 in capillary beds (400um*400um, 25*25 pixels, acquired in 4 mins) and decays from arterioles. Scans were obtained continuously at depths from 50 um to 300 um under the brain surface. Using 3D measurements and a 250 um depth stack, we removed the compounding effects on brain oxygenation diffusion from surrounding brain vessels. The entire measurement of each vasculature stack required less than 30 minutes. This study indicates that among vascular risk factors, hypertension can reduce oxygen delivery and could potentially contribute to cognition decline.

Oxytocin enhances inter-brain synchrony during social coordination in male adults

PubMed Central

Mu, Yan; Guo, Chunyan

2016-01-01

Recent brain imaging research has revealed oxytocin (OT) effects on an individual's brain activity during social interaction but tells little about whether and how OT modulates the coherence of inter-brain activity related to two individuals' coordination behavior. We developed a new real-time coordination game that required two individuals of a dyad to synchronize with a partner (coordination task) or with a computer (control task) by counting in mind rhythmically. Electroencephalography (EEG) was recorded simultaneously from a dyad to examine OT effects on inter-brain synchrony of neural activity during interpersonal coordination. Experiment 1 found that dyads showed smaller interpersonal time lags of counting and greater inter-brain synchrony of alpha-band neural oscillations during the coordination (vs control) task and these effects were reliably observed in female but not male dyads. Moreover, the increased alpha-band inter-brain synchrony predicted better interpersonal behavioral synchrony across all participants. Experiment 2, using a double blind, placebo-controlled between-subjects design, revealed that intranasal OT vs placebo administration in male dyads improved interpersonal behavioral synchrony in both the coordination and control tasks but specifically enhanced alpha-band inter-brain neural oscillations during the coordination task. Our findings provide first evidence that OT enhances inter-brain synchrony in male adults to facilitate social coordination. PMID:27510498

Evaluation of a signal intensity mask in the interpretation of functional MR imaging activation maps.

PubMed

Strigel, Roberta M; Moritz, Chad H; Haughton, Victor M; Badie, Behnam; Field, Aaron; Wood, David; Hartman, Michael; Rowley, Howard A

2005-03-01

The purpose of this study was to determine the incidence of susceptibility artifacts on functional MR imaging (fMRI) studies and their effect on fMRI readings. We hypothesized that the availability of the signal intensity maps (SIMs) changes the interpretation of fMRI studies in which susceptibility artifacts affected eloquent brain regions. We reviewed 152 consecutive clinical fMRI studies performed with a SIM. The SIM consisted of the initial echo-planar images (EPI) in each section thresholded to eliminate signal intensity from outside the brain and then overlaid on anatomic images. The cause of the artifact was then determined by examining the images. Cases with a susceptibility artifact in eloquent brain were included in a blinded study read by four readers, first without and then with the SIM. For each reader, the number of times the interpretation changed on viewing the SIM was counted. Of 152 patients, 44% had signal intensity loss involving cerebral cortex and 18% involving an eloquent brain region. Causes of the artifacts were: surgical site artifact, blood products, dental devices, calcium, basal ganglia calcifications, ICP monitors, embolization materials, and air. When provided with the SIM, readers changed interpretations in 8-38% of patient cases, depending on reader experience and size and location of susceptibility artifact. Patients referred for clinical fMRI have a high incidence of susceptibility artifacts, whose presence and size can be determined by inspection of the SIM but not anatomic images. The availability of the SIM may affect interpretation of the fMRI.

Uncovering Camouflage: Amygdala Activation Predicts Long-Term Memory of Induced Perceptual Insight

PubMed Central

Ludmer, Rachel; Dudai, Yadin; Rubin, Nava

2012-01-01

What brain mechanisms underlie learning of new knowledge from single events? We studied encoding in long-term memory of a unique type of one-shot experience, induced perceptual insight. While undergoing an fMRI brain scan, participants viewed degraded images of real-world pictures where the underlying objects were hard to recognize (‘camouflage’), followed by brief exposures to the original images (‘solution’), which led to induced insight (“Aha!”). A week later, participants’ memory was tested; a solution image was classified as ‘remembered’ if detailed perceptual knowledge was elicited from the camouflage image alone. During encoding, subsequently remembered images enjoyed higher activity in mid-level visual cortex and medial frontal cortex, but most pronouncedly in the amygdala, whose activity could be used to predict which solutions will remain in long-term memory. Our findings extend the known roles of amygdala in memory to include promoting of long-term memory of the sudden reorganization of internal representations. PMID:21382558

NIR time domain diffuse optical tomography experiments on human forearm

NASA Astrophysics Data System (ADS)

Zhao, Huijuan; Gao, Feng; Tanikawa, Yukari; Homma, Kazuhiro; Yamada, Yukio

2003-07-01

To date, the applications of near infrared (NIR) diffusion optical tomography (DOT) are mostly focused on the potential of imaging woman breast, human head hemodynamics and neonatal head. For the neonates, who are suffered from ischaemia or hemorrhages in brain, bedside monitoring of the cerebral perfusion situation, e.g., the blood oxygen saturation and blood volume, is necessary for avoiding permanent injure. NIR DOT is on the promising tools because it is noninvasive, smaller in size, and moveable. Prior to achieving the ultimate goal of imaging infant brain and woman breast using DOT, in this paper, the developed methodologies are justified by imaging in vivo human forearms. The absolute absorption- and scattering-coefficient images revealed the inner structure of the forearm and the bones were clearly distinguished from the muscle. The differential images showed the changes in oxy-hemoglobin, deoxy-hemoglobin and blood volume during the hand-gripping exercises, which are consistent with the physiological process reported on literatures.

Diffuse optical tomography and spectroscopy of breast cancer and fetal brain

NASA Astrophysics Data System (ADS)

Choe, Regine

Diffuse optical techniques utilize light in the near infrared spectral range to measure tissue physiology non-invasively. Based on these measurements, either on average or a three-dimensional spatial map of tissue properties such as total hemoglobin concentration, blood oxygen saturation and scattering can be obtained using model-based reconstruction algorithms. In this thesis, diffuse optical techniques were applied for in vivo breast cancer imaging and trans-abdominal fetal brain oxygenation monitoring. For in vivo breast cancer imaging, clinical diffuse optical tomography and related instrumentation was developed and used in several contexts. Bulk physiological properties were quantified for fifty-two healthy subjects in the parallel-plate transmission geometry. Three-dimensional images of breast were reconstructed for subjects with breast tumors and, tumor contrast with respect to normal tissue was found in total hemoglobin concentration and scattering and was quantified for twenty-two breast carcinomas. Tumor contrast and tumor volume changes during neoadjuvant chemotherapy were tracked for one subject and compared to the dynamic contrast-enhanced MRI. Finally, the feasibility for measuring blood flow of breast tumors using optical methods was demonstrated for seven subjects. In a qualitatively different set of experiments, the feasibility for trans-abdominal fetal brain oxygenation monitoring was demonstrated on pregnant ewes with induced fetal hypoxia. Preliminary clinical experiences were discussed to identify future directions. In total, this research has translated diffuse optical tomography techniques into clinical research environment.

Image-guided microbeam irradiation to brain tumour bearing mice using a carbon nanotube X-ray source array

PubMed Central

Zhang, Lei; Yuan, Hong; Burk, Laurel M; Inscoe, Christy R; Hadsell, Michael J; Chtcheprov, Pavel; Lee, Yueh Z; Lu, Jianping; Chang, Sha; Zhou, Otto

2014-01-01

Microbeam radiation therapy (MRT) is a promising experimental and preclinical radiotherapy method for cancer treatment. Synchrotron based MRT experiments have shown that spatially fractionated microbeam radiation has the unique capability of preferentially eradicating tumour cells while sparing normal tissue in brain tumour bearing animal models. We recently demonstrated the feasibility of generating orthovoltage microbeam radiation with an adjustable microbeam width using a carbon nanotube based X-ray source array. Here we report the preliminary results from our efforts in developing an image guidance procedure for the targeted delivery of the narrow microbeams to the small tumour region in the mouse brain. Magnetic resonance imaging was used for tumour identification, and on-board X-ray radiography was used for imaging of landmarks without contrast agents. The two images were aligned using 2D rigid body image registration to determine the relative position of the tumour with respect to a landmark. The targeting accuracy and consistency were evaluated by first irradiating a group of mice inoculated with U87 human glioma brain tumours using the present protocol and then determining the locations of the microbeam radiation tracks using γ-H2AX immunofluorescence staining. The histology results showed that among 14 mice irradiated, 11 received the prescribed number of microbeams on the targeted tumour, with an average localization accuracy of 454 μm measured directly from the histology (537 μm if measured from the registered histological images). Two mice received one of the three prescribed microbeams on the tumour site. One mouse was excluded from the analysis due to tissue staining errors. PMID:24556798

Developing 3D microscopy with CLARITY on human brain tissue: Towards a tool for informing and validating MRI-based histology.

PubMed

Morawski, Markus; Kirilina, Evgeniya; Scherf, Nico; Jäger, Carsten; Reimann, Katja; Trampel, Robert; Gavriilidis, Filippos; Geyer, Stefan; Biedermann, Bernd; Arendt, Thomas; Weiskopf, Nikolaus

2017-11-28

Recent breakthroughs in magnetic resonance imaging (MRI) enabled quantitative relaxometry and diffusion-weighted imaging with sub-millimeter resolution. Combined with biophysical models of MR contrast the emerging methods promise in vivo mapping of cyto- and myelo-architectonics, i.e., in vivo histology using MRI (hMRI) in humans. The hMRI methods require histological reference data for model building and validation. This is currently provided by MRI on post mortem human brain tissue in combination with classical histology on sections. However, this well established approach is limited to qualitative 2D information, while a systematic validation of hMRI requires quantitative 3D information on macroscopic voxels. We present a promising histological method based on optical 3D imaging combined with a tissue clearing method, Clear Lipid-exchanged Acrylamide-hybridized Rigid Imaging compatible Tissue hYdrogel (CLARITY), adapted for hMRI validation. Adapting CLARITY to the needs of hMRI is challenging due to poor antibody penetration into large sample volumes and high opacity of aged post mortem human brain tissue. In a pilot experiment we achieved transparency of up to 8 mm-thick and immunohistochemical staining of up to 5 mm-thick post mortem brain tissue by a combination of active and passive clearing, prolonged clearing and staining times. We combined 3D optical imaging of the cleared samples with tailored image processing methods. We demonstrated the feasibility for quantification of neuron density, fiber orientation distribution and cell type classification within a volume with size similar to a typical MRI voxel. The presented combination of MRI, 3D optical microscopy and image processing is a promising tool for validation of MRI-based microstructure estimates. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Novel Noninvasive Brain Disease Detection System Using a Facial Image Sensor

PubMed Central

Shu, Ting; Zhang, Bob; Tang, Yuan Yan

2017-01-01

Brain disease including any conditions or disabilities that affect the brain is fast becoming a leading cause of death. The traditional diagnostic methods of brain disease are time-consuming, inconvenient and non-patient friendly. As more and more individuals undergo examinations to determine if they suffer from any form of brain disease, developing noninvasive, efficient, and patient friendly detection systems will be beneficial. Therefore, in this paper, we propose a novel noninvasive brain disease detection system based on the analysis of facial colors. The system consists of four components. A facial image is first captured through a specialized sensor, where four facial key blocks are next located automatically from the various facial regions. Color features are extracted from each block to form a feature vector for classification via the Probabilistic Collaborative based Classifier. To thoroughly test the system and its performance, seven facial key block combinations were experimented. The best result was achieved using the second facial key block, where it showed that the Probabilistic Collaborative based Classifier is the most suitable. The overall performance of the proposed system achieves an accuracy −95%, a sensitivity −94.33%, a specificity −95.67%, and an average processing time (for one sample) of <1 min at brain disease detection. PMID:29292716

Brain vascular image segmentation based on fuzzy local information C-means clustering

NASA Astrophysics Data System (ADS)

Hu, Chaoen; Liu, Xia; Liang, Xiao; Hui, Hui; Yang, Xin; Tian, Jie

2017-02-01

Light sheet fluorescence microscopy (LSFM) is a powerful optical resolution fluorescence microscopy technique which enables to observe the mouse brain vascular network in cellular resolution. However, micro-vessel structures are intensity inhomogeneity in LSFM images, which make an inconvenience for extracting line structures. In this work, we developed a vascular image segmentation method by enhancing vessel details which should be useful for estimating statistics like micro-vessel density. Since the eigenvalues of hessian matrix and its sign describes different geometric structure in images, which enable to construct vascular similarity function and enhance line signals, the main idea of our method is to cluster the pixel values of the enhanced image. Our method contained three steps: 1) calculate the multiscale gradients and the differences between eigenvalues of Hessian matrix. 2) In order to generate the enhanced microvessels structures, a feed forward neural network was trained by 2.26 million pixels for dealing with the correlations between multi-scale gradients and the differences between eigenvalues. 3) The fuzzy local information c-means clustering (FLICM) was used to cluster the pixel values in enhance line signals. To verify the feasibility and effectiveness of this method, mouse brain vascular images have been acquired by a commercial light-sheet microscope in our lab. The experiment of the segmentation method showed that dice similarity coefficient can reach up to 85%. The results illustrated that our approach extracting line structures of blood vessels dramatically improves the vascular image and enable to accurately extract blood vessels in LSFM images.

The myth of the normal, average human brain--the ICBM experience: (1) subject screening and eligibility.

PubMed

Mazziotta, John C; Woods, Roger; Iacoboni, Marco; Sicotte, Nancy; Yaden, Kami; Tran, Mary; Bean, Courtney; Kaplan, Jonas; Toga, Arthur W

2009-02-01

In the course of developing an atlas and reference system for the normal human brain throughout the human age span from structural and functional brain imaging data, the International Consortium for Brain Mapping (ICBM) developed a set of "normal" criteria for subject inclusion and the associated exclusion criteria. The approach was to minimize inclusion of subjects with any medical disorders that could affect brain structure or function. In the past two years, a group of 1685 potential subjects responded to solicitation advertisements at one of the consortium sites (UCLA). Subjects were screened by a detailed telephone interview and then had an in-person history and physical examination. Of those who responded to the advertisement and considered themselves to be normal, only 31.6% (532 subjects) passed the telephone screening process. Of the 348 individuals who submitted to in-person history and physical examinations, only 51.7% passed these screening procedures. Thus, only 10.7% of those individuals who responded to the original advertisement qualified for imaging. The most frequent cause for exclusion in the second phase of subject screening was high blood pressure followed by abnormal signs on neurological examination. It is concluded that the majority of individuals who consider themselves normal by self-report are found not to be so by detailed historical interviews about underlying medical conditions and by thorough medical and neurological examinations. Recommendations are made with regard to the inclusion of subjects in brain imaging studies and the criteria used to select them.

Computer aided solution for segmenting the neuron line in hippocampal microscope images

NASA Astrophysics Data System (ADS)

Albaidhani, Tahseen; Jassim, Sabah; Al-Assam, Hisham

2017-05-01

The brain Hippocampus component is known to be responsible for memory and spatial navigation. Its functionality depends on the status of different blood vessels within the Hippocampus and is severely impaired by Alzheimer's disease as a result blockage of increasing number of blood vessels by accumulation of amyloid-beta (Aβ) protein. Accurate counting of blood vessels within the Hippocampus of mice brain, from microscopic images, is an active research area for the understanding of Alzheimer's disease. Here, we report our work on automatic detection of the Region of Interest, i.e. the region in which blood vessels are located. This area typically falls between the hippocampus edge and the line of neurons within the Hippocampus. This paper proposes a new method to detect and exclude the neuron line to improve the accuracy of blood vessel counting because some neurons on it might lead to false positive cases as they look like blood vessels. Our proposed solution is based on using trainable segmentation approach with morphological operations, taking into account variation in colour, intensity values, and image texture. Experiments on a sufficient number of microscopy images of mouse brain demonstrate the effectiveness of the developed solution in preparation for blood vessels counting.

Using connectome-based predictive modeling to predict individual behavior from brain connectivity

PubMed Central

Shen, Xilin; Finn, Emily S.; Scheinost, Dustin; Rosenberg, Monica D.; Chun, Marvin M.; Papademetris, Xenophon; Constable, R Todd

2017-01-01

Neuroimaging is a fast developing research area where anatomical and functional images of human brains are collected using techniques such as functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), and electroencephalography (EEG). Technical advances and large-scale datasets have allowed for the development of models capable of predicting individual differences in traits and behavior using brain connectivity measures derived from neuroimaging data. Here, we present connectome-based predictive modeling (CPM), a data-driven protocol for developing predictive models of brain-behavior relationships from connectivity data using cross-validation. This protocol includes the following steps: 1) feature selection, 2) feature summarization, 3) model building, and 4) assessment of prediction significance. We also include suggestions for visualizing the most predictive features (i.e., brain connections). The final result should be a generalizable model that takes brain connectivity data as input and generates predictions of behavioral measures in novel subjects, accounting for a significant amount of the variance in these measures. It has been demonstrated that the CPM protocol performs equivalently or better than most of the existing approaches in brain-behavior prediction. However, because CPM focuses on linear modeling and a purely data-driven driven approach, neuroscientists with limited or no experience in machine learning or optimization would find it easy to implement the protocols. Depending on the volume of data to be processed, the protocol can take 10–100 minutes for model building, 1–48 hours for permutation testing, and 10–20 minutes for visualization of results. PMID:28182017

Immediate memory for “when, where and what”: Short‐delay retrieval using dynamic naturalistic material

PubMed Central

Macaluso, Emiliano

2015-01-01

Abstract We investigated the neural correlates supporting three kinds of memory judgments after very short delays using naturalistic material. In two functional magnetic resonance imaging (fMRI) experiments, subjects watched short movie clips, and after a short retention (1.5–2.5 s), made mnemonic judgments about specific aspects of the clips. In Experiment 1, subjects were presented with two scenes and required to either choose the scene that happened earlier in the clip (“scene‐chronology”), or with a correct spatial arrangement (“scene‐layout”), or that had been shown (“scene‐recognition”). To segregate activity specific to seen versus unseen stimuli, in Experiment 2 only one probe image was presented (either target or foil). Across the two experiments, we replicated three patterns underlying the three specific forms of memory judgment. The precuneus was activated during temporal‐order retrieval, the superior parietal cortex was activated bilaterally for spatial‐related configuration judgments, whereas the medial frontal cortex during scene recognition. Conjunction analyses with a previous study that used analogous retrieval tasks, but a much longer delay (>1 day), demonstrated that this dissociation pattern is independent of retention delay. We conclude that analogous brain regions mediate task‐specific retrieval across vastly different delays, consistent with the proposal of scale‐invariance in episodic memory retrieval. Hum Brain Mapp 36:2495–2513, 2015. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. PMID:25773646

High-fidelity artifact correction for cone-beam CT imaging of the brain

NASA Astrophysics Data System (ADS)

Sisniega, A.; Zbijewski, W.; Xu, J.; Dang, H.; Stayman, J. W.; Yorkston, J.; Aygun, N.; Koliatsos, V.; Siewerdsen, J. H.

2015-02-01

CT is the frontline imaging modality for diagnosis of acute traumatic brain injury (TBI), involving the detection of fresh blood in the brain (contrast of 30-50 HU, detail size down to 1 mm) in a non-contrast-enhanced exam. A dedicated point-of-care imaging system based on cone-beam CT (CBCT) could benefit early detection of TBI and improve direction to appropriate therapy. However, flat-panel detector (FPD) CBCT is challenged by artifacts that degrade contrast resolution and limit application in soft-tissue imaging. We present and evaluate a fairly comprehensive framework for artifact correction to enable soft-tissue brain imaging with FPD CBCT. The framework includes a fast Monte Carlo (MC)-based scatter estimation method complemented by corrections for detector lag, veiling glare, and beam hardening. The fast MC scatter estimation combines GPU acceleration, variance reduction, and simulation with a low number of photon histories and reduced number of projection angles (sparse MC) augmented by kernel de-noising to yield a runtime of ~4 min per scan. Scatter correction is combined with two-pass beam hardening correction. Detector lag correction is based on temporal deconvolution of the measured lag response function. The effects of detector veiling glare are reduced by deconvolution of the glare response function representing the long range tails of the detector point-spread function. The performance of the correction framework is quantified in experiments using a realistic head phantom on a testbench for FPD CBCT. Uncorrected reconstructions were non-diagnostic for soft-tissue imaging tasks in the brain. After processing with the artifact correction framework, image uniformity was substantially improved, and artifacts were reduced to a level that enabled visualization of ~3 mm simulated bleeds throughout the brain. Non-uniformity (cupping) was reduced by a factor of 5, and contrast of simulated bleeds was improved from ~7 to 49.7 HU, in good agreement with the nominal blood contrast of 50 HU. Although noise was amplified by the corrections, the contrast-to-noise ratio (CNR) of simulated bleeds was improved by nearly a factor of 3.5 (CNR = 0.54 without corrections and 1.91 after correction). The resulting image quality motivates further development and translation of the FPD-CBCT system for imaging of acute TBI.

Warping of a computerized 3-D atlas to match brain image volumes for quantitative neuroanatomical and functional analysis

NASA Astrophysics Data System (ADS)

Evans, Alan C.; Dai, Weiqian; Collins, D. Louis; Neelin, Peter; Marrett, Sean

1991-06-01

We describe the implementation, experience and preliminary results obtained with a 3-D computerized brain atlas for topographical and functional analysis of brain sub-regions. A volume-of-interest (VOI) atlas was produced by manual contouring on 64 adjacent 2 mm-thick MRI slices to yield 60 brain structures in each hemisphere which could be adjusted, originally by global affine transformation or local interactive adjustments, to match individual MRI datasets. We have now added a non-linear deformation (warp) capability (Bookstein, 1989) into the procedure for fitting the atlas to the brain data. Specific target points are identified in both atlas and MRI spaces which define a continuous 3-D warp transformation that maps the atlas on to the individual brain image. The procedure was used to fit MRI brain image volumes from 16 young normal volunteers. Regional volume and positional variability were determined, the latter in such a way as to assess the extent to which previous linear models of brain anatomical variability fail to account for the true variation among normal individuals. Using a linear model for atlas deformation yielded 3-D fits of the MRI data which, when pooled across subjects and brain regions, left a residual mis-match of 6 - 7 mm as compared to the non-linear model. The results indicate a substantial component of morphometric variability is not accounted for by linear scaling. This has profound implications for applications which employ stereotactic coordinate systems which map individual brains into a common reference frame: quantitative neuroradiology, stereotactic neurosurgery and cognitive mapping of normal brain function with PET. In the latter case, the combination of a non-linear deformation algorithm would allow for accurate measurement of individual anatomic variations and the inclusion of such variations in inter-subject averaging methodologies used for cognitive mapping with PET.

Concussion-Mild Traumatic Brain Injury: Recoverable Injury with Potential for Serious Sequelae.

PubMed

Kamins, Joshua; Giza, Christopher C

2016-10-01

Concussion is increasingly recognized as a major public health issue. Most patients will return to baseline and experience full recovery, although a subset experiences persistent symptoms. Newer animal models and imaging studies are beginning to demonstrate that metabolic and neurovascular resolution may actually take longer than symptomatic recovery. Repeat traumatic brain injury within the metabolic window of dysfunction may result in worsened symptoms and prolonged recovery. The true risk for second impact syndrome appears to be small, and development of cerebral edema after a mild impact may be related to genetic risks rather than serial impacts. Published by Elsevier Inc.

Brain regions sensitive to the face inversion effect: a functional magnetic resonance imaging study in humans.

PubMed

Leube, Dirk T; Yoon, Hyo Woon; Rapp, Alexander; Erb, Michael; Grodd, Wolfgang; Bartels, Mathias; Kircher, Tilo T J

2003-05-22

Perception of upright faces relies on configural processing. Therefore recognition of inverted, compared to upright faces is impaired. In a functional magnetic resonance imaging experiment we investigated the neural correlate of a face inversion task. Thirteen healthy subjects were presented with a equal number of upright and inverted faces alternating with a low level baseline with an upright and inverted picture of an abstract symbol. Brain activation was calculated for upright minus inverted faces. For this differential contrast, we found a signal change in the right superior temporal sulcus and right insula. Configural properties are processed in a network comprising right superior temporal and insular cortex.

Neuroimaging in pedophilia.

PubMed

Wiebking, Christine; Northoff, Georg

2013-04-01

Paraphilia is a set of disorders characterized by abnormal sexual desires. Perhaps most discussed amongst them, pedophilia is a complex interaction of disturbances of the emotional, cognitive and sexual experience. Using new imaging techniques such as functional magnetic resonance imaging, neural correlates of emotional, sexual and cognitive abnormalities and interactions have been investigated. As described on the basis of current research, altered patterns of brain activity, especially in the frontal areas of the brain, are seen in pedophilia. Building on these results, the analysis of neural correlates of impaired psychological functions opens the opportunity to further explore sexual deviances, which may contribute ultimately to the development of tools for risk assessment, classification methods and new therapeutic approaches.

An automatic rat brain extraction method based on a deformable surface model.

PubMed

Li, Jiehua; Liu, Xiaofeng; Zhuo, Jiachen; Gullapalli, Rao P; Zara, Jason M

2013-08-15

The extraction of the brain from the skull in medical images is a necessary first step before image registration or segmentation. While pre-clinical MR imaging studies on small animals, such as rats, are increasing, fully automatic imaging processing techniques specific to small animal studies remain lacking. In this paper, we present an automatic rat brain extraction method, the Rat Brain Deformable model method (RBD), which adapts the popular human brain extraction tool (BET) through the incorporation of information on the brain geometry and MR image characteristics of the rat brain. The robustness of the method was demonstrated on T2-weighted MR images of 64 rats and compared with other brain extraction methods (BET, PCNN, PCNN-3D). The results demonstrate that RBD reliably extracts the rat brain with high accuracy (>92% volume overlap) and is robust against signal inhomogeneity in the images. Copyright © 2013 Elsevier B.V. All rights reserved.

Validation tools for image segmentation

NASA Astrophysics Data System (ADS)

Padfield, Dirk; Ross, James

2009-02-01

A large variety of image analysis tasks require the segmentation of various regions in an image. For example, segmentation is required to generate accurate models of brain pathology that are important components of modern diagnosis and therapy. While the manual delineation of such structures gives accurate information, the automatic segmentation of regions such as the brain and tumors from such images greatly enhances the speed and repeatability of quantifying such structures. The ubiquitous need for such algorithms has lead to a wide range of image segmentation algorithms with various assumptions, parameters, and robustness. The evaluation of such algorithms is an important step in determining their effectiveness. Therefore, rather than developing new segmentation algorithms, we here describe validation methods for segmentation algorithms. Using similarity metrics comparing the automatic to manual segmentations, we demonstrate methods for optimizing the parameter settings for individual cases and across a collection of datasets using the Design of Experiment framework. We then employ statistical analysis methods to compare the effectiveness of various algorithms. We investigate several region-growing algorithms from the Insight Toolkit and compare their accuracy to that of a separate statistical segmentation algorithm. The segmentation algorithms are used with their optimized parameters to automatically segment the brain and tumor regions in MRI images of 10 patients. The validation tools indicate that none of the ITK algorithms studied are able to outperform with statistical significance the statistical segmentation algorithm although they perform reasonably well considering their simplicity.

Neuroplasticity as a function of second language learning: anatomical changes in the human brain.

PubMed

Li, Ping; Legault, Jennifer; Litcofsky, Kaitlyn A

2014-09-01

The brain has an extraordinary ability to functionally and physically change or reconfigure its structure in response to environmental stimulus, cognitive demand, or behavioral experience. This property, known as neuroplasticity, has been examined extensively in many domains. But how does neuroplasticity occur in the brain as a function of an individual's experience with a second language? It is not until recently that we have gained some understanding of this question by examining the anatomical changes as well as functional neural patterns that are induced by the learning and use of multiple languages. In this article we review emerging evidence regarding how structural neuroplasticity occurs in the brain as a result of one's bilingual experience. Our review aims at identifying the processes and mechanisms that drive experience-dependent anatomical changes, and integrating structural imaging evidence with current knowledge of functional neural plasticity of language and other cognitive skills. The evidence reviewed so far portrays a picture that is highly consistent with structural neuroplasticity observed for other domains: second language experience-induced brain changes, including increased gray matter (GM) density and white matter (WM) integrity, can be found in children, young adults, and the elderly; can occur rapidly with short-term language learning or training; and are sensitive to age, age of acquisition, proficiency or performance level, language-specific characteristics, and individual differences. We conclude with a theoretical perspective on neuroplasticity in language and bilingualism, and point to future directions for research. Copyright © 2014 Elsevier Ltd. All rights reserved.

Preparing hearts and minds: cardiac slowing and a cortical inhibitory network.

PubMed

Jennings, J R; van der Molen, M W; Tanase, C

2009-11-01

Preparing for a cued, speeded response induces a set of physiological changes. A review of the psychophysiology of preparation suggested that inhibition of action was an important process among the constellation of changes constituting attentive preparation. The current experiment combined event-related functional magnetic resonance imaging and cardiac inter-beat interval measures in an experiment that compared preparing for a response, watching stimuli without responding, and responding in the absence of preparation. Ten college-aged participants were tested in an initial psychophysiological experiment followed by two scanning sessions during which reverse spiral imaging was performed concurrent with inter-beat interval measurement. Two analytic approaches were used to confirm blood oxygenation level dependent responses during preparation, and these converged to show inferior prefrontal and related subthalamic nuclei activity in the context of other known changes related to brain attentional networks. Subthalamic nuclei changes were related to the depth of preparatory cardiac deceleration. This pattern of findings suggests that preparation involves the activation of a complex inhibitory neural network implicating brain and autonomic nervous systems.

Atlas-based fuzzy connectedness segmentation and intensity nonuniformity correction applied to brain MRI.

PubMed

Zhou, Yongxin; Bai, Jing

2007-01-01

A framework that combines atlas registration, fuzzy connectedness (FC) segmentation, and parametric bias field correction (PABIC) is proposed for the automatic segmentation of brain magnetic resonance imaging (MRI). First, the atlas is registered onto the MRI to initialize the following FC segmentation. Original techniques are proposed to estimate necessary initial parameters of FC segmentation. Further, the result of the FC segmentation is utilized to initialize a following PABIC algorithm. Finally, we re-apply the FC technique on the PABIC corrected MRI to get the final segmentation. Thus, we avoid expert human intervention and provide a fully automatic method for brain MRI segmentation. Experiments on both simulated and real MRI images demonstrate the validity of the method, as well as the limitation of the method. Being a fully automatic method, it is expected to find wide applications, such as three-dimensional visualization, radiation therapy planning, and medical database construction.

Brain Responses to Dynamic Facial Expressions: A Normative Meta-Analysis.

PubMed

Zinchenko, Oksana; Yaple, Zachary A; Arsalidou, Marie

2018-01-01

Identifying facial expressions is crucial for social interactions. Functional neuroimaging studies show that a set of brain areas, such as the fusiform gyrus and amygdala, become active when viewing emotional facial expressions. The majority of functional magnetic resonance imaging (fMRI) studies investigating face perception typically employ static images of faces. However, studies that use dynamic facial expressions (e.g., videos) are accumulating and suggest that a dynamic presentation may be more sensitive and ecologically valid for investigating faces. By using quantitative fMRI meta-analysis the present study examined concordance of brain regions associated with viewing dynamic facial expressions. We analyzed data from 216 participants that participated in 14 studies, which reported coordinates for 28 experiments. Our analysis revealed bilateral fusiform and middle temporal gyri, left amygdala, left declive of the cerebellum and the right inferior frontal gyrus. These regions are discussed in terms of their relation to models of face processing.

ELSI Priorities for Brain Imaging

PubMed Central

Illes, Judy; De Vries, Raymond; Cho, Mildred K.; Schraedley-Desmond, Pam

2006-01-01

As one of the most compelling technologies for imaging the brain, functional MRI (fMRI) produces measurements and persuasive pictures of research subjects making cognitive judgments and even reasoning through difficult moral decisions. Even after centuries of studying the link between brain and behavior, this capability presents a number of novel significant questions. For example, what are the implications of biologizing human experience? How might neuroimaging disrupt the mysteries of human nature, spirituality, and personal identity? Rather than waiting for an ethical agenda to emerge from some unpredictable combination of the concerns of ethicists and researchers, the attention of journalists, or after controversy is sparked by research that cannot be retracted, we queried key figures in bioethics and the humanities, neuroscience, media, industry, and patient advocacy in focus groups and interviews. We identified specific ethical, legal and social issues (ELSI) that highlight researcher obligations and the nonclinical impact of the technology at this new frontier. PMID:16500831

Spatial working memory in heavy cannabis users: a functional magnetic resonance imaging study.

PubMed

Kanayama, Gen; Rogowska, Jadwiga; Pope, Harrison G; Gruber, Staci A; Yurgelun-Todd, Deborah A

2004-11-01

Many neuropsychological studies have documented deficits in working memory among recent heavy cannabis users. However, little is known about the effects of cannabis on brain activity. We assessed brain function among recent heavy cannabis users while they performed a working memory task. Functional magnetic resonance imaging was used to examine brain activity in 12 long-term heavy cannabis users, 6-36 h after last use, and in 10 control subjects while they performed a spatial working memory task. Regional brain activation was analyzed and compared using statistical parametric mapping techniques. Compared with controls, cannabis users exhibited increased activation of brain regions typically used for spatial working memory tasks (such as prefrontal cortex and anterior cingulate). Users also recruited additional regions not typically used for spatial working memory (such as regions in the basal ganglia). These findings remained essentially unchanged when re-analyzed using subjects' ages as a covariate. Brain activation showed little or no significant correlation with subjects' years of education, verbal IQ, lifetime episodes of cannabis use, or urinary cannabinoid levels at the time of scanning. Recent cannabis users displayed greater and more widespread brain activation than normal subjects when attempting to perform a spatial working memory task. This observation suggests that recent cannabis users may experience subtle neurophysiological deficits, and that they compensate for these deficits by "working harder"-calling upon additional brain regions to meet the demands of the task.

Automating cell detection and classification in human brain fluorescent microscopy images using dictionary learning and sparse coding.

PubMed

Alegro, Maryana; Theofilas, Panagiotis; Nguy, Austin; Castruita, Patricia A; Seeley, William; Heinsen, Helmut; Ushizima, Daniela M; Grinberg, Lea T

2017-04-15

Immunofluorescence (IF) plays a major role in quantifying protein expression in situ and understanding cell function. It is widely applied in assessing disease mechanisms and in drug discovery research. Automation of IF analysis can transform studies using experimental cell models. However, IF analysis of postmortem human tissue relies mostly on manual interaction, often subjected to low-throughput and prone to error, leading to low inter and intra-observer reproducibility. Human postmortem brain samples challenges neuroscientists because of the high level of autofluorescence caused by accumulation of lipofuscin pigment during aging, hindering systematic analyses. We propose a method for automating cell counting and classification in IF microscopy of human postmortem brains. Our algorithm speeds up the quantification task while improving reproducibility. Dictionary learning and sparse coding allow for constructing improved cell representations using IF images. These models are input for detection and segmentation methods. Classification occurs by means of color distances between cells and a learned set. Our method successfully detected and classified cells in 49 human brain images. We evaluated our results regarding true positive, false positive, false negative, precision, recall, false positive rate and F1 score metrics. We also measured user-experience and time saved compared to manual countings. We compared our results to four open-access IF-based cell-counting tools available in the literature. Our method showed improved accuracy for all data samples. The proposed method satisfactorily detects and classifies cells from human postmortem brain IF images, with potential to be generalized for applications in other counting tasks. Copyright © 2017 Elsevier B.V. All rights reserved.

Noninvasive diffusive optical imaging of the auditory response to birdsong in the zebra finch

PubMed Central

Lee, James V.; Maclin, Edward L.; Low, Kathy A.; Gratton, Gabriele; Fabiani, Monica; Clayton, David F.

2013-01-01

Songbirds communicate by learned vocalizations with concomitant changes in neurophysiological and genomic activities in discrete parts of the brain. Here we tested a novel implementation of diffusive optical imaging (also known as diffuse optical imaging, DOI) for monitoring brain physiology associated with vocal signal perception. DOI noninvasively measures brain activity using red and near-infrared light delivered through optic fibers (optodes) resting on the scalp. DOI does not harm subjects, so it raises the possibility of repeatedly measuring brain activity and the effects of accumulated experience in the same subject over an entire life span, all while leaving tissue intact for further study. We developed a custom-made apparatus for interfacing optodes to the zebra finch (Taeniopygia guttata) head using 3D modeling software and rapid prototyping technology, and applied it to record responses to presentations of birdsong in isoflurane-anesthetized zebra finches. We discovered a subtle but significant difference between the hemoglobin spectra of zebra finches and mammals which has a major impact in how hemodynamic responses are interpreted in the zebra finch. Our measured responses to birdsong playback were robust, highly repeatable, and readily observed in single trials. Responses were complex in shape and closely paralleled responses described in mammals. They were localized to the caudal medial portion of the brain, consistent with response localization from prior gene expression, electrophysiological, and functional magnetic resonance imaging studies. These results define an approach for collecting neurophysiological data from songbirds that should be applicable to diverse species and adaptable for studies in awake behaving animals. PMID:23322445

A simple one-step method to prepare fluorescent carbon dots and their potential application in non-invasive glioma imaging

NASA Astrophysics Data System (ADS)

Ruan, Shaobo; Qian, Jun; Shen, Shun; Zhu, Jianhua; Jiang, Xinguo; He, Qin; Gao, Huile

2014-08-01

Fluorescent carbon dots (CD) possess impressive potential in bioimaging because of their low photobleaching, absence of optical blinking and good biocompatibility. However, their relatively short excitation/emission wavelengths restrict their application in in vivo imaging. In the present study, a kind of CD was prepared by a simple heat treatment method using glycine as the only precursor. The diameter of CD was lower than 5 nm, and the highest emission wavelength was 500 nm. However, at 600 nm, there was still a relatively strong fluorescent emission, suggesting CD could be used for in vivo imaging. Additionally, several experiments demonstrated that CD possessed good serum stability and low cytotoxicity. In vitro, CD could be taken up into C6 glioma cells in a time- and concentration-dependent manner, with both endosomes and mitochondria involved. In vivo, CD could be used for non-invasive glioma imaging because of its high accumulation in the glioma site of the brain, which was demonstrated by both in vivo imaging and ex vivo tissue imaging. Furthermore, the fluorescent distribution in tissue slices also showed CD distributed in glioma with high intensity, while with a low intensity in normal brain tissue. In conclusion, CD were prepared using a simple method with relatively long excitation and emission wavelengths and could be used for non-invasive glioma imaging.Fluorescent carbon dots (CD) possess impressive potential in bioimaging because of their low photobleaching, absence of optical blinking and good biocompatibility. However, their relatively short excitation/emission wavelengths restrict their application in in vivo imaging. In the present study, a kind of CD was prepared by a simple heat treatment method using glycine as the only precursor. The diameter of CD was lower than 5 nm, and the highest emission wavelength was 500 nm. However, at 600 nm, there was still a relatively strong fluorescent emission, suggesting CD could be used for in vivo imaging. Additionally, several experiments demonstrated that CD possessed good serum stability and low cytotoxicity. In vitro, CD could be taken up into C6 glioma cells in a time- and concentration-dependent manner, with both endosomes and mitochondria involved. In vivo, CD could be used for non-invasive glioma imaging because of its high accumulation in the glioma site of the brain, which was demonstrated by both in vivo imaging and ex vivo tissue imaging. Furthermore, the fluorescent distribution in tissue slices also showed CD distributed in glioma with high intensity, while with a low intensity in normal brain tissue. In conclusion, CD were prepared using a simple method with relatively long excitation and emission wavelengths and could be used for non-invasive glioma imaging. Electronic supplementary information (ESI) available. See DOI: 10.1039/c4nr02657h

Assessing Relevance of External Cognitive Measures

PubMed Central

Cairó, Osvaldo

2017-01-01

The arrival of modern brain imaging technologies has provided new opportunities for examining the biological essence of human intelligence as well as the relationship between brain size and cognition. Thanks to these advances, we can now state that the relationship between brain size and intelligence has never been well understood. This view is supported by findings showing that cognition is correlated more with brain tissues than sheer brain size. The complexity of cellular and molecular organization of neural connections actually determines the computational capacity of the brain. In this review article, we determine that while genotypes are responsible for defining the theoretical limits of intelligence, what is primarily responsible for determining whether those limits are reached or exceeded is experience (environmental influence). Therefore, we contend that the gene-environment interplay defines the intelligent quotient of an individual. PMID:28270753

Detection of white matter injury in concussion using high-definition fiber tractography.

PubMed

Shin, Samuel S; Pathak, Sudhir; Presson, Nora; Bird, William; Wagener, Lauren; Schneider, Walter; Okonkwo, David O; Fernandez-Miranda, Juan C

2014-01-01

Over the last few decades, structural imaging techniques of the human brain have undergone significant strides. High resolution provided by recent developments in magnetic resonance imaging (MRI) allows improved detection of injured regions in patients with moderate-to-severe traumatic brain injury (TBI). In addition, diffusion imaging techniques such as diffusion tensor imaging (DTI) has gained much interest recently due to its possible utility in detecting structural integrity of white matter pathways in mild TBI (mTBI) cases. However, the results from recent DTI studies in mTBI patients remain equivocal. Also, there are important shortcomings for DTI such as limited resolution in areas of multiple crossings and false tract formation. The detection of white matter damage in concussion remains challenging, and development of imaging biomarkers for mTBI is still in great need. In this chapter, we discuss our experience with high-definition fiber tracking (HDFT), a diffusion spectrum imaging-based technique. We also discuss ongoing developments and specific advantages HDFT may offer concussion patients. © 2014 S. Karger AG, Basel.

Topology preserving non-rigid image registration using time-varying elasticity model for MRI brain volumes.

PubMed

Ahmad, Sahar; Khan, Muhammad Faisal

2015-12-01

In this paper, we present a new non-rigid image registration method that imposes a topology preservation constraint on the deformation. We propose to incorporate the time varying elasticity model into the deformable image matching procedure and constrain the Jacobian determinant of the transformation over the entire image domain. The motion of elastic bodies is governed by a hyperbolic partial differential equation, generally termed as elastodynamics wave equation, which we propose to use as a deformation model. We carried out clinical image registration experiments on 3D magnetic resonance brain scans from IBSR database. The results of the proposed registration approach in terms of Kappa index and relative overlap computed over the subcortical structures were compared against the existing topology preserving non-rigid image registration methods and non topology preserving variant of our proposed registration scheme. The Jacobian determinant maps obtained with our proposed registration method were qualitatively and quantitatively analyzed. The results demonstrated that the proposed scheme provides good registration accuracy with smooth transformations, thereby guaranteeing the preservation of topology. Copyright © 2015 Elsevier Ltd. All rights reserved.

Comparing three-dimensional serial optical coherence tomography histology to MRI imaging in the entire mouse brain

NASA Astrophysics Data System (ADS)

Castonguay, Alexandre; Lefebvre, Joël; Pouliot, Philippe; Lesage, Frédéric

2018-01-01

An automated serial histology setup combining optical coherence tomography (OCT) imaging with vibratome sectioning was used to image eight wild type mouse brains. The datasets resulted in thousands of volumetric tiles resolved at a voxel size of (4.9×4.9×6.5) μm3 stitched back together to give a three-dimensional map of the brain from which a template OCT brain was obtained. To assess deformation caused by tissue sectioning, reconstruction algorithms, and fixation, OCT datasets were compared to both in vivo and ex vivo magnetic resonance imaging (MRI) imaging. The OCT brain template yielded a highly detailed map of the brain structure, with a high contrast in white matter fiber bundles and was highly resemblant to the in vivo MRI template. Brain labeling using the Allen brain framework showed little variation in regional brain volume among imaging modalities with no statistical differences. The high correspondence between the OCT template brain and its in vivo counterpart demonstrates the potential of whole brain histology to validate in vivo imaging.

The effects of handwriting experience on functional brain development in pre-literate children

PubMed Central

James, Karin H.; Engelhardt, Laura

2014-01-01

In an age of increasing technology, the possibility that typing on a keyboard will replace handwriting raises questions about the future usefulness of handwriting skills. Here we present evidence that brain activation during letter perception is influenced in different, important ways by previous handwriting of letters versus previous typing or tracing of those same letters. Preliterate, five-year old children printed, typed, or traced letters and shapes, then were shown images of these stimuli while undergoing functional MRI scanning. A previously documented “reading circuit” was recruited during letter perception only after handwriting—not after typing or tracing experience. These findings demonstrate that handwriting is important for the early recruitment in letter processing of brain regions known to underlie successful reading. Handwriting therefore may facilitate reading acquisition in young children. PMID:25541600

Reward, salience, and attentional networks are activated by religious experience in devout Mormons

PubMed Central

Ferguson, Michael A.; Nielsen, Jared A.; King, Jace B.; Dai, Li; Giangrasso, Danielle M.; Holman, Rachel; Korenberg, Julie R.; Anderson, Jeffrey S.

2017-01-01

High-level cognitive and emotional experience arises from brain activity, but the specific brain substrates for religious and spiritual euphoria remain unclear. We demonstrate using functional magnetic resonance imaging scans in 19 devout Mormons that a recognizable feeling central to their devotional practice was reproducibly associated with activation in nucleus accumbens, ventromedial prefrontal cortex, and frontal attentional regions. Nucleus accumbens activation preceded peak spiritual feelings by 1–3 s and was replicated in four separate tasks. Attentional activation in the anterior cingulate and frontal eye fields was greater in the right hemisphere. The association of abstract ideas and brain reward circuitry may interact with frontal attentional and emotive salience processing, suggesting a mechanism whereby doctrinal concepts may come to be intrinsically rewarding and motivate behavior in religious individuals. PMID:27834117

The integration processing of the visual and auditory information in videos of real-world events: an ERP study.

PubMed

Liu, Baolin; Wang, Zhongning; Jin, Zhixing

2009-09-11

In real life, the human brain usually receives information through visual and auditory channels and processes the multisensory information, but studies on the integration processing of the dynamic visual and auditory information are relatively few. In this paper, we have designed an experiment, where through the presentation of common scenario, real-world videos, with matched and mismatched actions (images) and sounds as stimuli, we aimed to study the integration processing of synchronized visual and auditory information in videos of real-world events in the human brain, through the use event-related potentials (ERPs) methods. Experimental results showed that videos of mismatched actions (images) and sounds would elicit a larger P400 as compared to videos of matched actions (images) and sounds. We believe that the P400 waveform might be related to the cognitive integration processing of mismatched multisensory information in the human brain. The results also indicated that synchronized multisensory information would interfere with each other, which would influence the results of the cognitive integration processing.

Pilot Study on Long Term Effects of HZE Exposure on the Canine Brain

NASA Astrophysics Data System (ADS)

Budinger, T.; Brennan, K.; Pearlstein, R.

A ground-based pilot experiment was initiated in December 1992 to evaluate the long term effects on health and aging after HZE cosmic radiation of the canine brain. Six adult male beagle dogs (1 yr) from the UC Davis breeding colony at the Laboratory for Energy Related Health Research were researched in this study. Iron nuclei at 600 MeV/amu (180 keV/mm) were used to irradiate the whole brain. The fluence of 3 x 106 iron nuclei/ cm2 mimics the HZE exposure (all > He) for a 2- year mission to Mars. The HZE irradiation was a fully stripped iron particle beam at the LBNL BEVALAC. Using a Raster Scanner we were able to spread the beam to deliver a uniform dose over the brain. The total dose to the brain was 200 cGy. Four dogs were whole brain irradiated with iron and two dogs served as litter-mate controls. The control dogs received a similar amount of background neutron irradiation as the irradiated dogs. One of the control dogs died suddenly 3/98 of intestinal cancer unrelated to the brain irradiation. That brain was not harvested before autolysis had prevented analysis. Periodic PET metabolism and yearly MRI studies have been done on these dog's brain since irradiation. All dogs had yearly physical, neurological and blood chemistry work-ups. PET imaging was performed with the Donner 600-crystal high-resolution PET (2.6 mm resolution) and with the commercial PET, CTI/Siemens ECAT 951 PET Scanner (5 mm resolution). NMR imaging is performed with the 1 5T GE Signa at UCSF using T spoiled gradient imaging.1 sequences for T1 contrast at 1 mm resolution as well as a T2 weighted spin echo imaging sequence at 1 mm resolution. A major goal of this work is to present an accurate method for measuring surface areas and volumes of the irradiated vs the non-irradiated canine brain using MRI data which are isotropic in resolution at the 1 mm level. This allows us to monitor the changes in brain size with aging and radiation exposure. Nine years post irradiation, these dog brains (+ 3 additional age-matched controls) were in-situ perfused with 4% paraformaldehyde/01.M phosphate buffer. The brain was removed and fixed in the same fixative for 2 weeks. Brain sections were embedded in parafin and cut at 6 or 12 μm thickness. Histology included H&E, Luxol fast blue and Silver staining. Immunochemistry included Amyloidprecursor protein. There was no marked increase in amyloid plaque formation in the irradiated dogs. Imaging and histology results will be presented at the COSPAR conference.

Brain Injury in Neonates with Complex Congenital Heart Disease: What Is the Predictive Value of MRI in the Fetal Period?

PubMed

Brossard-Racine, M; du Plessis, A; Vezina, G; Robertson, R; Donofrio, M; Tworetzky, W; Limperopoulos, C

2016-07-01

Brain injury in neonates with congenital heart disease is an important predictor of adverse neurodevelopmental outcome. Impaired brain development in congenital heart disease may have a prenatal origin, but the sensitivity and specificity of fetal brain MR imaging for predicting neonatal brain lesions are currently unknown. We sought to determine the value of conventional fetal MR imaging for predicting abnormal findings on neonatal preoperative MR imaging in neonates with complex congenital heart disease. MR imaging studies were performed in 103 fetuses with confirmed congenital heart disease (mean gestational age, 31.57 ± 3.86 weeks) and were repeated postnatally before cardiac surgery (mean age, 6.8 ± 12.2 days). Each MR imaging study was read by a pediatric neuroradiologist. Brain abnormalities were detected in 17/103 (16%) fetuses by fetal MR imaging and in 33/103 (32%) neonates by neonatal MR imaging. Only 9/33 studies with abnormal neonatal findings were preceded by abnormal findings on fetal MR imaging. The sensitivity and specificity of conventional fetal brain MR imaging for predicting neonatal brain abnormalities were 27% and 89%, respectively. Brain abnormalities detected by in utero MR imaging in fetuses with congenital heart disease are associated with higher risk of postnatal preoperative brain injury. However, a substantial proportion of anomalies on postnatal MR imaging were not present on fetal MR imaging; this result is likely due to the limitations of conventional fetal MR imaging and the emergence of new lesions that occurred after the fetal studies. Postnatal brain MR imaging studies are needed to confirm the presence of injury before open heart surgery. © 2016 by American Journal of Neuroradiology.

Compact and mobile high resolution PET brain imager

DOEpatents

Majewski, Stanislaw [Yorktown, VA; Proffitt, James [Newport News, VA

2011-02-08

A brain imager includes a compact ring-like static PET imager mounted in a helmet-like structure. When attached to a patient's head, the helmet-like brain imager maintains the relative head-to-imager geometry fixed through the whole imaging procedure. The brain imaging helmet contains radiation sensors and minimal front-end electronics. A flexible mechanical suspension/harness system supports the weight of the helmet thereby allowing for patient to have limited movements of the head during imaging scans. The compact ring-like PET imager enables very high resolution imaging of neurological brain functions, cancer, and effects of trauma using a rather simple mobile scanner with limited space needs for use and storage.

A midas plugin to enable construction of reproducible web-based image processing pipelines

PubMed Central

Grauer, Michael; Reynolds, Patrick; Hoogstoel, Marion; Budin, Francois; Styner, Martin A.; Oguz, Ipek

2013-01-01

Image processing is an important quantitative technique for neuroscience researchers, but difficult for those who lack experience in the field. In this paper we present a web-based platform that allows an expert to create a brain image processing pipeline, enabling execution of that pipeline even by those biomedical researchers with limited image processing knowledge. These tools are implemented as a plugin for Midas, an open-source toolkit for creating web based scientific data storage and processing platforms. Using this plugin, an image processing expert can construct a pipeline, create a web-based User Interface, manage jobs, and visualize intermediate results. Pipelines are executed on a grid computing platform using BatchMake and HTCondor. This represents a new capability for biomedical researchers and offers an innovative platform for scientific collaboration. Current tools work well, but can be inaccessible for those lacking image processing expertise. Using this plugin, researchers in collaboration with image processing experts can create workflows with reasonable default settings and streamlined user interfaces, and data can be processed easily from a lab environment without the need for a powerful desktop computer. This platform allows simplified troubleshooting, centralized maintenance, and easy data sharing with collaborators. These capabilities enable reproducible science by sharing datasets and processing pipelines between collaborators. In this paper, we present a description of this innovative Midas plugin, along with results obtained from building and executing several ITK based image processing workflows for diffusion weighted MRI (DW MRI) of rodent brain images, as well as recommendations for building automated image processing pipelines. Although the particular image processing pipelines developed were focused on rodent brain MRI, the presented plugin can be used to support any executable or script-based pipeline. PMID:24416016

A midas plugin to enable construction of reproducible web-based image processing pipelines.

PubMed

Grauer, Michael; Reynolds, Patrick; Hoogstoel, Marion; Budin, Francois; Styner, Martin A; Oguz, Ipek

2013-01-01

Image processing is an important quantitative technique for neuroscience researchers, but difficult for those who lack experience in the field. In this paper we present a web-based platform that allows an expert to create a brain image processing pipeline, enabling execution of that pipeline even by those biomedical researchers with limited image processing knowledge. These tools are implemented as a plugin for Midas, an open-source toolkit for creating web based scientific data storage and processing platforms. Using this plugin, an image processing expert can construct a pipeline, create a web-based User Interface, manage jobs, and visualize intermediate results. Pipelines are executed on a grid computing platform using BatchMake and HTCondor. This represents a new capability for biomedical researchers and offers an innovative platform for scientific collaboration. Current tools work well, but can be inaccessible for those lacking image processing expertise. Using this plugin, researchers in collaboration with image processing experts can create workflows with reasonable default settings and streamlined user interfaces, and data can be processed easily from a lab environment without the need for a powerful desktop computer. This platform allows simplified troubleshooting, centralized maintenance, and easy data sharing with collaborators. These capabilities enable reproducible science by sharing datasets and processing pipelines between collaborators. In this paper, we present a description of this innovative Midas plugin, along with results obtained from building and executing several ITK based image processing workflows for diffusion weighted MRI (DW MRI) of rodent brain images, as well as recommendations for building automated image processing pipelines. Although the particular image processing pipelines developed were focused on rodent brain MRI, the presented plugin can be used to support any executable or script-based pipeline.

Non-rigid registration of 3D ultrasound for neurosurgery using automatic feature detection and matching.

PubMed

Machado, Inês; Toews, Matthew; Luo, Jie; Unadkat, Prashin; Essayed, Walid; George, Elizabeth; Teodoro, Pedro; Carvalho, Herculano; Martins, Jorge; Golland, Polina; Pieper, Steve; Frisken, Sarah; Golby, Alexandra; Wells, William

2018-06-04

The brain undergoes significant structural change over the course of neurosurgery, including highly nonlinear deformation and resection. It can be informative to recover the spatial mapping between structures identified in preoperative surgical planning and the intraoperative state of the brain. We present a novel feature-based method for achieving robust, fully automatic deformable registration of intraoperative neurosurgical ultrasound images. A sparse set of local image feature correspondences is first estimated between ultrasound image pairs, after which rigid, affine and thin-plate spline models are used to estimate dense mappings throughout the image. Correspondences are derived from 3D features, distinctive generic image patterns that are automatically extracted from 3D ultrasound images and characterized in terms of their geometry (i.e., location, scale, and orientation) and a descriptor of local image appearance. Feature correspondences between ultrasound images are achieved based on a nearest-neighbor descriptor matching and probabilistic voting model similar to the Hough transform. Experiments demonstrate our method on intraoperative ultrasound images acquired before and after opening of the dura mater, during resection and after resection in nine clinical cases. A total of 1620 automatically extracted 3D feature correspondences were manually validated by eleven experts and used to guide the registration. Then, using manually labeled corresponding landmarks in the pre- and post-resection ultrasound images, we show that our feature-based registration reduces the mean target registration error from an initial value of 3.3 to 1.5 mm. This result demonstrates that the 3D features promise to offer a robust and accurate solution for 3D ultrasound registration and to correct for brain shift in image-guided neurosurgery.

Enactive cinema paves way for understanding complex real-time social interaction in neuroimaging experiments

PubMed Central

Tikka, Pia; Väljamäe, Aleksander; de Borst, Aline W.; Pugliese, Roberto; Ravaja, Niklas; Kaipainen, Mauri; Takala, Tapio

2012-01-01

We outline general theoretical and practical implications of what we promote as enactive cinema for the neuroscientific study of online socio-emotional interaction. In a real-time functional magnetic resonance imaging (rt-fMRI) setting, participants are immersed in cinematic experiences that simulate social situations. While viewing, their physiological reactions—including brain responses—are tracked, representing implicit and unconscious experiences of the on-going social situations. These reactions, in turn, are analyzed in real-time and fed back to modify the cinematic sequences they are viewing while being scanned. Due to the engaging cinematic content, the proposed setting focuses on living-by in terms of shared psycho-physiological epiphenomena of experience rather than active coping in terms of goal-oriented motor actions. It constitutes a means to parametrically modify stimuli that depict social situations and their broader environmental contexts. As an alternative to studying the variation of brain responses as a function of a priori fixed stimuli, this method can be applied to survey the range of stimuli that evoke similar responses across participants at particular brain regions of interest. PMID:23125829

Enactive cinema paves way for understanding complex real-time social interaction in neuroimaging experiments.

PubMed

Tikka, Pia; Väljamäe, Aleksander; de Borst, Aline W; Pugliese, Roberto; Ravaja, Niklas; Kaipainen, Mauri; Takala, Tapio

2012-01-01

We outline general theoretical and practical implications of what we promote as enactive cinema for the neuroscientific study of online socio-emotional interaction. In a real-time functional magnetic resonance imaging (rt-fMRI) setting, participants are immersed in cinematic experiences that simulate social situations. While viewing, their physiological reactions-including brain responses-are tracked, representing implicit and unconscious experiences of the on-going social situations. These reactions, in turn, are analyzed in real-time and fed back to modify the cinematic sequences they are viewing while being scanned. Due to the engaging cinematic content, the proposed setting focuses on living-by in terms of shared psycho-physiological epiphenomena of experience rather than active coping in terms of goal-oriented motor actions. It constitutes a means to parametrically modify stimuli that depict social situations and their broader environmental contexts. As an alternative to studying the variation of brain responses as a function of a priori fixed stimuli, this method can be applied to survey the range of stimuli that evoke similar responses across participants at particular brain regions of interest.

The development and evaluation of head probes for optical imaging of the infant head

NASA Astrophysics Data System (ADS)

Branco, Gilberto

The objective of this thesis was to develop and evaluate optical imaging probes for mapping oxygenation and haemodynamic changes in the newborn infant brain. Two imaging approaches are being developed at University College London (UCL): optical topography (surface mapping of the cortex) and optical tomography (volume imaging). Both have the potential to provide information about the function of the normal brain and about a variety of neurophysiologies! abnormalities. Both techniques require an array of optical fibres/fibre bundles to be held in contact with the head, for periods of time from tens of seconds to an hour or more. The design of suitable probes must ensure the comfort and safety of the subject, and provide measurements minimally sensitive to external sources of light and patient motion. A series of prototype adaptable helmets were developed for optical tomography of the premature infant brain using the UCL 32-channel time-resolved system. They were required to attach 32 optical fibre bundles over the infant scalp, and were designed to accommodate infants with a variety of head shapes and sizes, aged between 24-weeks gestational age and term. Continual improvements to the helmet design were introduced following the evaluation of each prototype on infants in the hospital. Data were acquired to generate images revealing the concentration and oxygenation of blood in the brain, and the response of the brain to sensory stimulation. This part of the project also involved designing and testing new methods of acquiring calibration data using reference phantoms. The second focus of the project was the development of probes for use with the UCL frequency-multiplexed near-infrared topography system. This is being used to image functional activation in the infant cortex. A series of probes were developed and experiments were conducted to evaluate their sensitivity to patient motion and to compression of the probe. The probes have been used for a variety of functional activation studies.

Specificities of Awake Craniotomy and Brain Mapping in Children for Resection of Supratentorial Tumors in the Language Area.

PubMed

Delion, Matthieu; Terminassian, Aram; Lehousse, Thierry; Aubin, Ghislaine; Malka, Jean; N'Guyen, Sylvie; Mercier, Philippe; Menei, Philippe

2015-12-01

In the pediatric population, awake craniotomy began to be used for the resection of brain tumor located close to eloquent areas. Some specificities must be taken into account to adapt this method to children. The aim of this clinical study is to not only confirm the feasibility of awake craniotomy and language brain mapping in the pediatric population but also identify the specificities and necessary adaptations of the procedure. Six children aged 11 to 16 were operated on while awake under local anesthesia with language brain mapping for supratentorial brain lesions (tumor and cavernoma). The preoperative planning comprised functional magnetic resonance imaging (MRI) and neuropsychologic and psychologic assessment. The specific preoperative preparation is clearly explained including hypnosis conditioning and psychiatric evaluation. The success of the procedure was based on the ability to perform the language brain mapping and the tumor removal without putting the patient to sleep. We investigated the pediatric specificities, psychological experience, and neuropsychologic follow-up. The children experienced little anxiety, probably in large part due to the use of hypnosis. We succeeded in doing the cortical-subcortical mapping and removing the tumor without putting the patient to sleep in all cases. The psychological experience was good, and the neuropsychologic follow-up showed a favorable evolution. Preoperative preparation and hypnosis in children seemed important for performing awake craniotomy and contributing language brain mapping with the best possible psychological experience. The pediatrics specificities are discussed. Copyright © 2015 Elsevier Inc. All rights reserved.

Repetition priming influences distinct brain systems: evidence from task-evoked data and resting-state correlations.

PubMed

Wig, Gagan S; Buckner, Randy L; Schacter, Daniel L

2009-05-01

Behavioral dissociations suggest that a single experience can separately influence multiple processing components. Here we used a repetition priming functional magnetic resonance imaging paradigm that directly contrasted the effects of stimulus and decision changes to identify the underlying brain systems. Direct repetition of stimulus features caused marked reductions in posterior regions of the inferior temporal lobe that were insensitive to whether the decision was held constant or changed between study and test. By contrast, prefrontal cortex showed repetition effects that were sensitive to the exact stimulus-to-decision mapping. Analysis of resting-state functional connectivity revealed that the dissociated repetition effects are embedded within distinct brain systems. Regions that were sensitive to changes in the stimulus correlated with perceptual cortices, whereas the decision changes attenuated activity in regions correlated with middle-temporal regions and a frontoparietal control system. These results thus explain the long-known dissociation between perceptual and conceptual components of priming by revealing how a single experience can separately influence distinct, concurrently active brain systems.

Neuroprotective effects of yoga practice: age-, experience-, and frequency-dependent plasticity

PubMed Central

Villemure, Chantal; Čeko, Marta; Cotton, Valerie A.; Bushnell, M. Catherine

2015-01-01

Yoga combines postures, breathing, and meditation. Despite reported health benefits, yoga’s effects on the brain have received little study. We used magnetic resonance imaging to compare age-related gray matter (GM) decline in yogis and controls. We also examined the effect of increasing yoga experience and weekly practice on GM volume and assessed which aspects of weekly practice contributed most to brain size. Controls displayed the well documented age-related global brain GM decline while yogis did not, suggesting that yoga contributes to protect the brain against age-related decline. Years of yoga experience correlated mostly with GM volume differences in the left hemisphere (insula, frontal operculum, and orbitofrontal cortex) suggesting that yoga tunes the brain toward a parasympatically driven mode and positive states. The number of hours of weekly practice correlated with GM volume in the primary somatosensory cortex/superior parietal lobule (S1/SPL), precuneus/posterior cingulate cortex (PCC), hippocampus, and primary visual cortex (V1). Commonality analyses indicated that the combination of postures and meditation contributed the most to the size of the hippocampus, precuneus/PCC, and S1/SPL while the combination of meditation and breathing exercises contributed the most to V1 volume. Yoga’s potential neuroprotective effects may provide a neural basis for some of its beneficial effects. PMID:26029093

Structural brain changes linked to delayed first language acquisition in congenitally deaf individuals.

PubMed

Pénicaud, Sidonie; Klein, Denise; Zatorre, Robert J; Chen, Jen-Kai; Witcher, Pamela; Hyde, Krista; Mayberry, Rachel I

2013-02-01

Early language experience is essential for the development of a high level of linguistic proficiency in adulthood and in a recent functional Magnetic Resonance Imaging (fMRI) experiment, we showed that a delayed acquisition of a first language results in changes in the functional organization of the adult brain (Mayberry et al., 2011). The present study extends the question to explore if delayed acquisition of a first language also modulates the structural development of the brain. To this end, we carried out anatomical MRI in the same group of congenitally deaf individuals who varied in the age of acquisition of a first language, American Sign Language -ASL (Mayberry et al., 2011) and used a neuroanatomical technique, Voxel-Based Morphometry (VBM), to explore changes in gray and white matter concentrations across the brain related to the age of first language acquisition. The results show that delayed acquisition of a first language is associated with changes in tissue concentration in the occipital cortex close to the area that has been found to show functional recruitment during language processing in these deaf individuals with a late age of acquisition. These findings suggest that a lack of early language experience affects not only the functional but also the anatomical organization of the brain. Copyright © 2012 Elsevier Inc. All rights reserved.

Brain templates and atlases.

PubMed

Evans, Alan C; Janke, Andrew L; Collins, D Louis; Baillet, Sylvain

2012-08-15

The core concept within the field of brain mapping is the use of a standardized, or "stereotaxic", 3D coordinate frame for data analysis and reporting of findings from neuroimaging experiments. This simple construct allows brain researchers to combine data from many subjects such that group-averaged signals, be they structural or functional, can be detected above the background noise that would swamp subtle signals from any single subject. Where the signal is robust enough to be detected in individuals, it allows for the exploration of inter-individual variance in the location of that signal. From a larger perspective, it provides a powerful medium for comparison and/or combination of brain mapping findings from different imaging modalities and laboratories around the world. Finally, it provides a framework for the creation of large-scale neuroimaging databases or "atlases" that capture the population mean and variance in anatomical or physiological metrics as a function of age or disease. However, while the above benefits are not in question at first order, there are a number of conceptual and practical challenges that introduce second-order incompatibilities among experimental data. Stereotaxic mapping requires two basic components: (i) the specification of the 3D stereotaxic coordinate space, and (ii) a mapping function that transforms a 3D brain image from "native" space, i.e. the coordinate frame of the scanner at data acquisition, to that stereotaxic space. The first component is usually expressed by the choice of a representative 3D MR image that serves as target "template" or atlas. The native image is re-sampled from native to stereotaxic space under the mapping function that may have few or many degrees of freedom, depending upon the experimental design. The optimal choice of atlas template and mapping function depend upon considerations of age, gender, hemispheric asymmetry, anatomical correspondence, spatial normalization methodology and disease-specificity. Accounting, or not, for these various factors in defining stereotaxic space has created the specter of an ever-expanding set of atlases, customized for a particular experiment, that are mutually incompatible. These difficulties continue to plague the brain mapping field. This review article summarizes the evolution of stereotaxic space in term of the basic principles and associated conceptual challenges, the creation of population atlases and the future trends that can be expected in atlas evolution. Copyright © 2012 Elsevier Inc. All rights reserved.

Pulse Coupled Neural Networks for the Segmentation of Magnetic Resonance Brain Images.

DTIC Science & Technology

1996-12-01

PULSE COUPLED NEURAL NETWORKS FOR THE SEGMENTATION OF MAGNETIC RESONANCE BRAIN IMAGES THESIS Shane Lee Abrahamson First Lieutenant, USAF AFIT/GCS/ENG...COUPLED NEURAL NETWORKS FOR THE SEGMENTATION OF MAGNETIC RESONANCE BRAIN IMAGES THESIS Shane Lee Abrahamson First Lieutenant, USAF AFIT/GCS/ENG/96D-01...research develops an automated method for segmenting Magnetic Resonance (MR) brain images based on Pulse Coupled Neural Networks (PCNN). MR brain image

Greater cerebellar gray matter volume in car drivers: an exploratory voxel-based morphometry study

PubMed Central

Sakai, Hiroyuki; Ando, Takafumi; Sadato, Norihiro; Uchiyama, Yuji

2017-01-01

Previous functional neuroimaging studies have identified multiple brain areas associated with distinct aspects of car driving in simulated traffic environments. Few studies, however, have examined brain morphology associated with everyday car-driving experience in real traffic. Thus, the aim of the current study was to identify gray matter volume differences between drivers and non-drivers. We collected T1-weighted structural brain images from 73 healthy young adults (36 drivers and 37 non-drivers). We performed a whole-brain voxel-based morphometry analysis to examine between-group differences in regional gray matter volume. Compared with non-drivers, drivers showed significantly greater gray matter volume in the left cerebellar hemisphere, which has been associated with cognitive rather than motor functioning. In contrast, we found no brain areas with significantly greater gray matter volume in non-drivers compared with drivers. Our findings indicate that experience with everyday car driving in real traffic is associated with greater gray matter volume in the left cerebellar hemisphere. This brain area may be involved in abilities that are critical for driving a car, but are not commonly or frequently used during other daily activities. PMID:28417971

Decoding power-spectral profiles from FMRI brain activities during naturalistic auditory experience.

PubMed

Hu, Xintao; Guo, Lei; Han, Junwei; Liu, Tianming

2017-02-01

Recent studies have demonstrated a close relationship between computational acoustic features and neural brain activities, and have largely advanced our understanding of auditory information processing in the human brain. Along this line, we proposed a multidisciplinary study to examine whether power spectral density (PSD) profiles can be decoded from brain activities during naturalistic auditory experience. The study was performed on a high resolution functional magnetic resonance imaging (fMRI) dataset acquired when participants freely listened to the audio-description of the movie "Forrest Gump". Representative PSD profiles existing in the audio-movie were identified by clustering the audio samples according to their PSD descriptors. Support vector machine (SVM) classifiers were trained to differentiate the representative PSD profiles using corresponding fMRI brain activities. Based on PSD profile decoding, we explored how the neural decodability correlated to power intensity and frequency deviants. Our experimental results demonstrated that PSD profiles can be reliably decoded from brain activities. We also suggested a sigmoidal relationship between the neural decodability and power intensity deviants of PSD profiles. Our study in addition substantiates the feasibility and advantage of naturalistic paradigm for studying neural encoding of complex auditory information.

Greater cerebellar gray matter volume in car drivers: an exploratory voxel-based morphometry study.

PubMed

Sakai, Hiroyuki; Ando, Takafumi; Sadato, Norihiro; Uchiyama, Yuji

2017-04-18

Previous functional neuroimaging studies have identified multiple brain areas associated with distinct aspects of car driving in simulated traffic environments. Few studies, however, have examined brain morphology associated with everyday car-driving experience in real traffic. Thus, the aim of the current study was to identify gray matter volume differences between drivers and non-drivers. We collected T1-weighted structural brain images from 73 healthy young adults (36 drivers and 37 non-drivers). We performed a whole-brain voxel-based morphometry analysis to examine between-group differences in regional gray matter volume. Compared with non-drivers, drivers showed significantly greater gray matter volume in the left cerebellar hemisphere, which has been associated with cognitive rather than motor functioning. In contrast, we found no brain areas with significantly greater gray matter volume in non-drivers compared with drivers. Our findings indicate that experience with everyday car driving in real traffic is associated with greater gray matter volume in the left cerebellar hemisphere. This brain area may be involved in abilities that are critical for driving a car, but are not commonly or frequently used during other daily activities.

Continuous functional magnetic resonance imaging reveals dynamic nonlinearities of "dose-response" curves for finger opposition.

PubMed

Berns, G S; Song, A W; Mao, H

1999-07-15

Linear experimental designs have dominated the field of functional neuroimaging, but although successful at mapping regions of relative brain activation, the technique assumes that both cognition and brain activation are linear processes. To test these assumptions, we performed a continuous functional magnetic resonance imaging (MRI) experiment of finger opposition. Subjects performed a visually paced bimanual finger-tapping task. The frequency of finger tapping was continuously varied between 1 and 5 Hz, without any rest blocks. After continuous acquisition of fMRI images, the task-related brain regions were identified with independent components analysis (ICA). When the time courses of the task-related components were plotted against tapping frequency, nonlinear "dose- response" curves were obtained for most subjects. Nonlinearities appeared in both the static and dynamic sense, with hysteresis being prominent in several subjects. The ICA decomposition also demonstrated the spatial dynamics with different components active at different times. These results suggest that the brain response to tapping frequency does not scale linearly, and that it is history-dependent even after accounting for the hemodynamic response function. This implies that finger tapping, as measured with fMRI, is a nonstationary process. When analyzed with a conventional general linear model, a strong correlation to tapping frequency was identified, but the spatiotemporal dynamics were not apparent.

Demeclocycline as a contrast agent for detecting brain neoplasms using confocal microscopy

NASA Astrophysics Data System (ADS)

Wirth, Dennis; Smith, Thomas W.; Moser, Richard; Yaroslavsky, Anna N.

2015-04-01

Complete resection of brain tumors improves life expectancy and quality. Thus, there is a strong need for high-resolution detection and microscopically controlled removal of brain neoplasms. The goal of this study was to test demeclocycline as a contrast enhancer for the intraoperative detection of brain tumors. We have imaged benign and cancerous brain tumors using multimodal confocal microscopy. The tumors investigated included pituitary adenoma, meningiomas, glioblastomas, and metastatic brain cancers. Freshly excised brain tissues were stained in 0.75 mg ml-1 aqueous solution of demeclocyline. Reflectance images were acquired at 402 nm. Fluorescence signals were excited at 402 nm and registered between 500 and 540 nm. After imaging, histological sections were processed from the imaged specimens and compared to the optical images. Fluorescence images highlighted normal and cancerous brain cells, while reflectance images emphasized the morphology of connective tissue. The optical and histological images were in accordance with each other for all types of tumors investigated. Demeclocyline shows promise as a contrast agent for intraoperative detection of brain tumors.

Oxytocin enhances inter-brain synchrony during social coordination in male adults.

PubMed

Mu, Yan; Guo, Chunyan; Han, Shihui

2016-12-01

Recent brain imaging research has revealed oxytocin (OT) effects on an individual's brain activity during social interaction but tells little about whether and how OT modulates the coherence of inter-brain activity related to two individuals' coordination behavior. We developed a new real-time coordination game that required two individuals of a dyad to synchronize with a partner (coordination task) or with a computer (control task) by counting in mind rhythmically. Electroencephalography (EEG) was recorded simultaneously from a dyad to examine OT effects on inter-brain synchrony of neural activity during interpersonal coordination. Experiment 1 found that dyads showed smaller interpersonal time lags of counting and greater inter-brain synchrony of alpha-band neural oscillations during the coordination (vs control) task and these effects were reliably observed in female but not male dyads. Moreover, the increased alpha-band inter-brain synchrony predicted better interpersonal behavioral synchrony across all participants. Experiment 2, using a double blind, placebo-controlled between-subjects design, revealed that intranasal OT vs placebo administration in male dyads improved interpersonal behavioral synchrony in both the coordination and control tasks but specifically enhanced alpha-band inter-brain neural oscillations during the coordination task. Our findings provide first evidence that OT enhances inter-brain synchrony in male adults to facilitate social coordination. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

An imaging genetics approach to understanding social influence

PubMed Central

Falk, Emily B.; Way, Baldwin M.; Jasinska, Agnes J.

2012-01-01

Normative social influences shape nearly every aspect of our lives, yet the biological processes mediating the impact of these social influences on behavior remain incompletely understood. In this Hypothesis, we outline a theoretical framework and an integrative research approach to the study of social influences on the brain and genetic moderators of such effects. First, we review neuroimaging evidence linking social influence and conformity to the brain's reward system. We next review neuroimaging evidence linking social punishment (exclusion) to brain systems involved in the experience of pain, as well as evidence linking exclusion to conformity. We suggest that genetic variants that increase sensitivity to social cues may predispose individuals to be more sensitive to either social rewards or punishments (or potentially both), which in turn increases conformity and susceptibility to normative social influences more broadly. To this end, we review evidence for genetic moderators of neurochemical responses in the brain, and suggest ways in which genes and pharmacology may modulate sensitivity to social influences. We conclude by proposing an integrative imaging genetics approach to the study of brain mediators and genetic modulators of a variety of social influences on human attitudes, beliefs, and actions. PMID:22701416

Radiosynthesis and in Vivo Evaluation of [11C]A1070722, a High Affinity GSK-3 PET Tracer in Primate Brain.

PubMed

Prabhakaran, Jaya; Zanderigo, Francesca; Sai, Kiran Kumar Solingapuram; Rubin-Falcone, Harry; Jorgensen, Matthew J; Kaplan, Jay R; Mintz, Akiva; Mann, J John; Kumar, J S Dileep

2017-08-16

Dysfunction of glycogen synthase kinase 3 (GSK-3) is implicated in the etiology of Alzheimer's disease, Parkinson's disease, diabetes, pain, and cancer. A radiotracer for functional positron emission tomography (PET) imaging could be used to study the kinase in brain disorders and to facilitate the development of small molecule inhibitors of GSK-3 for treatment. At present, there is no target-specific or validated PET tracer available for the in vivo monitoring of GSK-3. We radiolabeled the small molecule inhibitor [ 11 C]1-(7-methoxy- quinolin-4-yl)-3-(6-(trifluoromethyl)pyridin-2-yl)urea ([ 11 C]A1070722) with high affinity to GSK-3 (K i = 0.6 nM) in excellent radiochemical yield. PET imaging experiments in anesthetized vervet/African green monkey exhibited that [ 11 C]A1070722 penetrated the blood-brain barrier (BBB) and accumulated in brain regions, with highest radioactivity binding in frontal cortex followed by parietal cortex and anterior cingulate, and with the lowest bindings found in caudate, putamen, and thalamus, similarly to the known distribution of GSK-3 in human brain. Our studies suggest that [ 11 C]A1070722 can be a potential PET radiotracer for the in vivo quantification of GSK-3 in brain.

HDAC6 Brain Mapping with [ 18 F]Bavarostat Enabled by a Ru-Mediated Deoxyfluorination

DOE Office of Scientific and Technical Information (OSTI.GOV)

Strebl, Martin G.; Campbell, Arthur J.; Zhao, Wen -Ning

Histone deacetylase 6 (HDAC6) function and dysregulation have been implicated in the etiology of certain cancers and more recently in central nervous system (CNS) disorders including Rett syndrome, Alzheimer’s and Parkinson’s diseases, and major depressive disorder. HDAC6-selective inhibitors have therapeutic potential, but in the CNS drug space the development of highly brain penetrant HDAC inhibitors has been a persistent challenge. Moreover, no tool exists to directly characterize HDAC6 and its related biology in the living human brain. Here, we report a highly brain penetrant HDAC6 inhibitor, Bavarostat, that exhibits excellent HDAC6 selectivity (>80-fold over all other Zn-containing HDAC paralogues), modulatesmore » tubulin acetylation selectively over histone acetylation, and has excellent brain penetrance. We further demonstrate that Bavarostat can be radiolabeled with 18F by deoxyfluorination through in situ formation of a ruthenium π-complex of the corresponding phenol precursor: the only method currently suitable for synthesis of [ 18F]Bavarostat. In conclusion, by using [ 18F]Bavarostat in a series of rodent and nonhuman primate imaging experiments, we demonstrate its utility for mapping HDAC6 in the living brain, which sets the stage for first-in-human neurochemical imaging of this important target.« less

HDAC6 Brain Mapping with [ 18 F]Bavarostat Enabled by a Ru-Mediated Deoxyfluorination

DOE PAGES

Strebl, Martin G.; Campbell, Arthur J.; Zhao, Wen -Ning; ...

2017-09-06

Histone deacetylase 6 (HDAC6) function and dysregulation have been implicated in the etiology of certain cancers and more recently in central nervous system (CNS) disorders including Rett syndrome, Alzheimer’s and Parkinson’s diseases, and major depressive disorder. HDAC6-selective inhibitors have therapeutic potential, but in the CNS drug space the development of highly brain penetrant HDAC inhibitors has been a persistent challenge. Moreover, no tool exists to directly characterize HDAC6 and its related biology in the living human brain. Here, we report a highly brain penetrant HDAC6 inhibitor, Bavarostat, that exhibits excellent HDAC6 selectivity (>80-fold over all other Zn-containing HDAC paralogues), modulatesmore » tubulin acetylation selectively over histone acetylation, and has excellent brain penetrance. We further demonstrate that Bavarostat can be radiolabeled with 18F by deoxyfluorination through in situ formation of a ruthenium π-complex of the corresponding phenol precursor: the only method currently suitable for synthesis of [ 18F]Bavarostat. In conclusion, by using [ 18F]Bavarostat in a series of rodent and nonhuman primate imaging experiments, we demonstrate its utility for mapping HDAC6 in the living brain, which sets the stage for first-in-human neurochemical imaging of this important target.« less

A taste for words and sounds: a case of lexical-gustatory and sound-gustatory synesthesia

PubMed Central

Colizoli, Olympia; Murre, Jaap M. J.; Rouw, Romke

2013-01-01

Gustatory forms of synesthesia involve the automatic and consistent experience of tastes that are triggered by non-taste related inducers. We present a case of lexical-gustatory and sound-gustatory synesthesia within one individual, SC. Most words and a subset of non-linguistic sounds induce the experience of taste, smell and physical sensations for SC. SC's lexical-gustatory associations were significantly more consistent than those of a group of controls. We tested for effects of presentation modality (visual vs. auditory), taste-related congruency, and synesthetic inducer-concurrent direction using a priming task. SC's performance did not differ significantly from a trained control group. We used functional magnetic resonance imaging to investigate the neural correlates of SC's synesthetic experiences by comparing her brain activation to the literature on brain networks related to language, music, and sound processing, in addition to synesthesia. Words that induced a strong taste were contrasted to words that induced weak-to-no tastes (“tasty” vs. “tasteless” words). Brain activation was also measured during passive listening to music and environmental sounds. Brain activation patterns showed evidence that two regions are implicated in SC's synesthetic experience of taste and smell: the left anterior insula and left superior parietal lobe. Anterior insula activation may reflect the synesthetic taste experience. The superior parietal lobe is proposed to be involved in binding sensory information across sub-types of synesthetes. We conclude that SC's synesthesia is genuine and reflected in her brain activation. The type of inducer (visual-lexical, auditory-lexical, and non-lexical auditory stimuli) could be differentiated based on patterns of brain activity. PMID:24167497

Practice and Learning: Spatiotemporal Differences in Thalamo-Cortical-Cerebellar Networks Engagement across Learning Phases in Schizophrenia.

PubMed

Korostil, Michele; Remington, Gary; McIntosh, Anthony Randal

2016-01-01

Understanding how practice mediates the transition of brain-behavior networks between early and later stages of learning is constrained by the common approach to analysis of fMRI data. Prior imaging studies have mostly relied on a single scan, and parametric, task-related analyses. Our experiment incorporates a multisession fMRI lexicon-learning experiment with multivariate, whole-brain analysis to further knowledge of the distributed networks supporting practice-related learning in schizophrenia (SZ). Participants with SZ were compared with healthy control (HC) participants as they learned a novel lexicon during two fMRI scans over a several day period. All participants were trained to equal task proficiency prior to scanning. Behavioral-Partial Least Squares, a multivariate analytic approach, was used to analyze the imaging data. Permutation testing was used to determine statistical significance and bootstrap resampling to determine the reliability of the findings. With practice, HC participants transitioned to a brain-accuracy network incorporating dorsostriatal regions in late-learning stages. The SZ participants did not transition to this pattern despite comparable behavioral results. Instead, successful learners with SZ were differentiated primarily on the basis of greater engagement of perceptual and perceptual-integration brain regions. There is a different spatiotemporal unfolding of brain-learning relationships in SZ. In SZ, given the same amount of practice, the movement from networks suggestive of effortful learning toward subcortically driven procedural one differs from HC participants. Learning performance in SZ is driven by varying levels of engagement in perceptual regions, which suggests perception itself is impaired and may impact downstream, "higher level" cognition.

Graph Theoretical Analysis of BOLD Functional Connectivity during Human Sleep without EEG Monitoring.

PubMed

Lv, Jun; Liu, Dongdong; Ma, Jing; Wang, Xiaoying; Zhang, Jue

2015-01-01

Functional brain networks of human have been revealed to have small-world properties by both analyzing electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) time series. In our study, by using graph theoretical analysis, we attempted to investigate the changes of paralimbic-limbic cortex between wake and sleep states. Ten healthy young people were recruited to our experiment. Data from 2 subjects were excluded for the reason that they had not fallen asleep during the experiment. For each subject, blood oxygen level dependency (BOLD) images were acquired to analyze brain network, and peripheral pulse signals were obtained continuously to identify if the subject was in sleep periods. Results of fMRI showed that brain networks exhibited stronger small-world characteristics during sleep state as compared to wake state, which was in consistent with previous studies using EEG synchronization. Moreover, we observed that compared with wake state, paralimbic-limbic cortex had less connectivity with neocortical system and centrencephalic structure in sleep. In conclusion, this is the first study, to our knowledge, has observed that small-world properties of brain functional networks altered when human sleeps without EEG synchronization. Moreover, we speculate that paralimbic-limbic cortex organization owns an efficient defense mechanism responsible for suppressing the external environment interference when humans sleep, which is consistent with the hypothesis that the paralimbic-limbic cortex may be functionally disconnected from brain regions which directly mediate their interactions with the external environment. Our findings also provide a reasonable explanation why stable sleep exhibits homeostasis which is far less susceptible to outside world.

How to Reduce Head CT Orders in Children with Hydrocephalus Using the Lean Six Sigma Methodology: Experience at a Major Quaternary Care Academic Children's Center.

PubMed

Tekes, A; Jackson, E M; Ogborn, J; Liang, S; Bledsoe, M; Durand, D J; Jallo, G; Huisman, T A G M

2016-06-01

Lean Six Sigma methodology is increasingly used to drive improvement in patient safety, quality of care, and cost-effectiveness throughout the US health care delivery system. To demonstrate our value as specialists, radiologists can combine lean methodologies along with imaging expertise to optimize imaging elements-of-care pathways. In this article, we describe a Lean Six Sigma project with the goal of reducing the relative use of pediatric head CTs in our population of patients with hydrocephalus by 50% within 6 months. We applied a Lean Six Sigma methodology using a multidisciplinary team at a quaternary care academic children's center. The existing baseline imaging practice for hydrocephalus was outlined in a Kaizen session, and potential interventions were discussed. An improved radiation-free workflow with ultrafast MR imaging was created. Baseline data were collected for 3 months by using the departmental radiology information system. Data collection continued postintervention and during the control phase (each for 3 months). The percentage of neuroimaging per technique (head CT, head ultrasound, ultrafast brain MR imaging, and routine brain MR imaging) was recorded during each phase. The improved workflow resulted in a 75% relative reduction in the percentage of hydrocephalus imaging performed by CT between the pre- and postintervention/control phases (Z-test, P = .0001). Our lean interventions in the pediatric hydrocephalus care pathway resulted in a significant reduction in head CT orders and increased use of ultrafast brain MR imaging. © 2016 by American Journal of Neuroradiology.

Subthalamic nucleus deep brain stimulation for Parkinson's disease: evidence for effectiveness and limitations from 12 years' experience.

PubMed

Chan, Anne Y Y; Yeung, Jonas H M; Mok, Vincent C T; Ip, Vincent H L; Wong, Adrian; Kuo, S H; Chan, Danny T M; Zhu, X L; Wong, Edith; Lau, Claire K Y; Wong, Rosanna K M; Tang, Venus; Lau, Christine; Poon, W S

2014-12-01

To present the result and experience of subthalamic nucleus deep brain stimulation for Parkinson's disease. Case series. Prince of Wales Hospital, Hong Kong. A cohort of patients with Parkinson's disease received subthalamic nucleus deep brain stimulation from September 1998 to January 2010. Patient assessment data before and after the operation were collected prospectively. Forty-one patients (21 male and 20 female) with Parkinson's disease underwent bilateral subthalamic nucleus deep brain stimulation and were followed up for a median interval of 12 months. For the whole group, the mean improvements of Unified Parkinson's Disease Rating Scale (UPDRS) parts II and III were 32.5% and 31.5%, respectively (P<0.001). Throughout the years, a multidisciplinary team was gradually built. The deep brain stimulation protocol evolved and was substantiated by updated patient selection criteria and outcome assessment, integrated imaging and neurophysiological targeting, refinement of surgical technique as well as the accumulation of experience in deep brain stimulation programming. Most of the structural improvement occurred before mid-2005. Patients receiving the operation before June 2005 (19 cases) and after (22 cases) were compared; the improvements in UPDRS part III were 13.2% and 55.2%, respectively (P<0.001). There were three operative complications (one lead migration, one cerebral haematoma, and one infection) in the group operated on before 2005. There was no operative mortality. The functional state of Parkinson's disease patients with motor disabilities refractory to best medical treatment improved significantly after subthalamic nucleus deep brain stimulation. A dedicated multidisciplinary team building, refined protocol for patient selection and assessment, improvement of targeting methods, meticulous surgical technique, and experience in programming are the key factors contributing to the improved outcome.

EGFR-directed Affibody for fluorescence-guided glioma surgery: time-dose analysis (Conference Presentation)

NASA Astrophysics Data System (ADS)

Ribeiro de Souza, Ana Luiza; Marra, Kayla; Gunn, Jason R.; Elliott, Jonathan T.; Samkoe, Kimberley S.; Paulsen, Keith D.; Draney, Daniel R.; Feldwisch, Joachim

2016-03-01

The key to fluorescence guided surgical oncology is the ability to create specific contrast between normal and glioma tissue. The blood brain barrier that limits the delivery of substances to the normal brain is broken in tumors, allowing accumulation of agents in the tumor interior. However, for a clinical success, imaging agents should be in the infiltrative edges to minimize the resection of normal brain while enable the removal of tumor. The aberrant overexpression and/or activation of EGFR is associated with many types of cancers, including glioblastoma and the injection of a fluorescent molecule targeted to these receptors would improve tumor contrast during fluorescence guided surgery. Affibody molecules have intentional medium affinity and high potential specificity, which are the desirable features of a good surgical imaging agent. The aim of this study was evaluate the brain/glioma uptake of ABY029 labeled with near-infrared dye IRDye800CW after intravenous injection. Rats were either inoculated with orthotopic implantations of U251 human glioma cell line or PBS (shams control) in the brain. The tumors were allowed to grow for 2-3 weeks before carrying out fluorescent tracer experiments. Fluorescent imaging of ex vivo brain slices from rats was acquired at different time points after infection of fluorescently labeled EGFR-specific affibody to verify which time provided maximal contrast tumor to normal brain. Although the tumor was most clearly visualized after 1h of IRDye800CW-labeled ABY029 injection, the tumor location could be identified from the background after 48h. These results suggest that the NIR-labeled affibody examined shows excellent potential to increase surgical visualization for confirmed EGFR positive tumors.

Beef assessments using functional magnetic resonance imaging and sensory evaluation.

PubMed

Tapp, W N; Davis, T H; Paniukov, D; Brooks, J C; Brashears, M M; Miller, M F

2017-04-01

Functional magnetic resonance imaging (fMRI) has been used to unveil how some foods and basic rewards are processed in the human brain. This study evaluated how resting state functional connectivity in regions of the human brain changed after differing qualities of beef steaks were consumed. Functional images of participants (n=8) were collected after eating high or low quality beef steaks on separate days, after consumption a sensory ballot was administered to evaluate consumers' perceptions of tenderness, juiciness, flavor, and overall liking. Imaging data showed that high quality steak samples resulted in greater functional connectivity to the striatum, medial orbitofrontal cortex, and insular cortex at various stages after consumption (P≤0.05). Furthermore, high quality steaks elicited higher sensory ballot scores for each palatability trait (P≤0.01). Together, these results suggest that resting state fMRI may be a useful tool for evaluating the neural process that follows positive sensory experiences such as the enjoyment of high quality beef steaks. Published by Elsevier Ltd.

Default network connectivity decodes brain states with simulated microgravity.

PubMed

Zeng, Ling-Li; Liao, Yang; Zhou, Zongtan; Shen, Hui; Liu, Yadong; Liu, Xufeng; Hu, Dewen

2016-04-01

With great progress of space navigation technology, it becomes possible to travel beyond Earth's gravity. So far, it remains unclear whether the human brain can function normally within an environment of microgravity and confinement. Particularly, it is a challenge to figure out some neuroimaging-based markers for rapid screening diagnosis of disrupted brain function in microgravity environment. In this study, a 7-day -6° head down tilt bed rest experiment was used to simulate the microgravity, and twenty healthy male participants underwent resting-state functional magnetic resonance imaging scans at baseline and after the simulated microgravity experiment. We used a multivariate pattern analysis approach to distinguish the brain states with simulated microgravity from normal gravity based on the functional connectivity within the default network, resulting in an accuracy of no less than 85 % via cross-validation. Moreover, most discriminative functional connections were mainly located between the limbic system and cortical areas and were enhanced after simulated microgravity, implying a self-adaption or compensatory enhancement to fulfill the need of complex demand in spatial navigation and motor control functions in microgravity environment. Overall, the findings suggest that the brain states in microgravity are likely different from those in normal gravity and that brain connectome could act as a biomarker to indicate the brain state in microgravity.

Spontaneous brain activity predicts learning ability of foreign sounds.

PubMed

Ventura-Campos, Noelia; Sanjuán, Ana; González, Julio; Palomar-García, María-Ángeles; Rodríguez-Pujadas, Aina; Sebastián-Gallés, Núria; Deco, Gustavo; Ávila, César

2013-05-29

Can learning capacity of the human brain be predicted from initial spontaneous functional connectivity (FC) between brain areas involved in a task? We combined task-related functional magnetic resonance imaging (fMRI) and resting-state fMRI (rs-fMRI) before and after training with a Hindi dental-retroflex nonnative contrast. Previous fMRI results were replicated, demonstrating that this learning recruited the left insula/frontal operculum and the left superior parietal lobe, among other areas of the brain. Crucially, resting-state FC (rs-FC) between these two areas at pretraining predicted individual differences in learning outcomes after distributed (Experiment 1) and intensive training (Experiment 2). Furthermore, this rs-FC was reduced at posttraining, a change that may also account for learning. Finally, resting-state network analyses showed that the mechanism underlying this reduction of rs-FC was mainly a transfer in intrinsic activity of the left frontal operculum/anterior insula from the left frontoparietal network to the salience network. Thus, rs-FC may contribute to predict learning ability and to understand how learning modifies the functioning of the brain. The discovery of this correspondence between initial spontaneous brain activity in task-related areas and posttraining performance opens new avenues to find predictors of learning capacities in the brain using task-related fMRI and rs-fMRI combined.

Imaging Brain Function with Functional Near-Infrared Spectroscopy in Unconstrained Environments.

PubMed

Balardin, Joana B; Zimeo Morais, Guilherme A; Furucho, Rogério A; Trambaiolli, Lucas; Vanzella, Patricia; Biazoli, Claudinei; Sato, João R

2017-01-01

Assessing the neural correlates of motor and cognitive processes under naturalistic experimentation is challenging due to the movement constraints of traditional brain imaging technologies. The recent advent of portable technologies that are less sensitive to motion artifacts such as Functional Near Infrared Spectroscopy (fNIRS) have been made possible the study of brain function in freely-moving participants. In this paper, we describe a series of proof-of-concept experiments examining the potential of fNIRS in assessing the neural correlates of cognitive and motor processes in unconstrained environments. We show illustrative applications for practicing a sport (i.e., table tennis), playing a musical instrument (i.e., piano and violin) alone or in duo and performing daily activities for many hours (i.e., continuous monitoring). Our results expand upon previous research on the feasibility and robustness of fNIRS to monitor brain hemodynamic changes in different real life settings. We believe that these preliminary results showing the flexibility and robustness of fNIRS measurements may contribute by inspiring future work in the field of applied neuroscience.

Imaging Brain Function with Functional Near-Infrared Spectroscopy in Unconstrained Environments

PubMed Central

Balardin, Joana B.; Zimeo Morais, Guilherme A.; Furucho, Rogério A.; Trambaiolli, Lucas; Vanzella, Patricia; Biazoli, Claudinei; Sato, João R.

2017-01-01

Assessing the neural correlates of motor and cognitive processes under naturalistic experimentation is challenging due to the movement constraints of traditional brain imaging technologies. The recent advent of portable technologies that are less sensitive to motion artifacts such as Functional Near Infrared Spectroscopy (fNIRS) have been made possible the study of brain function in freely-moving participants. In this paper, we describe a series of proof-of-concept experiments examining the potential of fNIRS in assessing the neural correlates of cognitive and motor processes in unconstrained environments. We show illustrative applications for practicing a sport (i.e., table tennis), playing a musical instrument (i.e., piano and violin) alone or in duo and performing daily activities for many hours (i.e., continuous monitoring). Our results expand upon previous research on the feasibility and robustness of fNIRS to monitor brain hemodynamic changes in different real life settings. We believe that these preliminary results showing the flexibility and robustness of fNIRS measurements may contribute by inspiring future work in the field of applied neuroscience. PMID:28567011

Exploring sex differences in the adult zebra finch brain: In vivo diffusion tensor imaging and ex vivo super-resolution track density imaging.

PubMed

Hamaide, Julie; De Groof, Geert; Van Steenkiste, Gwendolyn; Jeurissen, Ben; Van Audekerke, Johan; Naeyaert, Maarten; Van Ruijssevelt, Lisbeth; Cornil, Charlotte; Sijbers, Jan; Verhoye, Marleen; Van der Linden, Annemie

2017-02-01

Zebra finches are an excellent model to study the process of vocal learning, a complex socially-learned tool of communication that forms the basis of spoken human language. So far, structural investigation of the zebra finch brain has been performed ex vivo using invasive methods such as histology. These methods are highly specific, however, they strongly interfere with performing whole-brain analyses and exclude longitudinal studies aimed at establishing causal correlations between neuroplastic events and specific behavioral performances. Therefore, the aim of the current study was to implement an in vivo Diffusion Tensor Imaging (DTI) protocol sensitive enough to detect structural sex differences in the adult zebra finch brain. Voxel-wise comparison of male and female DTI parameter maps shows clear differences in several components of the song control system (i.e. Area X surroundings, the high vocal center (HVC) and the lateral magnocellular nucleus of the anterior nidopallium (LMAN)), which corroborate previous findings and are in line with the clear behavioral difference as only males sing. Furthermore, to obtain additional insights into the 3-dimensional organization of the zebra finch brain and clarify findings obtained by the in vivo study, ex vivo DTI data of the male and female brain were acquired as well, using a recently established super-resolution reconstruction (SRR) imaging strategy. Interestingly, the SRR-DTI approach led to a marked reduction in acquisition time without interfering with the (spatial and angular) resolution and SNR which enabled to acquire a data set characterized by a 78μm isotropic resolution including 90 diffusion gradient directions within 44h of scanning time. Based on the reconstructed SRR-DTI maps, whole brain probabilistic Track Density Imaging (TDI) was performed for the purpose of super resolved track density imaging, further pushing the resolution up to 40μm isotropic. The DTI and TDI maps realized atlas-quality anatomical maps that enable a clear delineation of most components of the song control and auditory systems. In conclusion, this study paves the way for longitudinal in vivo and high-resolution ex vivo experiments aimed at disentangling neuroplastic events that characterize the critical period for vocal learning in zebra finch ontogeny. Copyright © 2016 Elsevier Inc. All rights reserved.

Repeated Structural Imaging Reveals Nonlinear Progression of Experience-Dependent Volume Changes in Human Motor Cortex.

PubMed

Wenger, Elisabeth; Kühn, Simone; Verrel, Julius; Mårtensson, Johan; Bodammer, Nils Christian; Lindenberger, Ulman; Lövdén, Martin

2017-05-01

Evidence for experience-dependent structural brain change in adult humans is accumulating. However, its time course is not well understood, as intervention studies typically consist of only 2 imaging sessions (before vs. after training). We acquired up to 18 structural magnetic resonance images over a 7-week period while 15 right-handed participants practiced left-hand writing and drawing. After 4 weeks, we observed increases in gray matter of both left and right primary motor cortices relative to a control group; 3 weeks later, these differences were no longer reliable. Time-series analyses revealed that gray matter in the primary motor cortices expanded during the first 4 weeks and then partially renormalized, in particular in the right hemisphere, despite continued practice and increasing task proficiency. Similar patterns of expansion followed by partial renormalization are also found in synaptogenesis, cortical map plasticity, and maturation, and may qualify as a general principle of structural plasticity. Research on human brain plasticity needs to encompass more than 2 measurement occasions to capture expansion and potential renormalization processes over time. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Quantification of intensity variations in functional MR images using rotated principal components

NASA Astrophysics Data System (ADS)

Backfrieder, W.; Baumgartner, R.; Sámal, M.; Moser, E.; Bergmann, H.

1996-08-01

In functional MRI (fMRI), the changes in cerebral haemodynamics related to stimulated neural brain activity are measured using standard clinical MR equipment. Small intensity variations in fMRI data have to be detected and distinguished from non-neural effects by careful image analysis. Based on multivariate statistics we describe an algorithm involving oblique rotation of the most significant principal components for an estimation of the temporal and spatial distribution of the stimulated neural activity over the whole image matrix. This algorithm takes advantage of strong local signal variations. A mathematical phantom was designed to generate simulated data for the evaluation of the method. In simulation experiments, the potential of the method to quantify small intensity changes, especially when processing data sets containing multiple sources of signal variations, was demonstrated. In vivo fMRI data collected in both visual and motor stimulation experiments were analysed, showing a proper location of the activated cortical regions within well known neural centres and an accurate extraction of the activation time profile. The suggested method yields accurate absolute quantification of in vivo brain activity without the need of extensive prior knowledge and user interaction.

The human parental brain: In vivo neuroimaging

PubMed Central

Swain, James E.

2015-01-01

Interacting parenting thoughts and behaviors, supported by key brain circuits, critically shape human infants’ current and future behavior. Indeed, the parent–infant relationship provides infants with their first social environment, forming templates for what they can expect from others, how to interact with them and ultimately how they go on to themselves to be parents. This review concentrates on magnetic resonance imaging experiments of the human parent brain, which link brain physiology with parental thoughts and behaviors. After reviewing brain imaging techniques, certain social cognitive and affective concepts are reviewed, including empathy and trust—likely critical to parenting. Following that is a thorough study-by-study review of the state-of-the-art with respect to human neuroimaging studies of the parental brain—from parent brain responses to salient infant stimuli, including emotionally charged baby cries and brief visual stimuli to the latest structural brain studies. Taken together, this research suggests that networks of highly conserved hypothalamic–midbrain–limbic–paralimbic–cortical circuits act in concert to support parental brain responses to infants, including circuits for limbic emotion response and regulation. Thus, a model is presented in which infant stimuli activate sensory analysis brain regions, affect corticolimbic limbic circuits that regulate emotional response, motivation and reward related to their infant, ultimately organizing parenting impulses, thoughts and emotions into coordinated behaviors as a map for future studies. Finally, future directions towards integrated understanding of the brain basis of human parenting are outlined with profound implications for understanding and contributing to long term parent and infant mental health. PMID:21036196

Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization.

PubMed

Molina, David; Pérez-Beteta, Julián; Martínez-González, Alicia; Martino, Juan; Velasquez, Carlos; Arana, Estanislao; Pérez-García, Víctor M

2017-01-01

Textural measures have been widely explored as imaging biomarkers in cancer. However, their robustness under dynamic range and spatial resolution changes in brain 3D magnetic resonance images (MRI) has not been assessed. The aim of this work was to study potential variations of textural measures due to changes in MRI protocols. Twenty patients harboring glioblastoma with pretreatment 3D T1-weighted MRIs were included in the study. Four different spatial resolution combinations and three dynamic ranges were studied for each patient. Sixteen three-dimensional textural heterogeneity measures were computed for each patient and configuration including co-occurrence matrices (CM) features and run-length matrices (RLM) features. The coefficient of variation was used to assess the robustness of the measures in two series of experiments corresponding to (i) changing the dynamic range and (ii) changing the matrix size. No textural measures were robust under dynamic range changes. Entropy was the only textural feature robust under spatial resolution changes (coefficient of variation under 10% in all cases). Textural measures of three-dimensional brain tumor images are not robust neither under dynamic range nor under matrix size changes. Standards should be harmonized to use textural features as imaging biomarkers in radiomic-based studies. The implications of this work go beyond the specific tumor type studied here and pose the need for standardization in textural feature calculation of oncological images.

Improving the convergence rate in affine registration of PET and SPECT brain images using histogram equalization.

PubMed

Salas-Gonzalez, D; Górriz, J M; Ramírez, J; Padilla, P; Illán, I A

2013-01-01

A procedure to improve the convergence rate for affine registration methods of medical brain images when the images differ greatly from the template is presented. The methodology is based on a histogram matching of the source images with respect to the reference brain template before proceeding with the affine registration. The preprocessed source brain images are spatially normalized to a template using a general affine model with 12 parameters. A sum of squared differences between the source images and the template is considered as objective function, and a Gauss-Newton optimization algorithm is used to find the minimum of the cost function. Using histogram equalization as a preprocessing step improves the convergence rate in the affine registration algorithm of brain images as we show in this work using SPECT and PET brain images.

Enhanced learning of natural visual sequences in newborn chicks.

PubMed

Wood, Justin N; Prasad, Aditya; Goldman, Jason G; Wood, Samantha M W

2016-07-01

To what extent are newborn brains designed to operate over natural visual input? To address this question, we used a high-throughput controlled-rearing method to examine whether newborn chicks (Gallus gallus) show enhanced learning of natural visual sequences at the onset of vision. We took the same set of images and grouped them into either natural sequences (i.e., sequences showing different viewpoints of the same real-world object) or unnatural sequences (i.e., sequences showing different images of different real-world objects). When raised in virtual worlds containing natural sequences, newborn chicks developed the ability to recognize familiar images of objects. Conversely, when raised in virtual worlds containing unnatural sequences, newborn chicks' object recognition abilities were severely impaired. In fact, the majority of the chicks raised with the unnatural sequences failed to recognize familiar images of objects despite acquiring over 100 h of visual experience with those images. Thus, newborn chicks show enhanced learning of natural visual sequences at the onset of vision. These results indicate that newborn brains are designed to operate over natural visual input.

A Primer on Brain Imaging in Developmental Psychopathology: What Is It Good For?

ERIC Educational Resources Information Center

Pine, Daniel S.

2006-01-01

This primer introduces a Special Section on brain imaging, which includes a commentary and 10 data papers presenting applications of brain imaging to questions on developmental psychopathology. This primer serves two purposes. First, the article summarizes the strength and weaknesses of various brain-imaging techniques typically employed in…

Brain MR image segmentation using NAMS in pseudo-color.

PubMed

Li, Hua; Chen, Chuanbo; Fang, Shaohong; Zhao, Shengrong

2017-12-01

Image segmentation plays a crucial role in various biomedical applications. In general, the segmentation of brain Magnetic Resonance (MR) images is mainly used to represent the image with several homogeneous regions instead of pixels for surgical analyzing and planning. This paper proposes a new approach for segmenting MR brain images by using pseudo-color based segmentation with Non-symmetry and Anti-packing Model with Squares (NAMS). First of all, the NAMS model is presented. The model can represent the image with sub-patterns to keep the image content and largely reduce the data redundancy. Second, the key idea is proposed that convert the original gray-scale brain MR image into a pseudo-colored image and then segment the pseudo-colored image with NAMS model. The pseudo-colored image can enhance the color contrast in different tissues in brain MR images, which can improve the precision of segmentation as well as directly visual perceptional distinction. Experimental results indicate that compared with other brain MR image segmentation methods, the proposed NAMS based pseudo-color segmentation method performs more excellent in not only segmenting precisely but also saving storage.

Structural Image Analysis of the Brain in Neuropsychology Using Magnetic Resonance Imaging (MRI) Techniques.

PubMed

Bigler, Erin D

2015-09-01

Magnetic resonance imaging (MRI) of the brain provides exceptional image quality for visualization and neuroanatomical classification of brain structure. A variety of image analysis techniques provide both qualitative as well as quantitative methods to relate brain structure with neuropsychological outcome and are reviewed herein. Of particular importance are more automated methods that permit analysis of a broad spectrum of anatomical measures including volume, thickness and shape. The challenge for neuropsychology is which metric to use, for which disorder and the timing of when image analysis methods are applied to assess brain structure and pathology. A basic overview is provided as to the anatomical and pathoanatomical relations of different MRI sequences in assessing normal and abnormal findings. Some interpretive guidelines are offered including factors related to similarity and symmetry of typical brain development along with size-normalcy features of brain anatomy related to function. The review concludes with a detailed example of various quantitative techniques applied to analyzing brain structure for neuropsychological outcome studies in traumatic brain injury.

Automating Cell Detection and Classification in Human Brain Fluorescent Microscopy Images Using Dictionary Learning and Sparse Coding

PubMed Central

Alegro, Maryana; Theofilas, Panagiotis; Nguy, Austin; Castruita, Patricia A.; Seeley, William; Heinsen, Helmut; Ushizima, Daniela M.

2017-01-01

Background Immunofluorescence (IF) plays a major role in quantifying protein expression in situ and understanding cell function. It is widely applied in assessing disease mechanisms and in drug discovery research. Automation of IF analysis can transform studies using experimental cell models. However, IF analysis of postmortem human tissue relies mostly on manual interaction, often subjected to low-throughput and prone to error, leading to low inter and intra-observer reproducibility. Human postmortem brain samples challenges neuroscientists because of the high level of autofluorescence caused by accumulation of lipofuscin pigment during aging, hindering systematic analyses. We propose a method for automating cell counting and classification in IF microscopy of human postmortem brains. Our algorithm speeds up the quantification task while improving reproducibility. New method Dictionary learning and sparse coding allow for constructing improved cell representations using IF images. These models are input for detection and segmentation methods. Classification occurs by means of color distances between cells and a learned set. Results Our method successfully detected and classified cells in 49 human brain images. We evaluated our results regarding true positive, false positive, false negative, precision, recall, false positive rate and F1 score metrics. We also measured user-experience and time saved compared to manual countings. Comparison with existing methods We compared our results to four open-access IF-based cell-counting tools available in the literature. Our method showed improved accuracy for all data samples. Conclusion The proposed method satisfactorily detects and classifies cells from human postmortem brain IF images, with potential to be generalized for applications in other counting tasks. PMID:28267565

fMRI of pain studies using laser-induced heat on skin with and without the loved one near the subject - a pilot study on 'love hurts'

NASA Astrophysics Data System (ADS)

Sofina, T.; Kamil, W. A.; Ahmad, A. H.

2014-11-01

The aims of this study are to image and investigate the areas of brain response to laser-induced heat pain, to analyse for any difference in the brain response when a subject is alone and when her loved one is present next to the MRI gantry. Pain stimuli was delivered using Th-YAG laser to four female subjects. Blood-Oxygenation-Level-Dependent (BOLD) fMRI experiment was performed using blocked design paradigm with five blocks of painful (P) stimuli and five blocks of non-painful (NP) stimuli arranged in pseudorandom order with an 18 seconds rest (R) between each stimulation phase. Brain images were obtained from 3T Philips Achieva MRI scanner using 32-channel SENSE head coil. A T1-weighted image (TR/TE/slice/FOV = 9ms/4ms/4mm slices/240×240mm) was obtained for verification of brain anatomical structures. An echo-planar-imaging sequence were used for the functional scans (TR/TE/slice/flip/FOV=2000ms/35ms/4mm slices/90°/220×220mm). fMRI data sets were analysed using SPM 8.0 involving preprocessing steps followed by t-contrast analysis for individuals and FFX analysis. In both with and without-loved-one conditions, neuronal responses were seen in the somatosensory gyrus, supramarginal gyrus, thalamus and insula regions, consistent with pain-related areas. FFX analysis showed that the presence of loved one produced more activation in the frontal and supramarginal gyrus during painful and non-painful stimulations compared to absence of a loved one. Brain response to pain is modulated by the presence of a loved one, causing more activation in the cognitive/emotional area i.e. 'love hurts'.

A novel content-based active contour model for brain tumor segmentation.

PubMed

Sachdeva, Jainy; Kumar, Vinod; Gupta, Indra; Khandelwal, Niranjan; Ahuja, Chirag Kamal

2012-06-01

Brain tumor segmentation is a crucial step in surgical and treatment planning. Intensity-based active contour models such as gradient vector flow (GVF), magneto static active contour (MAC) and fluid vector flow (FVF) have been proposed to segment homogeneous objects/tumors in medical images. In this study, extensive experiments are done to analyze the performance of intensity-based techniques for homogeneous tumors on brain magnetic resonance (MR) images. The analysis shows that the state-of-art methods fail to segment homogeneous tumors against similar background or when these tumors show partial diversity toward the background. They also have preconvergence problem in case of false edges/saddle points. However, the presence of weak edges and diffused edges (due to edema around the tumor) leads to oversegmentation by intensity-based techniques. Therefore, the proposed method content-based active contour (CBAC) uses both intensity and texture information present within the active contour to overcome above-stated problems capturing large range in an image. It also proposes a novel use of Gray-Level Co-occurrence Matrix to define texture space for tumor segmentation. The effectiveness of this method is tested on two different real data sets (55 patients - more than 600 images) containing five different types of homogeneous, heterogeneous, diffused tumors and synthetic images (non-MR benchmark images). Remarkable results are obtained in segmenting homogeneous tumors of uniform intensity, complex content heterogeneous, diffused tumors on MR images (T1-weighted, postcontrast T1-weighted and T2-weighted) and synthetic images (non-MR benchmark images of varying intensity, texture, noise content and false edges). Further, tumor volume is efficiently extracted from 2-dimensional slices and is named as 2.5-dimensional segmentation. Copyright © 2012 Elsevier Inc. All rights reserved.

High-Speed and Scalable Whole-Brain Imaging in Rodents and Primates.

PubMed

Seiriki, Kaoru; Kasai, Atsushi; Hashimoto, Takeshi; Schulze, Wiebke; Niu, Misaki; Yamaguchi, Shun; Nakazawa, Takanobu; Inoue, Ken-Ichi; Uezono, Shiori; Takada, Masahiko; Naka, Yuichiro; Igarashi, Hisato; Tanuma, Masato; Waschek, James A; Ago, Yukio; Tanaka, Kenji F; Hayata-Takano, Atsuko; Nagayasu, Kazuki; Shintani, Norihito; Hashimoto, Ryota; Kunii, Yasuto; Hino, Mizuki; Matsumoto, Junya; Yabe, Hirooki; Nagai, Takeharu; Fujita, Katsumasa; Matsuda, Toshio; Takuma, Kazuhiro; Baba, Akemichi; Hashimoto, Hitoshi

2017-06-21

Subcellular resolution imaging of the whole brain and subsequent image analysis are prerequisites for understanding anatomical and functional brain networks. Here, we have developed a very high-speed serial-sectioning imaging system named FAST (block-face serial microscopy tomography), which acquires high-resolution images of a whole mouse brain in a speed range comparable to that of light-sheet fluorescence microscopy. FAST enables complete visualization of the brain at a resolution sufficient to resolve all cells and their subcellular structures. FAST renders unbiased quantitative group comparisons of normal and disease model brain cells for the whole brain at a high spatial resolution. Furthermore, FAST is highly scalable to non-human primate brains and human postmortem brain tissues, and can visualize neuronal projections in a whole adult marmoset brain. Thus, FAST provides new opportunities for global approaches that will allow for a better understanding of brain systems in multiple animal models and in human diseases. Copyright © 2017 Elsevier Inc. All rights reserved.

Genes and Experience in the Development of Executive Attention and Effortful Control

ERIC Educational Resources Information Center

Rothbart, Mary K.; Posner, Michael I.

2005-01-01

The executive attention network is involved in regulating emotions and cognitions, forming a neural basis for temperamental self-regulation. New brain imaging and molecular genetics methods can enhance our understanding of common mechanisms of self-regulation and individual differences in their expression.

Deformably registering and annotating whole CLARITY brains to an atlas via masked LDDMM

NASA Astrophysics Data System (ADS)

Kutten, Kwame S.; Vogelstein, Joshua T.; Charon, Nicolas; Ye, Li; Deisseroth, Karl; Miller, Michael I.

2016-04-01

The CLARITY method renders brains optically transparent to enable high-resolution imaging in the structurally intact brain. Anatomically annotating CLARITY brains is necessary for discovering which regions contain signals of interest. Manually annotating whole-brain, terabyte CLARITY images is difficult, time-consuming, subjective, and error-prone. Automatically registering CLARITY images to a pre-annotated brain atlas offers a solution, but is difficult for several reasons. Removal of the brain from the skull and subsequent storage and processing cause variable non-rigid deformations, thus compounding inter-subject anatomical variability. Additionally, the signal in CLARITY images arises from various biochemical contrast agents which only sparsely label brain structures. This sparse labeling challenges the most commonly used registration algorithms that need to match image histogram statistics to the more densely labeled histological brain atlases. The standard method is a multiscale Mutual Information B-spline algorithm that dynamically generates an average template as an intermediate registration target. We determined that this method performs poorly when registering CLARITY brains to the Allen Institute's Mouse Reference Atlas (ARA), because the image histogram statistics are poorly matched. Therefore, we developed a method (Mask-LDDMM) for registering CLARITY images, that automatically finds the brain boundary and learns the optimal deformation between the brain and atlas masks. Using Mask-LDDMM without an average template provided better results than the standard approach when registering CLARITY brains to the ARA. The LDDMM pipelines developed here provide a fast automated way to anatomically annotate CLARITY images; our code is available as open source software at http://NeuroData.io.

Evaluating Aesthetic Experience through Personal-Appearance Styles: A Behavioral and Electrophysiological Study

PubMed Central

Cheung, Mei-chun; Law, Derry; Yip, Joanne

2014-01-01

Consumers' aesthetic experience has often been linked with the concept of beauty, which is regarded as subjective and may vary between individuals, cultures and places, and across time. With the advent of brain-imaging techniques, there is more and more evidence to suggest that aesthetic experience lies not only in the eye of the beholder, but also in the brain of the beholder. However, there are gaps in the previous research in this area, as several significant issues have not yet been addressed. Specifically, it is unclear whether the human brain really pays more attention and generates more positive emotional responses to beautiful things. To explore the brain activity relating to consumers' aesthetic experiences, 15 participants were recruited voluntarily to view a series of personal-appearance styles. They were invited to make aesthetic judgments while their brain activity was recorded by electroencephalography. Two electroencephalographic (EEG) indicators, theta coherence and frontal alpha symmetry, were utilized. Theta coherence is a measure of linear synchronization between signals at two electrode sites. It reflects the degree of functional cooperation between the underlying neuronal substrates and was used to explore the attentional processing involved in aesthetic judgments. Frontal alpha asymmetry is derived by subtracting the log-transformed absolute alpha power of the left hemisphere from the analogous log-transformed alpha power of the right hemisphere. It was used as an indicator of emotional response. During aesthetic judgments, long-range theta coherence increased in both hemispheres and more positive frontal alpha asymmetry was found when the styles were judged to be beautiful. Therefore, participants demonstrated brain activity suggestive of central executive processing and more positive emotional responses when they considered styles to be beautiful. The study provides some insight into the brain activity associated with consumers' aesthetic experiences, and suggests new directions for exploring consumer behavior from the perspective of neuroscience. PMID:25551635

Evaluating aesthetic experience through personal-appearance styles: a behavioral and electrophysiological study.

PubMed

Cheung, Mei-chun; Law, Derry; Yip, Joanne

2014-01-01

Consumers' aesthetic experience has often been linked with the concept of beauty, which is regarded as subjective and may vary between individuals, cultures and places, and across time. With the advent of brain-imaging techniques, there is more and more evidence to suggest that aesthetic experience lies not only in the eye of the beholder, but also in the brain of the beholder. However, there are gaps in the previous research in this area, as several significant issues have not yet been addressed. Specifically, it is unclear whether the human brain really pays more attention and generates more positive emotional responses to beautiful things. To explore the brain activity relating to consumers' aesthetic experiences, 15 participants were recruited voluntarily to view a series of personal-appearance styles. They were invited to make aesthetic judgments while their brain activity was recorded by electroencephalography. Two electroencephalographic (EEG) indicators, theta coherence and frontal alpha symmetry, were utilized. Theta coherence is a measure of linear synchronization between signals at two electrode sites. It reflects the degree of functional cooperation between the underlying neuronal substrates and was used to explore the attentional processing involved in aesthetic judgments. Frontal alpha asymmetry is derived by subtracting the log-transformed absolute alpha power of the left hemisphere from the analogous log-transformed alpha power of the right hemisphere. It was used as an indicator of emotional response. During aesthetic judgments, long-range theta coherence increased in both hemispheres and more positive frontal alpha asymmetry was found when the styles were judged to be beautiful. Therefore, participants demonstrated brain activity suggestive of central executive processing and more positive emotional responses when they considered styles to be beautiful. The study provides some insight into the brain activity associated with consumers' aesthetic experiences, and suggests new directions for exploring consumer behavior from the perspective of neuroscience.

Half brain irradiation in a murine model of breast cancer brain metastasis: magnetic resonance imaging and histological assessments of dose-response.

PubMed

Zarghami, Niloufar; Murrell, Donna H; Jensen, Michael D; Dick, Frederick A; Chambers, Ann F; Foster, Paula J; Wong, Eugene

2018-06-01

Brain metastasis is becoming increasingly prevalent in breast cancer due to improved extra-cranial disease control. With emerging availability of modern image-guided radiation platforms, mouse models of brain metastases and small animal magnetic resonance imaging (MRI), we examined brain metastases' responses from radiotherapy in the pre-clinical setting. In this study, we employed half brain irradiation to reduce inter-subject variability in metastases dose-response evaluations. Half brain irradiation was performed on a micro-CT/RT system in a human breast cancer (MDA-MB-231-BR) brain metastasis mouse model. Radiation induced DNA double stranded breaks in tumors and normal mouse brain tissue were quantified using γ-H2AX immunohistochemistry at 30 min (acute) and 11 days (longitudinal) after half-brain treatment for doses of 8, 16 and 24 Gy. In addition, tumor responses were assessed volumetrically with in-vivo longitudinal MRI and histologically for tumor cell density and nuclear size. In the acute setting, γ-H2AX staining in tumors saturated at higher doses while normal mouse brain tissue continued to increase linearly in the phosphorylation of H2AX. While γ-H2AX fluorescence intensities returned to the background level in the brain 11 days after treatment, the residual γ-H2AX phosphorylation in the radiated tumors remained elevated compared to un-irradiated contralateral tumors. With radiation, MRI-derived relative tumor growth was significantly reduced compared to the un-irradiated side. While there was no difference in MRI tumor volume growth between 16 and 24 Gy, there was a significant reduction in tumor cell density from histology with increasing dose. In the longitudinal study, nuclear size in the residual tumor cells increased significantly as the radiation dose was increased. Radiation damages to the DNAs in the normal brain parenchyma are resolved over time, but remain unrepaired in the treated tumors. Furthermore, there is a radiation dose response in nuclear size of surviving tumor cells. Increase in nuclear size together with unrepaired DNA damage indicated that the surviving tumor cells post radiation had continued to progress in the cell cycle with DNA replication, but failed cytokinesis. Half brain irradiation provides efficient evaluation of dose-response for cancer cell lines, a pre-requisite to perform experiments to understand radio-resistance in brain metastases.

Multicolor Fluorescence Imaging of Traumatic Brain Injury in a Cryolesion Mouse Model

PubMed Central

2012-01-01

Traumatic brain injury is characterized by initial tissue damage, which then can lead to secondary processes such as cell death and blood-brain-barrier disruption. Clinical and preclinical studies of traumatic brain injury typically employ anatomical imaging techniques and there is a need for new molecular imaging methods that provide complementary biochemical information. Here, we assess the ability of a targeted, near-infrared fluorescent probe, named PSS-794, to detect cell death in a brain cryolesion mouse model that replicates certain features of traumatic brain injury. In short, the model involves brief contact of a cold rod to the head of a living, anesthetized mouse. Using noninvasive whole-body fluorescence imaging, PSS-794 permitted visualization of the cryolesion in the living animal. Ex vivo imaging and histological analysis confirmed PSS-794 localization to site of brain cell death. The nontargeted, deep-red Tracer-653 was validated as a tracer dye for monitoring blood-brain-barrier disruption, and a binary mixture of PSS-794 and Tracer-653 was employed for multicolor imaging of cell death and blood-brain-barrier permeability in a single animal. The imaging data indicates that at 3 days after brain cryoinjury the amount of cell death had decreased significantly, but the integrity of the blood-brain-barrier was still impaired; at 7 days, the blood-brain-barrier was still three times more permeable than before cryoinjury. PMID:22860222

Clinical indications for high-field 1.5 T intraoperative magnetic resonance imaging and neuro-navigation for neurosurgical procedures. Review of initial 100 cases.

PubMed

Maesawa, Satoshi; Fujii, Masazumi; Nakahara, Norimoto; Watanabe, Tadashi; Saito, Kiyoshi; Kajita, Yasukazu; Nagatani, Tetsuya; Wakabayashi, Toshihiko; Yoshida, Jun

2009-08-01

Initial experiences are reviewed in an integrated operation theater equipped with an intraoperative high-field (1.5 T) magnetic resonance (MR) imager and neuro-navigation (BrainSUITE), to evaluate the indications and limitations. One hundred consecutive cases were treated, consisting of 38 gliomas, 49 other tumors, 11 cerebrovascular diseases, and 2 functional diseases. The feasibility and usefulness of the integrated theater were evaluated for individual diseases, focusing on whether intraoperative images (including diffusion tensor imaging) affected the surgical strategy. The extent of resection and outcomes in each histological category of brain tumors were examined. Intraoperative high-field MR imaging frequently affected or modified the surgical strategy in the glioma group (27/38 cases, 71.1%), but less in the other tumor group (13/49 cases, 26.5%). The surgical strategy was not modified in cerebrovascular or functional diseases, but the success of procedures and the absence of complications could be confirmed. In glioma surgery, subtotal or greater resection was achieved in 22 of the 31 patients (71%) excluding biopsies, and intraoperative images revealed tumor remnants resulting in the extension of resection in 21 of the 22 patients (95.4%), the highest rate of extension among all types of pathologies. The integrated neuro-navigation improved workflow. The best indication for intraoperative high-field MR imaging and integrated neuro-navigation is brain tumors, especially gliomas, and is supplementary in assuring quality in surgery for cerebrovascular or functional diseases. Immediate quality assurance is provided in several types of neurosurgical procedures.

Occurrence of phantom genitalia after gender reassignment surgery.

PubMed

Ramachandran, V S; McGeoch, Paul D

2007-01-01

Transsexuals are individuals who identify as a member of the gender opposite to that which they are born. Many transsexuals report that they have always had a feeling of a mismatch between their inner gender-based "body image" and that of their body's actual physical form. Often transsexuals undergo gender reassignment surgery to convert their bodies to the sex they feel they should have been born. The vivid sensation of still having a limb although it has been amputated, a phantom limb, was first described by Weir Mitchell over a century ago. The same phenomenon is also occurs after amputation of the penis or a breast. Around 60% of men who have had to have their penis amputated for cancer will experience a phantom penis. It has recently been shown that a significant factor in these phantom sensations is "cross-activation" between the de-afferented cortex and surrounding areas. Despite this it also known that much of our body image is innately "hard-wired" into our brains; congenitally limbless patients can still experience phantom sensations. We hypothesise that, perhaps due to a dissociation during embryological development, the brains of transsexuals are "hard-wired" in manner, which is opposite to that of their biological sex. We go on to predict that male-to-female transsexuals will be much less likely to experience a phantom penis than a "normal" man who has had his penis amputated for another reason. The same will be true of female-to-male transsexuals who have had breast removal surgery. We also predict that some female-to-male transsexuals will have a phantom penis even although there is not one physically there. We believe that this is an easily testable hypothesis, which, if correct, would offer insights into both the basis of transsexuality and provide farther evidence that we have a gender specific body image, with a strong innate component that is "hard-wired" into our brains. This would furnish us with a better understanding the mechanism by which nature and nurture interact to link the brain-based internal body image with external sexual morphology. We would emphasise here that transsexuality should not be regarded as "abnormal" but instead as part of the spectrum of human behaviour.

Specific α4β2 Nicotinic Acetylcholine Receptor Binding of [F-18]Nifene in the Rhesus Monkey

PubMed Central

Hillmer, A.T.; Wooten, D.W.; Moirano, J.; Slesarev, M.; Barnhart, T.E.; Engle, J.W.; Nickles, R.J.; Murali, D.; Schneider, M.; Mukherjee, J.; Christian, B.T.

2013-01-01

Objective [F-18]Nifene is a PET radioligand developed to image α4β2* nicotinic acetylcholine receptors (nAChR) in the brain. This work assesses the in vivo binding and imaging characteristics of [F-18]nifene in rhesus monkeys for the development of PET experiments examining nAChR binding. Methods Dynamic PET imaging experiments with [F-18]nifene were acquired in 4 anesthetized macaca mulatta (rhesus) monkeys using a microPET P4 scanner. Data acquisition was initiated with a bolus injection of 109 ± 17 MBq [F-18]nifene and the time course of the radioligand in the brain was measured for up to 120 minutes. For two experiments, a displacement dose of (−)nicotine (0.03 mg/kg, i.v.) was given 45–60 minutes post injection and followed 30 minutes later with a second [F-18]nifene injection to measure radioligand nondisplaceable uptake. Time activity curves were extracted in the regions of the antereoventral thalamus (AVT), lateral geniculate nucleus region (LGN), frontal cortex, and the cerebellum (CB). Results The highest levels of [F-18]nifene uptake were observed in the AVT and LGN. Target-to-CB ratios reached maximum values of 3.3 ± 0.4 in the AVT and 3.2 ± 0.3 in the LG 30–45 minutes post-injection. Significant binding of [F-18]nifene was observed in the subiculum, insula cortex, temporal cortex, cingulate gyrus, frontal cortex, striatum, and midbrain areas. The (−)nicotine displaced bound [F-18]nifene to near background levels within 15 minutes post-drug injection. No discernable displacement was observed in the CB, suggesting its potential as a reference region. Logan graphical estimates using the CB as a reference region yielded binding potentials (BPND) of 1.6 ± 0.1 in the AVT, and 1.3 ± 0.1 in the LGN. The post-nicotine injection displayed uniform nondisplaceable uptake of [F-18]nifene throughout gray and white brain matter. Conclusions [F-18]Nifene exhibits rapid equilibration and a moderately high target to background binding profile in the α4β2* nAChR rich regions of the brain, thus providing favorable imaging characteristics as a PET radiotracer for nAChR assay. PMID:21674627

Virtual wall-based haptic-guided teleoperated surgical robotic system for single-port brain tumor removal surgery.

PubMed

Seung, Sungmin; Choi, Hongseok; Jang, Jongseong; Kim, Young Soo; Park, Jong-Oh; Park, Sukho; Ko, Seong Young

2017-01-01

This article presents a haptic-guided teleoperation for a tumor removal surgical robotic system, so-called a SIROMAN system. The system was developed in our previous work to make it possible to access tumor tissue, even those that seat deeply inside the brain, and to remove the tissue with full maneuverability. For a safe and accurate operation to remove only tumor tissue completely while minimizing damage to the normal tissue, a virtual wall-based haptic guidance together with a medical image-guided control is proposed and developed. The virtual wall is extracted from preoperative medical images, and the robot is controlled to restrict its motion within the virtual wall using haptic feedback. Coordinate transformation between sub-systems, a collision detection algorithm, and a haptic-guided teleoperation using a virtual wall are described in the context of using SIROMAN. A series of experiments using a simplified virtual wall are performed to evaluate the performance of virtual wall-based haptic-guided teleoperation. With haptic guidance, the accuracy of the robotic manipulator's trajectory is improved by 57% compared to one without. The tissue removal performance is also improved by 21% ( p < 0.05). The experiments show that virtual wall-based haptic guidance provides safer and more accurate tissue removal for single-port brain surgery.

Detection of early seizures by diffuse optical tomography

NASA Astrophysics Data System (ADS)

Zhang, Tao; Hajihashemi, M. Reza; Zhou, Junli; Carney, Paul R.; Jiang, Huabei

2015-03-01

In epilepsy it has been challenging to detect early changes in brain activity that occurs prior to seizure onset and to map their origin and evolution for possible intervention. Besides, preclinical seizure experiments need to be conducted in awake animals with images reconstructed and displayed in real-time. We demonstrate using a rat model of generalized epilepsy that diffuse optical tomography (DOT) provides a unique functional neuroimaging modality for noninvasively and continuously tracking brain activities with high spatiotemporal resolution. We developed methods to conduct seizure experiments in fully awake rats using a subject-specific helmet and a restraining mechanism. For the first time, we detected early hemodynamic responses with heterogeneous patterns several minutes preceding the electroencephalographic seizure onset, supporting the presence of a "pre-seizure" state both in anesthetized and awake rats. Using a novel time-series analysis of scattering images, we show that the analysis of scattered diffuse light is a sensitive and reliable modality for detecting changes in neural activity associated with generalized seizure. We found widespread hemodynamic changes evolving from local regions of the bilateral cortex and thalamus to the entire brain, indicating that the onset of generalized seizures may originate locally rather than diffusely. Together, these findings suggest DOT represents a powerful tool for mapping early seizure onset and propagation pathways.

Human sexual response.

PubMed

Basson, Rosemary

2015-01-01

The human sexual response to sexually arousing stimuli is a motivational incentive-based cycle comprising subjective experience and physiologic changes. Clinical and empirical data support a circular model of overlapping phases of variable order. Brain imaging data of sexual arousal identify areas of cerebral activation and inhibition reflecting a complex network of cognitive, motivational, emotional, and autonomic components. Psychologic and biologic factors influence the brain's appraisal and processing of sexual stimuli to allow or disallow subsequent arousal. The sexual and non-sexual outcomes influence motivation to future sexual intimacy. Variability is marked both between individuals and within a person's sexual life, influenced by multiple factors, including stage of life cycle, mental health, and relationship happiness. Neurologic disease can interrupt the cycle at many points: by limiting motivation, reducing ability to attend to and feel sexual stimuli, and accomplishing the movements needed to stimulate and experience intercourse. Impairments to genital congestion, penile erection, and orgasm may also occur. Disease-associated changes to the interpersonal relationship and self-image plus frequently comorbid depression will tend to lessen motivation and temper the brain's appraisal of sexual stimuli, so precluding arousal. Therapy begins by explaining the sexual response cycle, clarifying the points of interruption in the patient's own cycle so as to guide treatment. © 2015 Elsevier B.V. All rights reserved.

A study of the standard brain in Japanese children: morphological comparison with the MNI template.

PubMed

Uchiyama, Hitoshi T; Seki, Ayumi; Tanaka, Daisuke; Koeda, Tatsuya; Jcs Group

2013-03-01

Functional magnetic resonance imaging (MRI) studies involve normalization so that the brains of different subjects can be described using the same coordinate system. However, standard brain templates, including the Montreal Neurological Institute (MNI) template that is most frequently used at present, were created based on the brains of Western adults. Because morphological characteristics of the brain differ by race and ethnicity and between adults and children, errors are likely to occur when data from the brains of non-Western individuals are processed using these templates. Therefore, this study was conducted to collect basic data for the creation of a Japanese pediatric standard brain. Participants in this study were 45 healthy children (contributing 65 brain images) between the ages of 6 and 9 years, who had nothing notable in their perinatal and other histories and neurological findings, had normal physical findings and cognitive function, exhibited no behavioral abnormalities, and provided analyzable MR images. 3D-T1-weighted images were obtained using a 1.5-T MRI device, and images from each child were adjusted to the reference image by affine transformation using SPM8. The lengths were measured and compared with those of the MNI template. The Western adult standard brain and the Japanese pediatric standard brain obtained in this study differed greatly in size, particularly along the anteroposterior diameter and in height, suggesting that the correction rates are high, and that errors are likely to occur in the normalization of pediatric brain images. We propose that the use of the Japanese pediatric standard brain created in this study will improve the accuracy of identification of brain regions in functional brain imaging studies involving children. Copyright © 2012 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

Self-calibrated correlation imaging with k-space variant correlation functions.

PubMed

Li, Yu; Edalati, Masoud; Du, Xingfu; Wang, Hui; Cao, Jie J

2018-03-01

Correlation imaging is a previously developed high-speed MRI framework that converts parallel imaging reconstruction into the estimate of correlation functions. The presented work aims to demonstrate this framework can provide a speed gain over parallel imaging by estimating k-space variant correlation functions. Because of Fourier encoding with gradients, outer k-space data contain higher spatial-frequency image components arising primarily from tissue boundaries. As a result of tissue-boundary sparsity in the human anatomy, neighboring k-space data correlation varies from the central to the outer k-space. By estimating k-space variant correlation functions with an iterative self-calibration method, correlation imaging can benefit from neighboring k-space data correlation associated with both coil sensitivity encoding and tissue-boundary sparsity, thereby providing a speed gain over parallel imaging that relies only on coil sensitivity encoding. This new approach is investigated in brain imaging and free-breathing neonatal cardiac imaging. Correlation imaging performs better than existing parallel imaging techniques in simulated brain imaging acceleration experiments. The higher speed enables real-time data acquisition for neonatal cardiac imaging in which physiological motion is fast and non-periodic. With k-space variant correlation functions, correlation imaging gives a higher speed than parallel imaging and offers the potential to image physiological motion in real-time. Magn Reson Med 79:1483-1494, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Enhanced visualization of MR angiogram with modified MIP and 3D image fusion

NASA Astrophysics Data System (ADS)

Kim, JongHyo; Yeon, Kyoung M.; Han, Man Chung; Lee, Dong Hyuk; Cho, Han I.

1997-05-01

We have developed a 3D image processing and display technique that include image resampling, modification of MIP, volume rendering, and fusion of MIP image with volumetric rendered image. This technique facilitates the visualization of the 3D spatial relationship between vasculature and surrounding organs by overlapping the MIP image on the volumetric rendered image of the organ. We applied this technique to a MR brain image data to produce an MRI angiogram that is overlapped with 3D volume rendered image of brain. MIP technique was used to visualize the vasculature of brain, and volume rendering was used to visualize the other structures of brain. The two images are fused after adjustment of contrast and brightness levels of each image in such a way that both the vasculature and brain structure are well visualized either by selecting the maximum value of each image or by assigning different color table to each image. The resultant image with this technique visualizes both the brain structure and vasculature simultaneously, allowing the physicians to inspect their relationship more easily. The presented technique will be useful for surgical planning for neurosurgery.

Semiautomated volumetry of the cerebrum, cerebellum-brain stem, and temporal lobe on brain magnetic resonance images.

PubMed

Hayashi, Norio; Sanada, Shigeru; Suzuki, Masayuki; Matsuura, Yukihiro; Kawahara, Kazuhiro; Tsujii, Hideo; Yamamoto, Tomoyuki; Matsui, Osamu

2008-02-01

The aim of this study was to develop an automated method of segmenting the cerebrum, cerebellum-brain stem, and temporal lobe simultaneously on magnetic resonance (MR) images. We obtained T1-weighted MR images from 10 normal subjects and 19 patients with brain atrophy. To perform automated volumetry from MR images, we performed the following three steps: (1) segmentation of the brain region; (2) separation between the cerebrum and the cerebellum-brain stem; and (3) segmentation of the temporal lobe. Evaluation was based on the correctly recognized region (CRR) (i.e., the region recognized by both the automated and manual methods). The mean CRRs of the normal and atrophic brains were 98.2% and 97.9% for the cerebrum, 87.9% and 88.5% for the cerebellum-brain stem, and 76.9% and 85.8% for the temporal lobe, respectively. We introduce an automated volumetric method for the cerebrum, cerebellum-brain stem, and temporal lobe on brain MR images. Our method can be applied to not only the normal brain but also the atrophic brain.

ViRPET--combination of virtual reality and PET brain imaging

DOEpatents

Majewski, Stanislaw; Brefczynski-Lewis, Julie

2017-05-23

Various methods, systems and apparatus are provided for brain imaging during virtual reality stimulation. In one example, among others, a system for virtual ambulatory environment brain imaging includes a mobile brain imager configured to obtain positron emission tomography (PET) scans of a subject in motion, and a virtual reality (VR) system configured to provide one or more stimuli to the subject during the PET scans. In another example, a method for virtual ambulatory environment brain imaging includes providing stimulation to a subject through a virtual reality (VR) system; and obtaining a positron emission tomography (PET) scan of the subject while moving in response to the stimulation from the VR system. The mobile brain imager can be positioned on the subject with an array of imaging photodetector modules distributed about the head of the subject.

Multicontrast multiecho FLASH MRI for targeting the subthalamic nucleus.

PubMed

Xiao, Yiming; Beriault, Silvain; Pike, G Bruce; Collins, D Louis

2012-06-01

The subthalamic nucleus (STN) is one of the most common stimulation targets for treating Parkinson's disease using deep brain stimulation (DBS). This procedure requires precise placement of the stimulating electrode. Common practice of DBS implantation utilizes microelectrode recording to locate the sites with the correct electrical response after an initial location estimate based on a universal human brain atlas that is linearly scaled to the patient's anatomy as seen on the preoperative images. However, this often results in prolonged surgical time and possible surgical complications since the small-sized STN is difficult to visualize on conventional magnetic resonance (MR) images and its intersubject variability is not sufficiently considered in the atlas customization. This paper proposes a multicontrast, multiecho MR imaging (MRI) method that directly delineates the STN and other basal ganglia structures through five co-registered image contrasts (T1-weighted navigation image, R2 map, susceptibility-weighted imaging (phase, magnitude and fusion image)) obtained within a clinically acceptable time. The image protocol was optimized through both simulation and in vivo experiments to obtain the best image quality. Taking advantage of the multiple echoes and high readout bandwidths, no interimage registration is required since all images are produced in one acquisition, and image distortion and chemical shift are reduced. This MRI protocol is expected to mitigate some of the shortcomings of the state-of-the-art DBS implantation methods. Copyright © 2012 Elsevier Inc. All rights reserved.

How to Build a Hybrid Neurofeedback Platform Combining EEG and fMRI

PubMed Central

Mano, Marsel; Lécuyer, Anatole; Bannier, Elise; Perronnet, Lorraine; Noorzadeh, Saman; Barillot, Christian

2017-01-01

Multimodal neurofeedback estimates brain activity using information acquired with more than one neurosignal measurement technology. In this paper we describe how to set up and use a hybrid platform based on simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), then we illustrate how to use it for conducting bimodal neurofeedback experiments. The paper is intended for those willing to build a multimodal neurofeedback system, to guide them through the different steps of the design, setup, and experimental applications, and help them choose a suitable hardware and software configuration. Furthermore, it reports practical information from bimodal neurofeedback experiments conducted in our lab. The platform presented here has a modular parallel processing architecture that promotes real-time signal processing performance and simple future addition and/or replacement of processing modules. Various unimodal and bimodal neurofeedback experiments conducted in our lab showed high performance and accuracy. Currently, the platform is able to provide neurofeedback based on electroencephalography and functional magnetic resonance imaging, but the architecture and the working principles described here are valid for any other combination of two or more real-time brain activity measurement technologies. PMID:28377691

The study on increasing the equivalent SNR in the certain DOI by adjusting the SD separation in near-infrared brain imaging application

NASA Astrophysics Data System (ADS)

Wang, Jinhai; Liu, Dongyuan; Sun, Jinggong; Zhang, Yanjun; Sun, Qiuming; Ma, Jun; Zheng, Yu; Wang, Huiquan

2016-10-01

Near-infrared (NIR) brain imaging is one of the most promising techniques for brain research in recent years. As a significant supplement to the clinical imaging technique, such as CT and MRI, the NIR technique can achieve a fast, non-invasive, and low cost imaging of the brain, which is widely used for the brain functional imaging and hematoma detection. NIR imaging can achieve an imaging depth up to only several centimeters due to the reduced optical attenuation. The structure of the human brain is so particularly complex, from the perspective of optical detection, the measurement light needs go through the skin, skull, cerebrospinal fluid (CSF), grey matter, and white matter, and then reverses the order reflected by the detector. The more photons from the Depth of Interest (DOI) in brain the detector capture, the better detection accuracy and stability can be obtained. In this study, the Equivalent Signal to Noise Ratio (ESNR) was defined as the proportion of the photons from the DOI to the total photons the detector evaluated the best Source and Detector (SD) separation. The Monte-Carlo (MC) simulation was used to establish a multi brain layer model to analyze the distribution of the ESNR along the radial direction for different DOIs and several basic brain optical and structure parameters. A map between the best detection SD separation, in which distance the ESNR was the highest, and the brain parameters was established for choosing the best detection point in the NIR brain imaging application. The results showed that the ESNR was very sensitivity to the SD separation. So choosing the best SD separation based on the ESNR is very significant for NIR brain imaging application. It provides an important reference and new thinking for the brain imaging in the near infrared.

The role of image registration in brain mapping

PubMed Central

Toga, A.W.; Thompson, P.M.

2008-01-01

Image registration is a key step in a great variety of biomedical imaging applications. It provides the ability to geometrically align one dataset with another, and is a prerequisite for all imaging applications that compare datasets across subjects, imaging modalities, or across time. Registration algorithms also enable the pooling and comparison of experimental findings across laboratories, the construction of population-based brain atlases, and the creation of systems to detect group patterns in structural and functional imaging data. We review the major types of registration approaches used in brain imaging today. We focus on their conceptual basis, the underlying mathematics, and their strengths and weaknesses in different contexts. We describe the major goals of registration, including data fusion, quantification of change, automated image segmentation and labeling, shape measurement, and pathology detection. We indicate that registration algorithms have great potential when used in conjunction with a digital brain atlas, which acts as a reference system in which brain images can be compared for statistical analysis. The resulting armory of registration approaches is fundamental to medical image analysis, and in a brain mapping context provides a means to elucidate clinical, demographic, or functional trends in the anatomy or physiology of the brain. PMID:19890483

A Learning-Based Wrapper Method to Correct Systematic Errors in Automatic Image Segmentation: Consistently Improved Performance in Hippocampus, Cortex and Brain Segmentation

PubMed Central

Wang, Hongzhi; Das, Sandhitsu R.; Suh, Jung Wook; Altinay, Murat; Pluta, John; Craige, Caryne; Avants, Brian; Yushkevich, Paul A.

2011-01-01

We propose a simple but generally applicable approach to improving the accuracy of automatic image segmentation algorithms relative to manual segmentations. The approach is based on the hypothesis that a large fraction of the errors produced by automatic segmentation are systematic, i.e., occur consistently from subject to subject, and serves as a wrapper method around a given host segmentation method. The wrapper method attempts to learn the intensity, spatial and contextual patterns associated with systematic segmentation errors produced by the host method on training data for which manual segmentations are available. The method then attempts to correct such errors in segmentations produced by the host method on new images. One practical use of the proposed wrapper method is to adapt existing segmentation tools, without explicit modification, to imaging data and segmentation protocols that are different from those on which the tools were trained and tuned. An open-source implementation of the proposed wrapper method is provided, and can be applied to a wide range of image segmentation problems. The wrapper method is evaluated with four host brain MRI segmentation methods: hippocampus segmentation using FreeSurfer (Fischl et al., 2002); hippocampus segmentation using multi-atlas label fusion (Artaechevarria et al., 2009); brain extraction using BET (Smith, 2002); and brain tissue segmentation using FAST (Zhang et al., 2001). The wrapper method generates 72%, 14%, 29% and 21% fewer erroneously segmented voxels than the respective host segmentation methods. In the hippocampus segmentation experiment with multi-atlas label fusion as the host method, the average Dice overlap between reference segmentations and segmentations produced by the wrapper method is 0.908 for normal controls and 0.893 for patients with mild cognitive impairment. Average Dice overlaps of 0.964, 0.905 and 0.951 are obtained for brain extraction, white matter segmentation and gray matter segmentation, respectively. PMID:21237273

Dye-enhanced multimodal confocal imaging as a novel approach to intraoperative diagnosis of brain tumors.

PubMed

Snuderl, Matija; Wirth, Dennis; Sheth, Sameer A; Bourne, Sarah K; Kwon, Churl-Su; Ancukiewicz, Marek; Curry, William T; Frosch, Matthew P; Yaroslavsky, Anna N

2013-01-01

Intraoperative diagnosis plays an important role in accurate sampling of brain tumors, limiting the number of biopsies required and improving the distinction between brain and tumor. The goal of this study was to evaluate dye-enhanced multimodal confocal imaging for discriminating gliomas from nonglial brain tumors and from normal brain tissue for diagnostic use. We investigated a total of 37 samples including glioma (13), meningioma (7), metastatic tumors (9) and normal brain removed for nontumoral indications (8). Tissue was stained in 0.05 mg/mL aqueous solution of methylene blue (MB) for 2-5 minutes and multimodal confocal images were acquired using a custom-built microscope. After imaging, tissue was formalin fixed and paraffin embedded for standard neuropathologic evaluation. Thirteen pathologists provided diagnoses based on the multimodal confocal images. The investigated tumor types exhibited distinctive and complimentary characteristics in both the reflectance and fluorescence responses. Images showed distinct morphological features similar to standard histology. Pathologists were able to distinguish gliomas from normal brain tissue and nonglial brain tumors, and to render diagnoses from the images in a manner comparable to haematoxylin and eosin (H&E) slides. These results confirm the feasibility of multimodal confocal imaging for intravital intraoperative diagnosis. © 2012 The Authors; Brain Pathology © 2012 International Society of Neuropathology.

Nanotomography of brain networks

NASA Astrophysics Data System (ADS)

Saiga, Rino; Mizutani, Ryuta; Takekoshi, Susumu; Osawa, Motoki; Arai, Makoto; Takeuchi, Akihisa; Uesugi, Kentaro; Terada, Yasuko; Suzuki, Yoshio; de Andrade, Vincent; de Carlo, Francesco

The first step to understanding how the brain functions is to analyze its 3D network. The brain network consists of neurons having micrometer to nanometer sized structures. Therefore, 3D analysis of brain tissue at the relevant resolution is essential for elucidating brain's functional mechanisms. Here, we report 3D structures of human and fly brain networks revealed with synchrotron radiation nanotomography, or nano-CT. Neurons were stained with high-Z elements to visualize their structures with X-rays. Nano-CT experiments were then performed at the 32-ID beamline of the Advanced Photon Source, Argonne National Laboratory and at the BL37XU and BL47XU beamlines of SPring-8. Reconstructed 3D images illustrated precise structures of human neurons, including dendritic spines responsible for synaptic connections. The network of the fly brain hemisphere was traced to build a skeletonized wire model. An article reviewing our study appeared in MIT Technology Review. Movies of the obtained structures can be found in our YouTube channel.

From Whole-Brain Data to Functional Circuit Models: The Zebrafish Optomotor Response.

PubMed

Naumann, Eva A; Fitzgerald, James E; Dunn, Timothy W; Rihel, Jason; Sompolinsky, Haim; Engert, Florian

2016-11-03

Detailed descriptions of brain-scale sensorimotor circuits underlying vertebrate behavior remain elusive. Recent advances in zebrafish neuroscience offer new opportunities to dissect such circuits via whole-brain imaging, behavioral analysis, functional perturbations, and network modeling. Here, we harness these tools to generate a brain-scale circuit model of the optomotor response, an orienting behavior evoked by visual motion. We show that such motion is processed by diverse neural response types distributed across multiple brain regions. To transform sensory input into action, these regions sequentially integrate eye- and direction-specific sensory streams, refine representations via interhemispheric inhibition, and demix locomotor instructions to independently drive turning and forward swimming. While experiments revealed many neural response types throughout the brain, modeling identified the dimensions of functional connectivity most critical for the behavior. We thus reveal how distributed neurons collaborate to generate behavior and illustrate a paradigm for distilling functional circuit models from whole-brain data. Copyright © 2016 Elsevier Inc. All rights reserved.

Neuroanatomical phenotyping of the mouse brain with three-dimensional autofluorescence imaging

PubMed Central

Wong, Michael D.; Dazai, Jun; Altaf, Maliha; Mark Henkelman, R.; Lerch, Jason P.; Nieman, Brian J.

2012-01-01

The structural organization of the brain is important for normal brain function and is critical to understand in order to evaluate changes that occur during disease processes. Three-dimensional (3D) imaging of the mouse brain is necessary to appreciate the spatial context of structures within the brain. In addition, the small scale of many brain structures necessitates resolution at the ∼10 μm scale. 3D optical imaging techniques, such as optical projection tomography (OPT), have the ability to image intact large specimens (1 cm3) with ∼5 μm resolution. In this work we assessed the potential of autofluorescence optical imaging methods, and specifically OPT, for phenotyping the mouse brain. We found that both specimen size and fixation methods affected the quality of the OPT image. Based on these findings we developed a specimen preparation method to improve the images. Using this method we assessed the potential of optical imaging for phenotyping. Phenotypic differences between wild-type male and female mice were quantified using computer-automated methods. We found that optical imaging of the endogenous autofluorescence in the mouse brain allows for 3D characterization of neuroanatomy and detailed analysis of brain phenotypes. This will be a powerful tool for understanding mouse models of disease and development and is a technology that fits easily within the workflow of biology and neuroscience labs. PMID:22718750

Advanced Pediatric Brain Imaging Research and Training Program

DTIC Science & Technology

2013-10-01

diffusion tensor imaging and perfusion ( arterial spin labeling) MRI data and to relate measures of global and regional brain microstructural organization...AD_________________ Award Number: W81XWH-11-2-0198 TITLE: Advanced Pediatric Brain Imaging...September 2013 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Advanced Pediatric Brain Imaging Research and Training Program 5b. GRANT NUMBER W81XWH

Expert system for neurosurgical treatment planning

NASA Astrophysics Data System (ADS)

Cheng, Andrew Y. S.; Chung, Sally S. Y.; Kwok, John C. K.

1996-04-01

A specially designed expert system is in development for neurosurgical treatment planning. The knowledge base contains knowledge and experiences on neurosurgical treatment planning from neurosurgeon consultants, who also determine the risks of different regions in human brains. When completed, the system can simulate the decision making process of neurosurgeons to determine the safest probing path for operation. The Computed Tomography (CT) or Magnetic Resonance Imaging (MRI) scan images for each patient are grabbed as the input. The system also allows neurosurgeons to include for any particular patient the additional information, such as how the tumor affects its neighboring functional regions, which is also important for calculating the safest probing path. It can then consider all the relevant information and find the most suitable probing path on the patient's brain. A 3D brain model is constructed for each set of the CT/MRI scan images and is displayed real-time together with the possible probing paths found. The precise risk value of each path is shown as a number between 0 and 1, together with its possible damages in text. Neurosurgeons can view more than one possible path simultaneously, and make the final decision on the selected path for operation.

Near-Infrared Neuroimaging with NinPy

PubMed Central

Strangman, Gary E.; Zhang, Quan; Zeffiro, Thomas

2009-01-01

There has been substantial recent growth in the use of non-invasive optical brain imaging in studies of human brain function in health and disease. Near-infrared neuroimaging (NIN) is one of the most promising of these techniques and, although NIN hardware continues to evolve at a rapid pace, software tools supporting optical data acquisition, image processing, statistical modeling, and visualization remain less refined. Python, a modular and computationally efficient development language, can support functional neuroimaging studies of diverse design and implementation. In particular, Python's easily readable syntax and modular architecture allow swift prototyping followed by efficient transition to stable production systems. As an introduction to our ongoing efforts to develop Python software tools for structural and functional neuroimaging, we discuss: (i) the role of non-invasive diffuse optical imaging in measuring brain function, (ii) the key computational requirements to support NIN experiments, (iii) our collection of software tools to support NIN, called NinPy, and (iv) future extensions of these tools that will allow integration of optical with other structural and functional neuroimaging data sources. Source code for the software discussed here will be made available at www.nmr.mgh.harvard.edu/Neural_SystemsGroup/software.html. PMID:19543449

MRI Segmentation of the Human Brain: Challenges, Methods, and Applications

PubMed Central

Despotović, Ivana

2015-01-01

Image segmentation is one of the most important tasks in medical image analysis and is often the first and the most critical step in many clinical applications. In brain MRI analysis, image segmentation is commonly used for measuring and visualizing the brain's anatomical structures, for analyzing brain changes, for delineating pathological regions, and for surgical planning and image-guided interventions. In the last few decades, various segmentation techniques of different accuracy and degree of complexity have been developed and reported in the literature. In this paper we review the most popular methods commonly used for brain MRI segmentation. We highlight differences between them and discuss their capabilities, advantages, and limitations. To address the complexity and challenges of the brain MRI segmentation problem, we first introduce the basic concepts of image segmentation. Then, we explain different MRI preprocessing steps including image registration, bias field correction, and removal of nonbrain tissue. Finally, after reviewing different brain MRI segmentation methods, we discuss the validation problem in brain MRI segmentation. PMID:25945121

Psychogenic amnesia--a malady of the constricted self.

PubMed

Staniloiu, Angelica; Markowitsch, Hans J; Brand, Matthias

2010-09-01

Autobiographical-episodic memory is the conjunction of subjective time, autonoetic consciousness and the experiencing self. Understanding the neural correlates of autobiographical-episodic memory might therefore be essential for shedding light on the neurobiology underlying the experience of being an autonoetic self. In this contribution we illustrate the intimate relationship between autobiographical-episodic memory and self by reviewing the clinical and neuropsychological features and brain functional imaging correlates of psychogenic amnesia - a condition that is usually characterized by severely impaired retrograde memory functioning, in absence of structural brain damage as detected by standard imaging. We demonstrate that in this disorder the autobiographical-episodic memory deficits do not exist in isolation, but occur with impairments of the autonoetic self-consciousness, emotional processing, and theory of mind or executive functions. Furthermore functional and metabolic brain alterations involving regions that are agreed upon to exert crucial roles in memory processes were frequently found to accompany the psychogenic memory "loss". Copyright © 2010 Elsevier Inc. All rights reserved.

Design of a serotonin 4 receptor radiotracer with decreased lipophilicity for single photon emission computed tomography.

PubMed

Fresneau, Nathalie; Dumas, Noé; Tournier, Benjamin B; Fossey, Christine; Ballandonne, Céline; Lesnard, Aurélien; Millet, Philippe; Charnay, Yves; Cailly, Thomas; Bouillon, Jean-Philippe; Fabis, Frédéric

2015-04-13

With the aim to develop a suitable radiotracer for the brain imaging of the serotonin 4 receptor subtype (5-HT4R) using single photon emission computed tomography (SPECT), we synthesized and evaluated a library of di- and triazaphenanthridines with lipophilicity values which were in the range expected to favour brain penetration, and which demonstrated specific binding to the target of interest. Adding additional nitrogen atoms to previously described phenanthridine ligands exhibiting a high unspecific binding, we were able to design a radioiodinated compound [(125)I]14. This compound exhibited a binding affinity value of 0.094 nM toward human 5-HT4R and a high selectivity over other serotonin receptor subtypes (5-HTR). In vivo SPECT imaging studies and competition experiments demonstrated that the decreased lipophilicity (in comparison with our previously reported compounds 4 and 5) allowed a more specific labelling of the 5-HT4R brain-containing regions. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Greater brain response to emotional expressions of their own children in mothers of preterm infants: an fMRI study.

PubMed

Montirosso, R; Arrigoni, F; Casini, E; Nordio, A; De Carli, P; Di Salle, F; Moriconi, S; Re, M; Reni, G; Borgatti, R

2017-06-01

The birth of a preterm infant and Neonatal Intensive Care Unit hospitalization constitute a potentially traumatic experience for mothers. Although behavioral studies investigated the parenting stress in preterm mothers, no study focused on the underlying neural mechanisms. We examined the effect of preterm births in mothers, by comparing brain activation in mothers of preterm and full-term infants. We used functional magnetic resonance imaging to measure the cerebral response of 10 first-time mothers of preterm infants (gestational age <32 weeks and/or birth weight <1500) and 11 mothers of full-term infants, viewing happy-, neutral- and distress-face images of their own infant, along with a matched unknown infant. While viewing own infant's face preterm mothers showed increased activation in emotional processing area (i.e., inferior frontal gyrus) and social cognition (i.e., supramarginal gyrus) and affiliative behavior (i.e., insula). Differential brain activation patterns in mothers appears to be a function of the atypical parenthood transition related to prematurity.

"Facilitated" amino acid transport is upregulated in brain tumors.

PubMed

Miyagawa, T; Oku, T; Uehara, H; Desai, R; Beattie, B; Tjuvajev, J; Blasberg, R

1998-05-01

The goal of this study was to determine the magnitude of "facilitated" amino acid transport across tumor and brain capillaries and to evaluate whether amino acid transporter expression is "upregulated" in tumor vessels compared to capillaries in contralateral brain tissue. Aminocyclopentane carboxylic acid (ACPC), a non-metabolized [14C]-labeled amino acid, and a reference molecule for passive vascular permeability, [67Ga]-gallium-diethylenetriaminepentaacetic acid (Ga-DTPA), were used in these studies. Two experimental rat gliomas were studied (C6 and RG2). Brain tissue was rapidly processed for double label quantitative autoradiography 10 minutes after intravenous injection of ACPC and Ga-DTPA. Parametric images of blood-to-brain transport (K1ACPC and K1Ga-DTPA, microL/min/g) produced from the autoradiograms and the histology were obtained from the same tissue section. These three images were registered in an image array processor; regions of interest in tumor and contralateral brain were defined on morphologic criteria (histology) and were transferred to the autoradiographic images to obtain mean values. The facilitated component of ACPC transport (deltaK1ACPC) was calculated from the K1ACPC and K1Ga-DTPA data, and paired comparisons between tumor and contralateral brain were performed. ACPC flux, K1ACPC, across normal brain capillaries (22.6 +/- 8.1 microL/g/min) was >200-fold greater than that of Ga-DTPA (0.09 +/- 0.04 microL/g/min), and this difference was largely (approximately 90%) due to facilitated ACPC transport. Substantially higher K1ACPC values compared to corresponding K1DTPA values were also measured in C6 and RG2 gliomas. The deltaK1ACPC values for C6 glioma were more than twice that of contralateral brain cortex. K1ACPC and deltaK1ACPC values for RG2 gliomas was not significantly higher than that of contralateral cortex, although a approximately 2-fold difference in facilitated transport is obtained after normalization for differences in capillary surface area between RG2 tumors and contralateral cortex. K1ACPC, deltaK1ACPC, and K DTPA were directly related to tumor cell density, were higher in regions of "impending" necrosis, and the tumor/contralateral brain ACPC radio-activity ratios (0 to 10 minutes) were very similar to that obtained with 0 to 60 minutes experiments. These results indicate that facilitated transport of ACPC is upregulated across C6 and RG2 glioma capillaries, and that tumors can induce upregulation of amino acid transporter expression in their supporting vasculature. They also suggest that early imaging (e.g., 0 to 20 minutes) with radiolabeled amino acids in a clinical setting may be optimal for defining brain tumors.

An approach to optimize sample preparation for MALDI imaging MS of FFPE sections using fractional factorial design of experiments.

PubMed

Oetjen, Janina; Lachmund, Delf; Palmer, Andrew; Alexandrov, Theodore; Becker, Michael; Boskamp, Tobias; Maass, Peter

2016-09-01

A standardized workflow for matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI imaging MS) is a prerequisite for the routine use of this promising technology in clinical applications. We present an approach to develop standard operating procedures for MALDI imaging MS sample preparation of formalin-fixed and paraffin-embedded (FFPE) tissue sections based on a novel quantitative measure of dataset quality. To cover many parts of the complex workflow and simultaneously test several parameters, experiments were planned according to a fractional factorial design of experiments (DoE). The effect of ten different experiment parameters was investigated in two distinct DoE sets, each consisting of eight experiments. FFPE rat brain sections were used as standard material because of low biological variance. The mean peak intensity and a recently proposed spatial complexity measure were calculated for a list of 26 predefined peptides obtained by in silico digestion of five different proteins and served as quality criteria. A five-way analysis of variance (ANOVA) was applied on the final scores to retrieve a ranking of experiment parameters with increasing impact on data variance. Graphical abstract MALDI imaging experiments were planned according to fractional factorial design of experiments for the parameters under study. Selected peptide images were evaluated by the chosen quality metric (structure and intensity for a given peak list), and the calculated values were used as an input for the ANOVA. The parameters with the highest impact on the quality were deduced and SOPs recommended.

Non-caloric sweetener provides magnetic resonance imaging contrast for cancer detection.

PubMed

Bagga, Puneet; Haris, Mohammad; D'Aquilla, Kevin; Wilson, Neil E; Marincola, Francesco M; Schnall, Mitchell D; Hariharan, Hari; Reddy, Ravinder

2017-05-30

Image contrast enhanced by exogenous contrast agents plays a crucial role in the early detection, characterization, and determination of the precise location of cancers. Here, we investigate the feasibility of using a non-nutritive sweetener, sucralose (commercial name, Splenda), as magnetic resonance imaging (MRI) contrast agent for cancer studies. High-resolution nuclear-magnetic-resonance spectroscopy and MR studies on sucralose solution phantom were performed to detect the chemical exchange saturation transfer (CEST) property of sucralose hydroxyl protons with bulk water (sucCEST). For the animal experiments, female Fisher rats (F344/NCR) were used to generate 9L-gliosarcoma model. MRI with CEST experiments were performed on anesthetized rats at 9.4 T MR scanner. Following the baseline CEST scans, sucralose solution was intravenously administered in control and tumor bearing rats. CEST acquisitions were continued during and following the administration of sucralose. Following the sucCEST, Gadolinium-diethylenetriamine pentaacetic acid was injected to perform Gd-enhanced imaging for visualizing the tumor. The sucCEST contrast in vitro was found to correlate positively with the sucralose concentration and negatively with the pH, indicating the potential of this technique in cancer imaging. In a control animal, the CEST contrast from the brain was found to be unaffected following the administration of sucralose, demonstrating its blood-brain barrier impermeability. In a 9L glioma model, enhanced localized sucCEST contrast in the tumor region was detected while the unaffected brain region showed unaltered CEST effect implying the specificity of sucralose toward the tumorous tissue. The CEST asymmetry plots acquired from the tumor region before and after the sucralose infusion showed elevation of asymmetry at 1 ppm, pointing towards the role of sucralose in increased contrast. We show the feasibility of using sucralose and sucCEST in study of preclinical models of cancer. This study paves the way for the potential development of sucralose and other sucrose derivatives as contrast agents for clinical MRI applications.

Comparative Approach of MRI-Based Brain Tumor Segmentation and Classification Using Genetic Algorithm.

PubMed

Bahadure, Nilesh Bhaskarrao; Ray, Arun Kumar; Thethi, Har Pal

2018-01-17

The detection of a brain tumor and its classification from modern imaging modalities is a primary concern, but a time-consuming and tedious work was performed by radiologists or clinical supervisors. The accuracy of detection and classification of tumor stages performed by radiologists is depended on their experience only, so the computer-aided technology is very important to aid with the diagnosis accuracy. In this study, to improve the performance of tumor detection, we investigated comparative approach of different segmentation techniques and selected the best one by comparing their segmentation score. Further, to improve the classification accuracy, the genetic algorithm is employed for the automatic classification of tumor stage. The decision of classification stage is supported by extracting relevant features and area calculation. The experimental results of proposed technique are evaluated and validated for performance and quality analysis on magnetic resonance brain images, based on segmentation score, accuracy, sensitivity, specificity, and dice similarity index coefficient. The experimental results achieved 92.03% accuracy, 91.42% specificity, 92.36% sensitivity, and an average segmentation score between 0.82 and 0.93 demonstrating the effectiveness of the proposed technique for identifying normal and abnormal tissues from brain MR images. The experimental results also obtained an average of 93.79% dice similarity index coefficient, which indicates better overlap between the automated extracted tumor regions with manually extracted tumor region by radiologists.

3D spatially encoded and accelerated TE-averaged echo planar spectroscopic imaging in healthy human brain.

PubMed

Iqbal, Zohaib; Wilson, Neil E; Thomas, M Albert

2016-03-01

Several different pathologies, including many neurodegenerative disorders, affect the energy metabolism of the brain. Glutamate, a neurotransmitter in the brain, can be used as a biomarker to monitor these metabolic processes. One method that is capable of quantifying glutamate concentration reliably in several regions of the brain is TE-averaged (1) H spectroscopic imaging. However, this type of method requires the acquisition of multiple TE lines, resulting in long scan durations. The goal of this experiment was to use non-uniform sampling, compressed sensing reconstruction and an echo planar readout gradient to reduce the scan time by a factor of eight to acquire TE-averaged spectra in three spatial dimensions. Simulation of glutamate and glutamine showed that the 2.2-2.4 ppm spectral region contained 95% glutamate signal using the TE-averaged method. Peak integration of this spectral range and home-developed, prior-knowledge-based fitting were used for quantitation. Gray matter brain phantom measurements were acquired on a Siemens 3 T Trio scanner. Non-uniform sampling was applied retrospectively to these phantom measurements and quantitative results of glutamate with respect to creatine 3.0 (Glu/Cr) ratios showed a coefficient of variance of 16% for peak integration and 9% for peak fitting using eight-fold acceleration. In vivo scans of the human brain were acquired as well and five different brain regions were quantified using the prior-knowledge-based algorithm. Glu/Cr ratios from these regions agreed with previously reported results in the literature. The method described here, called accelerated TE-averaged echo planar spectroscopic imaging (TEA-EPSI), is a significant methodological advancement and may be a useful tool for categorizing glutamate changes in pathologies where affected brain regions are not known a priori. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Brain oxygen saturation assessment in neonates using T2-prepared blood imaging of oxygen saturation and near-infrared spectroscopy.

PubMed

Alderliesten, Thomas; De Vis, Jill B; Lemmers, Petra Ma; Hendrikse, Jeroen; Groenendaal, Floris; van Bel, Frank; Benders, Manon Jnl; Petersen, Esben T

2017-03-01

Although near-infrared spectroscopy is increasingly being used to monitor cerebral oxygenation in neonates, it has a limited penetration depth. The T 2 -prepared Blood Imaging of Oxygen Saturation (T 2 -BIOS) magnetic resonance sequence provides an oxygen saturation estimate on a voxel-by-voxel basis, without needing a respiratory calibration experiment. In 15 neonates, oxygen saturation measured by T 2 -prepared blood imaging of oxygen saturation and near-infrared spectroscopy were compared. In addition, these measures were compared to cerebral blood flow and venous oxygen saturation in the sagittal sinus. A strong linear relation was found between the oxygen saturation measured by magnetic resonance imaging and the oxygen saturation measured by near-infrared spectroscopy ( R 2  = 0.64, p < 0.001). Strong linear correlations were found between near-infrared spectroscopy oxygen saturation, and magnetic resonance imaging measures of frontal cerebral blood flow, whole brain cerebral blood flow and venous oxygen saturation in the sagittal sinus ( R 2  = 0.71, 0.50, 0.65; p < 0.01). The oxygen saturation obtained by T 2 -prepared blood imaging of oxygen saturation correlated with venous oxygen saturation in the sagittal sinus ( R 2  = 0.49, p = 0.023), but no significant correlations could be demonstrated with frontal and whole brain cerebral blood flow. These results suggest that measuring oxygen saturation by T 2 -prepared blood imaging of oxygen saturation is feasible, even in neonates. Strong correlations between the various methods work as a cross validation for near-infrared spectroscopy and T 2 -prepared blood imaging of oxygen saturation, confirming the validity of using of these techniques for determining cerebral oxygenation.

Magnetic resonance imaging of the brain in epileptic adult patients: experience in Ramathibodi Hospital.

PubMed

Solosrungruang, Anusorn; Laothamatas, Jiraporn; Chinwarun, Yotin

2007-04-01

The purpose of the present study was to classify the imaging structural abnormalities of epileptic adult patients referred for magnetic resonance imaging (MR imaging) of the brain at Ramathibodi Hospital and to correlate with the clinical data and EEG. MR imaging of 91 adult epileptic patients (age ranging from 15-85 years old with an average of 36.90 years old) were retrospectively reviewed and classified into eight groups according to etiologies. Then clinical data and EEG correlations were analyzed using the Kappa analysis. All of the MR imaging of the brain were performed at Ramathibodi Hospital from January 2001 to December 2002. Secondary generalized tonic clonic seizure was the most common clinical presenting seizure type. Extra temporal lobe epilepsy was the most common clinical diagnosis. Of the thirty-three patients who underwent EEG before performing MR imaging, 17 had normal EEG From MR imaging, temporal lobe lesion was the main affected location and mesial temporal sclerosis (MTS) was the most common cause of the epilepsy in patients. For age group classification, young adult (15-34 years old) and adult (35-64 years old) age groups, MTS was the most common etiology of epilepsy with cortical dysplasia being the second most common cause for the first group and vascular disease for the latter group. For the older age group (> 64 years old), vascular disease and idiopathic cause were equally common etiologies. MRI, EEG findings, and clinical data were all concordant with statistical significance. MRI is the non-invasive modality of choice for evaluation of the epileptic patients. The result is concordant with the clinical and EEG findings. It can detect and localize the structural abnormality accurately and is useful in the treatment planning.

Cone-beam CT of traumatic brain injury using statistical reconstruction with a post-artifact-correction noise model

NASA Astrophysics Data System (ADS)

Dang, H.; Stayman, J. W.; Sisniega, A.; Xu, J.; Zbijewski, W.; Yorkston, J.; Aygun, N.; Koliatsos, V.; Siewerdsen, J. H.

2015-03-01

Traumatic brain injury (TBI) is a major cause of death and disability. The current front-line imaging modality for TBI detection is CT, which reliably detects intracranial hemorrhage (fresh blood contrast 30-50 HU, size down to 1 mm) in non-contrast-enhanced exams. Compared to CT, flat-panel detector (FPD) cone-beam CT (CBCT) systems offer lower cost, greater portability, and smaller footprint suitable for point-of-care deployment. We are developing FPD-CBCT to facilitate TBI detection at the point-of-care such as in emergent, ambulance, sports, and military applications. However, current FPD-CBCT systems generally face challenges in low-contrast, soft-tissue imaging. Model-based reconstruction can improve image quality in soft-tissue imaging compared to conventional filtered back-projection (FBP) by leveraging high-fidelity forward model and sophisticated regularization. In FPD-CBCT TBI imaging, measurement noise characteristics undergo substantial change following artifact correction, resulting in non-negligible noise amplification. In this work, we extend the penalized weighted least-squares (PWLS) image reconstruction to include the two dominant artifact corrections (scatter and beam hardening) in FPD-CBCT TBI imaging by correctly modeling the variance change following each correction. Experiments were performed on a CBCT test-bench using an anthropomorphic phantom emulating intra-parenchymal hemorrhage in acute TBI, and the proposed method demonstrated an improvement in blood-brain contrast-to-noise ratio (CNR = 14.2) compared to FBP (CNR = 9.6) and PWLS using conventional weights (CNR = 11.6) at fixed spatial resolution (1 mm edge-spread width at the target contrast). The results support the hypothesis that FPD-CBCT can fulfill the image quality requirements for reliable TBI detection, using high-fidelity artifact correction and statistical reconstruction with accurate post-artifact-correction noise models.

Dedicated mobile volumetric cone-beam computed tomography for human brain imaging: A phantom study.

PubMed

Ryu, Jong-Hyun; Kim, Tae-Hoon; Jeong, Chang-Won; Jun, Hong-Young; Heo, Dong-Woon; Lee, Jinseok; Kim, Kyong-Woo; Yoon, Kwon-Ha

2015-01-01

Mobile computed tomography (CT) with a cone-beam source is increasingly used in the clinical field. Mobile cone-beam CT (CBCT) has great merits; however, its clinical utility for brain imaging has been limited due to problems including scan time and image quality. The aim of this study was to develop a dedicated mobile volumetric CBCT for obtaining brain images, and to optimize the imaging protocol using a brain phantom. The mobile volumetric CBCT system was evaluated with regards to scan time and image quality, measured as signal-to-noise-ratio (SNR), contrast-to-noise-ratio (CNR), spatial resolution (10% MTF), and effective dose. Brain images were obtained using a CT phantom. The CT scan took 5.14 s at 360 projection views. SNR and CNR were 5.67 and 14.5 at 120 kV/10 mA. SNR and CNR values showed slight improvement as the x-ray voltage and current increased (p < 0.001). Effective dose and 10% MTF were 0.92 mSv and 360 μ m at 120 kV/10 mA. Various intracranial structures were clearly visible in the brain phantom images. Using this CBCT under optimal imaging acquisition conditions, it is possible to obtain human brain images with low radiation dose, reproducible image quality, and fast scan time.

Brain-Computer Interface Based on Generation of Visual Images

PubMed Central

Bobrov, Pavel; Frolov, Alexander; Cantor, Charles; Fedulova, Irina; Bakhnyan, Mikhail; Zhavoronkov, Alexander

2011-01-01

This paper examines the task of recognizing EEG patterns that correspond to performing three mental tasks: relaxation and imagining of two types of pictures: faces and houses. The experiments were performed using two EEG headsets: BrainProducts ActiCap and Emotiv EPOC. The Emotiv headset becomes widely used in consumer BCI application allowing for conducting large-scale EEG experiments in the future. Since classification accuracy significantly exceeded the level of random classification during the first three days of the experiment with EPOC headset, a control experiment was performed on the fourth day using ActiCap. The control experiment has shown that utilization of high-quality research equipment can enhance classification accuracy (up to 68% in some subjects) and that the accuracy is independent of the presence of EEG artifacts related to blinking and eye movement. This study also shows that computationally-inexpensive Bayesian classifier based on covariance matrix analysis yields similar classification accuracy in this problem as a more sophisticated Multi-class Common Spatial Patterns (MCSP) classifier. PMID:21695206

In vivo metabolic labeling of sialoglycans in the mouse brain by using a liposome-assisted bioorthogonal reporter strategy

PubMed Central

Xie, Ran; Dong, Lu; Du, Yifei; Zhu, Yuntao; Hua, Rui; Zhang, Chen; Chen, Xing

2016-01-01

Mammalian brains are highly enriched with sialoglycans, which have been implicated in brain development and disease progression. However, in vivo labeling and visualization of sialoglycans in the mouse brain remain a challenge because of the blood−brain barrier. Here we introduce a liposome-assisted bioorthogonal reporter (LABOR) strategy for shuttling 9-azido sialic acid (9AzSia), a sialic acid reporter, into the brain to metabolically label sialoglycoconjugates, including sialylated glycoproteins and glycolipids. Subsequent bioorthogonal conjugation of the incorporated 9AzSia with fluorescent probes via click chemistry enabled fluorescence imaging of brain sialoglycans in living animals and in brain sections. Newly synthesized sialoglycans were found to widely distribute on neuronal cell surfaces, in particular at synaptic sites. Furthermore, large-scale proteomic profiling identified 140 brain sialylated glycoproteins, including a wealth of synapse-associated proteins. Finally, by performing a pulse−chase experiment, we showed that dynamic sialylation is spatially regulated, and that turnover of sialoglycans in the hippocampus is significantly slower than that in other brain regions. The LABOR strategy provides a means to directly visualize and monitor the sialoglycan biosynthesis in the mouse brain and will facilitate elucidating the functional role of brain sialylation. PMID:27125855

A brain phantom for motion-corrected PROPELLER showing image contrast and construction similar to those of in vivo MRI.

PubMed

Saotome, Kousaku; Matsushita, Akira; Matsumoto, Koji; Kato, Yoshiaki; Nakai, Kei; Murata, Koichi; Yamamoto, Tetsuya; Sankai, Yoshiyuki; Matsumura, Akira

2017-02-01

A fast spin-echo sequence based on the Periodically Rotated Overlapping Parallel Lines with Enhanced Reconstruction (PROPELLER) technique is a magnetic resonance (MR) imaging data acquisition and reconstruction method for correcting motion during scans. Previous studies attempted to verify the in vivo capabilities of motion-corrected PROPELLER in real clinical situations. However, such experiments are limited by repeated, stray head motion by research participants during the prescribed and precise head motion protocol of a PROPELLER acquisition. Therefore, our purpose was to develop a brain phantom set for motion-corrected PROPELLER. The profile curves of the signal intensities on the in vivo T 2 -weighted image (T 2 WI) and 3-D rapid prototyping technology were used to produce the phantom. In addition, we used a homemade driver system to achieve in-plane motion at the intended timing. We calculated the Pearson's correlation coefficient (R 2 ) between the signal intensities of the in vivo T 2 WI and the phantom T 2 WI and clarified the rotation precision of the driver system. In addition, we used the phantom set to perform initial experiments to show the rotational angle and frequency dependences of PROPELLER. The in vivo and phantom T 2 WIs were visually congruent, with a significant correlation (R 2 ) of 0.955 (p<.001). The rotational precision of the driver system was within 1 degree of tolerance. The experiment on the rotational angle dependency showed image discrepancies between the rotational angles. The experiment on the rotational frequency dependency showed that the reconstructed images became increasingly blurred by the corruption of the blades as the number of motions increased. In this study, we developed a phantom that showed image contrasts and construction similar to the in vivo T 2 WI. In addition, our homemade driver system achieved precise in-plane motion at the intended timing. Our proposed phantom set could perform systematic experiments with a real clinical MR image, which to date has not been possible in in vivo studies. Further investigation should focus on the improvement of the motion-correction algorithm in PROPELLER using our phantom set for what would traditionally be considered problematic patients (children, emergency patients, elderly, those with dementia, and so on). Copyright © 2016 Elsevier Inc. All rights reserved.

The iconographic brain. A critical philosophical inquiry into (the resistance of) the image

PubMed Central

De Vos, Jan

2014-01-01

The brain image plays a central role in contemporary image culture and, in turn, (co)constructs contemporary forms of subjectivity. The central aim of this paper is to probe the unmistakably potent interpellative power of brain images by delving into the power of imaging and the power of the image itself. This is not without relevance for the neurosciences, inasmuch as these do not take place in a vacuum; hence the importance of inquiring into the status of the image within scientific culture and science itself. I will mount a critical philosophical investigation of the brain qua image, focusing on the issue of mapping the mental onto the brain and how, in turn, the brain image plays a pivotal role in processes of subjectivation. Hereto, I draw upon Science & Technology Studies, juxtaposed with culture and ideology critique and theories of image culture. The first section sets out from Althusser's concept of interpellation, linking ideology to subjectivity. Doing so allows to spell out the central question of the paper: what could serve as the basis for a critical approach, or, where can a locus of resistance be found? In the second section, drawing predominantly on Baudrillard, I delve into the dimension of virtuality as this is opened up by brain image culture. This leads to the question of whether the digital brain must be opposed to old analog psychology: is it the psyche which resists? This issue is taken up in the third section which, ultimately, concludes that the psychological is not the requisite locus of resistance. The fourth section proceeds to delineate how the brain image is constructed from what I call the data-gaze (the claim that brain data are always already visual). In the final section, I discuss how an engagement with theories of iconology affords a critical understanding of the interpellative force of the brain image, which culminates in the somewhat unexpected claim that the sought after resistance lies in the very status of the image itself. PMID:24860480

The Constancy of Colored After-Images

PubMed Central

Zeki, Semir; Cheadle, Samuel; Pepper, Joshua; Mylonas, Dimitris

2017-01-01

We undertook psychophysical experiments to determine whether the color of the after-image produced by viewing a colored patch which is part of a complex multi-colored scene depends on the wavelength-energy composition of the light reflected from that patch. Our results show that it does not. The after-image, just like the color itself, depends on the ratio of light of different wavebands reflected from it and its surrounds. Hence, traditional accounts of after-images as being the result of retinal adaptation or the perceptual result of physiological opponency, are inadequate. We propose instead that the color of after-images is generated after colors themselves are generated in the visual brain. PMID:28539878

Brain activity in near-death experiencers during a meditative state.

PubMed

Beauregard, Mario; Courtemanche, Jérôme; Paquette, Vincent

2009-09-01

To measure brain activity in near-death experiencers during a meditative state. In two separate experiments, brain activity was measured with functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) during a Meditation condition and a Control condition. In the Meditation condition, participants were asked to mentally visualize and emotionally connect with the "being of light" allegedly encountered during their "near-death experience". In the Control condition, participants were instructed to mentally visualize the light emitted by a lamp. In the fMRI experiment, significant loci of activation were found during the Meditation condition (compared to the Control condition) in the right brainstem, right lateral orbitofrontal cortex, right medial prefrontal cortex, right superior parietal lobule, left superior occipital gyrus, left anterior temporal pole, left inferior temporal gyrus, left anterior insula, left parahippocampal gyrus and left substantia nigra. In the EEG experiment, electrode sites showed greater theta power in the Meditation condition relative to the Control condition at FP1, F7, F3, T5, P3, O1, FP2, F4, F8, P4, Fz, Cz and Pz. In addition, higher alpha power was detected at FP1, F7, T3 and FP2, whereas higher gamma power was found at FP2, F7, T4 and T5. The results indicate that the meditative state was associated with marked hemodynamic and neuroelectric changes in brain regions known to be involved either in positive emotions, visual mental imagery, attention or spiritual experiences.

A method of semi-quantifying β-AP in brain PET-CT 11C-PiB images.

PubMed

Jiang, Jiehui; Lin, Xiaoman; Wen, Junlin; Huang, Zhemin; Yan, Zhuangzhi

2014-01-01

Alzheimer's disease (AD) is a common health problem for elderly populations. Positron emission tomography-computed tomography (PET-CT)11C-PiB for beta-P (amyloid-β peptide, β-AP) imaging is an advanced method to diagnose AD in early stage. However, in practice radiologists lack a standardized value to semi-quantify β-AP. This paper proposes such a standardized value: SVβ-AP. This standardized value measures the mean ratio between the dimension of β-AP areas in PET and CT images. A computer aided diagnosis approach is also proposed to achieve SVβ-AP. A simulation experiment was carried out to pre-test the technical feasibility of the CAD approach and SVβ-AP. The experiment results showed that it is technically feasible.

Electrophysiological Source Imaging: A Noninvasive Window to Brain Dynamics.

PubMed

He, Bin; Sohrabpour, Abbas; Brown, Emery; Liu, Zhongming

2018-06-04

Brain activity and connectivity are distributed in the three-dimensional space and evolve in time. It is important to image brain dynamics with high spatial and temporal resolution. Electroencephalography (EEG) and magnetoencephalography (MEG) are noninvasive measurements associated with complex neural activations and interactions that encode brain functions. Electrophysiological source imaging estimates the underlying brain electrical sources from EEG and MEG measurements. It offers increasingly improved spatial resolution and intrinsically high temporal resolution for imaging large-scale brain activity and connectivity on a wide range of timescales. Integration of electrophysiological source imaging and functional magnetic resonance imaging could further enhance spatiotemporal resolution and specificity to an extent that is not attainable with either technique alone. We review methodological developments in electrophysiological source imaging over the past three decades and envision its future advancement into a powerful functional neuroimaging technology for basic and clinical neuroscience applications.

Words in the bilingual brain: an fNIRS brain imaging investigation of lexical processing in sign-speech bimodal bilinguals

PubMed Central

Kovelman, Ioulia; Shalinsky, Mark H.; Berens, Melody S.; Petitto, Laura-Ann

2014-01-01

Early bilingual exposure, especially exposure to two languages in different modalities such as speech and sign, can profoundly affect an individual's language, culture, and cognition. Here we explore the hypothesis that bimodal dual language exposure can also affect the brain's organization for language. These changes occur across brain regions universally important for language and parietal regions especially critical for sign language (Newman et al., 2002). We investigated three groups of participants (N = 29) that completed a word repetition task in American Sign Language (ASL) during fNIRS brain imaging. Those groups were (1) hearing ASL-English bimodal bilinguals (n = 5), (2) deaf ASL signers (n = 7), and (3) English monolinguals naïve to sign language (n = 17). The key finding of the present study is that bimodal bilinguals showed reduced activation in left parietal regions relative to deaf ASL signers when asked to use only ASL. In contrast, this group of bimodal signers showed greater activation in left temporo-parietal regions relative to English monolinguals when asked to switch between their two languages (Kovelman et al., 2009). Converging evidence now suggest that bimodal bilingual experience changes the brain bases of language, including the left temporo-parietal regions known to be critical for sign language processing (Emmorey et al., 2007). The results provide insight into the resilience and constraints of neural plasticity for language and bilingualism. PMID:25191247

Brain basis of early parent–infant interactions: psychology, physiology, and in vivo functional neuroimaging studies

PubMed Central

Swain, James E.; Lorberbaum, Jeffrey P.; Kose, Samet; Strathearn, Lane

2015-01-01

Parenting behavior critically shapes human infants’ current and future behavior. The parent–infant relationship provides infants with their first social experiences, forming templates of what they can expect from others and how to best meet others’ expectations. In this review, we focus on the neurobiology of parenting behavior, including our own functional magnetic resonance imaging (fMRI) brain imaging experiments of parents. We begin with a discussion of background, perspectives and caveats for considering the neurobiology of parent–infant relationships. Then, we discuss aspects of the psychology of parenting that are significantly motivating some of the more basic neuroscience research. Following that, we discuss some of the neurohormones that are important for the regulation of social bonding, and the dysregulation of parenting with cocaine abuse. Then, we review the brain circuitry underlying parenting, proceeding from relevant rodent and nonhuman primate research to human work. Finally, we focus on a study-by-study review of functional neuroimaging studies in humans. Taken together, this research suggests that networks of highly conserved hypothalamic–midbrain–limbic–paralimbic–cortical circuits act in concert to support aspects of parent response to infants, including the emotion, attention, motivation, empathy, decision-making and other thinking that are required to navigate the complexities of parenting. Specifically, infant stimuli activate basal forebrain regions, which regulate brain circuits that handle specific nurturing and caregiving responses and activate the brain’s more general circuitry for handling emotions, motivation, attention, and empathy – all of which are crucial for effective parenting. We argue that an integrated understanding of the brain basis of parenting has profound implications for mental health. PMID:17355399

Rapid Parametric Mapping of the Longitudinal Relaxation Time T1 Using Two-Dimensional Variable Flip Angle Magnetic Resonance Imaging at 1.5 Tesla, 3 Tesla, and 7 Tesla

PubMed Central

Dieringer, Matthias A.; Deimling, Michael; Santoro, Davide; Wuerfel, Jens; Madai, Vince I.; Sobesky, Jan; von Knobelsdorff-Brenkenhoff, Florian; Schulz-Menger, Jeanette; Niendorf, Thoralf

2014-01-01

Introduction Visual but subjective reading of longitudinal relaxation time (T1) weighted magnetic resonance images is commonly used for the detection of brain pathologies. For this non-quantitative measure, diagnostic quality depends on hardware configuration, imaging parameters, radio frequency transmission field (B1+) uniformity, as well as observer experience. Parametric quantification of the tissue T1 relaxation parameter offsets the propensity for these effects, but is typically time consuming. For this reason, this study examines the feasibility of rapid 2D T1 quantification using a variable flip angles (VFA) approach at magnetic field strengths of 1.5 Tesla, 3 Tesla, and 7 Tesla. These efforts include validation in phantom experiments and application for brain T1 mapping. Methods T1 quantification included simulations of the Bloch equations to correct for slice profile imperfections, and a correction for B1+. Fast gradient echo acquisitions were conducted using three adjusted flip angles for the proposed T1 quantification approach that was benchmarked against slice profile uncorrected 2D VFA and an inversion-recovery spin-echo based reference method. Brain T1 mapping was performed in six healthy subjects, one multiple sclerosis patient, and one stroke patient. Results Phantom experiments showed a mean T1 estimation error of (-63±1.5)% for slice profile uncorrected 2D VFA and (0.2±1.4)% for the proposed approach compared to the reference method. Scan time for single slice T1 mapping including B1+ mapping could be reduced to 5 seconds using an in-plane resolution of (2×2) mm2, which equals a scan time reduction of more than 99% compared to the reference method. Conclusion Our results demonstrate that rapid 2D T1 quantification using a variable flip angle approach is feasible at 1.5T/3T/7T. It represents a valuable alternative for rapid T1 mapping due to the gain in speed versus conventional approaches. This progress may serve to enhance the capabilities of parametric MR based lesion detection and brain tissue characterization. PMID:24621588

Rapid parametric mapping of the longitudinal relaxation time T1 using two-dimensional variable flip angle magnetic resonance imaging at 1.5 Tesla, 3 Tesla, and 7 Tesla.

PubMed

Dieringer, Matthias A; Deimling, Michael; Santoro, Davide; Wuerfel, Jens; Madai, Vince I; Sobesky, Jan; von Knobelsdorff-Brenkenhoff, Florian; Schulz-Menger, Jeanette; Niendorf, Thoralf

2014-01-01

Visual but subjective reading of longitudinal relaxation time (T1) weighted magnetic resonance images is commonly used for the detection of brain pathologies. For this non-quantitative measure, diagnostic quality depends on hardware configuration, imaging parameters, radio frequency transmission field (B1+) uniformity, as well as observer experience. Parametric quantification of the tissue T1 relaxation parameter offsets the propensity for these effects, but is typically time consuming. For this reason, this study examines the feasibility of rapid 2D T1 quantification using a variable flip angles (VFA) approach at magnetic field strengths of 1.5 Tesla, 3 Tesla, and 7 Tesla. These efforts include validation in phantom experiments and application for brain T1 mapping. T1 quantification included simulations of the Bloch equations to correct for slice profile imperfections, and a correction for B1+. Fast gradient echo acquisitions were conducted using three adjusted flip angles for the proposed T1 quantification approach that was benchmarked against slice profile uncorrected 2D VFA and an inversion-recovery spin-echo based reference method. Brain T1 mapping was performed in six healthy subjects, one multiple sclerosis patient, and one stroke patient. Phantom experiments showed a mean T1 estimation error of (-63±1.5)% for slice profile uncorrected 2D VFA and (0.2±1.4)% for the proposed approach compared to the reference method. Scan time for single slice T1 mapping including B1+ mapping could be reduced to 5 seconds using an in-plane resolution of (2×2) mm2, which equals a scan time reduction of more than 99% compared to the reference method. Our results demonstrate that rapid 2D T1 quantification using a variable flip angle approach is feasible at 1.5T/3T/7T. It represents a valuable alternative for rapid T1 mapping due to the gain in speed versus conventional approaches. This progress may serve to enhance the capabilities of parametric MR based lesion detection and brain tissue characterization.

An atlas-based multimodal registration method for 2D images with discrepancy structures.

PubMed

Lv, Wenchao; Chen, Houjin; Peng, Yahui; Li, Yanfeng; Li, Jupeng

2018-06-04

An atlas-based multimodal registration method for 2-dimension images with discrepancy structures was proposed in this paper. Atlas was utilized for complementing the discrepancy structure information in multimodal medical images. The scheme includes three steps: floating image to atlas registration, atlas to reference image registration, and field-based deformation. To evaluate the performance, a frame model, a brain model, and clinical images were employed in registration experiments. We measured the registration performance by the squared sum of intensity differences. Results indicate that this method is robust and performs better than the direct registration for multimodal images with discrepancy structures. We conclude that the proposed method is suitable for multimodal images with discrepancy structures. Graphical Abstract An Atlas-based multimodal registration method schematic diagram.

Discrete Neural Signatures of Basic Emotions.

PubMed

Saarimäki, Heini; Gotsopoulos, Athanasios; Jääskeläinen, Iiro P; Lampinen, Jouko; Vuilleumier, Patrik; Hari, Riitta; Sams, Mikko; Nummenmaa, Lauri

2016-06-01

Categorical models of emotions posit neurally and physiologically distinct human basic emotions. We tested this assumption by using multivariate pattern analysis (MVPA) to classify brain activity patterns of 6 basic emotions (disgust, fear, happiness, sadness, anger, and surprise) in 3 experiments. Emotions were induced with short movies or mental imagery during functional magnetic resonance imaging. MVPA accurately classified emotions induced by both methods, and the classification generalized from one induction condition to another and across individuals. Brain regions contributing most to the classification accuracy included medial and inferior lateral prefrontal cortices, frontal pole, precentral and postcentral gyri, precuneus, and posterior cingulate cortex. Thus, specific neural signatures across these regions hold representations of different emotional states in multimodal fashion, independently of how the emotions are induced. Similarity of subjective experiences between emotions was associated with similarity of neural patterns for the same emotions, suggesting a direct link between activity in these brain regions and the subjective emotional experience. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

High-sensitivity terahertz imaging of traumatic brain injury in a rat model

NASA Astrophysics Data System (ADS)

Zhao, Hengli; Wang, Yuye; Chen, Linyu; Shi, Jia; Ma, Kang; Tang, Longhuang; Xu, Degang; Yao, Jianquan; Feng, Hua; Chen, Tunan

2018-03-01

We demonstrated that different degrees of experimental traumatic brain injury (TBI) can be differentiated clearly in fresh slices of rat brain tissues using transmission-type terahertz (THz) imaging system. The high absorption region in THz images corresponded well with the injured area in visible images and magnetic resonance imaging results. The THz image and absorption characteristics of dehydrated paraffin-embedded brain slices and the hematoxylin and eosin (H&E)-stained microscopic images were investigated to account for the intrinsic differences in the THz images for the brain tissues suffered from different degrees of TBI and normal tissue aside from water. The THz absorption coefficients of rat brain tissues showed an increase in the aggravation of brain damage, particularly in the high-frequency range, whereas the cell density decreased as the order of mild, moderate, and severe TBI tissues compared with the normal tissue. Our results indicated that the different degrees of TBI were distinguishable owing to the different water contents and probable hematoma components distribution rather than intrinsic cell intensity. These promising results suggest that THz imaging has great potential as an alternative method for the fast diagnosis of TBI.

Brain extraction from normal and pathological images: A joint PCA/Image-Reconstruction approach.

PubMed

Han, Xu; Kwitt, Roland; Aylward, Stephen; Bakas, Spyridon; Menze, Bjoern; Asturias, Alexander; Vespa, Paul; Van Horn, John; Niethammer, Marc

2018-08-01

Brain extraction from 3D medical images is a common pre-processing step. A variety of approaches exist, but they are frequently only designed to perform brain extraction from images without strong pathologies. Extracting the brain from images exhibiting strong pathologies, for example, the presence of a brain tumor or of a traumatic brain injury (TBI), is challenging. In such cases, tissue appearance may substantially deviate from normal tissue appearance and hence violates algorithmic assumptions for standard approaches to brain extraction; consequently, the brain may not be correctly extracted. This paper proposes a brain extraction approach which can explicitly account for pathologies by jointly modeling normal tissue appearance and pathologies. Specifically, our model uses a three-part image decomposition: (1) normal tissue appearance is captured by principal component analysis (PCA), (2) pathologies are captured via a total variation term, and (3) the skull and surrounding tissue is captured by a sparsity term. Due to its convexity, the resulting decomposition model allows for efficient optimization. Decomposition and image registration steps are alternated to allow statistical modeling of normal tissue appearance in a fixed atlas coordinate system. As a beneficial side effect, the decomposition model allows for the identification of potentially pathological areas and the reconstruction of a quasi-normal image in atlas space. We demonstrate the effectiveness of our approach on four datasets: the publicly available IBSR and LPBA40 datasets which show normal image appearance, the BRATS dataset containing images with brain tumors, and a dataset containing clinical TBI images. We compare the performance with other popular brain extraction models: ROBEX, BEaST, MASS, BET, BSE and a recently proposed deep learning approach. Our model performs better than these competing approaches on all four datasets. Specifically, our model achieves the best median (97.11) and mean (96.88) Dice scores over all datasets. The two best performing competitors, ROBEX and MASS, achieve scores of 96.23/95.62 and 96.67/94.25 respectively. Hence, our approach is an effective method for high quality brain extraction for a wide variety of images. Copyright © 2018 Elsevier Inc. All rights reserved.

Behavioral, Brain Imaging and Genomic Measures to Predict Functional Outcomes Post - Bed Rest and Spaceflight

NASA Technical Reports Server (NTRS)

Mulavara, A. P.; DeDios, Y. E.; Gadd, N. E.; Caldwell, E. E.; Batson, C. D.; Goel, R.; Seidler, R. D.; Oddsson, L.; Zanello, S.; Clarke, T.;

An extensive assessment of network alignment algorithms for comparison of brain connectomes.

PubMed

Milano, Marianna; Guzzi, Pietro Hiram; Tymofieva, Olga; Xu, Duan; Hess, Christofer; Veltri, Pierangelo; Cannataro, Mario

2017-06-06

Recently the study of the complex system of connections in neural systems, i.e. the connectome, has gained a central role in neurosciences. The modeling and analysis of connectomes are therefore a growing area. Here we focus on the representation of connectomes by using graph theory formalisms. Macroscopic human brain connectomes are usually derived from neuroimages; the analyzed brains are co-registered in the image domain and brought to a common anatomical space. An atlas is then applied in order to define anatomically meaningful regions that will serve as the nodes of the network - this process is referred to as parcellation. The atlas-based parcellations present some known limitations in cases of early brain development and abnormal anatomy. Consequently, it has been recently proposed to perform atlas-free random brain parcellation into nodes and align brains in the network space instead of the anatomical image space, as a way to deal with the unknown correspondences of the parcels. Such process requires modeling of the brain using graph theory and the subsequent comparison of the structure of graphs. The latter step may be modeled as a network alignment (NA) problem. In this work, we first define the problem formally, then we test six existing state of the art of network aligners on diffusion MRI-derived brain networks. We compare the performances of algorithms by assessing six topological measures. We also evaluated the robustness of algorithms to alterations of the dataset. The results confirm that NA algorithms may be applied in cases of atlas-free parcellation for a fully network-driven comparison of connectomes. The analysis shows MAGNA++ is the best global alignment algorithm. The paper presented a new analysis methodology that uses network alignment for validating atlas-free parcellation brain connectomes. The methodology has been experimented on several brain datasets.

An External Matrix-Assisted Laser Desorption Ionization Source for Flexible FT-ICR Mass Spectrometry Imaging with Internal Calibration on Adjacent Samples

NASA Astrophysics Data System (ADS)

Smith, Donald F.; Aizikov, Konstantin; Duursma, Marc C.; Giskes, Frans; Spaanderman, Dirk-Jan; McDonnell, Liam A.; O'Connor, Peter B.; Heeren, Ron M. A.

2011-01-01

We describe the construction and application of a new MALDI source for FT-ICR mass spectrometry imaging. The source includes a translational X-Y positioning stage with a 10 × 10 cm range of motion for analysis of large sample areas, a quadrupole for mass selection, and an external octopole ion trap with electrodes for the application of an axial potential gradient for controlled ion ejection. An off-line LC MALDI MS/MS run demonstrates the utility of the new source for data- and position-dependent experiments. A FT-ICR MS imaging experiment of a coronal rat brain section yields ˜200 unique peaks from m/z 400-1100 with corresponding mass-selected images. Mass spectra from every pixel are internally calibrated with respect to polymer calibrants collected from an adjacent slide.

Functional mechanisms involved in the internal inhibition of taboo words.

PubMed

Severens, Els; Kühn, Simone; Hartsuiker, Robert J; Brass, Marcel

2012-04-01

The present study used functional magnetic resonance imaging to investigate brain processes associated with the inhibition of socially undesirable speech. It is tested whether the inhibition of undesirable speech is solely related to brain areas associated with classical stop signal tasks or rather also involves brain areas involved in endogenous self-control. During the experiment, subjects had to do a SLIP task, which was designed to elicit taboo or neutral spoonerisms. Here we show that the internal inhibition of taboo words activates the right inferior frontal gyrus, an area that has previously been associated with externally triggered inhibition. This finding strongly suggests that external social rules become internalized and act as a stop-signal.

Functional mechanisms involved in the internal inhibition of taboo words

PubMed Central

Kühn, Simone; Hartsuiker, Robert J.; Brass, Marcel

2012-01-01

The present study used functional magnetic resonance imaging to investigate brain processes associated with the inhibition of socially undesirable speech. It is tested whether the inhibition of undesirable speech is solely related to brain areas associated with classical stop signal tasks or rather also involves brain areas involved in endogenous self-control. During the experiment, subjects had to do a SLIP task, which was designed to elicit taboo or neutral spoonerisms. Here we show that the internal inhibition of taboo words activates the right inferior frontal gyrus, an area that has previously been associated with externally triggered inhibition. This finding strongly suggests that external social rules become internalized and act as a stop-signal. PMID:21609970

Deep brain stimulation as a functional scalpel.

PubMed

Broggi, G; Franzini, A; Tringali, G; Ferroli, P; Marras, C; Romito, L; Maccagnano, E

2006-01-01

Since 1995, at the Istituto Nazionale Neurologico "Carlo Besta" in Milan (INNCB,) 401 deep brain electrodes were implanted to treat several drug-resistant neurological syndromes (Fig. 1). More than 200 patients are still available for follow-up and therapeutical considerations. In this paper our experience is reviewed and pioneered fields are highlighted. The reported series of patients extends the use of deep brain stimulation beyond the field of Parkinson's disease to new fields such as cluster headache, disruptive behaviour, SUNCt, epilepsy and tardive dystonia. The low complication rate, the reversibility of the procedure and the available image guided surgery tools will further increase the therapeutic applications of DBS. New therapeutical applications are expected for this functional scalpel.

Structured Illumination Diffuse Optical Tomography for Mouse Brain Imaging

NASA Astrophysics Data System (ADS)

Reisman, Matthew David

As advances in functional magnetic resonance imaging (fMRI) have transformed the study of human brain function, they have also widened the divide between standard research techniques used in humans and those used in mice, where high quality images are difficult to obtain using fMRI given the small volume of the mouse brain. Optical imaging techniques have been developed to study mouse brain networks, which are highly valuable given the ability to study brain disease treatments or development in a controlled environment. A planar imaging technique known as optical intrinsic signal (OIS) imaging has been a powerful tool for capturing functional brain hemodynamics in rodents. Recent wide field-of-view implementations of OIS have provided efficient maps of functional connectivity from spontaneous brain activity in mice. However, OIS requires scalp retraction and is limited to imaging a 2-dimensional view of superficial cortical tissues. Diffuse optical tomography (DOT) is a non-invasive, volumetric neuroimaging technique that has been valuable for bedside imaging of patients in the clinic, but previous DOT systems for rodent neuroimaging have been limited by either sparse spatial sampling or by slow speed. My research has been to develop diffuse optical tomography for whole brain mouse neuroimaging by expanding previous techniques to achieve high spatial sampling using multiple camera views for detection and high speed using structured illumination sources. I have shown the feasibility of this method to perform non-invasive functional neuroimaging in mice and its capabilities of imaging the entire volume of the brain. Additionally, the system has been built with a custom, flexible framework to accommodate the expansion to imaging multiple dynamic contrasts in the brain and populations that were previously difficult or impossible to image, such as infant mice and awake mice. I have contributed to preliminary feasibility studies of these more advanced techniques using OIS, which can now be carried out using the structured illumination diffuse optical tomography technique to perform longitudinal, non-invasive studies of the whole volume of the mouse brain.

Trends in brain oxygenation during mental and physical exercise measured using near-infrared spectroscopy (NIRS): potential for early detection of Alzheimer's disease

NASA Astrophysics Data System (ADS)

Allen, Monica S.; Allen, Jeffery W.; Mikkilineni, Shweta; Liu, Hanli

2005-04-01

Motivation: Early diagnosis of Alzheimer's disease (AD) is crucial because symptoms respond best to available treatments in the initial stages of the disease. Recent studies have shown that marked changes in brain oxygenation during mental and physical tasks can be used for noninvasive functional brain imaging to detect Alzheimer"s disease. The goal of our study is to explore the possibility of using near infrared spectroscopy (NIRS) and mapping (NIRM) as a diagnostic tool for AD before the onset of significant morphological changes in the brain. Methods: A 16-channel NIRS brain imager was used to noninvasively measure spatial and temporal changes in cerebral hemodynamics induced during verbal fluency task and physical activity. The experiments involved healthy subjects (n = 10) in the age range of 25+/-5 years. The NIRS signals were taken from the subjects' prefrontal cortex during the activities. Results and Conclusion: Trends of oxygenated and deoxygenated hemoglobin in the prefrontal cortex of the brain were observed. During the mental stimulation, the subjects showed significant increase in oxygenated hemoglobin [HbO2] with a simultaneous decrease in deoxygenated hemoglobin [Hb]. However, physical exercise caused a rise in levels of HbO2 with small variations in Hb. This study basically demonstrates that NIRM taken from the prefrontal cortex of the human brain is sensitive to both mental and physical tasks and holds potential to serve as a diagnostic means for early detection of Alzheimer's disease.

Look again: effects of brain images and mind-brain dualism on lay evaluations of research.

PubMed

Hook, Cayce J; Farah, Martha J

2013-09-01

Brain scans have frequently been credited with uniquely seductive and persuasive qualities, leading to claims that fMRI research receives a disproportionate share of public attention and funding. It has been suggested that functional brain images are fascinating because they contradict dualist beliefs regarding the relationship between the body and the mind. Although previous research has indicated that brain images can increase judgments of an article's scientific reasoning, the hypotheses that brain scans make research appear more interesting, surprising, or worthy of funding have not been tested. Neither has the relation between the allure of brain imaging and dualism. In the following three studies, laypersons rated both fictional research descriptions and real science news articles accompanied by brain scans, bar charts, or photographs. Across 988 participants, we found little evidence of neuroimaging's seductive allure or of its relation to self-professed dualistic beliefs. These results, taken together with other recent null findings, suggest that brain images are less powerful than has been argued.

Three-dimensional atlas of iron, copper, and zinc in the mouse cerebrum and brainstem.

PubMed

Hare, Dominic J; Lee, Jason K; Beavis, Alison D; van Gramberg, Amanda; George, Jessica; Adlard, Paul A; Finkelstein, David I; Doble, Philip A

2012-05-01

Atlases depicting molecular and functional features of the brain are becoming an integral part of modern neuroscience. In this study we used laser ablation-inductively coupled plasma-mass spectrometry (LA-ICPMS) to quantitatively measure iron (Fe), copper (Cu), and zinc (Zn) levels in a serially sectioned C57BL/6 mouse brain (cerebrum and brainstem). Forty-six sections were analyzed in a single experiment of approximately 158 h in duration. We constructed a 46-plate reference atlas by aligning quantified images of metal distribution with corresponding coronal sections from the Allen Mouse Brain Reference Atlas. The 46 plates were also used to construct three-dimensional models of Fe, Cu, and Zn distribution. This atlas represents the first reconstruction of quantitative trace metal distribution through the brain by LA-ICPMS and will facilitate the study of trace metals in the brain and help to elucidate their role in neurobiology.

Combined multi-kernel head computed tomography images optimized for depicting both brain parenchyma and bone.

PubMed

Takagi, Satoshi; Nagase, Hiroyuki; Hayashi, Tatsuya; Kita, Tamotsu; Hayashi, Katsumi; Sanada, Shigeru; Koike, Masayuki

2014-01-01

The hybrid convolution kernel technique for computed tomography (CT) is known to enable the depiction of an image set using different window settings. Our purpose was to decrease the number of artifacts in the hybrid convolution kernel technique for head CT and to determine whether our improved combined multi-kernel head CT images enabled diagnosis as a substitute for both brain (low-pass kernel-reconstructed) and bone (high-pass kernel-reconstructed) images. Forty-four patients with nondisplaced skull fractures were included. Our improved multi-kernel images were generated so that pixels of >100 Hounsfield unit in both brain and bone images were composed of CT values of bone images and other pixels were composed of CT values of brain images. Three radiologists compared the improved multi-kernel images with bone images. The improved multi-kernel images and brain images were identically displayed on the brain window settings. All three radiologists agreed that the improved multi-kernel images on the bone window settings were sufficient for diagnosing skull fractures in all patients. This improved multi-kernel technique has a simple algorithm and is practical for clinical use. Thus, simplified head CT examinations and fewer images that need to be stored can be expected.

A philosophy for CNS radiotracer design.

PubMed

Van de Bittner, Genevieve C; Ricq, Emily L; Hooker, Jacob M

2014-10-21

Decades after its discovery, positron emission tomography (PET) remains the premier tool for imaging neurochemistry in living humans. Technological improvements in radiolabeling methods, camera design, and image analysis have kept PET in the forefront. In addition, the use of PET imaging has expanded because researchers have developed new radiotracers that visualize receptors, transporters, enzymes, and other molecular targets within the human brain. However, of the thousands of proteins in the central nervous system (CNS), researchers have successfully imaged fewer than 40 human proteins. To address the critical need for new radiotracers, this Account expounds on the decisions, strategies, and pitfalls of CNS radiotracer development based on our current experience in this area. We discuss the five key components of radiotracer development for human imaging: choosing a biomedical question, selection of a biological target, design of the radiotracer chemical structure, evaluation of candidate radiotracers, and analysis of preclinical imaging. It is particularly important to analyze the market of scientists or companies who might use a new radiotracer and carefully select a relevant biomedical question(s) for that audience. In the selection of a specific biological target, we emphasize how target localization and identity can constrain this process and discuss the optimal target density and affinity ratios needed for binding-based radiotracers. In addition, we discuss various PET test-retest variability requirements for monitoring changes in density, occupancy, or functionality for new radiotracers. In the synthesis of new radiotracer structures, high-throughput, modular syntheses have proved valuable, and these processes provide compounds with sites for late-stage radioisotope installation. As a result, researchers can manage the time constraints associated with the limited half-lives of isotopes. In order to evaluate brain uptake, a number of methods are available to predict bioavailability, blood-brain barrier (BBB) permeability, and the associated issues of nonspecific binding and metabolic stability. To evaluate the synthesized chemical library, researchers need to consider high-throughput affinity assays, the analysis of specific binding, and the importance of fast binding kinetics. Finally, we describe how we initially assess preclinical radiotracer imaging, using brain uptake, specific binding, and preliminary kinetic analysis to identify promising radiotracers that may be useful for human brain imaging. Although we discuss these five design components separately and linearly in this Account, in practice we develop new PET-based radiotracers using these design components nonlinearly and iteratively to develop new compounds in the most efficient way possible.

Physiological Observations and Omics to Develop Personalized Sensormotor Adaptability Countermeasures Using Bed Rest and Space Flight Data

NASA Technical Reports Server (NTRS)

Mulavara, A. P.; Seidler, R. D.; Feiveson, A.; Oddsson, L.; Zanello, S.; Oman, C. M.; Ploutz-Snyder, L.; Peters, B.; Cohen, H. S.; Reschke, M.;

Rapid language-related plasticity: microstructural changes in the cortex after a short session of new word learning.

PubMed

Hofstetter, Shir; Friedmann, Naama; Assaf, Yaniv

2017-04-01

Human brain imaging revealed that the brain can undergo structural plasticity following new learning experiences. Most magnetic resonance imaging (MRI) uncovered morphometric alternation in cortical density after the long-term training of weeks to months. A recent diffusion tensor imaging (DTI) study has found changes in diffusion indices after 2 h of training, primarily in the hippocampus. However, whether a short learning experience can induce microstructural changes in the neocortex is still unclear. Here, we used diffusion MRI, a method sensitive to tissue microstructure, to study cortical plasticity. To attain cortical involvement, we used a short language task (under 1 h) of introducing new lexical items (flower names) to the lexicon. We have found significant changes in diffusivity in cortical regions involved in language and reading (inferior frontal gyrus, middle temporal gyrus, and inferior parietal lobule). In addition, the difference in the values of diffusivity correlated with the lexical learning rate in the task. Moreover, significant changes were found in white matter tracts near the cortex, and the extent of change correlated with behavioral measures of lexical learning rate. These findings provide first evidence of short-term cortical plasticity in the human brain after a short language learning task. It seems that short training of less than an hour of high cognitive demand can induce microstructural changes in the cortex, suggesting a rapid time scale of neuroplasticity and providing additional evidence of the power of MRI to investigate the temporal and spatial progressions of this process.

Genetic control of postnatal human brain growth

PubMed Central

van Dyck, Laura I.; Morrow, Eric M.

2017-01-01

Purpose of review Studies investigating postnatal brain growth disorders inform the biology underlying the development of human brain circuitry. This research is becoming increasingly important for the diagnosis and treatment of childhood neurodevelopmental disorders, including autism and related disorders. Here we review recent research on typical and abnormal postnatal brain growth and examine potential biological mechanisms. Recent findings Clinically, brain growth disorders are heralded by diverging head size for a given age and sex, but are more precisely characterized by brain imaging, postmortem analysis, and animal model studies. Recent neuroimaging and molecular biological studies on postnatal brain growth disorders have broadened our view of both typical and pathological postnatal neurodevelopment. Correlating gene and protein function with brain growth trajectories uncovers postnatal biological mechanisms, including neuronal arborization, synaptogenesis and pruning, and gliogenesis and myelination. Recent investigations of childhood neurodevelopmental and neurodegenerative disorders highlight the underlying genetic programming and experience-dependent remodeling of neural circuitry. Summary In order to understand typical and abnormal postnatal brain development, clinicians and researchers should characterize brain growth trajectories in the context of neurogenetic syndromes. Understanding mechanisms and trajectories of postnatal brain growth will aid in differentiating, diagnosing, and potentially treating neurodevelopmental disorders. PMID:27898583

Imaging Predictors of Improvement From a Motor Learning-Based Intervention for Children With Unilateral Cerebral Palsy.

PubMed

Schertz, Mitchell; Shiran, Shelly I; Myers, Vicki; Weinstein, Maya; Fattal-Valevski, Aviva; Artzi, Moran; Ben Bashat, Dafna; Gordon, Andrew M; Green, Dido

2016-08-01

Background Motor-learning interventions may improve hand function in children with unilateral cerebral palsy (UCP) but with inconsistent outcomes across participants. Objective To examine if pre-intervention brain imaging predicts benefit from bimanual intervention. Method Twenty children with UCP with Manual Ability Classification System levels I to III, aged 7-16 years, participated in an intensive bimanual intervention. Assessments included the Assisting Hand Assessment (AHA), Jebsen Taylor Test of Hand Function (JTTHF) and Children's Hand Experience Questionnaire (CHEQ) at baseline (T1), completion (T2) and 8-10 weeks post-intervention (T3). Imaging at baseline included conventional structural (radiological score), functional (fMRI) and diffusion tensor imaging (DTI). Results Improvements were seen across assessments; AHA (P = 0.04), JTTHF (P < .001) and CHEQ (P < 0.001). Radiological score significantly correlated with improvement at T2; AHA (r = .475) and CHEQ (r = .632), but negatively with improvement on unimanual measures at T3 (JTTFH r = -.514). fMRI showed negative correlations between contralesional brain activation when moving the affected hand and AHA improvements (T2: r = -.562, T3: r = -0.479). Fractional Anisotropy in the affected posterior limb of the internal capsule correlated negatively with increased bimanual use on CHEQ at T2 (r = -547) and AHA at T3 (r = -.656). Conclusions Children with greater structural, functional and connective brain damage showed enhanced responses to bimanual intervention. Baseline imaging may identify parameters predicting response to intervention in children with UCP. © The Author(s) 2015.

Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization

PubMed Central

Pérez-Beteta, Julián; Martínez-González, Alicia; Martino, Juan; Velasquez, Carlos; Arana, Estanislao; Pérez-García, Víctor M.

2017-01-01

Purpose Textural measures have been widely explored as imaging biomarkers in cancer. However, their robustness under dynamic range and spatial resolution changes in brain 3D magnetic resonance images (MRI) has not been assessed. The aim of this work was to study potential variations of textural measures due to changes in MRI protocols. Materials and methods Twenty patients harboring glioblastoma with pretreatment 3D T1-weighted MRIs were included in the study. Four different spatial resolution combinations and three dynamic ranges were studied for each patient. Sixteen three-dimensional textural heterogeneity measures were computed for each patient and configuration including co-occurrence matrices (CM) features and run-length matrices (RLM) features. The coefficient of variation was used to assess the robustness of the measures in two series of experiments corresponding to (i) changing the dynamic range and (ii) changing the matrix size. Results No textural measures were robust under dynamic range changes. Entropy was the only textural feature robust under spatial resolution changes (coefficient of variation under 10% in all cases). Conclusion Textural measures of three-dimensional brain tumor images are not robust neither under dynamic range nor under matrix size changes. Standards should be harmonized to use textural features as imaging biomarkers in radiomic-based studies. The implications of this work go beyond the specific tumor type studied here and pose the need for standardization in textural feature calculation of oncological images. PMID:28586353

Evidence of successful modulation of brain activation and subjective experience during reappraisal of negative emotion in unmedicated depression.

PubMed

Dillon, Daniel Gerard; Pizzagalli, Diego Andrea

2013-05-30

Functional magnetic resonance imaging (fMRI) was used to examine cognitive regulation of negative emotion in 12 unmedicated patients with major depressive disorder (MDD) and 24 controls. The participants used reappraisal to increase (real condition) and reduce (photo condition) the personal relevance of negative and neutral pictures during fMRI as valence ratings were collected; passive viewing (look condition) served as a baseline. Reappraisal was not strongly affected by MDD. Ratings indicated that both groups successfully reappraised negative emotional experience. Both groups also showed better memory for negative vs. neutral pictures 2 weeks later. Across groups, increased brain activation was observed on negative/real vs. negative/look and negative/photo trials in left dorsolateral prefrontal cortex (DLPFC), rostral anterior cingulate, left parietal cortex, caudate, and right amygdala. Depressive severity was inversely correlated with activation modulation in the left DLPFC, right amygdala, and right cerebellum during negative reappraisal. The lack of group differences suggests that depressed adults can modulate the brain activation and subjective experience elicited by negative pictures when given clear instructions. However, the negative relationship between depression severity and effects of reappraisal on brain activation indicates that group differences may be detectable in larger samples of more severely depressed participants. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Brain lesions in septic shock: a magnetic resonance imaging study.

PubMed

Sharshar, Tarek; Carlier, Robert; Bernard, Francis; Guidoux, Céline; Brouland, Jean-Philippe; Nardi, Olivier; de la Grandmaison, Geoffroy Lorin; Aboab, Jérôme; Gray, Françoise; Menon, David; Annane, Djillali

2007-05-01

Understanding of sepsis-induced brain dysfunction remains poor, and relies mainly on data from animals or post-mortem studies in patients. The current study provided findings from magnetic resonance imaging of the brain in septic shock. Nine patients with septic shock and brain dysfunction [7 women, median age 63 years (interquartile range 61-79 years), SAPS II: 48 (44-56), SOFA: 8 (6-10)] underwent brain magnetic resonance imaging including gradient echo T1-weighted, fluid-attenuated inversion recovery (FLAIR), T2-weighted and diffusion isotropic images, and mapping of apparent diffusion coefficient. Brain imaging was normal in two patients, showed multiple ischaemic strokes in two patients, and in the remaining patients showed white matter lesions at the level of the centrum semiovale, predominating around Virchow-Robin spaces, ranging from small multiple areas to diffuse lesions, and characterised by hyperintensity on FLAIR images. The main lesions were also characterised by reduced signal on diffusion isotropic images and increased apparent diffusion coefficient. The lesions of the white matter worsened with increasing duration of shock and were correlated with Glasgow Outcome Score. This preliminary study showed that sepsis-induced brain lesions can be documented by magnetic resonance imaging. These lesions predominated in the white matter, suggesting increased blood-brain barrier permeability, and were associated with poor outcome.

Dorsal brain stem syndrome: MR imaging location of brain stem tegmental lesions in neonates with oral motor dysfunction.

PubMed

Quattrocchi, C C; Longo, D; Delfino, L N; Cilio, M R; Piersigilli, F; Capua, M D; Seganti, G; Danhaive, O; Fariello, G

2010-09-01

The anatomic extent of brain stem damage may provide information about clinical outcome and prognosis in children with hypoxic-ischemic encephalopathy and oral motor dysfunction. The aim of this study was to retrospectively characterize the location and extent of brain stem lesions in children with oral motor dysfunction. From January 2005 to August 2009, 43 infants hospitalized at our institution were included in the study because of a history of hypoxic-ischemic events. Of this group, 14 patients showed oral motor dysfunction and brain stem tegmental lesions detected at MR imaging. MR imaging showed hypoxic-ischemic lesions in supra- and infratentorial areas. Six of 14 patients revealed only infratentorial lesions. Focal symmetric lesions of the tegmental brain stem were always present. The lesions appeared hyperintense on T2-weighted images and hypointense on IR images. We found a strong association (P < .0001) between oral motor dysfunction and infratentorial lesions on MR imaging. Oral motor dysfunction was associated with brain stem tegmental lesions in posthypoxic-ischemic infants. The MR imaging examination should be directed to the brain stem, especially when a condition of prolonged gavage feeding is necessary in infants.

The Golden Beauty: Brain Response to Classical and Renaissance Sculptures

PubMed Central

Di Dio, Cinzia; Macaluso, Emiliano; Rizzolatti, Giacomo

2007-01-01

Is there an objective, biological basis for the experience of beauty in art? Or is aesthetic experience entirely subjective? Using fMRI technique, we addressed this question by presenting viewers, naïve to art criticism, with images of masterpieces of Classical and Renaissance sculpture. Employing proportion as the independent variable, we produced two sets of stimuli: one composed of images of original sculptures; the other of a modified version of the same images. The stimuli were presented in three conditions: observation, aesthetic judgment, and proportion judgment. In the observation condition, the viewers were required to observe the images with the same mind-set as if they were in a museum. In the other two conditions they were required to give an aesthetic or proportion judgment on the same images. Two types of analyses were carried out: one which contrasted brain response to the canonical and the modified sculptures, and one which contrasted beautiful vs. ugly sculptures as judged by each volunteer. The most striking result was that the observation of original sculptures, relative to the modified ones, produced activation of the right insula as well as of some lateral and medial cortical areas (lateral occipital gyrus, precuneus and prefrontal areas). The activation of the insula was particularly strong during the observation condition. Most interestingly, when volunteers were required to give an overt aesthetic judgment, the images judged as beautiful selectively activated the right amygdala, relative to those judged as ugly. We conclude that, in observers naïve to art criticism, the sense of beauty is mediated by two non-mutually exclusive processes: one based on a joint activation of sets of cortical neurons, triggered by parameters intrinsic to the stimuli, and the insula (objective beauty); the other based on the activation of the amygdala, driven by one's own emotional experiences (subjective beauty). PMID:18030335

Automatic tracking of cells for video microscopy in patch clamp experiments

PubMed Central

2014-01-01

Background Visualisation of neurons labeled with fluorescent proteins or compounds generally require exposure to intense light for a relatively long period of time, often leading to bleaching of the fluorescent probe and photodamage of the tissue. Here we created a technique to drastically shorten light exposure and improve the targeting of fluorescent labeled cells that is specially useful for patch-clamp recordings. We applied image tracking and mask overlay to reduce the time of fluorescence exposure and minimise mistakes when identifying neurons. Methods Neurons are first identified according to visual criteria (e.g. fluorescence protein expression, shape, viability etc.) and a transmission microscopy image Differential Interference Contrast (DIC) or Dodt contrast containing the cell used as a reference for the tracking algorithm. A fluorescence image can also be acquired later to be used as a mask (that can be overlaid on the target during live transmission video). As patch-clamp experiments require translating the microscope stage, we used pattern matching to track reference neurons in order to move the fluorescence mask to match the new position of the objective in relation to the sample. For the image processing we used the Open Source Computer Vision (OpenCV) library, including the Speeded-Up Robust Features (SURF) for tracking cells. The dataset of images (n = 720) was analyzed under normal conditions of acquisition and with influence of noise (defocusing and brightness). Results We validated the method in dissociated neuronal cultures and fresh brain slices expressing Enhanced Yellow Fluorescent Protein (eYFP) or Tandem Dimer Tomato (tdTomato) proteins, which considerably decreased the exposure to fluorescence excitation, thereby minimising photodamage. We also show that the neuron tracking can be used in differential interference contrast or Dodt contrast microscopy. Conclusion The techniques of digital image processing used in this work are an important addition to the set of microscopy tools used in modern electrophysiology, specially in experiments with neuron cultures and brain slices. PMID:24946774

Automatic tracking of cells for video microscopy in patch clamp experiments.

PubMed

Peixoto, Helton M; Munguba, Hermany; Cruz, Rossana M S; Guerreiro, Ana M G; Leao, Richardson N

2014-06-20

Visualisation of neurons labeled with fluorescent proteins or compounds generally require exposure to intense light for a relatively long period of time, often leading to bleaching of the fluorescent probe and photodamage of the tissue. Here we created a technique to drastically shorten light exposure and improve the targeting of fluorescent labeled cells that is specially useful for patch-clamp recordings. We applied image tracking and mask overlay to reduce the time of fluorescence exposure and minimise mistakes when identifying neurons. Neurons are first identified according to visual criteria (e.g. fluorescence protein expression, shape, viability etc.) and a transmission microscopy image Differential Interference Contrast (DIC) or Dodt contrast containing the cell used as a reference for the tracking algorithm. A fluorescence image can also be acquired later to be used as a mask (that can be overlaid on the target during live transmission video). As patch-clamp experiments require translating the microscope stage, we used pattern matching to track reference neurons in order to move the fluorescence mask to match the new position of the objective in relation to the sample. For the image processing we used the Open Source Computer Vision (OpenCV) library, including the Speeded-Up Robust Features (SURF) for tracking cells. The dataset of images (n = 720) was analyzed under normal conditions of acquisition and with influence of noise (defocusing and brightness). We validated the method in dissociated neuronal cultures and fresh brain slices expressing Enhanced Yellow Fluorescent Protein (eYFP) or Tandem Dimer Tomato (tdTomato) proteins, which considerably decreased the exposure to fluorescence excitation, thereby minimising photodamage. We also show that the neuron tracking can be used in differential interference contrast or Dodt contrast microscopy. The techniques of digital image processing used in this work are an important addition to the set of microscopy tools used in modern electrophysiology, specially in experiments with neuron cultures and brain slices.

Brain activity in hunger and satiety: an exploratory visually stimulated FMRI study.

PubMed

Führer, Dagmar; Zysset, Stefan; Stumvoll, Michael

2008-05-01

To explore neuroanatomical sites of eating behavior, we have developed a simple functional magnetic resonance imaging (fMRI) paradigm to image hunger vs. satiety using visual stimulation. Twelve healthy, lean, nonsmoking male subjects participated in this study. Pairs of food-neutral and food-related pictures were presented in a block design, after a 14-h fast and 1 h after ad libitum ingestion of a mixed meal. Statistically, a general linear model for serially autocorrelated observations with a P level<0.001 was used. During the hunger condition, significantly enhanced brain activity was found in the left striate and extrastriate cortex, the inferior parietal lobe, and the orbitofrontal cortices. Stimulation with food images was associated with increased activity in both insulae, the left striate and extrastriate cortex, and the anterior midprefrontal cortex. Nonfood images were associated with enhanced activity in the right parietal lobe and the left and right middle temporal gyrus. A significant interaction in activation pattern between the states of hunger and satiety and stimulation with food and nonfood images was found for the left anterior cingulate cortex, the superior occipital sulcus, and in the vicinity of the right amygdala. These preliminary data from a homogenous healthy male cohort suggest that central nervous system (CNS) activation is not only altered with hunger and satiety but that food and nonfood images have also specific effects on regional brain activity if exposure takes place in different states of satiety. Wider use of our or a similar approach would help to establish a uniform paradigm to map hunger and satiety to be used for further experiments.

Wide-area mapping of resting state hemodynamic correlations at microvascular resolution with multi-contrast optical imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Senarathna, Janaka; Hadjiabadi, Darian; Gil, Stacy; Thakor, Nitish V.; Pathak, Arvind P.

2017-02-01

Different brain regions exhibit complex information processing even at rest. Therefore, assessing temporal correlations between regions permits task-free visualization of their `resting state connectivity'. Although functional MRI (fMRI) is widely used for mapping resting state connectivity in the human brain, it is not well suited for `microvascular scale' imaging in rodents because of its limited spatial resolution. Moreover, co-registered cerebral blood flow (CBF) and total hemoglobin (HbT) data are often unavailable in conventional fMRI experiments. Therefore, we built a customized system that combines laser speckle contrast imaging (LSCI), intrinsic optical signal (IOS) imaging and fluorescence imaging (FI) to generate multi-contrast functional connectivity maps at a spatial resolution of 10 μm. This system comprised of three illumination sources: a 632 nm HeNe laser (for LSCI), a 570 nm ± 5 nm filtered white light source (for IOS), and a 473 nm blue laser (for FI), as well as a sensitive CCD camera operating at 10 frames per second for image acquisition. The acquired data enabled visualization of changes in resting state neurophysiology at microvascular spatial scales. Moreover, concurrent mapping of CBF and HbT-based temporal correlations enabled in vivo mapping of how resting brain regions were linked in terms of their hemodynamics. Additionally, we complemented this approach by exploiting the transit times of a fluorescent tracer (Dextran-FITC) to distinguish arterial from venous perfusion. Overall, we demonstrated the feasibility of wide area mapping of resting state connectivity at microvascular resolution and created a new toolbox for interrogating neurovascular function.

The Myth of the Normal, Average Human Brain—The ICBM Experience: (1) Subject Screening and Eligibility

PubMed Central

Mazziotta, John C.; Woods, Roger; Iacoboni, Marco; Sicotte, Nancy; Yaden, Kami; Tran, Mary; Bean, Courtney; Kaplan, Jonas; Toga, Arthur W.

2009-01-01

In the course of developing an atlas and reference system for the normal human brain throughout the human age span from structural and functional brain imaging data, the International Consortium for Brain Mapping (ICBM) developed a set of “normal” criteria for subject inclusion and the associated exclusion criteria. The approach was to minimize inclusion of subjects with any medical disorders that could affect brain structure or function. In the past two years, a group of 1,685 potential subjects responded to solicitation advertisements at one of the consortium sites (UCLA). Subjects were screened by a detailed telephone interview and then had an in-person history and physical examination. Of those who responded to the advertisement and considered themselves to be normal, only 31.6% (532 subjects) passed the telephone screening process. Of the 348 individuals who submitted to in-person history and physical examinations, only 51.7% passed these screening procedures. Thus, only 10.7% of those individuals who responded to the original advertisement qualified for imaging. The most frequent cause for exclusion in the second phase of subject screening was high blood pressure followed by abnormal signs on neurological examination. It is concluded that the majority of individuals who consider themselves normal by self-report are found not to be so by detailed historical interviews about underlying medical conditions and by thorough medical and neurological examinations. Recommendations are made with regard to the inclusion of subjects in brain imaging studies and the criteria used to select them. PMID:18775497

3-D in vivo brain tumor geometry study by scaling analysis

NASA Astrophysics Data System (ADS)

Torres Hoyos, F.; Martín-Landrove, M.

2012-02-01

A new method, based on scaling analysis, is used to calculate fractal dimension and local roughness exponents to characterize in vivo 3-D tumor growth in the brain. Image acquisition was made according to the standard protocol used for brain radiotherapy and radiosurgery, i.e., axial, coronal and sagittal magnetic resonance T1-weighted images, and comprising the brain volume for image registration. Image segmentation was performed by the application of the k-means procedure upon contrasted images. We analyzed glioblastomas, astrocytomas, metastases and benign brain tumors. The results show significant variations of the parameters depending on the tumor stage and histological origin.

Segmentation of magnetic resonance images using fuzzy algorithms for learning vector quantization.

PubMed

Karayiannis, N B; Pai, P I

1999-02-01

This paper evaluates a segmentation technique for magnetic resonance (MR) images of the brain based on fuzzy algorithms for learning vector quantization (FALVQ). These algorithms perform vector quantization by updating all prototypes of a competitive network through an unsupervised learning process. Segmentation of MR images is formulated as an unsupervised vector quantization process, where the local values of different relaxation parameters form the feature vectors which are represented by a relatively small set of prototypes. The experiments evaluate a variety of FALVQ algorithms in terms of their ability to identify different tissues and discriminate between normal tissues and abnormalities.

Focal brain lesions induced with ultraviolet irradiation.

PubMed

Nakata, Mariko; Nagasaka, Kazuaki; Shimoda, Masayuki; Takashima, Ichiro; Yamamoto, Shinya

2018-05-22

Lesion and inactivation methods have played important roles in neuroscience studies. However, traditional techniques for creating a brain lesion are highly invasive, and control of lesion size and shape using these techniques is not easy. Here, we developed a novel method for creating a lesion on the cortical surface via 365 nm ultraviolet (UV) irradiation without breaking the dura mater. We demonstrated that 2.0 mWh UV irradiation, but not the same amount of non-UV light irradiation, induced an inverted bell-shaped lesion with neuronal loss and accumulation of glial cells. Moreover, the volume of the UV irradiation-induced lesion depended on the UV light exposure amount. We further succeeded in visualizing the lesioned site in a living animal using magnetic resonance imaging (MRI). Importantly, we also observed using an optical imaging technique that the spread of neural activation evoked by adjacent cortical stimulation disappeared only at the UV-irradiated site. In summary, UV irradiation can induce a focal brain lesion with a stable shape and size in a less invasive manner than traditional lesioning methods. This method is applicable to not only neuroscientific lesion experiments but also studies of the focal brain injury recovery process.

Fine-Granularity Functional Interaction Signatures for Characterization of Brain Conditions

PubMed Central

Hu, Xintao; Zhu, Dajiang; Lv, Peili; Li, Kaiming; Han, Junwei; Wang, Lihong; Shen, Dinggang; Guo, Lei; Liu, Tianming

2014-01-01

In the human brain, functional activity occurs at multiple spatial scales. Current studies on functional brain networks and their alterations in brain diseases via resting-state functional magnetic resonance imaging (rs-fMRI) are generally either at local scale (regionally confined analysis and inter-regional functional connectivity analysis) or at global scale (graph theoretic analysis). In contrast, inferring functional interaction at fine-granularity sub-network scale has not been adequately explored yet. Here our hypothesis is that functional interaction measured at fine-granularity subnetwork scale can provide new insight into the neural mechanisms of neurological and psychological conditions, thus offering complementary information for healthy and diseased population classification. In this paper, we derived fine-granularity functional interaction (FGFI) signatures in subjects with Mild Cognitive Impairment (MCI) and Schizophrenia by diffusion tensor imaging (DTI) and rsfMRI, and used patient-control classification experiments to evaluate the distinctiveness of the derived FGFI features. Our experimental results have shown that the FGFI features alone can achieve comparable classification performance compared with the commonly used inter-regional connectivity features. However, the classification performance can be substantially improved when FGFI features and inter-regional connectivity features are integrated, suggesting the complementary information achieved from the FGFI signatures. PMID:23319242

Some Problems for Representations of Brain Organization Based on Activation in Functional Imaging

ERIC Educational Resources Information Center

Sidtis, John J.

2007-01-01

Functional brain imaging has overshadowed traditional lesion studies in becoming the dominant approach to the study of brain-behavior relationships. The proponents of functional imaging studies frequently argue that this approach provides an advantage over lesion studies by observing normal brain activity in vivo without the disruptive effects of…

Efficient and robust model-to-image alignment using 3D scale-invariant features.

PubMed

Toews, Matthew; Wells, William M

2013-04-01

This paper presents feature-based alignment (FBA), a general method for efficient and robust model-to-image alignment. Volumetric images, e.g. CT scans of the human body, are modeled probabilistically as a collage of 3D scale-invariant image features within a normalized reference space. Features are incorporated as a latent random variable and marginalized out in computing a maximum a posteriori alignment solution. The model is learned from features extracted in pre-aligned training images, then fit to features extracted from a new image to identify a globally optimal locally linear alignment solution. Novel techniques are presented for determining local feature orientation and efficiently encoding feature intensity in 3D. Experiments involving difficult magnetic resonance (MR) images of the human brain demonstrate FBA achieves alignment accuracy similar to widely-used registration methods, while requiring a fraction of the memory and computation resources and offering a more robust, globally optimal solution. Experiments on CT human body scans demonstrate FBA as an effective system for automatic human body alignment where other alignment methods break down. Copyright © 2012 Elsevier B.V. All rights reserved.

Efficient and Robust Model-to-Image Alignment using 3D Scale-Invariant Features

PubMed Central

Toews, Matthew; Wells, William M.

2013-01-01

This paper presents feature-based alignment (FBA), a general method for efficient and robust model-to-image alignment. Volumetric images, e.g. CT scans of the human body, are modeled probabilistically as a collage of 3D scale-invariant image features within a normalized reference space. Features are incorporated as a latent random variable and marginalized out in computing a maximum a-posteriori alignment solution. The model is learned from features extracted in pre-aligned training images, then fit to features extracted from a new image to identify a globally optimal locally linear alignment solution. Novel techniques are presented for determining local feature orientation and efficiently encoding feature intensity in 3D. Experiments involving difficult magnetic resonance (MR) images of the human brain demonstrate FBA achieves alignment accuracy similar to widely-used registration methods, while requiring a fraction of the memory and computation resources and offering a more robust, globally optimal solution. Experiments on CT human body scans demonstrate FBA as an effective system for automatic human body alignment where other alignment methods break down. PMID:23265799

Phase contrast portal imaging using synchrotron radiation

NASA Astrophysics Data System (ADS)

Umetani, K.; Kondoh, T.

2014-07-01

Microbeam radiation therapy is an experimental form of radiation treatment with great potential to improve the treatment of many types of cancer. We applied a synchrotron radiation phase contrast technique to portal imaging to improve targeting accuracy for microbeam radiation therapy in experiments using small animals. An X-ray imaging detector was installed 6.0 m downstream from an object to produce a high-contrast edge enhancement effect in propagation-based phase contrast imaging. Images of a mouse head sample were obtained using therapeutic white synchrotron radiation with a mean beam energy of 130 keV. Compared to conventional portal images, remarkably clear images of bones surrounding the cerebrum were acquired in an air environment for positioning brain lesions with respect to the skull structure without confusion with overlapping surface structures.

Toward knowledge-enhanced viewing using encyclopedias and model-based segmentation

NASA Astrophysics Data System (ADS)

Kneser, Reinhard; Lehmann, Helko; Geller, Dieter; Qian, Yue-Chen; Weese, Jürgen

2009-02-01

To make accurate decisions based on imaging data, radiologists must associate the viewed imaging data with the corresponding anatomical structures. Furthermore, given a disease hypothesis possible image findings which verify the hypothesis must be considered and where and how they are expressed in the viewed images. If rare anatomical variants, rare pathologies, unfamiliar protocols, or ambiguous findings are present, external knowledge sources such as medical encyclopedias are consulted. These sources are accessed using keywords typically describing anatomical structures, image findings, pathologies. In this paper we present our vision of how a patient's imaging data can be automatically enhanced with anatomical knowledge as well as knowledge about image findings. On one hand, we propose the automatic annotation of the images with labels from a standard anatomical ontology. These labels are used as keywords for a medical encyclopedia such as STATdx to access anatomical descriptions, information about pathologies and image findings. On the other hand we envision encyclopedias to contain links to region- and finding-specific image processing algorithms. Then a finding is evaluated on an image by applying the respective algorithm in the associated anatomical region. Towards realization of our vision, we present our method and results of automatic annotation of anatomical structures in 3D MRI brain images. Thereby we develop a complex surface mesh model incorporating major structures of the brain and a model-based segmentation method. We demonstrate the validity by analyzing the results of several training and segmentation experiments with clinical data focusing particularly on the visual pathway.

Single-shot T2 mapping using overlapping-echo detachment planar imaging and a deep convolutional neural network.

PubMed

Cai, Congbo; Wang, Chao; Zeng, Yiqing; Cai, Shuhui; Liang, Dong; Wu, Yawen; Chen, Zhong; Ding, Xinghao; Zhong, Jianhui

2018-04-24

An end-to-end deep convolutional neural network (CNN) based on deep residual network (ResNet) was proposed to efficiently reconstruct reliable T 2 mapping from single-shot overlapping-echo detachment (OLED) planar imaging. The training dataset was obtained from simulations that were carried out on SPROM (Simulation with PRoduct Operator Matrix) software developed by our group. The relationship between the original OLED image containing two echo signals and the corresponding T 2 mapping was learned by ResNet training. After the ResNet was trained, it was applied to reconstruct the T 2 mapping from simulation and in vivo human brain data. Although the ResNet was trained entirely on simulated data, the trained network was generalized well to real human brain data. The results from simulation and in vivo human brain experiments show that the proposed method significantly outperforms the echo-detachment-based method. Reliable T 2 mapping with higher accuracy is achieved within 30 ms after the network has been trained, while the echo-detachment-based OLED reconstruction method took approximately 2 min. The proposed method will facilitate real-time dynamic and quantitative MR imaging via OLED sequence, and deep convolutional neural network has the potential to reconstruct maps from complex MRI sequences efficiently. © 2018 International Society for Magnetic Resonance in Medicine.

A three-wavelength multi-channel brain functional imager based on digital lock-in photon-counting technique

NASA Astrophysics Data System (ADS)

Ding, Xuemei; Wang, Bingyuan; Liu, Dongyuan; Zhang, Yao; He, Jie; Zhao, Huijuan; Gao, Feng

2018-02-01

During the past two decades there has been a dramatic rise in the use of functional near-infrared spectroscopy (fNIRS) as a neuroimaging technique in cognitive neuroscience research. Diffuse optical tomography (DOT) and optical topography (OT) can be employed as the optical imaging techniques for brain activity investigation. However, most current imagers with analogue detection are limited by sensitivity and dynamic range. Although photon-counting detection can significantly improve detection sensitivity, the intrinsic nature of sequential excitations reduces temporal resolution. To improve temporal resolution, sensitivity and dynamic range, we develop a multi-channel continuous-wave (CW) system for brain functional imaging based on a novel lock-in photon-counting technique. The system consists of 60 Light-emitting device (LED) sources at three wavelengths of 660nm, 780nm and 830nm, which are modulated by current-stabilized square-wave signals at different frequencies, and 12 photomultiplier tubes (PMT) based on lock-in photon-counting technique. This design combines the ultra-high sensitivity of the photon-counting technique with the parallelism of the digital lock-in technique. We can therefore acquire the diffused light intensity for all the source-detector pairs (SD-pairs) in parallel. The performance assessments of the system are conducted using phantom experiments, and demonstrate its excellent measurement linearity, negligible inter-channel crosstalk, strong noise robustness and high temporal resolution.

The effects of probe placement on measured flow velocity in transcranial Doppler ultrasound imaging in-vitro and in-vivo experiments

NASA Astrophysics Data System (ADS)

de Jong, Daan L. K.; Meel-van den Abeelen, Aisha S. S.; Lagro, Joep; Claassen, Jurgen A. H. R.; Slump, Cornelis H.

2014-03-01

The measurement of the blood flow in the middle cerebral artery (MCA) using transcranial Doppler ultrasound (US) imaging is clinically relevant for the study of cerebral autoregulation. Especially in the aging population, impairement of the autoregulation may coincide or relate to loss of perfusion and consequently loss of brain function. The cerebral autoregulation can be assessed by relating the blood pressure to the blood flow in the brain. Doppler US is a widely used, non-invasive method to measure the blood flow in the MCA. However, Doppler flow imaging is known to produce results that are dependent of the operator. The angle of the probe insonation with respect to the centerline of the blood vessel is a well known factor for output variability. In patients also the skull must be traversed and the MCA must be detected, influencing the US signal intensity. In this contribution we report two studies. We describe first an in-vitro setup to study the Doppler flow in a situation where the ground truth is known. Secondly, we report on a study with healthy volunteers where the effects of small probe displacements on the flow velocity signals are investigated. For the latter purpose, a special probe holder was designed to control the experiment.

Altered Brain Activity in Unipolar Depression Revisited: Meta-analyses of Neuroimaging Studies.

PubMed

Müller, Veronika I; Cieslik, Edna C; Serbanescu, Ilinca; Laird, Angela R; Fox, Peter T; Eickhoff, Simon B

2017-01-01

During the past 20 years, numerous neuroimaging experiments have investigated aberrant brain activation during cognitive and emotional processing in patients with unipolar depression (UD). The results of those investigations, however, vary considerably; moreover, previous meta-analyses also yielded inconsistent findings. To readdress aberrant brain activation in UD as evidenced by neuroimaging experiments on cognitive and/or emotional processing. Neuroimaging experiments published from January 1, 1997, to October 1, 2015, were identified by a literature search of PubMed, Web of Science, and Google Scholar using different combinations of the terms fMRI (functional magnetic resonance imaging), PET (positron emission tomography), neural, major depression, depression, major depressive disorder, unipolar depression, dysthymia, emotion, emotional, affective, cognitive, task, memory, working memory, inhibition, control, n-back, and Stroop. Neuroimaging experiments (using fMRI or PET) reporting whole-brain results of group comparisons between adults with UD and healthy control individuals as coordinates in a standard anatomic reference space and using an emotional or/and cognitive challenging task were selected. Coordinates reported to show significant activation differences between UD and healthy controls during emotional or cognitive processing were extracted. By using the revised activation likelihood estimation algorithm, different meta-analyses were calculated. Meta-analyses tested for brain regions consistently found to show aberrant brain activation in UD compared with controls. Analyses were calculated across all emotional processing experiments, all cognitive processing experiments, positive emotion processing, negative emotion processing, experiments using emotional face stimuli, experiments with a sex discrimination task, and memory processing. All meta-analyses were calculated across experiments independent of reporting an increase or decrease of activity in major depressive disorder. For meta-analyses with a minimum of 17 experiments available, separate analyses were performed for increases and decreases. In total, 57 studies with 99 individual neuroimaging experiments comprising in total 1058 patients were included; 34 of them tested cognitive and 65 emotional processing. Overall analyses across cognitive processing experiments (P > .29) and across emotional processing experiments (P > .47) revealed no significant results. Similarly, no convergence was found in analyses investigating positive (all P > .15), negative (all P > .76), or memory (all P > .48) processes. Analyses that restricted inclusion of confounds (eg, medication, comorbidity, age) did not change the results. Inconsistencies exist across individual experiments investigating aberrant brain activity in UD and replication problems across previous neuroimaging meta-analyses. For individual experiments, these inconsistencies may relate to use of uncorrected inference procedures, differences in experimental design and contrasts, or heterogeneous clinical populations; meta-analytically, differences may be attributable to varying inclusion and exclusion criteria or rather liberal statistical inference approaches.

Altered Brain Activity in Unipolar Depression Revisited Meta-analyses of Neuroimaging Studies

PubMed Central

Müller, Veronika I.; Cieslik, Edna C.; Serbanescu, Ilinca; Laird, Angela R.; Fox, Peter T.; Eickhoff, Simon B.

2017-01-01

IMPORTANCE During the past 20 years, numerous neuroimaging experiments have investigated aberrant brain activation during cognitive and emotional processing in patients with unipolar depression (UD). The results of those investigations, however, vary considerably; moreover, previous meta-analyses also yielded inconsistent findings. OBJECTIVE To readdress aberrant brain activation in UD as evidenced by neuroimaging experiments on cognitive and/or emotional processing. DATA SOURCES Neuroimaging experiments published from January 1, 1997, to October 1, 2015, were identified by a literature search of PubMed, Web of Science, and Google Scholar using different combinations of the terms fMRI (functional magnetic resonance imaging), PET (positron emission tomography), neural, major depression, depression, major depressive disorder, unipolar depression, dysthymia, emotion, emotional, affective, cognitive, task, memory, working memory, inhibition, control, n-back, and Stroop. STUDY SELECTION Neuroimaging experiments (using fMRI or PET) reporting whole-brain results of group comparisons between adults with UD and healthy control individuals as coordinates in a standard anatomic reference space and using an emotional or/and cognitive challenging task were selected. DATA EXTRACTION AND SYNTHESIS Coordinates reported to show significant activation differences between UD and healthy controls during emotional or cognitive processing were extracted. By using the revised activation likelihood estimation algorithm, different meta-analyses were calculated. MAIN OUTCOMES AND MEASURES Meta-analyses tested for brain regions consistently found to show aberrant brain activation in UD compared with controls. Analyses were calculated across all emotional processing experiments, all cognitive processing experiments, positive emotion processing, negative emotion processing, experiments using emotional face stimuli, experiments with a sex discrimination task, and memory processing. All meta-analyses were calculated across experiments independent of reporting an increase or decrease of activity in major depressive disorder. For meta-analyses with a minimum of 17 experiments available, separate analyses were performed for increases and decreases. RESULTS In total, 57 studies with 99 individual neuroimaging experiments comprising in total 1058 patients were included; 34 of them tested cognitive and 65 emotional processing. Overall analyses across cognitive processing experiments (P > .29) and across emotional processing experiments (P > .47) revealed no significant results. Similarly, no convergence was found in analyses investigating positive (all P > .15), negative (all P > .76), or memory (all P > .48) processes. Analyses that restricted inclusion of confounds (eg, medication, comorbidity, age) did not change the results. CONCLUSIONS AND RELEVANCE Inconsistencies exist across individual experiments investigating aberrant brain activity in UD and replication problems across previous neuroimaging meta-analyses. For individual experiments, these inconsistencies may relate to use of uncorrected inference procedures, differences in experimental design and contrasts, or heterogeneous clinical populations; meta-analytically, differences may be attributable to varying inclusion and exclusion criteria or rather liberal statistical inference approaches. PMID:27829086

Non-invasive imaging of the levels and effects of glutathione on the redox status of mouse brain using electron paramagnetic resonance imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Emoto, Miho C.; Department of Neurology, Sapporo Medical University School of Medicine, Sapporo, Hokkaido 060-8556; Matsuoka, Yuta

Glutathione (GSH) is the most abundant non-protein thiol that buffers reactive oxygen species in the brain. GSH does not reduce nitroxides directly, but in the presence of ascorbates, addition of GSH increases ascorbate-induced reduction of nitroxides. In this study, we used electron paramagnetic resonance (EPR) imaging and the nitroxide imaging probe, 3-methoxycarbonyl-2,2,5,5-tetramethyl-piperidine-1-oxyl (MCP), to non-invasively obtain spatially resolved redox data from mouse brains depleted of GSH with diethyl maleate compared to control. Based on the pharmacokinetics of the reduction reaction of MCP in the mouse heads, the pixel-based rate constant of its reduction reaction was calculated as an index ofmore » the redox status in vivo and mapped as a “redox map”. The obtained redox maps from control and GSH-depleted mouse brains showed a clear change in the brain redox status, which was due to the decreased levels of GSH in brains as measured by a biochemical assay. We observed a linear relationship between the reduction rate constant of MCP and the level of GSH for both control and GSH-depleted mouse brains. Using this relationship, the GSH level in the brain can be estimated from the redox map obtained with EPR imaging. - Highlights: • Redox status of glutathione-depleted mouse brain was examined with EPR imaging. • Redox status of mouse brain changed depending on glutathione (GSH) levels in brains. • Linear relationship between GSH levels and redox status in brains was found. • Using this relation, estimation of GSH levels in brains is possible from EPR images.« less

Recognition Memory: A Review of the Critical Findings and an Integrated Theory for Relating Them

ERIC Educational Resources Information Center

Malmberg, Kenneth J.

2008-01-01

The development of formal models has aided theoretical progress in recognition memory research. Here, I review the findings that are critical for testing them, including behavioral and brain imaging results of single-item recognition, plurality discrimination, and associative recognition experiments under a variety of testing conditions. I also…

Assessing Amide Proton Transfer (APT) MRI Contrast Origins in 9 L Gliosarcoma in the Rat Brain Using Proteomic Analysis.

PubMed

Yan, Kun; Fu, Zongming; Yang, Chen; Zhang, Kai; Jiang, Shanshan; Lee, Dong-Hoon; Heo, Hye-Young; Zhang, Yi; Cole, Robert N; Van Eyk, Jennifer E; Zhou, Jinyuan

2015-08-01

To investigate the biochemical origin of the amide photon transfer (APT)-weighted hyperintensity in brain tumors. Seven 9 L gliosarcoma-bearing rats were imaged at 4.7 T. Tumor and normal brain tissue samples of equal volumes were prepared with a coronal rat brain matrix and a tissue biopsy punch. The total tissue protein and the cytosolic subproteome were extracted from both samples. Protein samples were analyzed using two-dimensional gel electrophoresis, and the proteins with significant abundance changes were identified by mass spectrometry. There was a significant increase in the cytosolic protein concentration in the tumor, compared to normal brain regions, but the total protein concentrations were comparable. The protein profiles of the tumor and normal brain tissue differed significantly. Six cytosolic proteins, four endoplasmic reticulum proteins, and five secreted proteins were considerably upregulated in the tumor. Our experiments confirmed an increase in the cytosolic protein concentration in tumors and identified several key proteins that may cause APT-weighted hyperintensity.

Deformable Image Registration based on Similarity-Steered CNN Regression.

PubMed

Cao, Xiaohuan; Yang, Jianhua; Zhang, Jun; Nie, Dong; Kim, Min-Jeong; Wang, Qian; Shen, Dinggang

2017-09-01

Existing deformable registration methods require exhaustively iterative optimization, along with careful parameter tuning, to estimate the deformation field between images. Although some learning-based methods have been proposed for initiating deformation estimation, they are often template-specific and not flexible in practical use. In this paper, we propose a convolutional neural network (CNN) based regression model to directly learn the complex mapping from the input image pair (i.e., a pair of template and subject) to their corresponding deformation field. Specifically, our CNN architecture is designed in a patch-based manner to learn the complex mapping from the input patch pairs to their respective deformation field. First, the equalized active-points guided sampling strategy is introduced to facilitate accurate CNN model learning upon a limited image dataset. Then, the similarity-steered CNN architecture is designed, where we propose to add the auxiliary contextual cue, i.e., the similarity between input patches, to more directly guide the learning process. Experiments on different brain image datasets demonstrate promising registration performance based on our CNN model. Furthermore, it is found that the trained CNN model from one dataset can be successfully transferred to another dataset, although brain appearances across datasets are quite variable.

Dynamic Circuitry for Updating Spatial Representations: III. From Neurons to Behavior

PubMed Central

Berman, Rebecca A.; Heiser, Laura M.; Dunn, Catherine A.; Saunders, Richard C.; Colby, Carol L.

2008-01-01

Each time the eyes move, the visual system must adjust internal representations to account for the accompanying shift in the retinal image. In the lateral intraparietal cortex (LIP), neurons update the spatial representations of salient stimuli when the eyes move. In previous experiments, we found that split-brain monkeys were impaired on double-step saccade sequences that required updating across visual hemifields, as compared to within hemifield (Berman et al. 2005; Heiser et al. 2005). Here we describe a subsequent experiment to characterize the relationship between behavioral performance and neural activity in LIP in the split-brain monkey. We recorded from single LIP neurons while split-brain and intact monkeys performed two conditions of the double-step saccade task: one required across-hemifield updating and the other within-hemifield updating. We found that, despite extensive experience with the task, the split-brain monkeys were significantly more accurate for within-hemifield as compared to across-hemifield sequences. In parallel, we found that population activity in LIP of the split-brain monkeys was significantly stronger for within-hemifield as compared to across-hemifield conditions of the double-step task. In contrast, in the normal monkey, both the average behavioral performance and population activity showed no bias toward the within-hemifield condition. Finally, we found that the difference between within-hemifield and across-hemifield performance in the split-brain monkeys was reflected at the level of single neuron activity in LIP. These findings indicate that remapping activity in area LIP is present in the split-brain monkey for the double-step task and co-varies with spatial behavior on within-hemifield compared to across-hemifield sequences. PMID:17493922

Imaging of brain metastases.

PubMed

Fink, Kathleen R; Fink, James R

2013-01-01

Imaging plays a key role in the diagnosis of central nervous system (CNS) metastasis. Imaging is used to detect metastases in patients with known malignancies and new neurological signs or symptoms, as well as to screen for CNS involvement in patients with known cancer. Computed tomography (CT) and magnetic resonance imaging (MRI) are the key imaging modalities used in the diagnosis of brain metastases. In difficult cases, such as newly diagnosed solitary enhancing brain lesions in patients without known malignancy, advanced imaging techniques including proton magnetic resonance spectroscopy (MRS), contrast enhanced magnetic resonance perfusion (MRP), diffusion weighted imaging (DWI), and diffusion tensor imaging (DTI) may aid in arriving at the correct diagnosis. This image-rich review discusses the imaging evaluation of patients with suspected intracranial involvement and malignancy, describes typical imaging findings of parenchymal brain metastasis on CT and MRI, and provides clues to specific histological diagnoses such as the presence of hemorrhage. Additionally, the role of advanced imaging techniques is reviewed, specifically in the context of differentiating metastasis from high-grade glioma and other solitary enhancing brain lesions. Extra-axial CNS involvement by metastases, including pachymeningeal and leptomeningeal metastases is also briefly reviewed.

Registration of 3D fetal neurosonography and MRI☆

PubMed Central

Kuklisova-Murgasova, Maria; Cifor, Amalia; Napolitano, Raffaele; Papageorghiou, Aris; Quaghebeur, Gerardine; Rutherford, Mary A.; Hajnal, Joseph V.; Noble, J. Alison; Schnabel, Julia A.

2013-01-01

We propose a method for registration of 3D fetal brain ultrasound with a reconstructed magnetic resonance fetal brain volume. This method, for the first time, allows the alignment of models of the fetal brain built from magnetic resonance images with 3D fetal brain ultrasound, opening possibilities to develop new, prior information based image analysis methods for 3D fetal neurosonography. The reconstructed magnetic resonance volume is first segmented using a probabilistic atlas and a pseudo ultrasound image volume is simulated from the segmentation. This pseudo ultrasound image is then affinely aligned with clinical ultrasound fetal brain volumes using a robust block-matching approach that can deal with intensity artefacts and missing features in the ultrasound images. A qualitative and quantitative evaluation demonstrates good performance of the method for our application, in comparison with other tested approaches. The intensity average of 27 ultrasound images co-aligned with the pseudo ultrasound template shows good correlation with anatomy of the fetal brain as seen in the reconstructed magnetic resonance image. PMID:23969169

Advantages in functional imaging of the brain.

PubMed

Mier, Walter; Mier, Daniela

2015-01-01

As neuronal pathologies cause only minor morphological alterations, molecular imaging techniques are a prerequisite for the study of diseases of the brain. The development of molecular probes that specifically bind biochemical markers and the advances of instrumentation have revolutionized the possibilities to gain insight into the human brain organization and beyond this-visualize structure-function and brain-behavior relationships. The review describes the development and current applications of functional brain imaging techniques with a focus on applications in psychiatry. A historical overview of the development of functional imaging is followed by the portrayal of the principles and applications of positron emission tomography (PET) and functional magnetic resonance imaging (fMRI), two key molecular imaging techniques that have revolutionized the ability to image molecular processes in the brain. We conclude that the juxtaposition of PET and fMRI in hybrid PET/MRI scanners enhances the significance of both modalities for research in neurology and psychiatry and might pave the way for a new area of personalized medicine.

A validation framework for brain tumor segmentation.

PubMed

Archip, Neculai; Jolesz, Ferenc A; Warfield, Simon K

2007-10-01

We introduce a validation framework for the segmentation of brain tumors from magnetic resonance (MR) images. A novel unsupervised semiautomatic brain tumor segmentation algorithm is also presented. The proposed framework consists of 1) T1-weighted MR images of patients with brain tumors, 2) segmentation of brain tumors performed by four independent experts, 3) segmentation of brain tumors generated by a semiautomatic algorithm, and 4) a software tool that estimates the performance of segmentation algorithms. We demonstrate the validation of the novel segmentation algorithm within the proposed framework. We show its performance and compare it with existent segmentation. The image datasets and software are available at http://www.brain-tumor-repository.org/. We present an Internet resource that provides access to MR brain tumor image data and segmentation that can be openly used by the research community. Its purpose is to encourage the development and evaluation of segmentation methods by providing raw test and image data, human expert segmentation results, and methods for comparing segmentation results.

Brain temperature in volunteers subjected to intranasal cooling.

PubMed

Covaciu, L; Weis, J; Bengtsson, C; Allers, M; Lunderquist, A; Ahlström, H; Rubertsson, S

2011-08-01

Intranasal cooling can be used to initiate therapeutic hypothermia. However, direct measurement of brain temperature is difficult and the intra-cerebral distribution of temperature changes with cooling is unknown. The purpose of this study was to measure the brain temperature of human volunteers subjected to intranasal cooling using non-invasive magnetic resonance (MR) methods. Intranasal balloons catheters circulated with saline at 20°C were applied for 60 min in ten awake volunteers. No sedation was used. Brain temperature changes were measured and mapped using MR spectroscopic imaging (MRSI) and phase-mapping techniques. Heart rate and blood pressure were monitored throughout the experiment. Rectal temperature was measured before and after the cooling. Mini Mental State Examination (MMSE) test and nasal inspection were done before and after the cooling. Questionnaires about the subjects' personal experience were completed after the experiment. Brain temperature decrease measured by MRSI was -1.7 ± 0.8°C and by phase-mapping -1.8 ± 0.9°C (n = 9) at the end of cooling. Spatial distribution of temperature changes was relatively uniform. Rectal temperature decreased by -0.5 ± 0.3°C (n = 5). The physiological parameters were stable and no shivering was reported. The volunteers remained alert during cooling and no cognitive dysfunctions were apparent in the MMSE test. Postcooling nasal examination detected increased nasal secretion in nine of the ten volunteers. Volunteers' acceptance of the method was good. Both MR techniques revealed brain temperature reductions after 60 min of intranasal cooling with balloons circulated with saline at 20°C in awake, unsedated volunteers.

Graphene-based carbon-layered electrode array technology for neural imaging and optogenetic applications

PubMed Central

Park, Dong-Wook; Schendel, Amelia A.; Mikael, Solomon; Brodnick, Sarah K.; Richner, Thomas J.; Ness, Jared P.; Hayat, Mohammed R.; Atry, Farid; Frye, Seth T.; Pashaie, Ramin; Thongpang, Sanitta; Ma, Zhenqiang; Williams, Justin C.

2014-01-01

Neural micro-electrode arrays that are transparent over a broad wavelength spectrum from ultraviolet to infrared could allow for simultaneous electrophysiology and optical imaging, as well as optogenetic modulation of the underlying brain tissue. The long-term biocompatibility and reliability of neural micro-electrodes also require their mechanical flexibility and compliance with soft tissues. Here we present a graphene-based, carbon-layered electrode array (CLEAR) device, which can be implanted on the brain surface in rodents for high-resolution neurophysiological recording. We characterize optical transparency of the device at >90% transmission over the ultraviolet to infrared spectrum and demonstrate its utility through optical interface experiments that use this broad spectrum transparency. These include optogenetic activation of focal cortical areas directly beneath electrodes, in vivo imaging of the cortical vasculature via fluorescence microscopy and 3D optical coherence tomography. This study demonstrates an array of interfacing abilities of the CLEAR device and its utility for neural applications. PMID:25327513

Functional imaging of the human brain using a modular, fibre-less, high-density diffuse optical tomography system.

PubMed

Chitnis, Danial; Cooper, Robert J; Dempsey, Laura; Powell, Samuel; Quaggia, Simone; Highton, David; Elwell, Clare; Hebden, Jeremy C; Everdell, Nicholas L

2016-10-01

We present the first three-dimensional, functional images of the human brain to be obtained using a fibre-less, high-density diffuse optical tomography system. Our technology consists of independent, miniaturized, silicone-encapsulated DOT modules that can be placed directly on the scalp. Four of these modules were arranged to provide up to 128, dual-wavelength measurement channels over a scalp area of approximately 60 × 65 mm 2 . Using a series of motor-cortex stimulation experiments, we demonstrate that this system can obtain high-quality, continuous-wave measurements at source-detector separations ranging from 14 to 55 mm in adults, in the presence of hair. We identify robust haemodynamic response functions in 5 out of 5 subjects, and present diffuse optical tomography images that depict functional haemodynamic responses that are well-localized in all three dimensions at both the individual and group levels. This prototype modular system paves the way for a new generation of wearable, wireless, high-density optical neuroimaging technologies.

Integrated software for the detection of epileptogenic zones in refractory epilepsy.

PubMed

Mottini, Alejandro; Miceli, Franco; Albin, Germán; Nuñez, Margarita; Ferrándo, Rodolfo; Aguerrebere, Cecilia; Fernandez, Alicia

2010-01-01

In this paper we present an integrated software designed to help nuclear medicine physicians in the detection of epileptogenic zones (EZ) by means of ictal-interictal SPECT and MR images. This tool was designed to be flexible, friendly and efficient. A novel detection method was included (A-contrario) along with the classical detection method (Subtraction analysis). The software's performance was evaluated with two separate sets of validation studies: visual interpretation of 12 patient images by an experimented observer and objective analysis of virtual brain phantom experiments by proposed numerical observers. Our results support the potential use of the proposed software to help nuclear medicine physicians in the detection of EZ in clinical practice.

Implementation of magnetic resonance elastography for the investigation of traumatic brain injuries

NASA Astrophysics Data System (ADS)

Boulet, Thomas

Magnetic resonance elastography (MRE) is a potentially transformative imaging modality allowing local and non-invasive measurement of biological tissue mechanical properties. It uses a specific phase contrast MR pulse sequence to measure induced vibratory motion in soft material, from which material properties can be estimated. Compared to other imaging techniques, MRE is able to detect tissue pathology at early stages by quantifying the changes in tissue stiffness associated with diseases. In an effort to develop the technique and improve its capabilities, two inversion algorithms were written to evaluate viscoelastic properties from the measured displacements fields. The first one was based on a direct algebraic inversion of the differential equation of motion, which decouples under certain simplifying assumptions, and featured a spatio-temporal multi-directional filter. The second one relies on a finite element discretization of the governing equations to perform a direct inversion. Several applications of this technique have also been investigated, including the estimation of mechanical parameters in various gel phantoms and polymers, as well as the use of MRE as a diagnostic tools for brain disorders. In this respect, the particular interest was to investigate traumatic brain injury (TBI), a complex and diverse injury affecting 1.7 million Americans annually. The sensitivity of MRE to TBI was first assessed on excised rat brains subjected to a controlled cortical impact (CCI) injury, before execution of in vivo experiments in mice. MRE was also applied in vivo on mouse models of medulloblastoma tumors and multiple sclerosis. These studies showed the potential of MRE in mapping the brain mechanically and providing non-invasive in vivo imaging markers for neuropathology and pathogenesis of brain diseases. Furthermore, MRE can easily be translatable to clinical settings; thus, while this technique may not be used directly to diagnose different abnormalities in the brain at this time, it may be helpful to detect abnormalities, follow therapies, and trace macroscopic changes that are not seen by conventional methods with clinical relevance.

Neural Correlates of Stress and Favorite-Food Cue Exposure in Adolescents: A Functional Magnetic Resonance Imaging Study

PubMed Central

Hommer, Rebecca E.; Seo, Dongju; Lacadie, Cheryl M.; Chaplin, Tara M.; Mayes, Linda C.; Sinha, Rajita; Potenza, Marc N.

2012-01-01

Adolescence is a critical period of neurodevelopment for stress and appetitive processing, as well as a time of increased vulnerability to stress and engagement in risky behaviors. The current study was conducted to examine brain activation patterns during stress and favorite-food-cue experiences relative to a neutral-relaxing condition in adolescents. Functional magnetic resonance imaging was employed using individualized script-driven guided imagery to compare brain responses to such experiences in 43 adolescents. Main effects of condition and gender were found, without a significant gender-by-condition interaction. Stress imagery, relative to neutral, was associated with activation in the caudate, thalamus, left hippocampus/parahippocampal gyrus, midbrain, left superior/middle temporal gyrus, and right posterior cerebellum. Appetitive imagery of favorite food was associated with caudate, thalamus, and midbrain activation compared to the neutral-relaxing condition. To understand neural correlates of anxiety and craving, subjective (self-reported) measures of stress-induced anxiety and favorite-food-cue-induced craving were correlated with brain activity during stress and appetitive food-cue conditions, respectively. High self-reported stress-induced anxiety was associated with hypoactivity in the striatum, thalamus, hippocampus and midbrain. Self-reported favorite-food-cue-induced craving was associated with blunted activity in cortical-striatal regions, including the right dorsal and ventral striatum, medial prefrontal cortex, motor cortex, and left anterior cingulate cortex. The current findings in adolescents indicate the activation of predominantly subcortical-striatal regions in the processing of stressful and appetitive experiences and link hypoactive striatal circuits to self-reported stress-induced anxiety and cue-induced favorite-food craving. PMID:22504779

Neural correlates of stress and favorite-food cue exposure in adolescents: a functional magnetic resonance imaging study.

PubMed

Hommer, Rebecca E; Seo, Dongju; Lacadie, Cheryl M; Chaplin, Tara M; Mayes, Linda C; Sinha, Rajita; Potenza, Marc N

2013-10-01

Adolescence is a critical period of neurodevelopment for stress and appetitive processing, as well as a time of increased vulnerability to stress and engagement in risky behaviors. This study was conducted to examine brain activation patterns during stress and favorite-food-cue experiences relative to a neutral-relaxing condition in adolescents. Functional magnetic resonance imaging was employed using individualized script-driven guided imagery to compare brain responses with such experiences in 43 adolescents. Main effects of condition and gender were found, without a significant gender-by-condition interaction. Stress imagery, relative to neutral, was associated with activation in the caudate, thalamus, left hippocampus/parahippocampal gyrus, midbrain, left superior/middle temporal gyrus, and right posterior cerebellum. Appetitive imagery of favorite food was associated with caudate, thalamus, and midbrain activation compared with the neutral-relaxing condition. To understand neural correlates of anxiety and craving, subjective (self-reported) measures of stress-induced anxiety and favorite-food-cue-induced craving were correlated with brain activity during stress and appetitive food-cue conditions, respectively. High self-reported stress-induced anxiety was associated with hypoactivity in the striatum, thalamus, hippocampus, and midbrain. Self-reported favorite-food-cue-induced craving was associated with blunted activity in cortical-striatal regions, including the right dorsal and ventral striatum, medial prefrontal cortex, motor cortex, and left anterior cingulate cortex. These findings in adolescents indicate the activation of predominantly subcortical-striatal regions in the processing of stressful and appetitive experiences and link hypoactive striatal circuits to self-reported stress-induced anxiety and cue-induced favorite-food craving. Copyright © 2012 Wiley Periodicals, Inc.

In-vivo imaging of the morphology and blood perfusion of brain tumours in rats with UHR-OCT (Conference Presentation)

NASA Astrophysics Data System (ADS)

Bizheva, Kostadinka; Tan, Bingyao; Fisher, Carl J.; Mason, Erik; Lilge, Lothar D.

2017-02-01

Brain tumors are characterized with morphological changes at cellular level such as enlarged, non-spherical nuclei, microcalcifications, cysts, etc., and are highly vascularized. In this study, two research-grade optical coherence tomography (OCT) systems operating at 800 nm and 1060 nm with axial resolution of 0.95 µm and 3.5 µm in biological tissue respectively, were used to image in vivo and ex vivo the structure of brain tumours in rats. Female Fischer 344 rats were used for this study, which has received ethics clearance by the Animal Research Ethics Committees of the University of Waterloo and the University Health Network, Toronto. Brain tumours were induced by injection of rat brain cancer cell line (RG2 glioma) through a small craniotomy. Presence of brain tumours was verified by MRI imaging on day 7 post tumour cells injection. The in vivo OCT imaging session was conducted on day 14 of the study with the 1060 nm OCT system and both morphological OCT, Doppler OCT and OMAG images were acquired from the brain tumour and the surrounding healthy brain tissue. After completion of the imaging procedure, the brains were harvested, fixed in formalin and reimaged after 2 weeks with the 800 nm OCT system. The in vivo and ex vivo OCT morphological images were correlated with H and E histology. Results from this study demonstrate that UHR-OCT can distinguish between healthy and cancerous brain tissue based on differences in structural and vascular pattern.

In vivo visualization and ex vivo quantification of murine breast cancer cells in the mouse brain using MRI cell tracking and electron paramagnetic resonance.

PubMed

Danhier, Pierre; Magat, Julie; Levêque, Philippe; De Preter, Géraldine; Porporato, Paolo E; Bouzin, Caroline; Jordan, Bénédicte F; Demeur, Gladys; Haufroid, Vincent; Feron, Olivier; Sonveaux, Pierre; Gallez, Bernard

2015-03-01

Cell tracking could be useful to elucidate fundamental processes of cancer biology such as metastasis. The aim of this study was to visualize, using MRI, and to quantify, using electron paramagnetic resonance (EPR), the entrapment of murine breast cancer cells labeled with superparamagnetic iron oxide particles (SPIOs) in the mouse brain after intracardiac injection. For this purpose, luciferase-expressing murine 4 T1-luc breast cancer cells were labeled with fluorescent Molday ION Rhodamine B SPIOs. Following intracardiac injection, SPIO-labeled 4 T1-luc cells were imaged using multiple gradient-echo sequences. Ex vivo iron oxide quantification in the mouse brain was performed using EPR (9 GHz). The long-term fate of 4 T1-luc cells after injection was characterized using bioluminescence imaging (BLI), brain MRI and immunofluorescence. We observed hypointense spots due to SPIO-labeled cells in the mouse brain 4 h after injection on T2 *-weighted images. Histology studies showed that SPIO-labeled cancer cells were localized within blood vessels shortly after delivery. Ex vivo quantification of SPIOs showed that less than 1% of the injected cells were taken up by the mouse brain after injection. MRI experiments did not reveal the development of macrometastases in the mouse brain several days after injection, but immunofluorescence studies demonstrated that these cells found in the brain established micrometastases. Concerning the metastatic patterns of 4 T1-luc cells, an EPR biodistribution study demonstrated that SPIO-labeled 4 T1-luc cells were also entrapped in the lungs of mice after intracardiac injection. BLI performed 6 days after injection of 4 T1-luc cells showed that this cell line formed macrometastases in the lungs and in the bones. Conclusively, EPR and MRI were found to be complementary for cell tracking applications. MRI cell tracking at 11.7 T allowed sensitive detection of isolated SPIO-labeled cells in the mouse brain, whereas EPR allowed the assessment of the number of SPIO-labeled cells in organs shortly after injection. Copyright © 2015 John Wiley & Sons, Ltd.

Wide-bore 1.5 T MRI-guided deep brain stimulation surgery: initial experience and technique comparison.

PubMed

Sillay, Karl A; Rusy, Deborah; Buyan-Dent, Laura; Ninman, Nancy L; Vigen, Karl K

2014-12-01

We report results of the initial experience with magnetic resonance image (MRI)-guided implantation of subthalamic nucleus (STN) deep brain stimulating (DBS) electrodes at the University of Wisconsin after having employed frame-based stereotaxy with previously available MR imaging techniques and microelectrode recording for STN DBS surgeries. Ten patients underwent MRI-guided DBS implantation of 20 electrodes between April 2011 and March 2013. The procedure was performed in a purpose-built intraoperative MRI suite configured specifically to allow MRI-guided DBS, using a wide-bore (70 cm) MRI system. Trajectory guidance was accomplished with commercially available system consisting of an MR-visible skull-mounted aiming device and a software guidance system processing intraoperatively acquired iterative MRI scans. A total of 10 patients (5 male, 5 female)-representative of the Parkinson Disease (PD) population-were operated on with standard technique and underwent 20 electrode placements under MRI-guided bilateral STN-targeted DBS placement. All patients completed the procedure with electrodes successfully placed in the STN. Procedure time improved with experience. Our initial experience confirms the safety of MRI-guided DBS, setting the stage for future investigations combining physiology and MRI guidance. Further follow-up is required to compare the efficacy of the MRI-guided surgery cohort to that of traditional frame-based stereotaxy. Copyright © 2014 Elsevier B.V. All rights reserved.

Imaging of Glial Cell Activation and White Matter Integrity in Brains of Active and Recently Retired National Football League Players.

PubMed

Coughlin, Jennifer M; Wang, Yuchuan; Minn, Il; Bienko, Nicholas; Ambinder, Emily B; Xu, Xin; Peters, Matthew E; Dougherty, John W; Vranesic, Melin; Koo, Soo Min; Ahn, Hye-Hyun; Lee, Merton; Cottrell, Chris; Sair, Haris I; Sawa, Akira; Munro, Cynthia A; Nowinski, Christopher J; Dannals, Robert F; Lyketsos, Constantine G; Kassiou, Michael; Smith, Gwenn; Caffo, Brian; Mori, Susumu; Guilarte, Tomas R; Pomper, Martin G

2017-01-01

Microglia, the resident immune cells of the central nervous system, play an important role in the brain's response to injury and neurodegenerative processes. It has been proposed that prolonged microglial activation occurs after single and repeated traumatic brain injury, possibly through sports-related concussive and subconcussive injuries. Limited in vivo brain imaging studies months to years after individuals experience a single moderate to severe traumatic brain injury suggest widespread persistent microglial activation, but there has been little study of persistent glial cell activity in brains of athletes with sports-related traumatic brain injury. To measure translocator protein 18 kDa (TSPO), a marker of activated glial cell response, in a cohort of National Football League (NFL) players and control participants, and to report measures of white matter integrity. This cross-sectional, case-control study included young active (n = 4) or former (n = 10) NFL players recruited from across the United States, and 16 age-, sex-, highest educational level-, and body mass index-matched control participants. This study was conducted at an academic research institution in Baltimore, Maryland, from January 29, 2015, to February 18, 2016. Positron emission tomography-based regional measures of TSPO using [11C]DPA-713, diffusion tensor imaging measures of regional white matter integrity, regional volumes on structural magnetic resonance imaging, and neuropsychological performance. The mean (SD) ages of the 14 NFL participants and 16 control participants were 31.3 (6.1) years and 27.6 (4.9) years, respectively. Players reported a mean (SD) of 7.0 (6.4) years (range, 1-21 years) since the last self-reported concussion. Using [11C]DPA-713 positron emission tomographic data from 12 active or former NFL players and 11 matched control participants, the NFL players showed higher total distribution volume in 8 of the 12 brain regions examined (P < .004). We also observed limited change in white matter fractional anisotropy and mean diffusivity in 13 players compared with 15 control participants. In contrast, these young players did not differ from control participants in regional brain volumes or in neuropsychological performance. The results suggest that localized brain injury and repair, indicated by higher TSPO signal and white matter changes, may be associated with NFL play. Further study is needed to confirm these findings and to determine whether TSPO signal and white matter changes in young NFL athletes are related to later onset of neuropsychiatric symptoms.

Understanding Others' Regret: A fMRI Study

PubMed Central

Canessa, Nicola; Motterlini, Matteo; Di Dio, Cinzia; Perani, Daniela; Scifo, Paola; Cappa, Stefano F.; Rizzolatti, Giacomo

2009-01-01

Previous studies showed that the understanding of others' basic emotional experiences is based on a “resonant” mechanism, i.e., on the reactivation, in the observer's brain, of the cerebral areas associated with those experiences. The present study aimed to investigate whether the same neural mechanism is activated both when experiencing and attending complex, cognitively-generated, emotions. A gambling task and functional-Magnetic-Resonance-Imaging (fMRI) were used to test this hypothesis using regret, the negative cognitively-based emotion resulting from an unfavorable counterfactual comparison between the outcomes of chosen and discarded options. Do the same brain structures that mediate the experience of regret become active in the observation of situations eliciting regret in another individual? Here we show that observing the regretful outcomes of someone else's choices activates the same regions that are activated during a first-person experience of regret, i.e. the ventromedial prefrontal cortex, anterior cingulate cortex and hippocampus. These results extend the possible role of a mirror-like mechanism beyond basic emotions. PMID:19826471

Attention, automaticity, and awareness in synesthesia.

PubMed

Mattingley, Jason B

2009-03-01

The phenomenon of synesthesia has occupied the thoughts of philosophers and artists for decades. With the advent modern behavioral and brain imaging techniques, scientific research on synesthesia has also moved into the mainstream of thought. Here I provide a cognitive neuroscience perspective on the condition, with a particular emphasis on grapheme-color synesthesia, the most common variant, in which individuals report vivid and consistent experiences of color in association with numerals, letters, and words. Behavioral studies have revealed several fundamental properties of induced synesthetic colors. First, although they seem to arise automatically, without the need for voluntary control, they are strongly modulated by selective attention. Second, they attain salience relatively early in visual processing, and so can influence perceptual judgments and guide focal attention in cluttered, achromatic displays. Third, brain activity during synesthetic color experiences arises from within the ventral temporal lobe, including color-selective area V4. It has been speculated that grapheme-color synesthesia arises from disinhibited feedback or abnormal cross-wiring between brain regions involved in extracting visual form and color.

Advancing multiscale structural mapping of the brain through fluorescence imaging and analysis across length scales

PubMed Central

Hogstrom, L. J.; Guo, S. M.; Murugadoss, K.; Bathe, M.

2016-01-01

Brain function emerges from hierarchical neuronal structure that spans orders of magnitude in length scale, from the nanometre-scale organization of synaptic proteins to the macroscopic wiring of neuronal circuits. Because the synaptic electrochemical signal transmission that drives brain function ultimately relies on the organization of neuronal circuits, understanding brain function requires an understanding of the principles that determine hierarchical neuronal structure in living or intact organisms. Recent advances in fluorescence imaging now enable quantitative characterization of neuronal structure across length scales, ranging from single-molecule localization using super-resolution imaging to whole-brain imaging using light-sheet microscopy on cleared samples. These tools, together with correlative electron microscopy and magnetic resonance imaging at the nanoscopic and macroscopic scales, respectively, now facilitate our ability to probe brain structure across its full range of length scales with cellular and molecular specificity. As these imaging datasets become increasingly accessible to researchers, novel statistical and computational frameworks will play an increasing role in efforts to relate hierarchical brain structure to its function. In this perspective, we discuss several prominent experimental advances that are ushering in a new era of quantitative fluorescence-based imaging in neuroscience along with novel computational and statistical strategies that are helping to distil our understanding of complex brain structure. PMID:26855758

Brain injury tolerance limit based on computation of axonal strain.

PubMed

Sahoo, Debasis; Deck, Caroline; Willinger, Rémy

2016-07-01

Traumatic brain injury (TBI) is the leading cause of death and permanent impairment over the last decades. In both the severe and mild TBIs, diffuse axonal injury (DAI) is the most common pathology and leads to axonal degeneration. Computation of axonal strain by using finite element head model in numerical simulation can enlighten the DAI mechanism and help to establish advanced head injury criteria. The main objective of this study is to develop a brain injury criterion based on computation of axonal strain. To achieve the objective a state-of-the-art finite element head model with enhanced brain and skull material laws, was used for numerical computation of real world head trauma. The implementation of new medical imaging data such as, fractional anisotropy and axonal fiber orientation from Diffusion Tensor Imaging (DTI) of 12 healthy patients into the finite element brain model was performed to improve the brain constitutive material law with more efficient heterogeneous anisotropic visco hyper-elastic material law. The brain behavior has been validated in terms of brain deformation against Hardy et al. (2001), Hardy et al. (2007), and in terms of brain pressure against Nahum et al. (1977) and Trosseille et al. (1992) experiments. Verification of model stability has been conducted as well. Further, 109 well-documented TBI cases were simulated and axonal strain computed to derive brain injury tolerance curve. Based on an in-depth statistical analysis of different intra-cerebral parameters (brain axonal strain rate, axonal strain, first principal strain, Von Mises strain, first principal stress, Von Mises stress, CSDM (0.10), CSDM (0.15) and CSDM (0.25)), it was shown that axonal strain was the most appropriate candidate parameter to predict DAI. The proposed brain injury tolerance limit for a 50% risk of DAI has been established at 14.65% of axonal strain. This study provides a key step for a realistic novel injury metric for DAI. Copyright © 2016 Elsevier Ltd. All rights reserved.

Brain-based decoding of mentally imagined film clips and sounds reveals experience-based information patterns in film professionals.

PubMed

de Borst, Aline W; Valente, Giancarlo; Jääskeläinen, Iiro P; Tikka, Pia

2016-04-01

In the perceptual domain, it has been shown that the human brain is strongly shaped through experience, leading to expertise in highly-skilled professionals. What has remained unclear is whether specialization also shapes brain networks underlying mental imagery. In our fMRI study, we aimed to uncover modality-specific mental imagery specialization of film experts. Using multi-voxel pattern analysis we decoded from brain activity of professional cinematographers and sound designers whether they were imagining sounds or images of particular film clips. In each expert group distinct multi-voxel patterns, specific for the modality of their expertise, were found during classification of imagery modality. These patterns were mainly localized in the occipito-temporal and parietal cortex for cinematographers and in the auditory cortex for sound designers. We also found generalized patterns across perception and imagery that were distinct for the two expert groups: they involved frontal cortex for the cinematographers and temporal cortex for the sound designers. Notably, the mental representations of film clips and sounds of cinematographers contained information that went beyond modality-specificity. We were able to successfully decode the implicit presence of film genre from brain activity during mental imagery in cinematographers. The results extend existing neuroimaging literature on expertise into the domain of mental imagery and show that experience in visual versus auditory imagery can alter the representation of information in modality-specific association cortices. Copyright © 2016 Elsevier Inc. All rights reserved.

A multi-purpose electromagnetic actuator for magnetic resonance elastography.

PubMed

Feng, Yuan; Zhu, Mo; Qiu, Suhao; Shen, Ping; Ma, Shengyuan; Zhao, Xuefeng; Hu, Chun-Hong; Guo, Liang

2018-04-19

An electromagnetic actuator was designed for magnetic resonance elastography (MRE). The actuator is unique in that it is simple, portable, and capable of brain, abdomen, and phantom imagings. A custom-built control unit was used for controlling the vibration frequency and synchronizing the trigger signals. An actuation unit was built and mounted on the specifically designed clamp and holders for different imaging applications. MRE experiments with respect to gel phantoms, brain, and liver showed that the actuator could produce stable and consistent mechanical waves. Estimated shear modulus using local frequency estimate method demonstrated that the measurement results were in line with that from MRE studies using different actuation systems. The relatively easy setup procedure and simple design indicated that the actuator system had the potential to be applied in many different clinical studies. Copyright © 2018 Elsevier Inc. All rights reserved.

Detecting stripe artifacts in ultrasound images.

PubMed

Maciak, Adam; Kier, Christian; Seidel, Günter; Meyer-Wiethe, Karsten; Hofmann, Ulrich G

2009-10-01

Brain perfusion diseases such as acute ischemic stroke are detectable through computed tomography (CT)-/magnetic resonance imaging (MRI)-based methods. An alternative approach makes use of ultrasound imaging. In this low-cost bedside method, noise and artifacts degrade the imaging process. Especially stripe artifacts show a similar signal behavior compared to acute stroke or brain perfusion diseases. This document describes how stripe artifacts can be detected and eliminated in ultrasound images obtained through harmonic imaging (HI). On the basis of this new method, both proper identification of areas with critically reduced brain tissue perfusion and classification between brain perfusion defects and ultrasound stripe artifacts are made possible.

Achromatic synesthesias - a functional magnetic resonance imaging study.

PubMed

Melero, H; Ríos-Lago, M; Peña-Melián, A; Álvarez-Linera, J

2014-09-01

Grapheme-color synesthetes experience consistent, automatic and idiosyncratic colors associated with specific letters and numbers. Frequently, these specific associations exhibit achromatic synesthetic qualities (e.g. white, black or gray). In this study, we have investigated for the first time the neural basis of achromatic synesthesias, their relationship to chromatic synesthesias and the achromatic congruency effect in order to understand not only synesthetic color but also other components of the synesthetic experience. To achieve this aim, functional magnetic resonance imaging experiments were performed in a group of associator grapheme-color synesthetes and matched controls who were stimulated with real chromatic and achromatic stimuli (Mondrians), and with letters and numbers that elicited different types of grapheme-color synesthesias (i.e. chromatic and achromatic inducers which elicited chromatic but also achromatic synesthesias, as well as congruent and incongruent ones). The information derived from the analysis of Mondrians and chromatic/achromatic synesthesias suggests that real and synesthetic colors/achromaticity do not fully share neural mechanisms. The whole-brain analysis of BOLD signals in response to the complete set of synesthetic inducers revealed that the functional peculiarities of the synesthetic brain are distributed, and reflect different components of the synesthetic experience: a perceptual component, an (attentional) feature binding component, and an emotional component. Additionally, the inclusion of achromatic experiences has provided new evidence in favor of the emotional binding theory, a line of interpretation which constitutes a bridge between grapheme-color synesthesia and other developmental modalities of the phenomenon. Copyright © 2014 Elsevier Inc. All rights reserved.

Geometry-aware multiscale image registration via OBBTree-based polyaffine log-demons.

PubMed

Seiler, Christof; Pennec, Xavier; Reyes, Mauricio

2011-01-01

Non-linear image registration is an important tool in many areas of image analysis. For instance, in morphometric studies of a population of brains, free-form deformations between images are analyzed to describe the structural anatomical variability. Such a simple deformation model is justified by the absence of an easy expressible prior about the shape changes. Applying the same algorithms used in brain imaging to orthopedic images might not be optimal due to the difference in the underlying prior on the inter-subject deformations. In particular, using an un-informed deformation prior often leads to local minima far from the expected solution. To improve robustness and promote anatomically meaningful deformations, we propose a locally affine and geometry-aware registration algorithm that automatically adapts to the data. We build upon the log-domain demons algorithm and introduce a new type of OBBTree-based regularization in the registration with a natural multiscale structure. The regularization model is composed of a hierarchy of locally affine transformations via their logarithms. Experiments on mandibles show improved accuracy and robustness when used to initialize the demons, and even similar performance by direct comparison to the demons, with a significantly lower degree of freedom. This closes the gap between polyaffine and non-rigid registration and opens new ways to statistically analyze the registration results.

The ultrasound brain helmet: feasibility study of multiple simultaneous 3D scans of cerebral vasculature.

PubMed

Smith, Stephen W; Ivancevich, Nikolas M; Lindsey, Brooks D; Whitman, John; Light, Edward; Fronheiser, Matthew; Nicoletto, Heather A; Laskowitz, Daniel T

2009-02-01

We describe early stage experiments to test the feasibility of an ultrasound brain helmet to produce multiple simultaneous real-time three-dimensional (3D) scans of the cerebral vasculature from temporal and suboccipital acoustic windows of the skull. The transducer hardware and software of the Volumetrics Medical Imaging (Durham, NC, USA) real-time 3D scanner were modified to support dual 2.5 MHz matrix arrays of 256 transmit elements and 128 receive elements which produce two simultaneous 64 degrees pyramidal scans. The real-time display format consists of two coronal B-mode images merged into a 128 degrees sector, two simultaneous parasagittal images merged into a 128 degrees x 64 degrees C-mode plane and a simultaneous 64 degrees axial image. Real-time 3D color Doppler scans from a skull phantom with latex blood vessel were obtained after contrast agent injection as a proof of concept. The long-term goal is to produce real-time 3D ultrasound images of the cerebral vasculature from a portable unit capable of internet transmission thus enabling interactive 3D imaging, remote diagnosis and earlier therapeutic intervention. We are motivated by the urgency for rapid diagnosis of stroke due to the short time window of effective therapeutic intervention.

Feature selection and classification of multiparametric medical images using bagging and SVM

NASA Astrophysics Data System (ADS)

Fan, Yong; Resnick, Susan M.; Davatzikos, Christos

2008-03-01

This paper presents a framework for brain classification based on multi-parametric medical images. This method takes advantage of multi-parametric imaging to provide a set of discriminative features for classifier construction by using a regional feature extraction method which takes into account joint correlations among different image parameters; in the experiments herein, MRI and PET images of the brain are used. Support vector machine classifiers are then trained based on the most discriminative features selected from the feature set. To facilitate robust classification and optimal selection of parameters involved in classification, in view of the well-known "curse of dimensionality", base classifiers are constructed in a bagging (bootstrap aggregating) framework for building an ensemble classifier and the classification parameters of these base classifiers are optimized by means of maximizing the area under the ROC (receiver operating characteristic) curve estimated from their prediction performance on left-out samples of bootstrap sampling. This classification system is tested on a sex classification problem, where it yields over 90% classification rates for unseen subjects. The proposed classification method is also compared with other commonly used classification algorithms, with favorable results. These results illustrate that the methods built upon information jointly extracted from multi-parametric images have the potential to perform individual classification with high sensitivity and specificity.

Novel Nanotechnologies for Brain Cancer Therapeutics and Imaging.

PubMed

Ferroni, Letizia; Gardin, Chiara; Della Puppa, Alessandro; Sivolella, Stefano; Brunello, Giulia; Scienza, Renato; Bressan, Eriberto; D'Avella, Domenico; Zavan, Barbara

2015-11-01

Despite progress in surgery, radiotherapy, and in chemotherapy, an effective curative treatment of brain cancer, specifically malignant gliomas, does not yet exist. The efficacy of current anti-cancer strategies in brain tumors is limited by the lack of specific therapies against malignant cells. Besides, the delivery of the drugs to brain tumors is limited by the presence of the blood-brain barrier. Nanotechnology today offers a unique opportunity to develop more effective brain cancer imaging and therapeutics. In particular, the development of nanocarriers that can be conjugated with several functional molecules including tumor-specific ligands, anticancer drugs, and imaging probes, can provide new devices which are able to overcome the difficulties of the classical strategies. Nanotechnology-based approaches hold great promise for revolutionizing brain cancer medical treatments, imaging, and diagnosis.

Performance analysis of unsupervised optimal fuzzy clustering algorithm for MRI brain tumor segmentation.

PubMed

Blessy, S A Praylin Selva; Sulochana, C Helen

2015-01-01

Segmentation of brain tumor from Magnetic Resonance Imaging (MRI) becomes very complicated due to the structural complexities of human brain and the presence of intensity inhomogeneities. To propose a method that effectively segments brain tumor from MR images and to evaluate the performance of unsupervised optimal fuzzy clustering (UOFC) algorithm for segmentation of brain tumor from MR images. Segmentation is done by preprocessing the MR image to standardize intensity inhomogeneities followed by feature extraction, feature fusion and clustering. Different validation measures are used to evaluate the performance of the proposed method using different clustering algorithms. The proposed method using UOFC algorithm produces high sensitivity (96%) and low specificity (4%) compared to other clustering methods. Validation results clearly show that the proposed method with UOFC algorithm effectively segments brain tumor from MR images.

Prenatal Brain MR Imaging: Reference Linear Biometric Centiles between 20 and 24 Gestational Weeks.

PubMed

Conte, G; Milani, S; Palumbo, G; Talenti, G; Boito, S; Rustico, M; Triulzi, F; Righini, A; Izzo, G; Doneda, C; Zolin, A; Parazzini, C

2018-05-01

Evaluation of biometry is a fundamental step in prenatal brain MR imaging. While different studies have reported reference centiles for MR imaging biometric data of fetuses in the late second and third trimesters of gestation, no one has reported them in fetuses in the early second trimester. We report centiles of normal MR imaging linear biometric data of a large cohort of fetal brains within 24 weeks of gestation. From the data bases of 2 referral centers of fetal medicine, accounting for 3850 examinations, we retrospectively collected 169 prenatal brain MR imaging examinations of singleton pregnancies, between 20 and 24 weeks of gestational age, with normal brain anatomy at MR imaging and normal postnatal neurologic development. To trace the reference centiles, we used the CG-LMS method. Reference biometric centiles for the developing structures of the cerebrum, cerebellum, brain stem, and theca were obtained. The overall interassessor agreement was adequate for all measurements. Reference biometric centiles of the brain structures in fetuses between 20 and 24 weeks of gestational age may be a reliable tool in assessing fetal brain development. © 2018 by American Journal of Neuroradiology.

Brain, emotion and decision making: the paradigmatic example of regret.

PubMed

Coricelli, Giorgio; Dolan, Raymond J; Sirigu, Angela

2007-06-01

Human decisions cannot be explained solely by rational imperatives but are strongly influenced by emotion. Theoretical and behavioral studies provide a sound empirical basis to the impact of the emotion of regret in guiding choice behavior. Recent neuropsychological and neuroimaging data have stressed the fundamental role of the orbitofrontal cortex in mediating the experience of regret. Functional magnetic resonance imaging data indicate that reactivation of activity within the orbitofrontal cortex and amygdala occurring during the phase of choice, when the brain is anticipating possible future consequences of decisions, characterizes the anticipation of regret. In turn, these patterns reflect learning based on cumulative emotional experience. Moreover, affective consequences can induce specific mechanisms of cognitive control of the choice processes, involving reinforcement or avoidance of the experienced behavior.

Imaging Human Brain Perfusion with Inhaled Hyperpolarized 129Xe MR Imaging.

PubMed

Rao, Madhwesha R; Stewart, Neil J; Griffiths, Paul D; Norquay, Graham; Wild, Jim M

2018-02-01

Purpose To evaluate the feasibility of directly imaging perfusion of human brain tissue by using magnetic resonance (MR) imaging with inhaled hyperpolarized xenon 129 ( 129 Xe). Materials and Methods In vivo imaging with 129 Xe was performed in three healthy participants. The combination of a high-yield spin-exchange optical pumping 129 Xe polarizer, custom-built radiofrequency coils, and an optimized gradient-echo MR imaging protocol was used to achieve signal sensitivity sufficient to directly image hyperpolarized 129 Xe dissolved in the human brain. Conventional T1-weighted proton (hydrogen 1 [ 1 H]) images and perfusion images by using arterial spin labeling were obtained for comparison. Results Images of 129 Xe uptake were obtained with a signal-to-noise ratio of 31 ± 9 and demonstrated structural similarities to the gray matter distribution on conventional T1-weighted 1 H images and to perfusion images from arterial spin labeling. Conclusion Hyperpolarized 129 Xe MR imaging is an injection-free means of imaging the perfusion of cerebral tissue. The proposed method images the uptake of inhaled xenon gas to the extravascular brain tissue compartment across the intact blood-brain barrier. This level of sensitivity is not readily available with contemporary MR imaging methods. © RSNA, 2017.

It's OK if 'my brain made me do it': people's intuitions about free will and neuroscientific prediction.

PubMed

Nahmias, Eddy; Shepard, Jason; Reuter, Shane

2014-11-01

In recent years, a number of prominent scientists have argued that free will is an illusion, appealing to evidence demonstrating that information about brain activity can be used to predict behavior before people are aware of having made a decision. These scientists claim that the possibility of perfect prediction based on neural information challenges the ordinary understanding of free will. In this paper we provide evidence suggesting that most people do not view the possibility of neuro-prediction as a threat to free will unless it also raises concerns about manipulation of the agent's behavior. In Experiment 1 two scenarios described future brain imaging technology that allows perfect prediction of decisions and actions based on earlier neural activity, and this possibility did not undermine most people's attributions of free will or responsibility, except in the scenario that also allowed manipulation. In Experiment 2 the scenarios increased the salience of the physicalist implications of neuro-prediction, while in Experiment 3 the scenarios suggested dualism, with perfect prediction by mindreaders. The patterns of results for these two experiments were similar to the results in Experiment 1, suggesting that participants do not understand free will to require specific metaphysical conditions regarding the mind-body relation. Most people seem to understand free will in a way that is not threatened by perfect prediction based on neural information, suggesting that they believe that just because "my brain made me do it," that does not mean that I didn't do it of my own free will. Copyright © 2014 Elsevier B.V. All rights reserved.

Computer-aided diagnosis with radiogenomics: analysis of the relationship between genotype and morphological changes of the brain magnetic resonance images.

PubMed

Kai, Chiharu; Uchiyama, Yoshikazu; Shiraishi, Junji; Fujita, Hiroshi; Doi, Kunio

2018-05-10

In the post-genome era, a novel research field, 'radiomics' has been developed to offer a new viewpoint for the use of genotypes in radiology and medicine research which have traditionally focused on the analysis of imaging phenotypes. The present study analyzed brain morphological changes related to the individual's genotype. Our data consisted of magnetic resonance (MR) images of patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD), as well as their apolipoprotein E (APOE) genotypes. First, statistical parametric mapping (SPM) 12 was used for three-dimensional anatomical standardization of the brain MR images. A total of 30 normal images were used to create a standard normal brain image. Z-score maps were generated to identify the differences between an abnormal image and the standard normal brain. Our experimental results revealed that cerebral atrophies, depending on genotypes, can occur in different locations and that morphological changes may differ between MCI and AD. Using a classifier to characterize cerebral atrophies related to an individual's genotype, we developed a computer-aided diagnosis (CAD) scheme to identify the disease. For the early detection of cerebral diseases, a screening system using MR images, called Brain Check-up, is widely performed in Japan. Therefore, our proposed CAD scheme would be used in Brain Check-up.

Attachment Security in Infancy: A Preliminary Study of Prospective Links to Brain Morphometry in Late Childhood

PubMed Central

Leblanc, Élizabel; Dégeilh, Fanny; Daneault, Véronique; Beauchamp, Miriam H.; Bernier, Annie

2017-01-01

A large body of longitudinal research provides compelling evidence for the critical role of early attachment relationships in children’s social, emotional, and cognitive development. It is expected that parent–child attachment relationships may also impact children’s brain development, however, studies linking normative caregiving experiences and brain structure are scarce. To our knowledge, no study has yet examined the associations between the quality of parent–infant attachment relationships and brain morphology during childhood. The aim of this preliminary study was to investigate the prospective links between mother–infant attachment security and whole-brain gray matter (GM) volume and thickness in late childhood. Attachment security toward the mother was assessed in 33 children when they were 15 months old. These children were then invited to undergo structural magnetic resonance imaging at 10–11 years of age. Results indicated that children more securely attached to their mother in infancy had larger GM volumes in the superior temporal sulcus and gyrus, temporo-parietal junction, and precentral gyrus in late childhood. No associations between attachment security and cortical thickness were found. If replicated, these results would suggest that a secure attachment relationship and its main features (e.g., adequate dyadic emotion regulation, competent exploration) may influence GM volume in brain regions involved in social, cognitive, and emotional functioning through experience-dependent processes. PMID:29312029

Interval From Imaging to Treatment Delivery in the Radiation Surgery Age: How Long Is Too Long?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seymour, Zachary A., E-mail: seymourz@radonc.ucsf.edu; Fogh, Shannon E.; Westcott, Sarah K.

Purpose: The purpose of this study was to evaluate workflow and patient outcomes related to frameless stereotactic radiation surgery (SRS) for brain metastases. Methods and Materials: We reviewed all treatment demographics, clinical outcomes, and workflow timing, including time from magnetic resonance imaging (MRI), computed tomography (CT) simulation, insurance authorization, and consultation to the start of SRS for brain metastases. Results: A total of 82 patients with 151 brain metastases treated with SRS were evaluated. The median times from consultation, insurance authorization, CT simulation, and MRI for treatment planning were 15, 7, 6, and 11 days to SRS. Local freedom from progressionmore » (LFFP) was lower in metastases with MRI ≥14 days before treatment (P=.0003, log rank). The 6- and 12-month LFFP rate were 95% and 75% for metastasis with interval of <14 days from MRI to treatment compared to 56% and 34% for metastases with MRI ≥14 days before treatment. On multivariate analysis, LFFP remained significantly lower for lesions with MRI ≥14 days at SRS (P=.002, Cox proportional hazards; hazard ratio: 3.4, 95% confidence interval: 1.6-7.3). Conclusions: Delay from MRI to SRS treatment delivery for brain metastases appears to reduce local control. Future studies should monitor the timing from imaging acquisition to treatment delivery. Our experience suggests that the time from MRI to treatment should be <14 days.« less

Joint Estimation of Effective Brain Wave Activation Modes Using EEG/MEG Sensor Arrays and Multimodal MRI Volumes.

PubMed

Galinsky, Vitaly L; Martinez, Antigona; Paulus, Martin P; Frank, Lawrence R

2018-04-13

In this letter, we present a new method for integration of sensor-based multifrequency bands of electroencephalography and magnetoencephalography data sets into a voxel-based structural-temporal magnetic resonance imaging analysis by utilizing the general joint estimation using entropy regularization (JESTER) framework. This allows enhancement of the spatial-temporal localization of brain function and the ability to relate it to morphological features and structural connectivity. This method has broad implications for both basic neuroscience research and clinical neuroscience focused on identifying disease-relevant biomarkers by enhancing the spatial-temporal resolution of the estimates derived from current neuroimaging modalities, thereby providing a better picture of the normal human brain in basic neuroimaging experiments and variations associated with disease states.

Minocycline Effects on Intracerebral Hemorrhage-Induced Iron Overload in Aged Rats: Brain Iron Quantification With Magnetic Resonance Imaging.

PubMed

Cao, Shenglong; Hua, Ya; Keep, Richard F; Chaudhary, Neeraj; Xi, Guohua

2018-04-01

Brain iron overload is a key factor causing brain injury after intracerebral hemorrhage (ICH). This study quantified brain iron levels after ICH with magnetic resonance imaging R2* mapping. The effect of minocycline on iron overload and ICH-induced brain injury in aged rats was also determined. Aged (18 months old) male Fischer 344 rats had an intracerebral injection of autologous blood or saline, and brain iron levels were measured by magnetic resonance imaging R2* mapping. Some ICH rats were treated with minocycline or vehicle. The rats were euthanized at days 7 and 28 after ICH, and brains were used for immunohistochemistry and Western blot analyses. Magnetic resonance imaging (T2-weighted, T2* gradient-echo, and R2* mapping) sequences were performed at different time points. ICH-induced brain iron overload in the perihematomal area could be quantified by R2* mapping. Minocycline treatment reduced brain iron accumulation, T2* lesion volume, iron-handling protein upregulation, neuronal cell death, and neurological deficits ( P <0.05). Magnetic resonance imaging R2* mapping is a reliable and noninvasive method, which can quantitatively measure brain iron levels after ICH. Minocycline reduced ICH-related perihematomal iron accumulation and brain injury in aged rats. © 2018 American Heart Association, Inc.

Non-contact tissue perfusion and oxygenation imaging using a LED based multispectral and a thermal imaging system, first results of clinical intervention studies

NASA Astrophysics Data System (ADS)

Klaessens, John H. G. M.; Nelisse, Martin; Verdaasdonk, Rudolf M.; Noordmans, Herke Jan

2013-03-01

During clinical interventions objective and quantitative information of the tissue perfusion, oxygenation or temperature can be useful for the surgical strategy. Local (point) measurements give limited information and affected areas can easily be missed, therefore imaging large areas is required. In this study a LED based multispectral imaging system (MSI, 17 different wavelengths 370nm-880nm) and a thermo camera were applied during clinical interventions: tissue flap transplantations (ENT), local anesthetic block and during open brain surgery (epileptic seizure). The images covered an area of 20x20 cm, when doing measurements in an (operating) room, they turned out to be more complicated than laboratory experiments due to light fluctuations, movement of the patient and limited angle of view. By constantly measuring the background light and the use of a white reference, light fluctuations and movement were corrected. Oxygenation concentration images could be calculated and combined with the thermal images. The effectively of local anesthesia of a hand could be predicted in an early stage using the thermal camera and the reperfusion of transplanted skin flap could be imaged. During brain surgery, a temporary hyper-perfused area was witnessed which was probably related to an epileptic attack. A LED based multispectral imaging system combined with thermal imaging provide complementary information on perfusion and oxygenation changes and are promising techniques for real-time diagnostics during clinical interventions.

Groupwise registration of MR brain images with tumors.

PubMed

Tang, Zhenyu; Wu, Yihong; Fan, Yong

2017-08-04

A novel groupwise image registration framework is developed for registering MR brain images with tumors. Our method iteratively estimates a normal-appearance counterpart for each tumor image to be registered and constructs a directed graph (digraph) of normal-appearance images to guide the groupwise image registration. Particularly, our method maps each tumor image to its normal appearance counterpart by identifying and inpainting brain tumor regions with intensity information estimated using a low-rank plus sparse matrix decomposition based image representation technique. The estimated normal-appearance images are groupwisely registered to a group center image guided by a digraph of images so that the total length of 'image registration paths' to be the minimum, and then the original tumor images are warped to the group center image using the resulting deformation fields. We have evaluated our method based on both simulated and real MR brain tumor images. The registration results were evaluated with overlap measures of corresponding brain regions and average entropy of image intensity information, and Wilcoxon signed rank tests were adopted to compare different methods with respect to their regional overlap measures. Compared with a groupwise image registration method that is applied to normal-appearance images estimated using the traditional low-rank plus sparse matrix decomposition based image inpainting, our method achieved higher image registration accuracy with statistical significance (p  =  7.02  ×  10 -9 ).

Photoacoustic imaging for transvascular drug delivery to the rat brain

NASA Astrophysics Data System (ADS)

Watanabe, Ryota; Sato, Shunichi; Tsunoi, Yasuyuki; Kawauchi, Satoko; Takemura, Toshiya; Terakawa, Mitsuhiro

2015-03-01

Transvascular drug delivery to the brain is difficult due to the blood-brain barrier (BBB). Thus, various methods for safely opening the BBB have been investigated, for which real-time imaging methods are desired both for the blood vessels and distribution of a drug. Photoacoustic (PA) imaging, which enables depth-resolved visualization of chromophores in tissue, would be useful for this purpose. In this study, we performed in vivo PA imaging of the blood vessels and distribution of a drug in the rat brain by using an originally developed compact PA imaging system with fiber-based illumination. As a test drug, Evans blue (EB) was injected to the tail vein, and a photomechanical wave was applied to the targeted brain tissue to increase the permeability of the blood vessel walls. For PA imaging of blood vessels and EB distribution, nanosecond pulses at 532 nm and 670 nm were used, respectively. We clearly visualized blood vessels with diameters larger than 50 μm and the distribution of EB in the brain, showing spatiotemporal characteristics of EB that was transvascularly delivered to the target tissue in the brain.

Enhanced coherence within the theta band between pairs of brains engaging in experienced versus naïve Reiki procedures.

PubMed

Ventura, Anabela Carraca; Persinger, Michael A

2014-08-01

The study objective was to discern whether the coherence between brain activities of the "patient" and practitioner differ between Reiki experts and novices. If the physical process associated with Reiki involves "convergence" between the practitioner and subject, then this congruence should be evident in time-dependent shared power within specific and meaningful frequency electroencephalographic bands. Simultaneous quantitative electroencephalogram measures (19 channels) were recorded from 9 pairs of subjects when 1 of the pairs was an experienced Reiki practitioner or had just been shown the procedure. Pairs recorded their experiences and images. The "practitioner" and "patient" pairs were measured within a quiet, comfortable acoustic chamber. Real-time correlations and coherence between pairs of brains for power (μV(2)·Hz(-1)) within the various frequency bands over the 10-min sessions were recorded and analyzed for each pair. Descriptors of experiences were analyzed for word meanings. Only the coherence within the theta range increased over time between the brains of the Reiki pairs relative to the Sham pairs, particularly over the left hemisphere. The pleasantness-unpleasantness rating for the words employed to describe experiences written after the experiment were more congruent for the Reiki pairs compared to the reference pairs. The increased synchronization of the cerebral activity of the participant and the practitioner during proximal therapies involving touch such as Reiki may be an important component of any subsequent beneficial effects.

Classical Wave Model of Quantum-Like Processing in Brain

NASA Astrophysics Data System (ADS)

Khrennikov, A.

2011-01-01

We discuss the conjecture on quantum-like (QL) processing of information in the brain. It is not based on the physical quantum brain (e.g., Penrose) - quantum physical carriers of information. In our approach the brain created the QL representation (QLR) of information in Hilbert space. It uses quantum information rules in decision making. The existence of such QLR was (at least preliminary) confirmed by experimental data from cognitive psychology. The violation of the law of total probability in these experiments is an important sign of nonclassicality of data. In so called "constructive wave function approach" such data can be represented by complex amplitudes. We presented 1,2 the QL model of decision making. In this paper we speculate on a possible physical realization of QLR in the brain: a classical wave model producing QLR . It is based on variety of time scales in the brain. Each pair of scales (fine - the background fluctuations of electromagnetic field and rough - the cognitive image scale) induces the QL representation. The background field plays the crucial role in creation of "superstrong QL correlations" in the brain.

A scientist's dilemma: follow my hypothesis or my findings?

PubMed

Komisaruk, Barry R

2012-06-01

Over the course of my 50 years of brain-behavioral research, choicepoints presented themselves as to either follow my original hypothesis or follow my puzzling empirical findings. I trusted the latter more than the former because I believe it is where reality is to be found. Phil Teitelbaum's teachings had a major influence on those decisions. In the present essay, I describe the evolution of those choicepoints that led me from studies of hormone-brain-behavior interactions to a rhythmical brain-behavior connection, to sexual behavior, pain blockage, human brain-behavior interactions, and human brain imaging. Along this tortuous course, I learned that vaginal stimulation can block pain, the vagus nerve apparently can convey genital sensory activity to the brain, bypassing spinal cord injury, and all major brain systems evidently contribute to women's orgasm. An important message I learned is: pay attention to what you observe in your experiments, and have the courage to follow it up, particularly if what you observe is not what you were looking for...because it, rather than your hypothesis, is more likely to reveal reality. Copyright © 2012 Elsevier B.V. All rights reserved.

Finding Imaging Patterns of Structural Covariance via Non-Negative Matrix Factorization

PubMed Central

Sotiras, Aristeidis; Resnick, Susan M.; Davatzikos, Christos

2015-01-01

In this paper, we investigate the use of Non-Negative Matrix Factorization (NNMF) for the analysis of structural neuroimaging data. The goal is to identify the brain regions that co-vary across individuals in a consistent way, hence potentially being part of underlying brain networks or otherwise influenced by underlying common mechanisms such as genetics and pathologies. NNMF offers a directly data-driven way of extracting relatively localized co-varying structural regions, thereby transcending limitations of Principal Component Analysis (PCA), Independent Component Analysis (ICA) and other related methods that tend to produce dispersed components of positive and negative loadings. In particular, leveraging upon the well known ability of NNMF to produce parts-based representations of image data, we derive decompositions that partition the brain into regions that vary in consistent ways across individuals. Importantly, these decompositions achieve dimensionality reduction via highly interpretable ways and generalize well to new data as shown via split-sample experiments. We empirically validate NNMF in two data sets: i) a Diffusion Tensor (DT) mouse brain development study, and ii) a structural Magnetic Resonance (sMR) study of human brain aging. We demonstrate the ability of NNMF to produce sparse parts-based representations of the data at various resolutions. These representations seem to follow what we know about the underlying functional organization of the brain and also capture some pathological processes. Moreover, we show that these low dimensional representations favorably compare to descriptions obtained with more commonly used matrix factorization methods like PCA and ICA. PMID:25497684

The association between cortisol and the BOLD response in male adolescents undergoing fMRI.

PubMed

Keulers, Esther H H; Stiers, Peter; Nicolson, Nancy A; Jolles, Jelle

2015-02-19

MRI participation has been shown to induce subjective and neuroendocrine stress reactions. A recent aging study showed that cortisol levels during fMRI have an age-dependent effect on cognitive performance and brain functioning. The present study examined whether this age-specific influence of cortisol on behavioral and brain activation levels also applies to adolescence. Salivary cortisol as well as subjective experienced anxiety were assessed during the practice session, at home, and before, during and after the fMRI session in young versus old male adolescents. Cortisol levels were enhanced pre-imaging relative to during and post-imaging in both age groups, suggesting anticipatory stress and anxiety. Overall, a negative correlation was found between cortisol output during the fMRI experiment and brain activation magnitude during performance of a gambling task. In young but not in old adolescents, higher cortisol output was related to stronger deactivation of clusters in the anterior and posterior cingulate cortex. In old but not in young adolescents, a negative correlation was found between cortisol and activation in the inferior parietal and in the superior frontal cortex. In sum, cortisol increased the deactivation of several brain areas, although the location of the affected areas in the brain was age-dependent. The present findings suggest that cortisol output during fMRI should be considered as confounder and integrated in analyzing developmental changes in brain activation during adolescence. Copyright © 2014 Elsevier B.V. All rights reserved.

Enhanced Brain Responses to Pain-Related Words in Chronic Back Pain Patients and Their Modulation by Current Pain.

PubMed

Ritter, Alexander; Franz, Marcel; Puta, Christian; Dietrich, Caroline; Miltner, Wolfgang H R; Weiss, Thomas

2016-08-10

Previous functional magnetic resonance imaging (fMRI) studies in healthy controls (HC) and pain-free migraine patients found activations to pain-related words in brain regions known to be activated while subjects experience pain. The aim of the present study was to identify neural activations induced by pain-related words in a sample of chronic back pain (CBP) patients experiencing current chronic pain compared to HC. In particular, we were interested in how current pain influences brain activations induced by pain-related adjectives. Subjects viewed pain-related, negative, positive, and neutral words; subjects were asked to generate mental images related to these words during fMRI scanning. Brain activation was compared between CBP patients and HC in response to the different word categories and examined in relation to current pain in CBP patients. Pain-related words vs. neutral words activated a network of brain regions including cingulate cortex and insula in subjects and patients. There was stronger activation in medial and dorsolateral prefrontal cortex (DLPFC) and anterior midcingulate cortex in CPB patients than in HC. The magnitude of activation for pain-related vs. negative words showed a negative linear relationship to CBP patients' current pain. Our findings confirm earlier observations showing that pain-related words activate brain networks similar to noxious stimulation. Importantly, CBP patients show even stronger activation of these structures while merely processing pain-related words. Current pain directly influences on this activation.

Brain activation in parietal area during manipulation with a surgical robot simulator.

PubMed

Miura, Satoshi; Kobayashi, Yo; Kawamura, Kazuya; Nakashima, Yasutaka; Fujie, Masakatsu G

2015-06-01

we present an evaluation method to qualify the embodiment caused by the physical difference between master-slave surgical robots by measuring the activation of the intraparietal sulcus in the user's brain activity during surgical robot manipulation. We show the change of embodiment based on the change of the optical axis-to-target view angle in the surgical simulator to change the manipulator's appearance in the monitor in terms of hand-eye coordination. The objective is to explore the change of brain activation according to the change of the optical axis-to-target view angle. In the experiments, we used a functional near-infrared spectroscopic topography (f-NIRS) brain imaging device to measure the brain activity of the seven subjects while they moved the hand controller to insert a curved needle into a target using the manipulator in a surgical simulator. The experiment was carried out several times with a variety of optical axis-to-target view angles. Some participants showed a significant peak (P value = 0.037, F-number = 2.841) when the optical axis-to-target view angle was 75°. The positional relationship between the manipulators and endoscope at 75° would be the closest to the human physical relationship between the hands and eyes.

Correspondence of the brain's functional architecture during activation and rest.

PubMed

Smith, Stephen M; Fox, Peter T; Miller, Karla L; Glahn, David C; Fox, P Mickle; Mackay, Clare E; Filippini, Nicola; Watkins, Kate E; Toro, Roberto; Laird, Angela R; Beckmann, Christian F

2009-08-04

Neural connections, providing the substrate for functional networks, exist whether or not they are functionally active at any given moment. However, it is not known to what extent brain regions are continuously interacting when the brain is "at rest." In this work, we identify the major explicit activation networks by carrying out an image-based activation network analysis of thousands of separate activation maps derived from the BrainMap database of functional imaging studies, involving nearly 30,000 human subjects. Independently, we extract the major covarying networks in the resting brain, as imaged with functional magnetic resonance imaging in 36 subjects at rest. The sets of major brain networks, and their decompositions into subnetworks, show close correspondence between the independent analyses of resting and activation brain dynamics. We conclude that the full repertoire of functional networks utilized by the brain in action is continuously and dynamically "active" even when at "rest."

Retractor-induced brain shift compensation in image-guided neurosurgery

NASA Astrophysics Data System (ADS)

Fan, Xiaoyao; Ji, Songbai; Hartov, Alex; Roberts, David; Paulsen, Keith

2013-03-01

In image-guided neurosurgery, intraoperative brain shift significantly degrades the accuracy of neuronavigation that is solely based on preoperative magnetic resonance images (pMR). To compensate for brain deformation and to maintain the accuracy in image guidance achieved at the start of surgery, biomechanical models have been developed to simulate brain deformation and to produce model-updated MR images (uMR) to compensate for brain shift. To-date, most studies have focused on shift compensation at early stages of surgery (i.e., updated images are only produced after craniotomy and durotomy). Simulating surgical events at later stages such as retraction and tissue resection are, perhaps, clinically more relevant because of the typically much larger magnitudes of brain deformation. However, these surgical events are substantially more complex in nature, thereby posing significant challenges in model-based brain shift compensation strategies. In this study, we present results from an initial investigation to simulate retractor-induced brain deformation through a biomechanical finite element (FE) model where whole-brain deformation assimilated from intraoperative data was used produce uMR for improved accuracy in image guidance. Specifically, intensity-encoded 3D surface profiles at the exposed cortical area were reconstructed from intraoperative stereovision (iSV) images before and after tissue retraction. Retractor-induced surface displacements were then derived by coregistering the surfaces and served as sparse displacement data to drive the FE model. With one patient case, we show that our technique is able to produce uMR that agrees well with the reconstructed iSV surface after retraction. The computational cost to simulate retractor-induced brain deformation was approximately 10 min. In addition, our approach introduces minimal interruption to the surgical workflow, suggesting the potential for its clinical application.

Hemorrhage detection in MRI brain images using images features

NASA Astrophysics Data System (ADS)

Moraru, Luminita; Moldovanu, Simona; Bibicu, Dorin; Stratulat (Visan), Mirela

2013-11-01

The abnormalities appear frequently on Magnetic Resonance Images (MRI) of brain in elderly patients presenting either stroke or cognitive impairment. Detection of brain hemorrhage lesions in MRI is an important but very time-consuming task. This research aims to develop a method to extract brain tissue features from T2-weighted MR images of the brain using a selection of the most valuable texture features in order to discriminate between normal and affected areas of the brain. Due to textural similarity between normal and affected areas in brain MR images these operation are very challenging. A trauma may cause microstructural changes, which are not necessarily perceptible by visual inspection, but they could be detected by using a texture analysis. The proposed analysis is developed in five steps: i) in the pre-processing step: the de-noising operation is performed using the Daubechies wavelets; ii) the original images were transformed in image features using the first order descriptors; iii) the regions of interest (ROIs) were cropped from images feature following up the axial symmetry properties with respect to the mid - sagittal plan; iv) the variation in the measurement of features was quantified using the two descriptors of the co-occurrence matrix, namely energy and homogeneity; v) finally, the meaningful of the image features is analyzed by using the t-test method. P-value has been applied to the pair of features in order to measure they efficacy.

Narrative literature review: Health, activity and participation issues for women following traumatic brain injury.

PubMed

O'Reilly, Kate; Wilson, Nathan; Peters, Kath

2017-06-06

This narrative review will draw attention to the current limitations within the literature related to women following traumatic brain injury in order to stimulate discussion and inform future directions for research. There is a wide-ranging body of research about traumatic brain injury with the higher incidence of brain injury among males reflected in this body of work. As a result, the specific gendered issues facing women with traumatic brain injury are not as well understood. A search of electronic databases was conducted using the terms "traumatic brain injury", "brain injury", "women", "participation", "concussion" and "outcomes". The 36 papers revealed the following five themes (1) Relationships and life satisfaction; (2) Perception of self and body image; (3) Meaningful occupation; (4) Sexuality and sexual health; and (5) Physical function. Without research, which focuses specifically on the experience of women and girls with traumatic brain injury there is a risk that clinical care, policy development and advocacy services will not effectively accommodate them. Implications for rehabilitation Exploring the gendered issues women may experience following traumatic brain injury will enhance clinicians understanding of the unique challenges they face. Such information has the potential to guide future directions for research, policy, and practice. Screening women for hormonal imbalances such as hypopituitarism following traumatic brain injury is recommended as this may assist clinicians in addressing the far reaching implications in regard to disability, quality of life and mood. The growing literature regarding the cumulative effect of repeat concussions following domestic violence and women's increased risk of sport-related concussion may assist clinicians in advocating for appropriate rehabilitation and community support services.

Multiprotocol MR image segmentation in multiple sclerosis: experience with over 1000 studies

NASA Astrophysics Data System (ADS)

Udupa, Jayaram K.; Nyul, Laszlo G.; Ge, Yulin; Grossman, Robert I.

2000-06-01

Multiple Sclerosis (MS) is an acquired disease of the central nervous system. Subjective cognitive and ambulatory test scores on a scale called EDSS are currently utilized to assess the disease severity. Various MRI protocols are being investigated to study the disease based on how it manifests itself in the images. In an attempt to eventually replace EDSS by an objective measure to assess the natural course of the disease and its response to therapy, we have developed image segmentation methods based on fuzzy connectedness to quantify various objects in multiprotocol MRI. These include the macroscopic objects such as lesions, the gray matter (GM), white matter (WM), cerebrospinal fluid (CSF), and brain parenchyma as well as the microscopic aspects of the diseased WM. Over 1000 studies have been processed to date. By far the strongest correlations with the clinical measures were demonstrated by the Magnetization Transfer Ratio (MTR) histogram parameters obtained for the various segmented tissue regions emphasizing the importance of considering the microscopic/diffused nature of the disease in the individual tissue regions. Brain parenchymal volume also demonstrated a strong correlation with the clinical measures indicating that brain atrophy is an important indicator of the disease. Fuzzy connectedness is a viable segmentation method for studying MS.

Whole head quantitative susceptibility mapping using a least-norm direct dipole inversion method.

PubMed

Sun, Hongfu; Ma, Yuhan; MacDonald, M Ethan; Pike, G Bruce

2018-06-15

A new dipole field inversion method for whole head quantitative susceptibility mapping (QSM) is proposed. Instead of performing background field removal and local field inversion sequentially, the proposed method performs dipole field inversion directly on the total field map in a single step. To aid this under-determined and ill-posed inversion process and obtain robust QSM images, Tikhonov regularization is implemented to seek the local susceptibility solution with the least-norm (LN) using the L-curve criterion. The proposed LN-QSM does not require brain edge erosion, thereby preserving the cerebral cortex in the final images. This should improve its applicability for QSM-based cortical grey matter measurement, functional imaging and venography of full brain. Furthermore, LN-QSM also enables susceptibility mapping of the entire head without the need for brain extraction, which makes QSM reconstruction more automated and less dependent on intermediate pre-processing methods and their associated parameters. It is shown that the proposed LN-QSM method reduced errors in a numerical phantom simulation, improved accuracy in a gadolinium phantom experiment, and suppressed artefacts in nine subjects, as compared to two-step and other single-step QSM methods. Measurements of deep grey matter and skull susceptibilities from LN-QSM are consistent with established reconstruction methods. Copyright © 2018 Elsevier Inc. All rights reserved.

A Simple Noise Correction Scheme for Diffusional Kurtosis Imaging

PubMed Central

Glenn, G. Russell; Tabesh, Ali; Jensen, Jens H.

2014-01-01

Purpose Diffusional kurtosis imaging (DKI) is sensitive to the effects of signal noise due to strong diffusion weightings and higher order modeling of the diffusion weighted signal. A simple noise correction scheme is proposed to remove the majority of the noise bias in the estimated diffusional kurtosis. Methods Weighted linear least squares (WLLS) fitting together with a voxel-wise, subtraction-based noise correction from multiple, independent acquisitions are employed to reduce noise bias in DKI data. The method is validated in phantom experiments and demonstrated for in vivo human brain for DKI-derived parameter estimates. Results As long as the signal-to-noise ratio (SNR) for the most heavily diffusion weighted images is greater than 2.1, errors in phantom diffusional kurtosis estimates are found to be less than 5 percent with noise correction, but as high as 44 percent for uncorrected estimates. In human brain, noise correction is also shown to improve diffusional kurtosis estimates derived from measurements made with low SNR. Conclusion The proposed correction technique removes the majority of noise bias from diffusional kurtosis estimates in noisy phantom data and is applicable to DKI of human brain. Features of the method include computational simplicity and ease of integration into standard WLLS DKI post-processing algorithms. PMID:25172990

Pharmacologic Modulation of Hand Pain in Osteoarthritis: A Double-Blind Placebo-Controlled Functional Magnetic Resonance Imaging Study Using Naproxen

PubMed Central

Sanders, Duncan; Krause, Kristina; O'Muircheartaigh, Jonathan; Thacker, Michael A; Huggins, John P; Vennart, William; Massat, Nathalie J; Choy, Ernest; Williams, Steven C R; Howard, Matthew A

2015-01-01

Objective In an attempt to shed light on management of chronic pain conditions, there has long been a desire to complement behavioral measures of pain perception with measures of underlying brain mechanisms. Using functional magnetic resonance imaging (fMRI), we undertook this study to investigate changes in brain activity following the administration of naproxen or placebo in patients with pain related to osteoarthritis (OA) of the carpometacarpal (CMC) joint. Methods A placebo-controlled, double-blind, 2-period crossover study was performed in 19 individuals with painful OA of the CMC joint of the right hand. Following placebo or naproxen treatment periods, a functionally relevant task was performed, and behavioral measures of the pain experience were collected in identical fMRI examinations. Voxelwise and a priori region of interest analyses were performed to detect between-period differences in brain activity. Results Significant reductions in brain activity following treatment with naproxen, compared to placebo, were observed in brain regions commonly associated with pain perception, including the bilateral primary somatosensory cortex, thalamus, and amygdala. Significant relationships between changes in perceived pain intensity and changes in brain activity were also observed in brain regions previously associated with pain intensity. Conclusion This study demonstrates the sensitivity of fMRI to detect the mechanisms underlying treatments of known efficacy. The data illustrate the enticing potential of fMRI as an adjunct to self-report for detecting early signals of efficacy of novel therapies, both pharmacologic and nonpharmacologic, in small numbers of individuals with persistent pain. PMID:25533872

A self-organized learning strategy for object recognition by an embedded line of attraction

NASA Astrophysics Data System (ADS)

Seow, Ming-Jung; Alex, Ann T.; Asari, Vijayan K.

2012-04-01

For humans, a picture is worth a thousand words, but to a machine, it is just a seemingly random array of numbers. Although machines are very fast and efficient, they are vastly inferior to humans for everyday information processing. Algorithms that mimic the way the human brain computes and learns may be the solution. In this paper we present a theoretical model based on the observation that images of similar visual perceptions reside in a complex manifold in an image space. The perceived features are often highly structured and hidden in a complex set of relationships or high-dimensional abstractions. To model the pattern manifold, we present a novel learning algorithm using a recurrent neural network. The brain memorizes information using a dynamical system made of interconnected neurons. Retrieval of information is accomplished in an associative sense. It starts from an arbitrary state that might be an encoded representation of a visual image and converges to another state that is stable. The stable state is what the brain remembers. In designing a recurrent neural network, it is usually of prime importance to guarantee the convergence in the dynamics of the network. We propose to modify this picture: if the brain remembers by converging to the state representing familiar patterns, it should also diverge from such states when presented with an unknown encoded representation of a visual image belonging to a different category. That is, the identification of an instability mode is an indication that a presented pattern is far away from any stored pattern and therefore cannot be associated with current memories. These properties can be used to circumvent the plasticity-stability dilemma by using the fluctuating mode as an indicator to create new states. We capture this behavior using a novel neural architecture and learning algorithm, in which the system performs self-organization utilizing a stability mode and an instability mode for the dynamical system. Based on this observation we developed a self- organizing line attractor, which is capable of generating new lines in the feature space to learn unrecognized patterns. Experiments performed on UMIST pose database and CMU face expression variant database for face recognition have shown that the proposed nonlinear line attractor is able to successfully identify the individuals and it provided better recognition rate when compared to the state of the art face recognition techniques. Experiments on FRGC version 2 database has also provided excellent recognition rate in images captured in complex lighting environments. Experiments performed on the Japanese female face expression database and Essex Grimace database using the self organizing line attractor have also shown successful expression invariant face recognition. These results show that the proposed model is able to create nonlinear manifolds in a multidimensional feature space to distinguish complex patterns.

Brain Tumor Image Segmentation in MRI Image

NASA Astrophysics Data System (ADS)

Peni Agustin Tjahyaningtijas, Hapsari

2018-04-01

Brain tumor segmentation plays an important role in medical image processing. Treatment of patients with brain tumors is highly dependent on early detection of these tumors. Early detection of brain tumors will improve the patient’s life chances. Diagnosis of brain tumors by experts usually use a manual segmentation that is difficult and time consuming because of the necessary automatic segmentation. Nowadays automatic segmentation is very populer and can be a solution to the problem of tumor brain segmentation with better performance. The purpose of this paper is to provide a review of MRI-based brain tumor segmentation methods. There are number of existing review papers, focusing on traditional methods for MRI-based brain tumor image segmentation. this paper, we focus on the recent trend of automatic segmentation in this field. First, an introduction to brain tumors and methods for brain tumor segmentation is given. Then, the state-of-the-art algorithms with a focus on recent trend of full automatic segmentaion are discussed. Finally, an assessment of the current state is presented and future developments to standardize MRI-based brain tumor segmentation methods into daily clinical routine are addressed.

How age of bilingual exposure can change the neural systems for language in the developing brain: a functional near infrared spectroscopy investigation of syntactic processing in monolingual and bilingual children.

PubMed

Jasinska, K K; Petitto, L A

2013-10-01

Is the developing bilingual brain fundamentally similar to the monolingual brain (e.g., neural resources supporting language and cognition)? Or, does early-life bilingual language experience change the brain? If so, how does age of first bilingual exposure impact neural activation for language? We compared how typically-developing bilingual and monolingual children (ages 7-10) and adults recruit brain areas during sentence processing using functional Near Infrared Spectroscopy (fNIRS) brain imaging. Bilingual participants included early-exposed (bilingual exposure from birth) and later-exposed individuals (bilingual exposure between ages 4-6). Both bilingual children and adults showed greater neural activation in left-hemisphere classic language areas, and additionally, right-hemisphere homologues (Right Superior Temporal Gyrus, Right Inferior Frontal Gyrus). However, important differences were observed between early-exposed and later-exposed bilinguals in their earliest-exposed language. Early bilingual exposure imparts fundamental changes to classic language areas instead of alterations to brain regions governing higher cognitive executive functions. However, age of first bilingual exposure does matter. Later-exposed bilinguals showed greater recruitment of the prefrontal cortex relative to early-exposed bilinguals and monolinguals. The findings provide fascinating insight into the neural resources that facilitate bilingual language use and are discussed in terms of how early-life language experiences can modify the neural systems underlying human language processing. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

A hybrid correlation analysis with application to imaging genetics

NASA Astrophysics Data System (ADS)

Hu, Wenxing; Fang, Jian; Calhoun, Vince D.; Wang, Yu-Ping

2018-03-01

Investigating the association between brain regions and genes continues to be a challenging topic in imaging genetics. Current brain region of interest (ROI)-gene association studies normally reduce data dimension by averaging the value of voxels in each ROI. This averaging may lead to a loss of information due to the existence of functional sub-regions. Pearson correlation is widely used for association analysis. However, it only detects linear correlation whereas nonlinear correlation may exist among ROIs. In this work, we introduced distance correlation to ROI-gene association analysis, which can detect both linear and nonlinear correlations and overcome the limitation of averaging operations by taking advantage of the information at each voxel. Nevertheless, distance correlation usually has a much lower value than Pearson correlation. To address this problem, we proposed a hybrid correlation analysis approach, by applying canonical correlation analysis (CCA) to the distance covariance matrix instead of directly computing distance correlation. Incorporating CCA into distance correlation approach may be more suitable for complex disease study because it can detect highly associated pairs of ROI and gene groups, and may improve the distance correlation level and statistical power. In addition, we developed a novel nonlinear CCA, called distance kernel CCA, which seeks the optimal combination of features with the most significant dependence. This approach was applied to imaging genetic data from the Philadelphia Neurodevelopmental Cohort (PNC). Experiments showed that our hybrid approach produced more consistent results than conventional CCA across resampling and both the correlation and statistical significance were increased compared to distance correlation analysis. Further gene enrichment analysis and region of interest (ROI) analysis confirmed the associations of the identified genes with brain ROIs. Therefore, our approach provides a powerful tool for finding the correlation between brain imaging and genomic data.

Increases in Brain 1H-MR Glutamine and Glutamate Signals Following Acute Exhaustive Endurance Exercise in the Rat

PubMed Central

Świątkiewicz, Maciej; Fiedorowicz, Michał; Orzeł, Jarosław; Wełniak-Kamińska, Marlena; Bogorodzki, Piotr; Langfort, Józef; Grieb, Paweł

2017-01-01

Objective: Proton magnetic resonance spectroscopy (1H-MRS) in ultra-high magnetic field can be used for non-invasive quantitative assessment of brain glutamate (Glu) and glutamine (Gln) in vivo. Glu, the main excitatory neurotransmitter in the central nervous system, is efficiently recycled between synapses and presynaptic terminals through Glu-Gln cycle which involves glutamine synthase confined to astrocytes, and uses 60–80% of energy in the resting human and rat brain. During voluntary or involuntary exercise many brain areas are significantly activated, which certainly intensifies Glu-Gln cycle. However, studies on the effects of exercise on 1H-MRS Glu and/or Gln signals from the brain provided divergent results. The present study on rats was performed to determine changes in 1H-MRS signals from three brain regions engaged in motor activity consequential to forced acute exercise to exhaustion. Method: After habituation to treadmill running, rats were subjected to acute treadmill exercise continued to exhaustion. Each animal participating in the study was subject to two identical imaging sessions performed under light isoflurane anesthesia, prior to, and following the exercise bout. In control experiments, two imaging sessions separated by the period of rest instead of exercise were performed. 1H-NMR spectra were recorded from the cerebellum, striatum, and hippocampus using a 7T small animal MR scanner. Results: Following exhaustive exercise statistically significant increases in the Gln and Glx signals were found in all three locations, whereas increases in the Glu signal were found in the cerebellum and hippocampus. In control experiments, no changes in 1H-MRS signals were found. Conclusion: Increase in glutamine signals from the brain areas engaged in motor activity may reflect a disequilibrium caused by increased turnover in the glutamate-glutamine cycle and a delay in the return of glutamine from astrocytes to neurons. Increased turnover of Glu-Gln cycle may be a result of functional activation caused by forced endurance exercise; the increased rate of ammonia detoxification may also contribute. Increases in glutamate in the cerebellum and hippocampus are suggestive of an anaplerotic increase in glutamate synthesis due to exercise-related stimulation of brain glucose uptake. The disequilibrium in the glutamate-glutamine cycle in brain areas activated during exercise may be a significant contributor to the central fatigue phenomenon. PMID:28197103

A simple rapid process for semi-automated brain extraction from magnetic resonance images of the whole mouse head.

PubMed

Delora, Adam; Gonzales, Aaron; Medina, Christopher S; Mitchell, Adam; Mohed, Abdul Faheem; Jacobs, Russell E; Bearer, Elaine L

2016-01-15

Magnetic resonance imaging (MRI) is a well-developed technique in neuroscience. Limitations in applying MRI to rodent models of neuropsychiatric disorders include the large number of animals required to achieve statistical significance, and the paucity of automation tools for the critical early step in processing, brain extraction, which prepares brain images for alignment and voxel-wise statistics. This novel timesaving automation of template-based brain extraction ("skull-stripping") is capable of quickly and reliably extracting the brain from large numbers of whole head images in a single step. The method is simple to install and requires minimal user interaction. This method is equally applicable to different types of MR images. Results were evaluated with Dice and Jacquard similarity indices and compared in 3D surface projections with other stripping approaches. Statistical comparisons demonstrate that individual variation of brain volumes are preserved. A downloadable software package not otherwise available for extraction of brains from whole head images is included here. This software tool increases speed, can be used with an atlas or a template from within the dataset, and produces masks that need little further refinement. Our new automation can be applied to any MR dataset, since the starting point is a template mask generated specifically for that dataset. The method reliably and rapidly extracts brain images from whole head images, rendering them useable for subsequent analytical processing. This software tool will accelerate the exploitation of mouse models for the investigation of human brain disorders by MRI. Copyright © 2015 Elsevier B.V. All rights reserved.

Development of functional imaging in the human brain (fMRI); the University of Minnesota experience

PubMed Central

Uğurbil, Kâmil

2012-01-01

The human functional magnetic resonance imaging (fMRI) experiments performed in the Center for Magnetic Resonance Research (CMRR), University of Minnesota, were planned between two colleagues who had worked together previously in Bell Laboratories in the late nineteen seventies, namely myself and Seiji Ogawa. These experiments were motivated by the Blood Oxygenation Level Dependent (BOLD) contrast developed by Seiji. We discussed and planned human studies to explore imaging human brain activity using the BOLD mechanism on the 4 Tesla human system that I was expecting to receive for CMRR. We started these experiments as soon as this 4 Tesla instrument became marginally operational. These were the very first studies performed on the 4 Tesla scanner in CMRR; had the scanner became functional earlier, they would have been started earlier as well. We had positive results certainly by August 1991 annual meeting of the Society of Magnetic Resonance in Medicine (SMRM) and took some of the data with us to that meeting. I believe, however, that neither the MGH colleagues nor us, at the time, had enough data and/or conviction to publish these extraordinary observations; it took more or less another six months or so before the papers from these two groups were submitted for publication within five days of each other to the Proceedings of the National Academy of Sciences, USA, after rejections by Nature. Based on this record, it is fair to say that fMRI was achieved independently and at about the same time at MGH, in an effort credited largely to Ken Kwong, and in CMRR, University of Minnesota in an effort led by myself and Seiji Ogawa. PMID:22342875

Synchrotron radiation imaging is a powerful tool to image brain microvasculature

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Mengqi; Sun, Danni; Xie, Yuanyuan

2014-03-15

Synchrotron radiation (SR) imaging is a powerful experimental tool for micrometer-scale imaging of microcirculation in vivo. This review discusses recent methodological advances and findings from morphological investigations of cerebral vascular networks during several neurovascular pathologies. In particular, it describes recent developments in SR microangiography for real-time assessment of the brain microvasculature under various pathological conditions in small animal models. It also covers studies that employed SR-based phase-contrast imaging to acquire 3D brain images and provide detailed maps of brain vasculature. In addition, a brief introduction of SR technology and current limitations of SR sources are described in this review. Inmore » the near future, SR imaging could transform into a common and informative imaging modality to resolve subtle details of cerebrovascular function.« less

Synchrotron radiation imaging is a powerful tool to image brain microvasculature.

PubMed

Zhang, Mengqi; Peng, Guanyun; Sun, Danni; Xie, Yuanyuan; Xia, Jian; Long, Hongyu; Hu, Kai; Xiao, Bo

2014-03-01

Synchrotron radiation (SR) imaging is a powerful experimental tool for micrometer-scale imaging of microcirculation in vivo. This review discusses recent methodological advances and findings from morphological investigations of cerebral vascular networks during several neurovascular pathologies. In particular, it describes recent developments in SR microangiography for real-time assessment of the brain microvasculature under various pathological conditions in small animal models. It also covers studies that employed SR-based phase-contrast imaging to acquire 3D brain images and provide detailed maps of brain vasculature. In addition, a brief introduction of SR technology and current limitations of SR sources are described in this review. In the near future, SR imaging could transform into a common and informative imaging modality to resolve subtle details of cerebrovascular function.

Label-free imaging of brain and brain tumor specimens with combined two-photon excited fluorescence and second harmonic generation microscopy

NASA Astrophysics Data System (ADS)

Jiang, Liwei; Wang, Xingfu; Wu, Zanyi; Du, Huiping; Wang, Shu; Li, Lianhuang; Fang, Na; Lin, Peihua; Chen, Jianxin; Kang, Dezhi; Zhuo, Shuangmu

2017-10-01

Label-free imaging techniques are gaining acceptance within the medical imaging field, including brain imaging, because they have the potential to be applied to intraoperative in situ identifications of pathological conditions. In this paper, we describe the use of two-photon excited fluorescence (TPEF) and second harmonic generation (SHG) microscopy in combination for the label-free detection of brain and brain tumor specimens; gliomas. Two independently detecting channels were chosen to subsequently collect TPEF/SHG signals from the specimen to increase TPEF/SHG image contrasts. Our results indicate that the combined TPEF/SHG microscopic techniques can provide similar rat brain structural information and produce a similar resolution like conventional H&E staining in neuropathology; including meninges, cerebral cortex, white-matter structure corpus callosum, choroid plexus, hippocampus, striatum, and cerebellar cortex. It can simultaneously detect infiltrating human brain tumor cells, the extracellular matrix collagen fiber of connective stroma within brain vessels and collagen depostion in tumor microenvironments. The nuclear-to-cytoplasmic ratio and collagen content can be extracted as quantitative indicators for differentiating brain gliomas from healthy brain tissues. With the development of two-photon fiberscopes and microendoscope probes and their clinical applications, the combined TPEF and SHG microcopy may become an important multimodal, nonlinear optical imaging approach for real-time intraoperative histological diagnostics of residual brain tumors. These occur in various brain regions during ongoing surgeries through the method of simultaneously identifying tumor cells, and the change of tumor microenvironments, without the need for the removal biopsies and without the need for tissue labelling or fluorescent markers.

[Brain imaging in autism spectrum disorders. A review].

PubMed

Dziobek, I; Köhne, S

2011-05-01

In the past two decades, an increasing number of functional and structural brain imaging studies has provided insights into the neurobiological basis of autism spectrum disorders (ASD). This article summarizes pertinent functional brain imaging studies addressing the neuronal underpinnings of ASD symptomatology (impairments in social interaction and communication, repetitive and restrictive behavior) and associated neuropsychological deficits (theory of mind, executive functions, central coherence), complemented by relevant structural imaging findings. The results of these studies show that although cognitive functions in ASD are generally mediated by the same brain regions as in typically developed individuals, the degree and especially the patterns of brain activation often differ. Therefore, a hypothesis of aberrant network connectivity has increasingly been favored over one of focal brain dysfunction.

Contrast enhancement in EIT imaging of the brain.

PubMed

Nissinen, A; Kaipio, J P; Vauhkonen, M; Kolehmainen, V

2016-01-01

We consider electrical impedance tomography (EIT) imaging of the brain. The brain is surrounded by the poorly conducting skull which has low conductivity compared to the brain. The skull layer causes a partial shielding effect which leads to weak sensitivity for the imaging of the brain tissue. In this paper we propose an approach based on the Bayesian approximation error approach, to enhance the contrast in brain imaging. With this approach, both the (uninteresting) geometry and the conductivity of the skull are embedded in the approximation error statistics, which leads to a computationally efficient algorithm that is able to detect features such as internal haemorrhage with significantly increased sensitivity and specificity. We evaluate the approach with simulations and phantom data.

A brain imaging repository of normal structural MRI across the life course: Brain Images of Normal Subjects (BRAINS).

PubMed

Job, Dominic E; Dickie, David Alexander; Rodriguez, David; Robson, Andrew; Danso, Sammy; Pernet, Cyril; Bastin, Mark E; Boardman, James P; Murray, Alison D; Ahearn, Trevor; Waiter, Gordon D; Staff, Roger T; Deary, Ian J; Shenkin, Susan D; Wardlaw, Joanna M

2017-01-01

The Brain Images of Normal Subjects (BRAINS) Imagebank (http://www.brainsimagebank.ac.uk) is an integrated repository project hosted by the University of Edinburgh and sponsored by the Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) collaborators. BRAINS provide sharing and archiving of detailed normal human brain imaging and relevant phenotypic data already collected in studies of healthy volunteers across the life-course. It particularly focusses on the extremes of age (currently older age, and in future perinatal) where variability is largest, and which are under-represented in existing databanks. BRAINS is a living imagebank where new data will be added when available. Currently BRAINS contains data from 808 healthy volunteers, from 15 to 81years of age, from 7 projects in 3 centres. Additional completed and ongoing studies of normal individuals from 1st to 10th decades are in preparation and will be included as they become available. BRAINS holds several MRI structural sequences, including T1, T2, T2* and fluid attenuated inversion recovery (FLAIR), available in DICOM (http://dicom.nema.org/); in future Diffusion Tensor Imaging (DTI) will be added where available. Images are linked to a wide range of 'textual data', such as age, medical history, physiological measures (e.g. blood pressure), medication use, cognitive ability, and perinatal information for pre/post-natal subjects. The imagebank can be searched to include or exclude ranges of these variables to create better estimates of 'what is normal' at different ages. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Auto-Context Convolutional Neural Network (Auto-Net) for Brain Extraction in Magnetic Resonance Imaging.

PubMed

Mohseni Salehi, Seyed Sadegh; Erdogmus, Deniz; Gholipour, Ali

2017-11-01

Brain extraction or whole brain segmentation is an important first step in many of the neuroimage analysis pipelines. The accuracy and the robustness of brain extraction, therefore, are crucial for the accuracy of the entire brain analysis process. The state-of-the-art brain extraction techniques rely heavily on the accuracy of alignment or registration between brain atlases and query brain anatomy, and/or make assumptions about the image geometry, and therefore have limited success when these assumptions do not hold or image registration fails. With the aim of designing an accurate, learning-based, geometry-independent, and registration-free brain extraction tool, in this paper, we present a technique based on an auto-context convolutional neural network (CNN), in which intrinsic local and global image features are learned through 2-D patches of different window sizes. We consider two different architectures: 1) a voxelwise approach based on three parallel 2-D convolutional pathways for three different directions (axial, coronal, and sagittal) that implicitly learn 3-D image information without the need for computationally expensive 3-D convolutions and 2) a fully convolutional network based on the U-net architecture. Posterior probability maps generated by the networks are used iteratively as context information along with the original image patches to learn the local shape and connectedness of the brain to extract it from non-brain tissue. The brain extraction results we have obtained from our CNNs are superior to the recently reported results in the literature on two publicly available benchmark data sets, namely, LPBA40 and OASIS, in which we obtained the Dice overlap coefficients of 97.73% and 97.62%, respectively. Significant improvement was achieved via our auto-context algorithm. Furthermore, we evaluated the performance of our algorithm in the challenging problem of extracting arbitrarily oriented fetal brains in reconstructed fetal brain magnetic resonance imaging (MRI) data sets. In this application, our voxelwise auto-context CNN performed much better than the other methods (Dice coefficient: 95.97%), where the other methods performed poorly due to the non-standard orientation and geometry of the fetal brain in MRI. Through training, our method can provide accurate brain extraction in challenging applications. This, in turn, may reduce the problems associated with image registration in segmentation tasks.

Clinics in diagnostic imaging (153). Severe hypoxic ischaemic brain injury.

PubMed Central

Chua, Wynne; Lim, Boon Keat; Lim, Tchoyoson Choie Cheio

2014-01-01

A 58-year-old Indian woman presented with asystole after an episode of haemetemesis, with a patient downtime of 20 mins. After initial resuscitation efforts, computed tomography of the brain, obtained to evaluate neurological injury, demonstrated evidence of severe hypoxic ischaemic brain injury. The imaging features of hypoxic ischaemic brain injury and the potential pitfalls with regard to image interpretation are herein discussed. PMID:25091891

Real-time reconstruction of three-dimensional brain surface MR image using new volume-surface rendering technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Watanabe, T.; Momose, T.; Oku, S.

It is essential to obtain realistic brain surface images, in which sulci and gyri are easily recognized, when examining the correlation between functional (PET or SPECT) and anatomical (MRI) brain studies. The volume rendering technique (VRT) is commonly employed to make three-dimensional (3D) brain surface images. This technique, however, takes considerable time to make only one 3D image. Therefore it has not been practical to make the brain surface images in arbitrary directions on a real-time basis using ordinary work stations or personal computers. The surface rendering technique (SRT), on the other hand, is much less computationally demanding, but themore » quality of resulting images is not satisfactory for our purpose. A new computer algorithm has been developed to make 3D brain surface MR images very quickly using a volume-surface rendering technique (VSRT), in which the quality of resulting images is comparable to that of VRT and computation time to SRT. In VSRT the process of volume rendering is done only once to the direction of the normal vector of each surface point, rather than each time a new view point is determined as in VRT. Subsequent reconstruction of the 3D image uses a similar algorithm to that of SRT. Thus we can obtain brain surface MR images of sufficient quality viewed from any direction on a real-time basis using an easily available personal computer (Macintosh Quadra 800). The calculation time to make a 3D image is less than 1 sec. in VSRT, while that is more than 15 sec. in the conventional VRT. The difference of resulting image quality between VSRT and VRT is almost imperceptible. In conclusion, our new technique for real-time reconstruction of 3D brain surface MR image is very useful and practical in the functional and anatomical correlation study.« less

An ultra-high field strength MR image-guided robotic needle delivery system for in-bore small animal interventions.

PubMed

Gravett, Matthew; Cepek, Jeremy; Fenster, Aaron

2017-11-01

The purpose of this study was to develop and validate an image-guided robotic needle delivery system for accurate and repeatable needle targeting procedures in mouse brains inside the 12 cm inner diameter gradient coil insert of a 9.4 T MR scanner. Many preclinical research techniques require the use of accurate needle deliveries to soft tissues, including brain tissue. Soft tissues are optimally visualized in MR images, which offer high-soft tissue contrast, as well as a range of unique imaging techniques, including functional, spectroscopy and thermal imaging, however, there are currently no solutions for delivering needles to small animal brains inside the bore of an ultra-high field MR scanner. This paper describes the mechatronic design, evaluation of MR compatibility, registration technique, mechanical calibration, the quantitative validation of the in-bore image-guided needle targeting accuracy and repeatability, and demonstrated the system's ability to deliver needles in situ. Our six degree-of-freedom, MR compatible, mechatronic system was designed to fit inside the bore of a 9.4 T MR scanner and is actuated using a combination of piezoelectric and hydraulic mechanisms. The MR compatibility and targeting accuracy of the needle delivery system are evaluated to ensure that the system is precisely calibrated to perform the needle targeting procedures. A semi-automated image registration is performed to link the robot coordinates to the MR coordinate system. Soft tissue targets can be accurately localized in MR images, followed by automatic alignment of the needle trajectory to the target. Intra-procedure visualization of the needle target location and the needle were confirmed through MR images after needle insertion. The effects of geometric distortions and signal noise were found to be below threshold that would have an impact on the accuracy of the system. The system was found to have negligible effect on the MR image signal noise and geometric distortion. The system was mechanically calibrated and the mean image-guided needle targeting and needle trajectory accuracies were quantified in an image-guided tissue mimicking phantom experiment to be 178 ± 54 μm and 0.27 ± 0.65°, respectively. An MR image-guided system for in-bore needle deliveries to soft tissue targets in small animal models has been developed. The results of the needle targeting accuracy experiments in phantoms indicate that this system has the potential to deliver needles to the smallest soft tissue structures relevant in preclinical studies, at a wide variety of needle trajectories. Future work in the form of a fully-automated needle driver with precise depth control would benefit this system in terms of its applicability to a wider range of animal models and organ targets. © 2017 American Association of Physicists in Medicine.

440th Brookhaven Lecture. Reward, Self Control and Free Will in Cocaine Addiction: Brain Imaging Results

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goldstein, Rita Z.

2008-10-01

Goldstein describes drug-addiction research, in which she tested a theoretical model postulating that drug-addicted individuals disproportionately attribute value to their drug of choice -- at the expense of other potentially but no-longer-rewarding stimuli and at the same time, experience decreased ability to inhibit their drug use.

Hemodynamic and Electrophysiological Relationship Involved in Human Face Processing: Evidence from a Combined fMRI-ERP Study

ERIC Educational Resources Information Center

Iidaka, Tetsuya; Matsumoto, Atsushi; Haneda, Kaoruko; Okada, Tomohisa; Sadato, Norihiro

2006-01-01

Functional magnetic resonance imaging (fMRI) and event-related potential (ERP) experiments were conducted in the same group of subjects and with an identical task paradigm to investigate a possible relationship between hemodynamic and electrophysiological responses within the brain. The subjects were instructed to judge whether visually presented…

Learning to Recognize Speakers of a Non-Native Language: Implications for the Functional Organization of Human Auditory Cortex

ERIC Educational Resources Information Center

Perrachione, Tyler K.; Wong, Patrick C. M.

2007-01-01

Brain imaging studies of voice perception often contrast activation from vocal and verbal tasks to identify regions uniquely involved in processing voice. However, such a strategy precludes detection of the functional relationship between speech and voice perception. In a pair of experiments involving identifying voices from native and foreign…

[First clinical experience with extended planning and navigation in an interventional MRI unit].

PubMed

Moche, M; Schmitgen, A; Schneider, J P; Bublat, M; Schulz, T; Voerkel, C; Trantakis, C; Bennek, J; Kahn, T; Busse, H

2004-07-01

To present an advanced concept for patient-based navigation and to report on our first clinical experience with interventions in the cranium, of soft-tissue structures (breast, liver) and in the musculoskeletal system. A PC-based navigation system was integrated into an existing interventional MRI environment. Intraoperatively acquired 3D data were used for interventional planning. The information content of these reference data was increased by integration of additional image modalities (e. g., fMRI, CT) and by color display of areas with early contrast media enhancement. Within 18 months, the system was used in 123 patients undergoing interventions in different anatomic regions (brain: 64, paranasal sinus: 9, breast: 20, liver: 17, bone: 9, muscle: 4). The mean duration of 64 brain interventions was compared with that of 36 procedures using the scanner's standard navigation. In contrast with the continuous scanning mode of the MR system (0.25 fps), the higher quality as well as the real time display (4 fps) of the MR images reconstructed from the 3D reference data allowed adequate hand-eye coordination. With our system, patient movement and tissue shifts could be immediately detected intraoperatively, and, in contrast to the standard procedure, navigation safely resumed after updating the reference data. The navigation system was characterized by good stability, efficient system integration and easy usability. Despite additional working steps still to be optimized, the duration of the image-guided brain tumor resections was not significantly longer. The presented system combines the advantage of intraoperative MRI with established visualization, planning, and real time capabilities of neuronavigation and can be efficiently applied in a broad range of non-neurosurgical interventions.

Decoding natural images from evoked brain activities using encoding models with invertible mapping.

PubMed

Li, Chao; Xu, Junhai; Liu, Baolin

2018-05-21

Recent studies have built encoding models in the early visual cortex, and reliable mappings have been made between the low-level visual features of stimuli and brain activities. However, these mappings are irreversible, so that the features cannot be directly decoded. To solve this problem, we designed a sparse framework-based encoding model that predicted brain activities from a complete feature representation. Moreover, according to the distribution and activation rules of neurons in the primary visual cortex (V1), three key transformations were introduced into the basic feature to improve the model performance. In this setting, the mapping was simple enough that it could be inverted using a closed-form formula. Using this mapping, we designed a hybrid identification method based on the support vector machine (SVM), and tested it on a published functional magnetic resonance imaging (fMRI) dataset. The experiments confirmed the rationality of our encoding model, and the identification accuracies for 2 subjects increased from 92% and 72% to 98% and 92% with the chance level only 0.8%. Copyright © 2018 Elsevier Ltd. All rights reserved.

Hypnosis and imaging of the living human brain.

PubMed

Landry, Mathieu; Raz, Amir

2015-01-01

Over more than two decades, studies using imaging techniques of the living human brain have begun to explore the neural correlates of hypnosis. The collective findings provide a gripping, albeit preliminary, account of the underlying neurobiological mechanisms involved in hypnotic phenomena. While substantial advances lend support to different hypotheses pertaining to hypnotic modulation of attention, control, and monitoring processes, the complex interactions among the many mediating variables largely hinder our ability to isolate robust commonalities across studies. The present account presents a critical integrative synthesis of neuroimaging studies targeting hypnosis as a function of suggestion. Specifically, hypnotic induction without task-specific suggestion is examined, as well as suggestions concerning sensation and perception, memory, and ideomotor response. The importance of carefully designed experiments is highlighted to better tease apart the neural correlates that subserve hypnotic phenomena. Moreover, converging findings intimate that hypnotic suggestions seem to induce specific neural patterns. These observations propose that suggestions may have the ability to target focal brain networks. Drawing on evidence spanning several technological modalities, neuroimaging studies of hypnosis pave the road to a more scientific understanding of a dramatic, yet largely evasive, domain of human behavior.

Resting-state functional magnetic resonance imaging: the impact of regression analysis.

PubMed

Yeh, Chia-Jung; Tseng, Yu-Sheng; Lin, Yi-Ru; Tsai, Shang-Yueh; Huang, Teng-Yi

2015-01-01

To investigate the impact of regression methods on resting-state functional magnetic resonance imaging (rsfMRI). During rsfMRI preprocessing, regression analysis is considered effective for reducing the interference of physiological noise on the signal time course. However, it is unclear whether the regression method benefits rsfMRI analysis. Twenty volunteers (10 men and 10 women; aged 23.4 ± 1.5 years) participated in the experiments. We used node analysis and functional connectivity mapping to assess the brain default mode network by using five combinations of regression methods. The results show that regressing the global mean plays a major role in the preprocessing steps. When a global regression method is applied, the values of functional connectivity are significantly lower (P ≤ .01) than those calculated without a global regression. This step increases inter-subject variation and produces anticorrelated brain areas. rsfMRI data processed using regression should be interpreted carefully. The significance of the anticorrelated brain areas produced by global signal removal is unclear. Copyright © 2014 by the American Society of Neuroimaging.

Zinc isotope ratio imaging of rat brain thin sections from stable isotope tracer studies by LA-MC-ICP-MS.

PubMed

Urgast, Dagmar S; Hill, Sarah; Kwun, In-Sook; Beattie, John H; Goenaga-Infante, Heidi; Feldmann, Jörg

2012-10-01

Zinc stable isotope tracers (⁶⁷Zn and ⁷⁰Zn) were injected into rats at two different time points to investigate the feasibility of using tracers to study zinc kinetics at the microscale within distinct tissue features. Laser ablation coupled to multi-collector ICP-MS was used to analyse average isotope ratios in liver thin sections and to generate bio-images showing zinc isotope ratio distribution in brain thin sections. Average isotope ratios of all samples from treated animals were found to be statistically different (P < 0.05) from samples from untreated control animals. Furthermore, differing isotope ratios in physiological features of the brain, namely hippocampus, amygdala, cortex and hypothalamus, were identified. This indicates that these regions differ in their zinc metabolism kinetics. While cortex and hypothalamus contain more tracer two days after injection than 14 days after injection, the opposite is true for hippocampus and amygdala. This study showed that stable isotope tracer experiments can be combined with laser ablation MC-ICP-MS to measure trace element kinetics in tissues at a microscale level.

The detectability of brain metastases using contrast-enhanced spin-echo or gradient-echo images: a systematic review and meta-analysis.

PubMed

Suh, Chong Hyun; Jung, Seung Chai; Kim, Kyung Won; Pyo, Junhee

2016-09-01

This study aimed to compare the detectability of brain metastases using contrast-enhanced spin-echo (SE) and gradient-echo (GRE) T1-weighted images. The Ovid-MEDLINE and EMBASE databases were searched for studies on the detectability of brain metastases using contrast-enhanced SE or GRE images. The pooled proportions for the detectability of brain metastases were assessed using random-effects modeling. Heterogeneity among studies was determined using χ (2) statistics for the pooled estimates and the inconsistency index, I (2) . To overcome heterogeneity, subgroup analyses according to slice thickness and lesion size were performed. A total of eight eligible studies, which included a sample size of 252 patients and 1413 brain metastases, were included. The detectability of brain metastases using SE images (89.2 %) was higher than using GRE images (81.6 %; adjusted 84.0 %), but this difference was not statistically significant (p = 0.2385). In subgroup analysis of studies with 1-mm-thick slices and small metastases (<5 mm in diameter), 3-dimensional (3D) SE images demonstrated a higher detectability in comparison to 3D GRE images (93.7 % vs 73.1 % in 1-mm-thick slices; 89.5 % vs 59.4 % for small metastases) (p < 0.0001). Although both SE or GRE images are acceptable for detecting brain metastases, contrast-enhanced 3D SE images using 1-mm-thick slices are preferred for detecting brain metastases, especially small lesions (<5 mm in diameter).

Whole-brain high in-plane resolution fMRI using accelerated EPIK for enhanced characterisation of functional areas at 3T

PubMed Central

Yun, Seong Dae

2017-01-01

The relatively high imaging speed of EPI has led to its widespread use in dynamic MRI studies such as functional MRI. An approach to improve the performance of EPI, EPI with Keyhole (EPIK), has been previously presented and its use in fMRI was verified at 1.5T as well as 3T. The method has been proven to achieve a higher temporal resolution and smaller image distortions when compared to single-shot EPI. Furthermore, the performance of EPIK in the detection of functional signals was shown to be comparable to that of EPI. For these reasons, we were motivated to employ EPIK here for high-resolution imaging. The method was optimised to offer the highest possible in-plane resolution and slice coverage under the given imaging constraints: fixed TR/TE, FOV and acceleration factors for parallel imaging and partial Fourier techniques. The performance of EPIK was evaluated in direct comparison to the optimised protocol obtained from EPI. The two imaging methods were applied to visual fMRI experiments involving sixteen subjects. The results showed that enhanced spatial resolution with a whole-brain coverage was achieved by EPIK (1.00 mm × 1.00 mm; 32 slices) when compared to EPI (1.25 mm × 1.25 mm; 28 slices). As a consequence, enhanced characterisation of functional areas has been demonstrated in EPIK particularly for relatively small brain regions such as the lateral geniculate nucleus (LGN) and superior colliculus (SC); overall, a significantly increased t-value and activation area were observed from EPIK data. Lastly, the use of EPIK for fMRI was validated with the simulation of different types of data reconstruction methods. PMID:28945780

The effects of exercise on cigarette cravings and brain activation in response to smoking-related images.

PubMed

Janse Van Rensburg, Kate; Taylor, Adrian; Benattayallah, Abdelmalek; Hodgson, Tim

2012-06-01

Smokers show heightened activation toward smoking-related stimuli and experience increased cravings which can precipitate smoking cessation relapse. Exercise can be effective for modulating cigarette cravings and attenuating reactivity to smoking cues, but the mechanism by which these effects occur remains uncertain. The objective of the study was to assess the effect of exercise on regional brain activation in response to smoking-related images during temporary nicotine abstinence. In a randomised crossover design, overnight abstinent smokers (n = 20) underwent an exercise (10-min moderate-intensity stationary cycling) and passive control (seating for the same duration) treatment, following 15 h of nicotine abstinence. After each treatment, participants underwent functional magnetic resonance imaging (fMRI) brain scanning while viewing a random series of blocked smoking or neutral images. Self-reported cravings were assessed at baseline, mid-, and post-treatments. There was a significant interaction effect (treatment × time) for desire to smoke, F (2,32) = 12.5, p < 0.001, with significantly lower scores following the exercise at all time points compared with the control treatment. After both exercise and rest, significant areas of activation were found in areas of the limbic lobe and in areas associated with visual attention in response to smoking-related stimuli. Smokers showed increased activation to smoking images in areas associated with primary and secondary visual processing following rest, but not following a session of exercise. The study shows differing activation towards smoking images following exercise compared to a control treatment and may point to a neuro-cognitive process following exercise that mediates effects on cigarette cravings.

Serial nonenhancing magnetic resonance imaging scans of high grade glioblastoma multiforme.

PubMed Central

Moore-Stovall, J.; Venkatesh, R.

1993-01-01

Magnetic resonance imaging (MRI) from clinical experience has proven to be superior to all other diagnostic imaging modalities, including computed tomography (CT) in the detection of intracranial neoplasms. Although glioblastoma multiforme presents a challenge for all diagnostic imaging modalities including MRI, MRI is paramount to CT in detecting subtle abnormal water accumulation in brain tissue caused by tumor even before there is disruption of the blood brain barrier. Currently, clinical research and investigational trials on nonionic gadolinium contrast agents have proven that nonionic gadolinium HP-DO3A (ProHance) contrast agents have lower osmolality and greater stability, which make them superior compounds to gadolinium diethylenetriamine-pentacetic acid (Gd-DTPA). Therefore, the nonionic gadolinium contrasts have been safely administered more rapidly, in higher or multiple doses for contrast enhanced MRI without adverse side effects or changes in serum iron or total bilirubin, and the intensity of the area of enhancement and number of lesions detected were superior to that of Gd-DTPA (Magnevist) at the standard dose (0.1 mmol/Kg). Perhaps if the nonionic gadolinium contrast agent, ProHance, had been approved by the Food and Drug Administration (FDA) when this MRI was performed in 1990 it would have aided in providing contrast enhancement and visualization of the tumor lesion to assist in patient diagnosis and management. Magnetic resonance imaging also provides unique multiplanar capabilities that allow for optimal visualization of the temporal and occipital lobes of the brain without bone interference.(ABSTRACT TRUNCATED AT 250 WORDS) Images Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9A Figure 9B Figure 10 Figure 11 Figure 12 Figure 13 PMID:8382751

Quantitative Imaging of Energy Expenditure in Human Brain

PubMed Central

Zhu, Xiao-Hong; Qiao, Hongyan; Du, Fei; Xiong, Qiang; Liu, Xiao; Zhang, Xiaoliang; Ugurbil, Kamil; Chen, Wei

2012-01-01

Despite the essential role of the brain energy generated from ATP hydrolysis in supporting cortical neuronal activity and brain function, it is challenging to noninvasively image and directly quantify the energy expenditure in the human brain. In this study, we applied an advanced in vivo 31P MRS imaging approach to obtain regional cerebral metabolic rates of high-energy phosphate reactions catalyzed by ATPase (CMRATPase) and creatine kinase (CMRCK), and to determine CMRATPase and CMRCK in pure grey mater (GM) and white mater (WM), respectively. It was found that both ATPase and CK rates are three times higher in GM than WM; and CMRCK is seven times higher than CMRATPase in GM and WM. Among the total brain ATP consumption in the human cortical GM and WM, 77% of them are used by GM in which approximately 96% is by neurons. A single cortical neuron utilizes approximately 4.7 billion ATPs per second in a resting human brain. This study demonstrates the unique utility of in vivo 31P MRS imaging modality for direct imaging of brain energy generated from ATP hydrolysis, and provides new insights into the human brain energetics and its role in supporting neuronal activity and brain function. PMID:22487547

Thalamotemporal alteration and postoperative seizures in temporal lobe epilepsy

PubMed Central

Richardson, Mark P.; Schoene‐Bake, Jan‐Christoph; O'Muircheartaigh, Jonathan; Elkommos, Samia; Kreilkamp, Barbara; Goh, Yee Yen; Marson, Anthony G.; Elger, Christian; Weber, Bernd

2015-01-01

Objective There are competing explanations for persistent postoperative seizures after temporal lobe surgery. One is that 1 or more particular subtypes of mesial temporal lobe epilepsy (mTLE) exist that are particularly resistant to surgery. We sought to identify a common brain structural and connectivity alteration in patients with persistent postoperative seizures using preoperative quantitative magnetic resonance imaging and diffusion tensor imaging (DTI). Methods We performed a series of studies in 87 patients with mTLE (47 subsequently rendered seizure free, 40 who continued to experience postoperative seizures) and 80 healthy controls. We investigated the relationship between imaging variables and postoperative seizure outcome. All patients had unilateral temporal lobe seizure onset, had ipsilateral hippocampal sclerosis as the only brain lesion, and underwent amygdalohippocampectomy. Results Quantitative imaging factors found not to be significantly associated with persistent seizures were volumes of ipsilateral and contralateral mesial temporal lobe structures, generalized brain atrophy, and extent of resection. There were nonsignificant trends for larger amygdala and entorhinal resections to be associated with improved outcome. However, patients with persistent seizures had significant atrophy of bilateral dorsomedial and pulvinar thalamic regions, and significant alterations of DTI‐derived thalamotemporal probabilistic paths bilaterally relative to those patients rendered seizure free and controls, even when corrected for extent of mesial temporal lobe resection. Interpretation Patients with bihemispheric alterations of thalamotemporal structural networks may represent a subtype of mTLE that is resistant to temporal lobe surgery. Increasingly sensitive multimodal imaging techniques should endeavor to transform these group‐based findings to individualize prediction of patient outcomes. Ann Neurol 2015;77:760–774 PMID:25627477

Colorization and Automated Segmentation of Human T2 MR Brain Images for Characterization of Soft Tissues

PubMed Central

Attique, Muhammad; Gilanie, Ghulam; Hafeez-Ullah; Mehmood, Malik S.; Naweed, Muhammad S.; Ikram, Masroor; Kamran, Javed A.; Vitkin, Alex

2012-01-01

Characterization of tissues like brain by using magnetic resonance (MR) images and colorization of the gray scale image has been reported in the literature, along with the advantages and drawbacks. Here, we present two independent methods; (i) a novel colorization method to underscore the variability in brain MR images, indicative of the underlying physical density of bio tissue, (ii) a segmentation method (both hard and soft segmentation) to characterize gray brain MR images. The segmented images are then transformed into color using the above-mentioned colorization method, yielding promising results for manual tracing. Our color transformation incorporates the voxel classification by matching the luminance of voxels of the source MR image and provided color image by measuring the distance between them. The segmentation method is based on single-phase clustering for 2D and 3D image segmentation with a new auto centroid selection method, which divides the image into three distinct regions (gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) using prior anatomical knowledge). Results have been successfully validated on human T2-weighted (T2) brain MR images. The proposed method can be potentially applied to gray-scale images from other imaging modalities, in bringing out additional diagnostic tissue information contained in the colorized image processing approach as described. PMID:22479421

The Importance of Neurogenic Inflammation in Blast-Induced Neurotrauma

DTIC Science & Technology

2013-01-01

mild/moderate BINT are imaged by magnetic resonance imaging ( MRI ) to visualize potential macrophage infiltration; blood-brain barrier (BBB) disturbance...TERMS blast, traumatic brain injury, brain, inflammation, magnetic resonance imaging , mice 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF...monitoring the success of therapeutic interventions. In this annual report we have utilized current live imaging methods (i.e. magnetic resonance

Patient-specific model-based segmentation of brain tumors in 3D intraoperative ultrasound images.

PubMed

Ilunga-Mbuyamba, Elisee; Avina-Cervantes, Juan Gabriel; Lindner, Dirk; Arlt, Felix; Ituna-Yudonago, Jean Fulbert; Chalopin, Claire

2018-03-01

Intraoperative ultrasound (iUS) imaging is commonly used to support brain tumor operation. The tumor segmentation in the iUS images is a difficult task and still under improvement because of the low signal-to-noise ratio. The success of automatic methods is also limited due to the high noise sensibility. Therefore, an alternative brain tumor segmentation method in 3D-iUS data using a tumor model obtained from magnetic resonance (MR) data for local MR-iUS registration is presented in this paper. The aim is to enhance the visualization of the brain tumor contours in iUS. A multistep approach is proposed. First, a region of interest (ROI) based on the specific patient tumor model is defined. Second, hyperechogenic structures, mainly tumor tissues, are extracted from the ROI of both modalities by using automatic thresholding techniques. Third, the registration is performed over the extracted binary sub-volumes using a similarity measure based on gradient values, and rigid and affine transformations. Finally, the tumor model is aligned with the 3D-iUS data, and its contours are represented. Experiments were successfully conducted on a dataset of 33 patients. The method was evaluated by comparing the tumor segmentation with expert manual delineations using two binary metrics: contour mean distance and Dice index. The proposed segmentation method using local and binary registration was compared with two grayscale-based approaches. The outcomes showed that our approach reached better results in terms of computational time and accuracy than the comparative methods. The proposed approach requires limited interaction and reduced computation time, making it relevant for intraoperative use. Experimental results and evaluations were performed offline. The developed tool could be useful for brain tumor resection supporting neurosurgeons to improve tumor border visualization in the iUS volumes.

Search and retrieval of medical images for improved diagnosis of neurodegenerative diseases

NASA Astrophysics Data System (ADS)

Ekin, Ahmet; Jasinschi, Radu; Turan, Erman; Engbers, Rene; van der Grond, Jeroen; van Buchem, Mark A.

2007-01-01

In the medical world, the accuracy of diagnosis is mainly affected by either lack of sufficient understanding of some diseases or the inter-, and/or intra-observer variability of the diagnoses. The former requires understanding the progress of diseases at much earlier stages, extraction of important information from ever growing amounts of data, and finally finding correlations with certain features and complications that will illuminate the disease progression. The latter (inter-, and intra- observer variability) is caused by the differences in the experience levels of different medical experts (inter-observer variability) or by mental and physical tiredness of one expert (intra-observer variability). We believe that the use of large databases can help improve the current status of disease understanding and decision making. By comparing large number of patients, some of the otherwise hidden relations can be revealed that results in better understanding, patients with similar complications can be found, the diagnosis and treatment can be compared so that the medical expert can make a better diagnosis. To this effect, this paper introduces a search and retrieval system for brain MR databases and shows that brain iron accumulation shape provides additional information to the shape-insensitive features, such as the total brain iron load, that are commonly used in the clinics. We propose to use Kendall's correlation value to automatically compare various returns to a query. We also describe a fully automated and fast brain MR image analysis system to detect degenerative iron accumulation in brain, as it is the case in Alzheimer's and Parkinson's. The system is composed of several novel image processing algorithms and has been extensively tested in Leiden University Medical Center over so far more than 600 patients.

Brain tumour classification and abnormality detection using neuro-fuzzy technique and Otsu thresholding.

PubMed

Renjith, Arokia; Manjula, P; Mohan Kumar, P

2015-01-01

Brain tumour is one of the main causes for an increase in transience among children and adults. This paper proposes an improved method based on Magnetic Resonance Imaging (MRI) brain image classification and image segmentation approach. Automated classification is encouraged by the need of high accuracy when dealing with a human life. The detection of the brain tumour is a challenging problem, due to high diversity in tumour appearance and ambiguous tumour boundaries. MRI images are chosen for detection of brain tumours, as they are used in soft tissue determinations. First of all, image pre-processing is used to enhance the image quality. Second, dual-tree complex wavelet transform multi-scale decomposition is used to analyse texture of an image. Feature extraction extracts features from an image using gray-level co-occurrence matrix (GLCM). Then, the Neuro-Fuzzy technique is used to classify the stages of brain tumour as benign, malignant or normal based on texture features. Finally, tumour location is detected using Otsu thresholding. The classifier performance is evaluated based on classification accuracies. The simulated results show that the proposed classifier provides better accuracy than previous method.

s-SMOOTH: Sparsity and Smoothness Enhanced EEG Brain Tomography

PubMed Central

Li, Ying; Qin, Jing; Hsin, Yue-Loong; Osher, Stanley; Liu, Wentai

2016-01-01

EEG source imaging enables us to reconstruct current density in the brain from the electrical measurements with excellent temporal resolution (~ ms). The corresponding EEG inverse problem is an ill-posed one that has infinitely many solutions. This is due to the fact that the number of EEG sensors is usually much smaller than that of the potential dipole locations, as well as noise contamination in the recorded signals. To obtain a unique solution, regularizations can be incorporated to impose additional constraints on the solution. An appropriate choice of regularization is critically important for the reconstruction accuracy of a brain image. In this paper, we propose a novel Sparsity and SMOOthness enhanced brain TomograpHy (s-SMOOTH) method to improve the reconstruction accuracy by integrating two recently proposed regularization techniques: Total Generalized Variation (TGV) regularization and ℓ1−2 regularization. TGV is able to preserve the source edge and recover the spatial distribution of the source intensity with high accuracy. Compared to the relevant total variation (TV) regularization, TGV enhances the smoothness of the image and reduces staircasing artifacts. The traditional TGV defined on a 2D image has been widely used in the image processing field. In order to handle 3D EEG source images, we propose a voxel-based Total Generalized Variation (vTGV) regularization that extends the definition of second-order TGV from 2D planar images to 3D irregular surfaces such as cortex surface. In addition, the ℓ1−2 regularization is utilized to promote sparsity on the current density itself. We demonstrate that ℓ1−2 regularization is able to enhance sparsity and accelerate computations than ℓ1 regularization. The proposed model is solved by an efficient and robust algorithm based on the difference of convex functions algorithm (DCA) and the alternating direction method of multipliers (ADMM). Numerical experiments using synthetic data demonstrate the advantages of the proposed method over other state-of-the-art methods in terms of total reconstruction accuracy, localization accuracy and focalization degree. The application to the source localization of event-related potential data further demonstrates the performance of the proposed method in real-world scenarios. PMID:27965529

Multi-modal imaging of long-term recovery post-stroke by positron emission tomography and matrix-assisted laser desorption/ionisation mass spectrometry.

PubMed

Henderson, Fiona; Hart, Philippa J; Pradillo, Jesus M; Kassiou, Michael; Christie, Lidan; Williams, Kaye J; Boutin, Herve; McMahon, Adam

2018-05-15

Stroke is a leading cause of disability worldwide. Understanding the recovery process post-stroke is essential; however, longer-term recovery studies are lacking. In vivo positron emission tomography (PET) can image biological recovery processes, but is limited by spatial resolution and its targeted nature. Untargeted mass spectrometry imaging offers high spatial resolution, providing an ideal ex vivo tool for brain recovery imaging. Magnetic resonance imaging (MRI) was used to image a rat brain 48 h after ischaemic stroke to locate the infarcted regions of the brain. PET was carried out 3 months post-stroke using the tracers [ 18 F]DPA-714 for TSPO and [ 18 F]IAM6067 for sigma-1 receptors to image neuroinflammation and neurodegeneration, respectively. The rat brain was flash-frozen immediately after PET scanning, and sectioned for matrix-assisted laser desorption/ionisation mass spectrometry (MALDI-MS) imaging. Three months post-stroke, PET imaging shows minimal detection of neurodegeneration and neuroinflammation, indicating that the brain has stabilised. However, MALDI-MS images reveal distinct differences in lipid distributions (e.g. phosphatidylcholine and sphingomyelin) between the scar and the healthy brain, suggesting that recovery processes are still in play. It is currently not known if the altered lipids in the scar will change on a longer time scale, or if they are stabilised products of the brain post-stroke. The data demonstrates the ability to combine MALD-MS with in vivo PET to image different aspects of stroke recovery. Copyright © 2018 John Wiley & Sons, Ltd.

Individual differences in transcranial electrical stimulation current density

PubMed Central

Russell, Michael J; Goodman, Theodore; Pierson, Ronald; Shepherd, Shane; Wang, Qiang; Groshong, Bennett; Wiley, David F

2013-01-01

Transcranial electrical stimulation (TCES) is effective in treating many conditions, but it has not been possible to accurately forecast current density within the complex anatomy of a given subject's head. We sought to predict and verify TCES current densities and determine the variability of these current distributions in patient-specific models based on magnetic resonance imaging (MRI) data. Two experiments were performed. The first experiment estimated conductivity from MRIs and compared the current density results against actual measurements from the scalp surface of 3 subjects. In the second experiment, virtual electrodes were placed on the scalps of 18 subjects to model simulated current densities with 2 mA of virtually applied stimulation. This procedure was repeated for 4 electrode locations. Current densities were then calculated for 75 brain regions. Comparison of modeled and measured external current in experiment 1 yielded a correlation of r = .93. In experiment 2, modeled individual differences were greatest near the electrodes (ten-fold differences were common), but simulated current was found in all regions of the brain. Sites that were distant from the electrodes (e.g. hypothalamus) typically showed two-fold individual differences. MRI-based modeling can effectively predict current densities in individual brains. Significant variation occurs between subjects with the same applied electrode configuration. Individualized MRI-based modeling should be considered in place of the 10-20 system when accurate TCES is needed. PMID:24285948

Targeting MT1-MMP as an ImmunoPET-Based Strategy for Imaging Gliomas

PubMed Central

Oteo, M.; Romero, E.; Cámara, J. A.; de Martino, A.; Arroyo, A. G.; Morcillo, M. Á.; Squatrito, M.; Martinez-Torrecuadrada, J. L.; Mulero, F.

2016-01-01

Background A critical challenge in the management of Glioblastoma Multiforme (GBM) tumors is the accurate diagnosis and assessment of tumor progression in a noninvasive manner. We have identified Membrane-type 1 matrix metalloproteinase (MT1-MMP) as an attractive biomarker for GBM imaging since this protein is actively involved in tumor growth and progression, correlates with tumor grade and is closely associated with poor prognosis in GBM patients. Here, we report the development of an immunoPET tracer for effective detection of MT1-MMP in GBM models. Methods An anti-human MT1-MMP monoclonal antibody (mAb), LEM2/15, was conjugated to p-isothiocyanatobenzyl-desferrioxamine (DFO-NCS) for 89Zr labeling. Biodistribution and PET imaging studies were performed in xenograft mice bearing human GBM cells (U251) expressing MT1-MMP and non-expressing breast carcinoma cells (MCF-7) as negative control. Two orthotopic brain GBM models, patient-derived neurospheres (TS543) and U251 cells, with different degrees of blood-brain barrier (BBB) disruption were also used for PET imaging experiments. Results 89Zr labeling of DFO-LEM2/15 was achieved with high yield (>90%) and specific activity (78.5 MBq/mg). Biodistribution experiments indicated that 89Zr-DFO-LEM2/15 showed excellent potential as a radiotracer for detection of MT1-MMP positive GBM tumors. PET imaging also indicated a specific and prominent 89Zr-DFO-LEM2/15 uptake in MT1-MMP+ U251 GBM tumors compared to MT1-MMP- MCF-7 breast tumors. Results obtained in orthotopic brain GBM models revealed a high dependence of a disrupted BBB for tracer penetrance into tumors. 89Zr-DFO-LEM2/15 showed much higher accumulation in TS543 tumors with a highly disrupted BBB than in U251 orthotopic model in which the BBB permeability was only partially increased. Histological analysis confirmed the specificity of the immunoconjugate in all GBM models. Conclusion A new anti MT1-MMP-mAb tracer, 89Zr-DFO-LEM2/15, was synthesized efficiently. In vivo validation showed high-specific-contrast imaging of MT1-MMP positive GBM tumors and provided strong evidence for utility of MT1-MMP-targeted immunoPET as an alternate to nonspecific imaging of GBM. PMID:27462980

Mechanism of Chronic Pain in Rodent Brain Imaging

NASA Astrophysics Data System (ADS)

Chang, Pei-Ching

Chronic pain is a significant health problem that greatly impacts the quality of life of individuals and imparts high costs to society. Despite intense research effort in understanding of the mechanism of pain, chronic pain remains a clinical problem that has few effective therapies. The advent of human brain imaging research in recent years has changed the way that chronic pain is viewed. To further extend the use of human brain imaging techniques for better therapies, the adoption of imaging technique onto the animal pain models is essential, in which underlying brain mechanisms can be systematically studied using various combination of imaging and invasive techniques. The general goal of this thesis is to addresses how brain develops and maintains chronic pain in an animal model using fMRI. We demonstrate that nucleus accumbens, the central component of mesolimbic circuitry, is essential in development of chronic pain. To advance our imaging technique, we develop an innovative methodology to carry out fMRI in awake, conscious rat. Using this cutting-edge technique, we show that allodynia is assoicated with shift brain response toward neural circuits associated nucleus accumbens and prefrontal cortex that regulate affective and cognitive component of pain. Taken together, this thesis provides a deeper understanding of how brain mediates pain. It builds on the existing body of knowledge through maximizing the depth of insight into brain imaging of chronic pain.